WK5 CHAP5 Microeconomic Concepts Current State of US Health Care Industry

WK5 CHAP5 Microeconomic Concepts Current State of US Health Care Industry

Identify and describe the current state of the health care industry or a particular segment of the healthcare industry

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using the Microeconomic concepts and tools we have studied this semester. You will find an overview of the economics of health care in chapter 30 and a discussion of Medicare in Chapter 5. For this week, you will want to supplement this reading with research from a newspaper or newsmagazine or from a reputable online source that deals with U.S. Healthcare.

For this week your post should:

List the pros and cons related to the current system in place in the United States along with a short explanation of health insurance and how it relates to this debate.
Apply either supply and demand analysis (week 2 material) or elasticity analysis (week 3 material) or the examination of market structures (weeks 4-5 material).
Develop your own solution to this social issue, but you must understand and explain the economic costs of your decision.
Hint: You may want to compare healthcare systems in other countries.

This is always a very interesting discussion. Healthcare is a problem in this nation and has been for a long time. Part of it is the unique system we have.

If this topic is of interest to you, I would recommend two books:

An American Sickness by Elisabeth Rosenthal and Code Red An Economist Explains How to Revive the American Healthcare System without Destroying It.

HCA521 Unit 5 Healthcare Tech Fundamentals of Information Systems Paper

HCA521 Unit 5 Healthcare Tech Fundamentals of Information Systems Paper

M04_GART2674_01_SE_C04.QXD 4 8/4/09 1:53 PM Page 74 Fundamentals of Information Systems LEARNING

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OUTCOMES H After completing this chapter, you I should be able to: 䊏 Understand fundamental G concepts of computers 䊏 Discriminate between hardware and software G 䊏 Define computer input and output S 䊏 Discuss components of a database 䊏 Compare different types of , computer data and explain relational data 䊏 䊏 䊏 Describe different types of computer networks Understand how a wireless network functions S Understand how interoperability standards help disparate systems H exchange data A ACRONYMS USED IN CHAPTER 4 N I Acronyms are used extensively in both medicine and computers. The following C acronyms are used in this chapter. ASCII American Standard Code Q for LAN Local-Area Network Information Interchange U LED Light Emitting Diode BLOB Binary Large Object MDS Minimum Data Set A CAT Computerized Axial Tomography MRI CCOW Clinical Context Object Workgroup CD 1 Computer Output to Laser 1Disk Central Processing Unit 0 Digital Imaging and Communication 5 in Medicine Digital Video Disk T Health Information Management S PACS OR PAC SYSTEM Picture Archiving and Communication System COLD CPU DICOM DVD HIM Compact Disk Magnetic Resonance Imaging PDA Personal Digital Assistant PDF Portable Document Format PET Positron Emission Tomography POP3 Post Office Protocol, Version 3 RAID Redundant Array of Independent Disks RAM Random Access Memory Health Information System RIS Radiology Information System HL7 Health Level 7 SAN Storage Area Network HTTP Hypertext Transfer Protocol SMTP Simple Mail Transfer Protocol IMAP Internet Message Access Protocol SSL Secured Socket Layer I/O Input/Output TCP/IP Transmission Control Protocol/Internet Protocol TIFF Tagged Image File Format HIS ISP Internet Service Provider JPEG Joint Photographic Experts Group 74 Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 75 FUNDAMENTALS OF INFORMATION SYSTEMS VPN Virtual Private Network WAN Wide-Area Network VOIP Voice-Over-Internet Protocol WI-FI Wireless Fidelity 75 The Technology behind Health Systems As a student of this course you probably already use computers, but depending on your previous computer experience and previous courses you have taken, you may or may not understand them. The purpose of this chapter is to familiarize you with some of the terminology and concepts that make a computer work and that make dozens of computers work together as a health information H system (HIS). Computer systems are generally discussed in terms of I two components: hardware and software. G Hardware G Hardware refers to the components you can physically see and touch: the computer, circuit S boards, computer chips, monitor screen, keyboard, mouse, cables, wires, printers, and so forth. , later), the switches, routers, netWhen multiple computers are connected in a network (discussed work cards, and cabling that connect them are also referred to as the hardware. Let’s look at some specific types of hardware. S CPU The central processing unit (CPU) is sometimes referred to as the computer’s brain. It is H usually a single chip, which controls the flow of information to and from other parts of the A computer. It often adds, subtracts, modifies, and otherwise “processes” the information passing through it according to instructions from the software. N MEMORY AND STORAGE Computers can hold vast quantities I of information, but only a little of it is in the CPU at any one time. Information not currently being processed is stored elsewhere. Some of the places where it is stored include optical disksC (CD or DVD), the hard drive, and computer memory chips. In most cases, the computer can both Qread the information stored on the device and write (save) information back to the device. U Random access memory (RAM) chips keep information in electronic circuits, which operate at or near the same speed as the CPU. This provides the CPUAwith the ability to access the infor- mation it needs very quickly such that the CPU can read and write information to RAM almost continuously. However, RAM information is only in memory while the computer is turned on. 1 memory chips hold only a certain When the computer is turned off, the memory is cleared. Also, quantity of information; anything more than the chip can hold 1 must be stored elsewhere. Hard drives store information magnetically on disks that spin at high speeds inside a sealed 0 magnet, the information stored unit. Unless the disk becomes damaged or exposed to a strong there is stable, and is retained even when the power is turned 5 off. Hard drives can store vast quantities of information and are the computer’s principal storage device. The CPU can both save and T drives are very fast, they are conretrieve information from the hard drive. Though modern hard siderably slower than the purely electronic circuits of RAM S memory. Figure 4-1 allows you to identify many of the hardware components discussed in this section. Because it generates intense amounts of heat, the CPU is covered by metal fins (heat sink) and a fan. The actual CPU is not visible in the picture. Optical disks, such as CD-ROMs or DVDs, use lasers to burn information for long-term storage. The CPU can read and write optical disks just as it can hard drives, although an optical disk transfers information slower than does a hard drive. The advantage of an optical disk is that the storage is permanent. The disk is not affected by magnetism, has an extremely long life span, and can be removed from the computer when not needed. Although each disk has a fixed capacity, an unlimited number of disks can be used, making optical disks ideal for archiving records that are not frequently accessed. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.qxd 76 8/22/09 5:04 PM Page 76 CHAPTER 4 FIGURE 4-1 Interior of workstation showing CPU, RAM, ROM, and optical and hard drives. H I G G S , S H A N Although certain types of optical disks are reusable, optical disks cannot be written over accidentally. Optical disks are oftenIused for the transfer and storage of large radiology images. They are a reliable media for permanent C record archives. Read-only memory (ROM) chips are computer chips with electronic circuits that retain inforQ or other parts of the computer can read a ROM chip as mation when the power is off. The CPU quickly as a RAM chip, but cannot U accidentally write over the information stored on the ROM. This type of memory is usually used to store instructions the computer needs to start up; also devices within the computer such as A the hard drive may store information about its configuration on a ROM chip. Magnetic tape was used in the early days of computing to actively store and retrieve data. Today it is used only to back up data1stored on hard drives. INPUT AND OUTPUT DEVICES 1 How does information get into the computer? Then once the information is in the computer, how0do you see it? The computer terms for these concepts are input (putting information in) and output 5 (information coming out of the computer). Sometimes the abbreviation I/O is used, which simply stands for input/output. The main devices for inputting T information into the computer are the keyboard and mouse. Likewise the most popular output device S is the monitor or screen. Newer technology such as the Tablet PC (shown later in Figure 4-3) and touch screens, which are often used in kiosks, combine these functions, allowing the screen to act as both an input and an output device. Printers are also output devices. The only output device for early computers was a teletype printer. Even after monitors came into use as the predominant display technology, business processes were so oriented toward paper records that most computer information was also printed, wasting tons of paper that also had to be stored. In the 21st century businesses and healthcare organizations are increasingly using scanners to store images of documents instead of storing the paper documents. A scanner is an input device that looks and works much like a modern office copier, except where a copier prints a copy, a scanner sends it to a computer as a digital image. The image of the document can be retrieved and Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 77 FUNDAMENTALS OF INFORMATION SYSTEMS displayed on the computer screen or even reprinted whenever it is needed. A small scanner is shown in Figure 4-2. However, if a document that an organization needs to keep, such as financial and other reports, was originally generated by a computer, then there is no need to waste time and paper printing the computer report, then scanning it back in as a document image. Some systems can directly create the report as an image file. This process, sometimes referred to by the acronym COLD (computer output to laser disk), will be discussed later in this chapter. Other input devices include microphones and cameras, which can capture sound, digital pictures, and video to be saved directly in the computer. The monitor screen and computer speakers are the output devices for these H types of files. Voice files and document image files can be converted to computer data using special computer programsI(voice recognition and optical character recognition software, respectively). G Tablet PCs (Figure 4-3) and PDAs (personal digital assistants) can receive handwritten input. G Using an inkless pen, called a stylus, that will not damage the screen, the user writes on the S screen. Handwriting recognition software interprets the handwritten characters and changes them into typed letters and numbers, which can then be saved as computer data. , Medical images such as x-rays, CAT scans, MRIs, and PET scans are major input sources for health information systems. These diagnostic devices are able to save images directly from the medical device that captures them. Other medical devices that Scan output their information to an electronic patient chart include ultrasound and electrocardiogram devices and even those that H measure vital signs. So far the input and output methods we have discussed are A those by which humans and computers interact, but for sheer quantity of data input and output, the greatest volume is the elecN of input and output is conducted tronic exchange between computers. A small portion of this type using the memory storage devices we discussed earlier: CD-ROM, DVD, and portable RAM I devices. However, most of the data exchanged between of computers is via networks, which are C discussed later in this chapter. Because our primary method of inputtingQinformation into the computer is keyboarding, and our primary method of using that information U is looking at a screen, workers who use a computer all day can develop various ailments A from repeating the same motions, sitting at the same angle to the monitor, screen glare, and other factors. Computer ergonomics is the study of the physical effect of 1 human/computer interaction on workers with the goal of 1 minimizing or eliminating problems. Ergonomics in the healthcare workplace goes beyond 0 the computers. It is applied to the height and shape of desks, nurses’ stations, wall units, portable carts, and the 5 height at which monitors are mounted. Another consider- T ation unique to healthcare is the ability to protect the keyboard, mouse, and the screens of portable devices so they S can be sanitized without damaging the electronics. Figure 4-4 shows a workstation mounted at a nurses’ station using a bracket that allows the user to adjust the height and angle of both the monitor and keyboard for maximum ergonomics. ERGONOMICS 77 FIGURE 4-2 A scanner captures an image of a document. (Courtesy of Allscripts, LLC.) FIGURE 4-3 Clinician using a tablet PC. (Courtesy of GE Healthcare.) Software The second major component of our discussion is software. It consists of the logic, programs, and routines that make the Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 78 8/4/09 1:53 PM Page 78 CHAPTER 4 hardware useful and provide instructions to the computer for processing the information it receives. It is referred to as “soft” because it is intangible. Unlike hardware, you cannot physically touch it. When you turn on your computer and when you start a desired program, those programs are temporarily loaded in the CPU and RAM. When you close a program those functions disappear. Our discussion of software will be broadly grouped into two types: operating system software and application software. FIGURE 4-4 Ergonomically mounted workstation in a nursing unit. OPERATING SYSTEMS Operating system software consists of programs that enable us to work with a computer’s hardware. This type of software includes functions that allow the CPU and other control chips to operate the monitor display, memory storage devices, and input/output devices, including the keyboard and HYou are probably most familiar with the Windows® or mouse. Macintosh I operating systems; however, in HIS environments you may also find UNIX®, AIX®, HP-UX®, and LINUX®, which are G also operating systems. An Goperating system is not simply a single program, but rather thousands of little functions and programs that perform different S operations. Generations of computer science advances have evolved , into today’s operating systems, making it possible for you to click the mouse, start a program, and see the characters you type appear on the screen. A few of the layers of this underlying technology S are explained in the later section titled Bits and Bytes—How Computers “Think.” H In a healthcare facility most of the computers are linked A software is part of the operating systems just discussed, together into a network. The networking but we will learn more about networks N later in this chapter. APPLICATION SOFTWARE Applications I are the software that you use every day. They make the computer “apply” to the task we need done. A word processor is a good example of application C between an operating system and application software, software. To understand the differences consider this simple example: Let us Qsay you want to write a paper for class. You click on the word processor icon on your computer screen and the operating system loads the software into U the CPU. You type your paper, spell check it, save it, and print it out. During your word processing session, A the operating system handled the many things common to all applications. It captured the signals from the keyboard and mouse, interpreted what letters they were, and provided those to the application. In contrast, the word processor kept track 1 were spelled correctly, and when it was time to go to the of how characters formed words, if they next line and start a new paragraph 1 or a new page. The application allowed you to decide what font was used and whether or not to center the title of your paper. Meanwhile, with each key0 stroke, the operating system communicated with your monitor so the characters appeared on your screen. 5 When you saved your work, the application called on the operating system, which stored it on the hard disk and kept track of itsTlocation for future retrieval. When you printed your paper, the application software sent not only S the text but information about the margins, font changes, ink color, and so forth. However, it was the operating system that located the printer device, set up communications with it, regulated how fast the text was sent to it, and kept track of the printer’s progress. Unless you choose to become a computer or network technician, almost everything you do on a computer in an HIM profession will be focused on application software. Examples of HIS applications include patient registration and scheduling software, electronic health records, clinical information systems, computerized order entry systems, billing and coding software, document imaging systems, radiology information systems, and laboratory information systems, as well as generalized applications such as word processing, spreadsheets, and e-mail. Some of these applications will be discussed in more depth in later chapters. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 79 FUNDAMENTALS OF INFORMATION SYSTEMS Bits and Bytes—How Computers “Think” 1 Computer processor and memory chips contain millions of transistors, each of which act like an on/off switch. These represent the smallest unit of information in the computer called a bit. Bits represent the values zero and one. If the transistor switch is off, the bit is zero; if the transistor switch is on, the bit is one. Imagine that the eight LED lights in Figure 4-5 represent a group of eight bits. Where the LED is green, the bit is on; where it is off, the LED is not lit. Look at the number next to each LED in Figure 4-5; notice that each successive number is twice as large as the one above it. When bits are grouped together, each succeeding bit in the group represents a number twice as large as the previous bit. From this humble beginning, the computer forms a binary number system. Binary means made up of two parts, in this case zero and a designated number. Eight bits, grouped together, form the basic unit of computing called a byte. Figure 4-5 has eight bits, therefore it also illustrates one byte. The value of a byte is the cumulative total of its bits which are “on.” For instance, in Figure 4-5 the LEDs next H to bits 1 and 64 are on; the other LEDs represent bits that are “off” or zero. The sum of bits that are “on” represents the value of I the byte, which in this figure is 65. G to do math. For example, to add Logically, you can see how a computer could use this system four to this number, turn on the third bit. The sum of the byteGwould then be (1 ⫹ 4 ⫹ 64 ⫽ 69). However, most of the data we see in the computer consists of letters, words, names, so how do S bits become alphabetical? In 1963 the American Standard Code for Information Interchange (ASCII) standardized text , bytes by assigning a meaning to each possible combination of bits.1 Bytes with values of 1 through 31 are used to control the flow of information in the computer. Bytes with values of 32 through 126 represent printable characters of the alphabet, punctuation, and numerals. Bytes with S values of 128 through 255 are used as for extended characters. As an example, the table shown H later in Figure 4-7 lists the values assigned to the alphabet characters in ASCII. For example, the value 65 shown in Figure 4-5 equates to the letter “A” in theA ASCII standard. Although everything in computer memory is a function of bits being on or off, not everything N on, the highest number the comis limited to 8-bit bytes. If all of the bits in Figure 4-6 are turned puter could calculate would be 256. To go beyond this limit, I data types are defined that use a larger number of bits. For example, a numeric integer is 16 bits. Integers can be used for whole C numbers from –32,767 to 32,767. Long integers use 32 bits to handle larger whole numbers. Numeric data that has decimal fractions is a data type calledQ double, which has 64 bits. 2 79 4 8 16 32 64 128 FIGURE 4-5 LED lights illustrate 8 bits. 1 2 4 8 16 32 64 128 256 FIGURE 4-6 Maximum value of a byte is 256. EXTENDING FUNCTIONALITY So it’s all math, right? Well,U actually that is true. The genius of modern computer science has been the ability to take the basic A arithmetic function derived from turning bits on and off and extend it into all of the possible data types we use today. Take color for example. The smallest dot on a computer screen, called a pixel, can 1 be displayed in millions of colors by using a large number of bits. If the pixel data were one bit, the only colors would be white (bit 1 it can display 256 colors. When on) or black (bit off)—but define that pixel as eight bits and image data is defined as true color, it uses 32 bits and suddenly 0 the computer can render all the nuances of a CAT scan or an MRI. 5 circuits in the scanner capture the When images are scanned into a medical record, electronic reflection of each pixel on the page and express it as a numerical T value. The computer stores these digits in a file that it recognizes as image data. S of a doctor dictating a note. A Similarly, with sound files, a microphone captures the voice sound card converts the electrical signal into numbers representing the frequency of the sound wave at each instant. Computer software stores these in a file it recognizes as a sound file. Even the computer software is really just ones and zeros stored in a type of file that the computer recognizes as program instructions. Virtually, everything in computer processing is a function of handling bits in specific size groups, defined as specific data types. 1 ASCII characters use only seven bits. The eighth bit, called the parity bit, was originally reserved for error checking. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 80 8/4/09 1:53 PM Page 80 CHAPTER 4 All that we see and hear from the computer is really just a marvelous expression derived from binary math. Computer science has built layer upon layer of functionality over these fundamental concepts, so that the user and even the programmer seldom need to think of bits and bytes. Although an operating system’s “data type” refers to how bits are grouped into logical units, in application software “data type” refers to how data is used: as a text character, a date, a mathematical value, and so forth. Hereafter, when we refer to a data type, we will be referring to the application-level definition. Databases Thus far we have discussed the operating system and application software in terms of its ability to store, retrieve, and process information. In computer systems, information that is input is called data. Data is stored in an arrangement H defined by the software to make it easy to identify and retrieve the data later. The structure defined by the application to hold the data is called a database. I Healthcare systems typically have numerous databases. A database can be structured inG any of many different ways, but before exploring different types of databases, let us first discuss some of the key concepts of data. G Characters S A character is the smallest unit of ,text data. Text characters (sometimes called alphanumeric characters) are limited to letters, numbers, a space, and punctuation marks as defined in the ASCII table shown in Figure 4-7. Some application software disallows certain punctuation marks; other software permits special Ssymbols such as © to be used as data. H Fields separate data into defined units Athat can be recognized later. For example, when you look at an envelope, your brain recognizes the street, city, state, and zip code by the way they are sepN arated and the order in which they appear. Similarly, a database may have separate fields for the street address, the city, state, and zipI code. Storing data in defined fields not only allows the application software to retrieve and redisC play the data in the correct form, but it also allows the software to find and process pieces of data quickly. For example, having the zipQ code in its own field would make it possible for the application to sort and print addresses in zipUcode order. A Fields FIGURE 4-7 Decimal values for alphabet characters in the ASCII table. Alphabet Portion of the ASCII Table (abridged) Value Char. Uppercase Value Char. 75 K 1 1 0 5 T S Value Char. Value Char. Value Char. 86 V 95 e 106 p 87 W 96 f 107 q 88 X 97 g 108 r 89 Y 98 h 109 s 90 Z 99 i 110 t 100 j 111 u 101 k 112 v 65 A 76 L 66 B 77 M 67 C 78 N 68 D 79 O 69 E 80 P 70 F 81 Q 71 G 82 R 91 a 102 l 113 w 72 H 83 S 92 b 103 m 114 x 73 I 84 T 93 c 104 n 115 y 74 J 85 U 94 d 105 o 116 z Lowercase Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 81 FUNDAMENTALS OF INFORMATION SYSTEMS 81 Fields not only separate data into logical groups, but define the type of data in the field as well. Some basic field types are alphanumeric (text), numeric, and dates. Numeric fields are further defined as integers (whole numbers) or decimal numbers such as money. Field types help the computer display and process the data correctly. For example, to print a report in chronological order, the computer needs to know that the number in a date field represents year, month, and day. When printing the amount field on the patient bill, the computer needs to know that the value in the numeric field is monetary and should be printed with two decimal places. Records The next level of a database is a record. Records are made up of a group fields about a specific thing. For example, an address record may contain the fields for street address, city, state, and zip code. One record would hold the address data for patient Gloria Green; a separate address record Hcould have thousands of address would hold the address data for Rosa Garcia. The database records for thousands of patients, but each record would have I the same group of fields, arranged in the same order. G type of record can be made up of A database will have many different types of records. Each different fields, arranged in a different order, for a different purpose. We have discussed a record G type for a patient’s address, but the database also has a record type for the patient’s insurance S information, and yet another record type for the patient’s visit. Although spreadsheet programs are far simpler than the, databases in healthcare, if you are familiar with Excel® you may be able to visualize the concepts of fields, records, tables, and files. For example, Figure 4-8 shows an Excel file containing patient information. Think of rows 2, 3, and 4 as records of data—one for each patient. Think of the S columns as fields. Notice how each record has the same number of fields, even if there is no data. For example, Mr. Baker has no midH dle name, but the place for the middle name is reserved. A N How are records stored? Some databases are a collection of many separate files, each holding a I certain type of record. Other databases store all types of records in one or more large files and then define tables to group records of the same type together.CSeveral data tables are shown later in Figure 4-10. Q DATA DICTIONARY Figure 4-8 was intended merely to provide a visual concept. A database U would not usually have the field names in the data table. Fields and tables are defined elsewhere in the database or application and are referred to as the data A dictionary. Files and Tables 1 1 0 5 T S FIGURE 4-8 Excel spreadsheet of patient information. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 82 8/4/09 1:53 PM Page 82 CHAPTER 4 Patient Info Table Field Name Len. Data Type Pat_# 12 Integer Last_Name 22 Alpha First_Name 15 Alpha Middle_Name 15 Alpha Birthdate 10 Date Patient Address Field Name Pat_# Address City State Zip Field Name Pat_# Encounter_# Date Time Provider_# Field Name Provider_# Last_Name First_Name Middle_Name Credentials FIGURE 4-9 HLen. I 12 G25 G25 S2 , 10 S Patient Visits HLen. A12 N15 I 10 C5 Q4 U AProvider Info Table Len. 112 122 015 515 T10 S Data Type Long Integer Alpha Alpha Alpha Alpha Data Type Long Integer Double Date Alpha Integer Data Type Integer Alpha Alpha Alpha Alpha Data dictionary tables. The data dictionary defines the field name, the maximum length of data the field can hold, and the type of data the field will contain. It also defines the record layout; that is, the order of the fields in the record. Figure 4-9 illustrates a data dictionary for the tables used in Figure 4-10. Figure 4-10 illustrates the data from four different tables. The columns represent the fields, and the rows represent the records. Each table holds a different kind of data. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 83 FUNDAMENTALS OF INFORMATION SYSTEMS 83 Patient Info Table Pat_# Last_Name First_Name Middle_Name Birthdate 59301 Garcia Rosa Marie 19781229 18889 Green Gloria Leigh 19511202 1398 Baker Harold 19680118 Patient Address Table Pat_# Address City 59301 1301 Paces Ferry Rd Atlanta State Zip GA 30339-1301 Pat_# Encounter_# Date 59301 100875 20071220 HGA I GA G G STime , 09:00 59301 111219 20080211 11:15 59301 120547 18889 1398 3529 Cobb Dr Smyrna 9856 Peachtree Rd Atlanta Patient Visits Table Provider_# 1 2 3 FIGURE 4-10 30080-3529 30305-9856 Provider_# 1 2 S16:30 1 H Provider Info Table A Last_Name First_Name Credentials NMiddle_Name I Carl Jones Clive MD CAnn Smith Marsha ARNP Q Lopez Roseanne MD Data tables for patients, addresses, U encounters and providers. A RELATIONAL DATA 20080601 1 The data dictionary may also indicate the relationship between records in 1 to be very efficient. Long pieces one table to related records in another. Databases are designed of information that will be used many times can be stored once, and referenced only by an ID 0 field that takes less space to store. Two examples of this can be found in Figure 4-10: 5 䊏 䊏 The HIS registration system has assigned each patient a unique ID number (stored in the T do not need the entire name, only first field). The Patient Address and Patient Visits records the patient ID. Each time the application reads an address S or visit record, it can automatically retrieve the patient’s name from the related Patient Info record. A second example, similar in concept, is that the Patient Visits records do not need to repeatedly store the full name of the doctor in every encounter record. It is only necessary to use an ID field that relates to a table of providers in the practice. Virtually all healthcare information systems use relational databases. Well-designed relational databases store information efficiently, retrieve data very quickly, and expand easily as the organization’s data grows. Figure 4-11 illustrates how data from the different database tables in Figure 4-10 is used when printing a patient statement. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 84 8/4/09 1:53 PM Page 84 CHAPTER 4 FIGURE 4-11 Information from different database tables is used to print a patient’s bill. P.O. Box 811 Atlanta, GA 30305-0811 PHONE (404) 555-2010 TO Patient ID 59301 DATE Patient May 31, 2010 Rosa Garcia 1301 Paces Ferry Rd Atlanta, GA 30339-1301 Database DESCRIPTION Visit Records Provider DOCTOR AMOUNT 05/16/2010 Extended Office Visit (Est. Patient) Clive Jones, MD 70.00 05/23/2010 Brief Office Visit (Est. Patient) Marsha Smith, ARNP 45.00 Address H I G G S , SUBTOTAL Patient is responsible for balances not paid by insurance FIGURE 4-12 Photo of wildflowers (inset) enlarged to show pixels in one flower. STATEMENT GOOD HEALTH ASSOCIATES BILLED TO INSURANCE TOTAL DUE NOW 115.00 115.00 .00 S H Images A Information stored in a healthcare system is not limited to the ASCII data we have discussed so far. Images that are used to diagnoseN the patient such as x-rays, MRIs, and CAT scans as well as scanned images of paper documents Iare also part of the patient’s record. Images are captured and stored using different sets of standards. The DICOM (Digital Imaging and Communication in C images. Typical standards for photographs and scanned Medicine) standard is used for diagnostic documents include these three: Q 䊏 JPEG (Joint Photographic Experts U Group) 䊏 TIFF (Tagged Image File Format) A 䊏 PDF (Portable Document Format). 1 1 0 5 T S Conceptually, medical image files are made up of data similar to the photographs you take with your digital camera, except they are higher quality. A digital image consists of millions of dots, too small to see. In Figure 4-12 a portion of a digital photo is magnified to show the dots. Whereas the smallest unit of ASCII data is a character (one byte), the smallest unit of an image is a pixel. A pixel represents the color, brightness, and contrast of a single dot in the image as a number. The amount of detail that can be seen in a digital image is a factor of the number of pixels (dots) per inch, and the number of bits used for each pixel. (Pixel size was discussed in more detail earlier in the Bits and Bytes—How Computers “Think” section.) IMAGE STORAGE: FILE OR BLOB Images can contain millions of pixels, making the amount of data enormous. Some of the image standards listed Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 85 FUNDAMENTALS OF INFORMATION SYSTEMS 85 above permit the data to be compressed for storage and then restored to near original quality for viewing. Some of the standards keep the image in its original size and do not compress it, making the file size very large. Diagnostic and radiology images are typically stored in a Picture Archiving and Communication System (PACS) or a Radiology Information System (RIS) computer. Some healthcare systems store images of scanned documents in the same system as the patient’s electronic chart, whereas other systems use a separate computer for document image storage. Images are binary data, but not ASCII data. Images vary in size, can be very large, and therefore do not fit well in the records and fields of the types of databases we have studied so far. There are two popular techniques for storing and retrieving images. Both methods use the database to catalog information about the image such as the patient, date, type of image, and a description. A field in the catalog record also indicates where the image is located. In the first method, systems keep images as individual files on a hard drive, CD, or DVD. The database catalog records include a field containing theHpath (location) to the image files stored on the disk drive so the image can be accessed when desired. I The second method is to set up a portion of the database to hold binary large objects (BLOBs). Image data can then be stored directly in the database (though separate from the G data stored in fields). When an application requests the image, the database retrieves the G BLOB. The database recognizes that it is not data from a field and passes it on to the requestS ing application. Image systems can also store many other types of digital information including audio or , video files. S H A a mainframe. Users had screens In the early days, hospitals had a single giant computer called and keyboards called terminals, but all of the computer processing N was done by the mainframe. Today healthcare organizations of all sizes have hundreds of computers connected together as a I network. Networks allow computers to seamlessly pass information C to one another and to share resources such as printers, scanners, application software, and central disk storage. Networks Q in the operating system. There require special hardware and software, some of which is included are several types of networks and many types of network software. U Here we discuss but a few that are found in healthcare. A Networks Network Hardware Networks require a network card for each computer (some newer 1 computers have this built in). A network router is also required. The router is also sometimes called a hub or switch. It identifies 1 each computer on the network and manages the flow of information throughout. Network cables, wires specially manufactured to handle data at high speeds, are 0 run from the router to each computer. (Wireless networking is also used, as discussed in a later section.) 5 T Clients and Servers Most healthcare organizations set up networks to allow manyScomputers to share the information stored in one or more large databases. This is called a client/server configuration. The desktop computers throughout the facility need only a portion of the software (called the client) and rely on a main computer (called a server or host) to store, process, and retrieve the data. Generally, the server is a larger, more powerful computer than the client computers, but its function is passive. That is, it waits for requests from the client, and then serves the requested data to the client. The client can be a typical desktop computer, a laptop, or a Tablet PC or other portable device. The client sends requests and waits for replies from the server. A familiar example of this is e-mail. The application software you use to retrieve, write, and send e-mail messages is the client. Each time you receive or send a message, your computer is communicating with an e-mail server. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 86 8/4/09 1:53 PM Page 86 CHAPTER 4 H I G G S , S FIGURE 4-13 Multiple servers H at a large inpatient facility. A N Each client workstation in a healthcare facility typically communicates with multiple servers. Some examples might include a registration server, a clinical information system server I (for medical records), image servers, e-mail servers, application servers, and print servers. C at a large inpatient facility. Figure 4-13 shows a number of servers Q Local-Area Networks U Local-area networks (LANs) are computers that are connected by a network serving just the organization or facility in which they A are located. Each computer on the network is called a node. A LAN allows computers to share printers, files, and other resources in common. The cables and switches used in a LAN allow for high-speed transfer of information within the net1 and can be designed to keep the data very secure. work. A LAN can be managed locally 1 0 similar to a LAN except that they cover larger geoWide-area networks (WANs) function graphic areas. To do so, the WAN 5 typically uses telecommunication lines to connect two or more LANs into one large private network. The phone company provides a secure connection that prevents computers not on the T WAN from accessing it. For example, a WAN might beSused where a hospital owns several healthcare facilities Wide-Area Networks that are miles apart. It would be too expensive for the hospital to run its own wires that distance, so the hospital would lease high-speed telephone lines to connect the LAN at each facility into one large network. Given permission to do so, any node on the network could communicate with computers at all of the other facilities as seamlessly as if they were in the same LAN. A WAN may not transfer data as quickly as a LAN because the portion of the network using the phone lines may limit its speed. This is partially because the point at which the LAN connects to the phone lines can act as a bottleneck when large amounts of data are being sent over the WAN, and also because the cost of the phone lines will be based on their quality and capacity. Businesses have to balance the expected normal usage of the WAN with their budget. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.qxd 8/22/09 5:04 PM Page 87 FUNDAMENTALS OF INFORMATION SYSTEMS 87 Several types of telecommunications are available for a WAN. The two most prevalent are leased line, point-to-point connections, or frame relay. Frame relay uses a computer node at the phone company to securely send the data transparently through the phone circuits to a node near the other end of the WAN. Frame relay is cheaper for a geographically large WAN because the business leases a point-to-point connection only as far as the phone company node. Internet LANs and WANs are private networks that can be accessed only by the users in that network. In contrast, the Internet is a worldwide public network that can be accessed by any computer anywhere. Most people know about the Internet because of the services they use on it such as e-mail, research, games, and web pages; however, it is also used to exchange data. The Internet was created by interconnecting millions of smaller business, academic, and government networks. It is a very large network of networks, functionally similar to the other types of networks we have discussed. H I in common. Networks use a Different types of networks have certain things protocol or set of rules for how they are to communicate on the network. Networks also assign a G unique ID or number to each computer on the network. Although several standard protocols are in use for variousG LANs, the entire worldwide Internet uses one specific protocol: TCP/IP, which stands for Transmission Control Protocol/Internet S Protocol. The TCP/IP protocol is now also commonly used for LANs and WANs. The difference between the Internet and other networks, is seen in how the Internet works. When a LAN or WAN is represented in a schematic design, lines connect each node of the network to the hub/switch or router. In contrast, the Internet is represented in the schematic as a S one side and out to its destination cloud (as shown in Figure 4-14) because information goes into without relying on any predefined circuit. H To help you understand how this works, let us compare the post office and the phone comA establish an electrical connection pany. When you make a phone call, the wires and circuits must PROTOCOLS N I C Q U A DMZ Server Router Hub/Switch Firewall Internet FIGURE 4-14 Drawing of a network configuration. 1 1 0 5 T S Wireless Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 88 8/4/09 1:53 PM Page 88 CHAPTER 4 with the phone of the person you are calling before their phone rings and the call can go through. When you write a letter, you address the envelope and deposit it in the mailbox. You don’t know how the post office will transport it or what roads the trucks will take, but in the end it is delivered to the address on the envelope. The Internet Protocol encloses data in packets that have an address on them. The packets are sent through the various networks making up the Internet until they arrive at their address. Figure 4-14 is a drawing of a LAN configuration. Each workstation is connected to the router, which is sometimes also called a hub or switch. The black connecting lines represent cables or wires that are run throughout the facility. Each server is also connected to the router. Figure 4-14 also shows that the network is connected to the Internet. The Internet is shown as a cloud. Two components shown at the top of the figure are used to secure the network. The first is the firewall. This may be a special device, a component of the router, or a dedicated computer. The firewall screens packets coming in from the Internet. The firewall can be set up to limit connections to only certain networks, Hcomputers, or TCP/IP ports. The second level of protection is the server at the top labeled DMZ. This is a computer that I or be used to send messages out of the network but which can provide information to the public cannot be used to access the hospital’s G internal network from outside. G The flexibility of the Internet protocol and its ability to get information to and from almost any point in a worldwide network obviously has a lot of potential S for healthcare. Providers can access their patients’ charts, communicate with patients, transmit , medical images, and work from anywhere. However, the Internet is not very secure. The packets of data pass through many computers and networks on their way to their destination. They can be copied, opened, and read by anyone with enough technical savvy. S so we can use the accessibility of the Internet, but protect How do we secure the information the information? Two ways of doingH this are to use a secured socket layer (SSL) or a virtual private network (VPN). Both of these rely on encrypting the transmission. There are other secure A transmission schemes not covered here. SSL adds security to HTTP (Hypertext N Transfer Protocol) web pages, sending only encoded data within the packets, and then decrypting it when it is received to display the web page. This I prevents anyone intercepting the transmitted packets from making sense of them. SSL, however, is limited to the type of things you can C do on a web page. Some providers and organizations want to run software that is on their network computers Q from home or elsewhere. As we discussed earlier, the most secure method would be a point-toU However, if that is not possible or if the provider is not point connection to the hospital’s network. always accessing the network from the same location, a VPN may be used. A The VPN uses the Internet to transport packets of data, but it has its own software that encrypts and decrypts the packets between the sending and receiving systems. The VPN also verifies the identity of the person signing 1 on, ensuring access only to those who are permitted to use the system. A VPN is not limited to web pages and may be used to secure the data being trans1such as an electronic health record system. mitted for other application software, SECURE REMOTE ACCESS 0 5 Remote access today both in and out of the office includes wireless devices that access the netT networks are connected to the LAN through a radio transwork while the user is mobile. Wireless ceiver called an access point, which S is actually wired to the router like other network nodes. Wireless Networks The portable device has a built-in radio transceiver and a unique ID. When it is near an access point, it sends packets of data using Wi-Fi, a high radio-frequency. The access point receives the packets and sends them along on the network. Where there are multiple access points, the closest point automatically takes over transmissions, as the user walks from one location to another. Figure 4-15 illustrates the coverage area of an office with multiple access points. The red lines indicate the wired LAN cables connecting the computers and access points. The overlapping teal and lavender circles represent the range of radio signals from each access point. The laptop computer in the exam room is communicating with access point 1 due to its proximity. If the laptop were moved to one of the other exam rooms, access point 2 would automatically take over the connection. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 89 FUNDAMENTALS OF INFORMATION SYSTEMS FIGURE 4-15 office. 89 H I G Access points of a wireless network in a medical G S , Printers and Reports S In addition to sharing files and data, one of the main resources shared on a network are printers. H Despite the move toward electronic records, healthcare organizations are anything but paperless. There is a frequent need to print orders, reports, and forms throughout the facility. The ability for A a networked computer to send output to a printer that is not directly attached to it has many N advantages, including these: 䊏 䊏 䊏 䊏 I Saves the cost of attaching a printer to every computer. Saves the desk space attached printers would occupy. C Allows the use of faster printers with more features thatQ would be too expensive to buy for individual workstations. U Saves time because, rather than printing a report in one department and carrying it to A right in the other department. another, it is possible to sent the output to a printer located Many larger printers have their own network card, allowing them to be connected directly to the LAN without being connected to a workstation. However,1printers that are connected to workstations may also be used as network printers if the workstation is configured for this. 1 Report Server 0 Because reports make up a large portion of what is printed,5we will discuss a related topic: the report server. The advantage of the large relational databases we discussed earlier in this chapter T purposes. For example, patient is that they contain a great deal of data that is useful for reporting records contain information such as the dates the patient was S seen, the procedures that were billed, the amount paid by insurance, and the amount outstanding. This data, gathered from all of the accounts, is then used to produce monthly financial reports, length of stay reports, and billing and productivity reports, to name just a few. The report does not exist as organized data. To generate the report, the application software queries the database and begins collating and sorting data from fields within relevant records returned from the server. Finally, the organized data is formatted with headings and columns and sent to the printer as the finished product you see when you look at a report. When an organization runs a lot of large or complicated reports, the gathering, sorting, and printing of the reports can impact the performance of the database server. To minimize this, some applications make use of a report server, a computer that is used only for the generation of Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.qxd 90 8/22/09 5:04 PM Page 90 CHAPTER 4 reports. The database server is still queried for the relevant data records, but that information is copied temporarily to the report server, which handles the sorting, organizing, and printing of the report. Because the data in the report server is only a temporary copy, it is deleted when the report is finished. Cold Businesses are required to keep copies of a large number of financial and compliance reports generated every month. Over time these records require a lot of storage space, so many organizations choose to keep those reports in a computer document imaging system of the type discussed earlier for use with patient records. Organizations that intend to store reports in a document image system can do so without printing and then scanning them by using some type of COLD (computer output to laser disk) software. Rather than printing a paper copy, COLD software captures the printer output and converts it into an image file, exactly asHit would appear on the piece of paper. The file is archived onto an optical disk (CD or DVD) for permanent storage. I Computer systems can also achieve similar results using software other than COLD. One example you may be familiar with isG the PDF or Portable Document Format. If you participate in online banking services, you may be able to download your bank or credit card statement as a G PDF file. In these examples, the bank may not be printing the statement you download, but rather S statement directly into a PDF file. their computers output an image of your , Interoperability Standards S The ability of various software systems to communicate with each other and to share data saves H information in multiple systems. Where group medical the time and effort of reentering the same practices often use software from only one or two vendors the ability to share data within the A application is assured. However, it is not uncommon for larger organizations such as hospitals to N by various vendors. have from 60 to 600 software applications Whereas the network protocols I we have discussed so far enable the workstations and servers to exchange packets of data, nothing in the protocol has defined the content of those packets. Similarly, the databases weCdiscussed defined the data in fields and records and data types, but nothing assured that the data Q in one database could be understood by another application or database. Uinformation industry has created standards that define the To solve this problem, the health exchange of patient and medical data Abetween applications. To facilitate the interoperability of diverse systems, vendors who create application software must support and adhere to the standards. Two concepts important to interoperability of healthcare systems are data elements and HL7. 1 1 One might confuse the term data elements with fields or records that hold data, but the concept 0 to paper records as well as computer records. Data eleis broader. The term data element applies ments do not define the layout of the5database, but rather are a broad set of standards that establish what types of information health systems ought to keep. For example the patient’s address is T one of the standard data elements. However, we see in Figure 4-10 that the address is divided into four fields. A different database might use six fields for the address, but it would still be considS Data Elements ered one data element. Including standard data elements in a database design makes it likely that the application will have data similar to other systems. This not only improves interoperability but provides common elements for system-wide reports. Data Sets A data set is a list of data elements collected for a particular purpose. For example, an admission record would need all the data elements of the patient demographics, insurance information, next of kin, and so forth. In a paper system, this would be done by making sure the paper form contained all of the appropriate boxes and that they were filled in correctly. Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 91 FUNDAMENTALS OF INFORMATION SYSTEMS 91 In an electronic system, many elements of the data are entered only once, and then assembled into the data set as needed. For example, the patient demographics, insurance information, and next-of-kin information would be retrieved from the patient registration system without reentering the data. Usually a healthcare data set represents the minimum list of data elements that must be collected. Examples of standard data sets in healthcare will be discussed in Chapter 5. HL7 As you learned in Chapter 2, HL7 stands for Health Level Seven, a nonprofit organization that developed and maintains the leading messaging standard used to exchange clinical and administrative data between different healthcare computer systems. The acronym is also used as the name of the standard itself. HL7 specifications are independent of any application or vendor; therefore, applications that can send and receive HL7 messages can potentially exchange Hinformation. If a hospital has one vendor’s system for registration and another vendor’s radiology system, the simple act of transferring patient information from the admissions office to theIradiology department would not be easy without HL7. G Of course, HL7 goes much further than specifying the communication of patient admission, G registration, and discharge information. It includes a wide range of clinical information mesS of orders, lab results, radiology sages. As such it is the primary standard for the communication reports, clinical observations such as vital signs, and many other types of clinical data maintained , in the patient’s record. HL7 has been successful because it is very flexible both in its structure as well as its support for multiple coding standards. Healthcare systems use codes Sin place of text in many database fields. Procedure codes, diagnosis codes, lab test codes, and many other types of codes not only save H there are uniform standard codes space but ensure accurate interpretation of the data later. Although for some types of data, multiple code standards are being used Afor other types of data. Therefore, when a message is received, the codes and terms used by the other system may not match those used N message that contain coded data by the receiver. To overcome this problem, segments of the HL7 also identify what coding standard is being used. A special computer program called an HL7 transI lator is used to match the codes in the message with the codes used by the other application. The translator can also reconcile differences between two systemsC using different versions of HL7. Q U One of the main challenges in a large HIS department is to maintain the interoperability between multiple systems. For example, cross-reference tables are used Ato reconcile differences in the way Maintaining Interoperability various systems codify data. One database might assign a unique code to each provider; another might use the doctor’s Social Security number. As data is exchanged, a table of providers would 1 to provider record in that syshelp each application correctly match the ID for a patient’s doctor tem. When a new provider joins the practice, not only must 1 that person be added to every database, but to the cross-reference table as well. 0 regularly update their software This seems complex enough, but application venders also to new versions. Often the update involves changes to that5application’s database. Every new version must be tested to ensure that it will not fail. The HIS department must then analyze T any proposed database changes to ensure continued compatibility with the 60 or so other applications already running on the network. Healthcare organizations that use multiple venS dors typically have a separate set of computers used to test software changes without risk to daily operations. CCOW CCOW stands for the Clinical Context Object Workgroup, a subset of HL7. Like HL7 its acronym is used for the name of the group and the standard that the group developed. The purpose of the standard was to develop a means by which a facility that used applications from several different vendors for their electronic health record could make it easier for the users. For example, if one brand of software is used for the chart, but a different one for prescriptions and yet a third for writing lab orders, clinicians would have to log into three different applications Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 92 8/4/09 1:53 PM Page 92 CHAPTER 4 and search for the same patient in each application before they could record the encounter and orders. When CCOW is implemented, the user logs in once. When the user changes applications, the user is automatically logged into the new application and the patient, provider, and clinical encounter are automatically selected. This is called context management. Although CCOW makes things simpler for the end user, implementation is very difficult. Each vendor’s application software must be specifically written to enable CCOW, and the HIS department must set up special servers to handle the CCOW functions. CCOW is usually only found in inpatient settings, particularly teaching hospitals. Communication Systems Thus far we have discussed systemsHused for the patient and business records of a healthcare organization. Equally important, however, are the communication systems used by the staff in the I healthcare facility. A REAL-LIFE STORY G G S , A Look Behind the Hospital Network S H Craig Gillespie is a network specialist at a large hospital connected Ato multiple remote facilities. N stored on a SAN (storage area network) with a RAID 5 (redunI array of independent disks) with redundant connections all ur hospital has a variety of computer systems and operating dant systems linked not only by our internal LAN but also by a high- the C way through. Should a hard disk become damaged, this type speed WAN, which connects the main hospital to our downtown of configuration would allow us to swap out a disk drive without Q bringing the system down. business office and a couple of our other medical facilities. even Our network uses a Cisco backbone and multiple Cisco routers. U Finally, of course, we regularly back up the systems. Our Our servers include IBM AS 400s running IBM’s proprietary O/S 400 backup system uses a Robot tape library with eight drives in it. operating system; IBM P series running AIX; and a number of Intel- A With so many different applications in our facility, there are By Craig A. Gillespie O based servers running Red Hat Linux. Our PACS (Picture Archiving and Communication System) runs on a Sun system (Unix). The dietary department is using an application that runs on a Novell network and a few other applications that run Citrix. Oracle is the principal database our applications use. As the amount of data increases, the database grows in size. We usually have to manually increase the extent of the database about every five months. This is usually just because of the indexes. Because I don’t like taking our system down to rebuild indexes, I would rather grow it a little bit and wait until the system is down for something else to rebuild them. From a pure IT point of view, as a system administrator and database administrator, it doesn’t matter to me what the application is. What matters is how important is it; what are the response time requirements; and what can I do to make sure those happen? There are several things we do. First, a few of our systems are mirrored. That means the data is constantly written twice to two different systems, so if one goes down the other has the same up-to-the-minute data. In addition, the most important are things we can do to help the teams that support those applications as well. For example, the database, operating system, network, and many of our applications create log records of certain events, such as user logon, connections, error messages, and so forth. When an application team identifies certain errors or conditions they need to be alerted to, I use script languages to write little programs to scan the logs checking for certain things outside of the standard application area. When the scripts find something, the team can be alerted. When I talk to people who are interested in what I do I say, “Why don’t you try a little project at home to see if this kind of work is for you?” Take an old computer, purchase a copy of Red Hat Linux (a low–cost, Unix-type operating system), and build a proxy server or a mail server. This exercise will get you involved enough to have an understanding of what is going on. If you’re still interested, then try a little web development and some degree of programming. You don’t have to write a program, but learn enough to understand what is happening behind the scenes. These are suggestions to help you find out if the technology side of IT interests you. 1 1 0 5 T S Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 93 FUNDAMENTALS OF INFORMATION SYSTEMS 93 E-Mail Systems E-mail has become a primary communication tool in all types of businesses. The IT department has responsibility for the hospital’s e-mail system. These responsibilities include managing a mail server, assigning user e-mail addresses, managing e-mail record storage, and protecting the system from viruses and malicious software that can affect workstations, other servers, and the entire network. E-mail was used earlier in this chapter as an example of a client/server architecture. The e-mail program on the workstation is the client, sending and receiving messages to the e-mail server. The e-mail server is typically set up to communicate through a larger server outside the network, called a mail host. Like other components of networks, e-mail systems use a protocol. Several different protocols are available for e-mail. SMTP (Simple Mail Transfer Protocol) is the standard for sending messages; however, it cannot be used to retrieve messages. E-mail is retrieved from the mail host using either IMAPH (Internet Message Access Protocol) or POP3 (Post Office Protocol, version 3). I 䊏 䊏 IMAP holds messages on the host server until they are specifically deleted by the user. G POP3 holds messages on the mail host server, deleting them G from the host server once they are downloaded. S Most healthcare facilities use POP3 to retrieve e-mail from a host server operated by an , in the hospital’s e-mail server. Internet service provider (ISP). The downloaded e-mail is stored The typical hospital user’s e-mail client communicates only with the hospital’s e-mail server, not the mail host at the ISP. This arrangement helps shield the hospital’s e-mail system from the S public Internet. H Telecommunications A Historically, responsibility for a facility’s phone systems was assigned to engineering, physical N plant, or another department. Increasingly, however, telecommunications systems are becoming I the responsibility of IT departments. This makes sense for several reasons: 䊏 The phone switching systems are now computer based, C requiring IT expertise to manage them. Q 䊏 As organizations upgrade the wiring in their facilities, many are eliminating phone wires U and opting to use VoIP (Voice-over-Internet Protocol). VoIP uses special phones that provide phone service by sharing the computer network. A 䊏 The increase in wireless devices, including pagers, cordless intercoms, and medical telemetry devices, is more easily managed by one department than by several. Chapter 4 Summary The Technology behind Health Systems 1 1 0 5 T instructions that enable us to work. Operating S program systems and network software control computer hardware, Computer systems are generally discussed in terms of two components: hardware and software. Hardware refers to the components you can physically see and touch: the computer, circuit boards, computer chips, monitor screen, keyboard, mouse, cables, wires, printers, and so forth. Software refers to the operating system and application programs, which provide instructions to the hardware to process the information the computer receives and stores; that is, computer software gives functionality to the computer hardware, making it useful. Software consists of input/output devices, and communications with other computers. Application software allows us to perform specific tasks on a computer such as write a letter, enter a medical record, view an x-ray, send an e-mail, or order a medication. The fundamental unit of modern computing is called a bit. Bits are grouped together in logical units, the most common of which is called a byte. There are eight bits in one byte. Bits have a value of 0 or 1. When they are Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 94 8/4/09 1:53 PM Page 94 CHAPTER 4 grouped together as a byte, the value of the byte can range from 0 to 256. Computers create alphabet characters by using the numbers 32 through 128 to represent letters, numerals, and punctuation marks. This is called the ASCII table. The smallest unit of text data is a character. Text characters (sometimes called alphanumeric characters) are limited to letters, numbers, a space, and punctuation marks. Bits are also grouped into larger units to represent large numbers, digital images, or other types of data. The smallest unit of a digital image is called a pixel. Pixels are typically comprised of 8 to 32 bits, depending on how many colors are represented by the pixel. Computer data is information that can be stored and retrieved. Data and programs are stored on the hard disk, optical disks, or temporarily in RAM memory chips. Programs and data are retrieved and processed by a computer chip called the CPU or central processing unit. Databases Data is stored on disk drives in files and databases. Databases store data in defined structures called tables. Tables have records. The records are made up of fields, which have a defined field type and format. Examples of field types include numeric and alphanumeric or text fields. Numeric fields can be further defined to hold specific types of data such as money or dates. Networks Multiple computers can be linked together into a network. This allows them to communicate with each other to share files and information. A computer network consists of hardware such as cables, network cards, routers or switches, and networking software, which is sometimes included in the operating system. Wireless networks allow portable devices to communicate with the network using a radio signal called Wi-Fi. Antennas called access points are connected to the computer network. As a user moves throughout the facility, the portable computer automatically switches to the access point with the strongest signal, dynamically maintaining the connection to the network. Printers and Reports Computer output devices include printers, screens or monitors, and COLD (computer output to laser disk) software. COLD software converts printer output directly into an image file, thus bypassing the steps of printing and then scanning the paper report. Interoperability Standards Data H is input into the computer using a keyboard, mouse, touch screen, microphone, camera, or scanner. Data can also Ibe directly transferred from another computer or medical device. For computers to exchange data, it is necessary for G the data to be in a format that both systems understand. In G healthcare HL7 is the most prominent interoperability standard used today. (This is different from the HIPAA transacS tions discussed in Chapter 3 that are used for claims billing, ,reimbursement, and insurance eligibility.) When a facility uses application software from many different vendors for their electronic health records it is necS essary to use HL7 to maintain interoperability between the H various applications. Even with HL7 in place the users may find A that they have to sign into several applications to record the information about one patient. One solution to the probN lem is to allow the user to sign in and select the patient once, Ithen to use CCOW to maintain the context while switching between applications. C Q Communication Systems U The communication systems used by the staff in the healthcare facility include e-mail systems and telecommunicaA tions, which are now often placed in the IT department. One important advancement in application software is a networking application that allows the computer network to replace 1 the hospital telephone system. The application is called VoIP 1 and eliminates the need for the facility to maintain two dif0 ferent sets of wiring. 5 T S Critical Thinking Exercises 1. Look at your personal or home computer (or a school computer if you do not have one of your own). What operating system is on your computer? Name at least three application programs on the computer. 2. See if you can determine how much RAM is installed in your computer or the school’s computer. What are the steps you used to determine this? Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 95 FUNDAMENTALS OF INFORMATION SYSTEMS 95 Testing Your Knowledge of Chapter 4 1. What does the acronym COLD stand for? 2. What part of the computer hardware only retains data while the computer is on? 3. How many bits are in a byte? 4. Describe the difference between computer hardware and computer software. 5. What type of data is stored in a PACS? 6. Is a document scanner an input or output device? 7. A character is the smallest unit of text data. What is the H smallest unit of image data? 8. A database record can have different types of fields. I Name three different field types. G 9. What is the difference between a LAN and a WAN? 10. What is the acronym for the Internet protocol? 11. Name two ways discussed in this chapter for sending information securely over the Internet. 12. What is the name of the standard by which computers define alphabetical, numerical, and punctuation characters? 13. What is the acronym for the software that allows computer networks to be used for telephone systems? 14. What is a BLOB used for? 15. What computer chip is sometimes called the “brains” of the computer? G S , S H A N I C Q U A 1 1 0 5 T S Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 96 Comprehensive Evaluation of Chapters 1–4 This comprehensive evaluation will enable you and your instructor to determine your understanding of the material covered so far. 1. The hospital emergency department is what kind of facility? a. acute b. subacute c. inpatient d. outpatient 2. What type of nurse can diagnose patients and write orders? a. triage nurse b. licensed nurse practitioner c. licensed vocational nurse d. doctor’s nurse assistant 3. An inpatient was admitted June 10 and discharged June 14. What was the LOS? a. 3 days b. 4 days c. 10 days d. 14 days 4. What does the acronym CIO stand for? a. computer input/output b. computer interpreted observation c. chief information officer d. chief complaint 5. Which group first established standards for hospital records? a. American College of Surgeons b. American College of Pathologists c. American Medical Association d. American Hospital Association 6. A user authorized to view records on a document image system must be a: a. Registered Health Information Technician b. Registered Health Information Administrator c. registered health nurse d. none of the above For each of the following allied health professions, indicate whether the job is clinical or nonclinical: 7. Clinical application specialist a. clinical b. nonclinical H8. Lab technician I a. clinical b. nonclinical G G9. Coding specialist a. clinical S b. nonclinical , 10. Cancer registrar a. clinical S b. nonclinical H 11. Diagnosis-related groups are used for: A a. point of care documentation N b. Medicare billing and reimbursement I c. patient assessment d. decision support C 12. Which of the following is not one of the four compoQ nents of the HIPAA Administrative Simplification U Subsection? A a. Privacy b. Security c. Transactions and Code Sets d. Conditions of Participation 1 1 13. HIPAA security standards are divided into three 0 categories. Which of the following is not one of those 5 categories? T a. Physical Safeguards b. Ambulatory Safeguards S c. Administrative Safeguards d. Technical Safeguards 14. Which of the following is a covered entity under HIPAA? a. pharmaceutical manufacturers b. government agencies c. healthcare providers d. medical device manufacturers 96 Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. M04_GART2674_01_SE_C04.QXD 8/4/09 1:53 PM Page 97 COMPREHENSIVE EVALUATION OF CHAPTERS 1–4 97 24. Which of the following is not an image file type? a. ASCII b. DICOM c. JPEG d. TIFF 15. HIPAA requires which of the following to disclose health records for TPO? a. signed informed consent form b. signed patient authorization form c. patient receipt of privacy policy d. U.S. government authorization 25. CMS “deemed status” means that Joint Commission accreditation is deemed to have met CMS condition of participation requirements. T. true F. false 16. HIPAA requires an authorization to release PHI to be signed by: a. the patient or personal representative b. a physician or nurse c. the medical administrator or office manager d. a notary public 26. The position of security officer is exclusively found H only in very large healthcare facilities. I T. true Write the full name represented by each of the following G F. false acronyms: G 27. A pixel is the smallest unit of text data. 17. PHI ________________________________________ S T. true 18. EDI ________________________________________ F. false , 19. HIM ________________________________________ 20. EHR ________________________________________ S 21. What type of the computer memory only retains data while the computer is on? a. ROM b. RAM c. CPU d. CRT 22. How many bits are in a byte? a. Two b. Four c. Seven d. Eight 23. A data dictionary defines: a. medical terminology b. field names and position c. communication standards d. clinical vocabulary 28. A single database record can have more than one type of field. T. true F. false H A 29. Group medical practices are considered ambulatory N facilities. T. true I C F. false Q 30. A physical exam must be performed on a patient within 72 hours of a hospital admission. U T. true A F. false 1 1 0 5 T S 31. The hospital CEO is in charge of all medical staff. T. true F. false 32. Hospitals start a new chart each time a patient is admitted. T. true F. false Health Information Technology and Management, First Edition, by Richard Gartee. Published by Prentice Hall. Copyright © 2011 by Pearson Education, Inc. Instructions: This assignment must be done in APA format. A minimum word count of 300 words (not including references) is required. A minimum of 3 references (with in-text citations) is required. Please make sure that scholarly references are used. If you have any questions please feel free to ask. 1. Using comparative analysis and Scholarly/Academict style writing the difference between a LAN and a WAN? Is there a difference between them and when would each be utilized? What are the benefits and downsides of each? Book Reference: Gartee, R. (2011). Health information technologyand management. Upper Saddle River, NJ: Pearson. Instructors Notes: • • In professional writing avoid using first person “I” and third person “we”, as they detract from the quality and turn professional researched statements into opinions. Instead of “I” use, for example, use “the writer, the author or the researcher”. Approved sources for this course include the course textbook and scholarly articles from the Bethel library databases. No other source information is acceptable.
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Health Organization Mission statement Strategic Plan Assignment

Health Organization Mission statement Strategic Plan Assignment

How to Write a Strategic Plan

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The three pieces of the puzzle are:

•Where are we now?

•Where are we going?

•How will we get there?

1 Where are we now?

As you think about where your organization is now, you want to look at your foundational elements (mission and value) to make sure there has not been a change. More than likely, you will not revise these two areas very often. Then you want to look at your current position or your strategic position. This is where you look at what is happening internally and externally to determine how you need to shift or change. You should review your strategic position regularly through the use of a SWOT.

These elements are as follows:

•Mission statement: The mission describes your organization’s purpose — the purpose for which you were founded and why you exist. Some mission statements include the business of the organization. Others explain what products or services they produce or customers they serve. Does your mission statement say what you do? Why does your organization exist?

-Vision statement: Your vision is formulating a picture of what your organization’s future makeup will be and where the organization is headed. What will your organization look like in 5 to 10 years from now?

•Values and/or guiding principles: This clarifies what you stand for and believe in. Values guide the organization in its daily business. What are the core values and beliefs of your company? What values and beliefs guide your daily interactions? What are you and your people really committed to?

2. Where are we going?

The elements of the question “Where are we going?” help you answer other questions such as “What will my organization look like in the future?”, “Where are we headed?”, and “What is the future I want to create for my company?” Because the future is hard to predict, you can have fun imagining what it may look like. The following elements help you define the future for your business:

•Sustainable competitive advantage: A sustainable competitive advantage explains what you are best at compared to your competitors. Each company strives to create an advantage that continues to be competitive over time. What can you be best at? What is your uniqueness? What can your organization potentially do better than any other organization?

3. How will we get there?

Knowing how you’ll reach your vision is the meat of your strategic plan, but it’s also the most time consuming. The reason it takes so much time to develop is because there are a number of routes from your current position to your vision. Picking the right one determines how quickly or slowly you get to your final destination.

The parts of your plan that layout your roadmap are listed below:

•Strategic objectives: Strategic objectives are long-term, continuous strategic areas that help you connect your mission to your vision. Holistic objectives encompass four areas: financial, customer, operational, and people. What are the key activities that you need to perform in order to achieve your vision?

•Strategy: Strategy establishes a way to match your organization’s strengths with market opportunities so that your organization comes to mind when your customer has a need. This section explains how you travel to your final destination. Does your strategy match your strengths in a way that provides value to your customers? Does it build an organizational reputation and recognizable industry position?

•Short-term goals/priorities/initiatives: Short-term goals convert your strategic objectives into specific performance targets. You can use goals, priorities, or initiatives interchangeably. Here, I use goals to define short-term action. Effective goals clearly state what you want to accomplish, when you want to accomplish it, how you’re going to do it, and who’s going to be responsible. Each goal should be specific and measurable. What are the 1- to 3-year-goals you’re trying to achieve to reach your vision? What are your specific, measurable, and realistic targets of accomplishment?

•Action items: Action items are plans that set specific actions that lead to implementing your goals. They include start and end dates and appointing a person responsible Are your action items comprehensive enough to achieve your goals?

•Scorecard: A scorecard measures and manages your strategic plan. What are the key performance indicators you need to track to monitor whether you’re achieving your mission?

Pick 5 goal related measures you can use to track the progress of your plan and plug them into your scorecard.

Execution: In executing the plan, identify issues that surround who manages and monitors the plan and how the plan is communicated and supported. How committed are you to implementing the plan to move your organization forward? Will you commit money, resources, and time to support the plan?

Strategic Plan Rubric

Mission, Vision , Values and/or guiding principles statements……..10 points
Sustainable competitive advantage……..10 points
Strategic objectives……..15 points
Strategy……..10 points
Short-term goals/priorities/initiatives……..10 points
Action items……..15 points
Scorecard (minimum of five (5) goal related measures….20 points
Execution……..10 points

Adverse Childhood Experiences and Lifelong Health Article Discussion

Adverse Childhood Experiences and Lifelong Health Article Discussion

#1 Define ACEs. #2 What 8 experiences are included in ACEs? #3 What new adverse experiences did Finkelhor add to

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previous scales? #4 What is the cost of childhood abuse and neglect annually in America? #5 What changes does the American Academy of Pediatrics recommend to address toxic stress? Is our health a matter of how well we are raised? EDITORIAL Adverse Childhood Experiences and Lifelong Health I N MORE THAN 60 ARTICLES SINCE 1998, INTERnist Vincent Felitti, MD, pediatrician Robert Anda, MD, MS, and others have studied the relationship of childhood adversity and a variety of lifelong physical and emotional outcomes.1,2 Using a retrospective study design, they surveyed 17 337 adult health maintenance organization members (average age, 57 years) about crucial events during childhood and linked those events in a dose-response manner with cardiovascular disease; cancer; AIDS, and other sexually transmitted diseases; unwanted, often-highrisk pregnancies; chronic obstructive pulmonary disease; and a legacy of self-perpetuating child abuse. While it is hard to believe, many medical and child welfare professionals did not see the links among child abuse and other common social problems with poor health and premature death in adulthood.3 See also page 70 These 8 adverse childhood experiences (or ACEs), as they have come to be called, include exposure of a child before age 18 years to emotional abuse, physical abuse, contact sexual abuse, alcohol/substance abuse, mental illness, criminal behavior, parental separation/divorce, and domestic violence. While there have been questions about the validity of the study design, studies using ACEs have moved to less affluent samples to fit within an accepted universal ecobiodevelopmental framework for understanding health promotion and disease prevention across the lifespan and are supported by recent additional advances in neuroscience, molecular biology, and the social sciences.3-9 In this issue, Finkelhor et al10 seek to improve on this conceptual model and strengthen our understanding of the relationship between childhood adversity and lifelong health. Using data from telephone interviews in 2008 combined with a nationally representative sample of 2020 US children in a study not designed to measure the ACEs (the National Survey of Children’s Exposure to Violence10), the authors obtained incidence and prevalence estimates for a wide range of childhood victimizations and other adversities. They performed a secondary analysis that reconstructed the traditional ACE items and found that the current ACEs do predict current stress among adolescents in a dose-related fashion. Adolescent stress is thought to be a crucial mediator linking ACEs with longer-term health problems and illness and is a likely predictor of long-term negative life events.11 The authors then posit that there are problems methodologically with the retrospective nature of the current ACEs, which also miss things we know are problems associated with adult adversity, such as poor peer relationships, poor school performance, poverty, and unemployment. They then add additional variables to the original ACEs to see what contributes more to psychological distress, choosing new items that have been suggested by relationships of child maltreatment with childhood stress in current research. These additional adverse experiences include having parents who always argue, being friendless, having someone close with a bad illness or serious injury, peer victimization, property victimization, and exposure to community violence. In their models, the authors found that the prediction of current childhood stress was significantly improved by removing some of the original ACEs and adding others in these domains. While this is encouraging, they conclude that “our understanding of the most toxic adversities is still incomplete because of complex interrelationships among them.”10 While there is no doubt that childhood adversity causes and/or contributes to adult adversity, the results of the study by Finkelhor et al10 do help us to better understand toxic stress during childhood and potential critical situations in which we can intervene as families, communities, and a society. Using a study design with more predictive ACEs that measure adversity during childhood will minimize memory error and bias to achieve a more accurate and comprehensive assessment of childhood events. We will then be able to better identify children and families at risk before there is childhood stress or other measurable harm. Finkelhor et al10 are correct to say that we know enough to move to intervention and prevention. The seemingly large costs of child abuse and neglect ($80 billion in the US in 201212) pale in comparison with the economic and human burden of adult poor health and premature death. Some have said “Fight Crime, Invest in Kids,”13 and our response needs to include more than reactionary child welfare and criminal justice responses. Why do we not offer counseling to all children with psychological maltreatment or exposure to domestic violence?14-17 We need to connect the dots in childhood and adolescent trauma to improve the response of all the first responders (including physicians), publicize that these experiences have JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 95 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 downstream poor medical and mental health outcomes, optimize and expand the treatments we know work, and increase public support for these interventions.18 More immediately, we should be appalled if future health care reform does not include universal home visiting for newborns and their families because this has been clearly shown to improve numerous child health and developmental outcomes. As pediatricians, we have unique roles in preventing the adverse consequences of toxic stress using routine anticipatory guidance that strengthens family social supports, encourages positive parenting techniques, and facilitates a child’s social, emotional, and language skills. We should start in our medical home with identification and intervention and then move out of the office and into homes, schools, and the community while advocating for a growing number of evidence-based programs. The American Academy of Pediatrics19 has recommended that we (1) adopt the ecobiodevelopmental framework, (2) incorporate the growing scientific knowledge linking childhood adversity with lifelong health effects into pediatric training, (3) be more proactive in educating parents and other child welfare professionals about the long-term consequences of childhood stress, (4) be vocal advocates for the development and implementation of evidence-based interventions that reduce toxic stress or mitigate its effects, and (5) have our medical homes strengthen anticipatory guidance and screening for children and families at risk, with development of innovative service-provision adaptations and local resources to address the risks of toxic stress. We can use the ACEs to identify children and families now who will suffer later if we fail to act. We need to act now as physicians, professionals, and community leaders to reduce childhood adversity and promote lifelong health. Vincent J. Palusci, MD, MS Published Online: November 26, 2012. doi:10.1001 /jamapediatrics.2013.427 Author Affiliations: New York University School of Medicine, Frances L. Loeb Child Protection and Development Center, Bellevue Hospital, New York, New York. Correspondence: Dr Palusci, New York University School of Medicine, Frances L. Loeb Child Protection and Development Center, Bellevue Hospital, 462 First Ave, Room GC65, New York, NY 10016 (Vincent.palusci@nyumc.org). Conflict of Interest Disclosures: None reported. REFERENCES 1. Centers for Disease Control and Prevention. Adverse Childhood Experiences (ACE) Study: major findings by publication year. http://www.cdc.gov/ace/year.htm. Accessed June 15, 2012. 2. Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245-258. 3. Weiss MJS, Wagner SH. What explains the negative consequences of adverse childhood experiences on adult health? insights from cognitive and neuroscience research. Am J Prev Med. 1998;14(4):356-360. 4. Dube SR, Williamson DF, Thompson T, Felitti VJ, Anda RF. Assessing the reliability of retrospective reports of adverse childhood experiences among adult HMO members attending a primary care clinic. Child Abuse Negl. 2004;28(7):729-737. 5. Anda RF, Felitti VJ, Bremner JD, et al. The enduring effects of abuse and related adverse experiences in childhood: a convergence of evidence from neurobiology and epidemiology. Eur Arch Psychiatry Clin Neurosci. 2006;256(3):174-186. 6. Flaherty EG, Thompson R, Litrownik AJ, et al. Effect of early childhood adversity on child health. Arch Pediatr Adolesc Med. 2006;160(12):1232-1238. 7. Ramiro LS, Madrid BJ, Brown DW. Adverse childhood experiences (ACE) and health-risk behaviors among adults in a developing country setting. Child Abuse Negl. 2010;34(11):842-855. 8. Shonkoff JP, Garner AS; Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics. The lifelong effects of early childhood adversity and toxic stress. Pediatrics. 2012;129(1):e232-e246. 9. Shonkoff JP, Richter L, van der Gaag J, Bhutta ZA. An integrated framework for child survival and early childhood development. Pediatrics. 2012;129(2):e460-e472. 10. Finkelhor D, Shattuck A, Turner H, Hamby S. Improving the Adverse Childhood Experiences Study Scale [published online November 26, 2012]. JAMA Pediatr. 2013;167(1):70-75. 11. Middlebrooks JS, Audage NC. The Effects of Childhood Stress on Health Across the Lifespan. Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; 2008. 12. Gelles RJ, Perlman S. Estimated Annual Cost of Child Abuse and Neglect. Chicago, IL: Prevent Child Abuse America; 2012. 13. Fight Crime. Invest in Kids. http://www.fightcrime.org/. Accessed June 15, 2012. 14. Cohen JA, Mannarino AP, Iyengar S. Community treatment of posttraumatic stress disorder for children exposed to intimate partner violence: a randomized controlled trial. Arch Pediatr Adolesc Med. 2011;165(1):16-21. 15. Layne CM. Developing interventions for trauma-exposed children: a comment on progress to date, and 3 recommendations for further advancing the field. Arch Pediatr Adolesc Med. 2011;165(1):89-90. 16. Palusci VJ, Ondersma SJ. Services and recurrence after psychological maltreatment confirmed by child protective services. Child Maltreat. 2012;17(2):153-163. 17. Perrin EC, Sheldrick RC. The challenge of mental health care in pediatrics. Arch Pediatr Adolesc Med. 2012;166(3):287-288. 18. Asnes AG, Leventhal JM. Connecting the dots in childhood and adolescent trauma. Arch Pediatr Adolesc Med. 2011;165(1):87-89. 19. Garner AS, Shonkoff JP; the American Academy of Pediatrics Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics. Early childhood adversity, toxic stress, and the role of the pediatrician: translating developmental science into lifelong health. Pediatrics. 2012;129 (1):e224-e231 http://pediatrics.aappublications.org/content/129/1/e224. Accessed June 15, 2012. JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 96 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 ARTICLE Improving the Adverse Childhood Experiences Study Scale David Finkelhor, PhD; Anne Shattuck, MA; Heather Turner, PhD; Sherry Hamby, PhD Objective: To test and improve upon the list of adverse childhood experiences from the Adverse Childhood Experiences (ACE) Study scale by examining the ability of a broader range to correlate with mental health symptoms. Design: Nationally representative sample of children and adolescents. Setting and Participants: Telephone interviews with a nationally representative sample of 2030 youth aged 10 to 17 years who were asked about lifetime adversities and current distress symptoms. Main Outcome Measures: Lifetime adversities and participants, but the association was significantly improved (from R2 =0.21 to R2 =0.34) by removing some of the original ACE scale items and adding others in the domains of peer rejection, peer victimization, community violence exposure, school performance, and socioeconomic status. Conclusions: Our understanding of the most harmful childhood adversities is still incomplete because of complex interrelationships among them, but we know enough to proceed to interventional studies to determine whether prevention and remediation can improve long-term outcomes. current distress symptoms. Results: The adversities from the original ACE scale items were associated with mental health symptoms among the JAMA Pediatr. 2013;167(1):70-75. Published online November 26, 2012. doi:10.1001/jamapediatrics.2013.420 T Author Affiliations: Crimes Against Children Research Center, University of New Hampshire, Durham (Drs Finkelhor and Turner and Ms Shattuck); and Psychology Department, Sewanee, the University of the South, Sewanee, Tennessee (Dr Hamby). HE A DVERSE C HILDHOOD Experiences (ACE) Study1 has attracted considerable scientific and policy attention in recent years, in part because it suggests that potentially preventable childhood experiences, particularly physical and sexual abuse and neglect, may increase a person’s risk for serious health problems and higher mortality rates much later in life. The study has demonstrated relationships between adverse childhood experiences and many adult health risks.1-10 These results, which have been published widely in the health sciences, are based on a survey and medical records of more than 17 000 members of the Kaiser Health Plan in San Diego, California.1,11 Nonetheless, research using the ACE Study model has some important limitations, in part because of the retrospective way in which data on childhood adversities have been gathered. The average age of respondents when they supplied information about their childhood experiences was 55 to 57 years. As a result, it is hard to be certain, particularly from such JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 70 a remote vantage, whether it is these particular childhood experiences or unmeasured covariates that are the most important predictors. In addition, the ACE Study list of preventable childhood adversities omits certain domains judged by many developmental researchers to be important in predicting long-term health and well-being outcomes. Among the predictors missing from the ACE Study model are peer rejection, exposure to violence outside the family, low socioeconomic status, and poor academic performance. For editorial comment see page 95 For example, longitudinal studies show that growing up in poverty increases lifelong risk for various negative life events and negative health outcomes.12-14 Peer rejection and lack of friends are associated with the development of many disorders.15-17 Poor school performance in childhood is associated with poor outcomes in adulthood, such as unemployment.18 Witnessing community violence has been WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Author Aff Against Ch Center, Uni Hampshire Finkelhor a Shattuck); Departmen University Sewanee, T Hamby). shown to be a mental health hazard for adults and children.19,20 These major childhood adversities are not currently measured by the ACE scale. In addition, measuring childhood adversities during childhood, rather than later, may offer other improvements to the ACE Study’s early life predictors of health outcomes.21 It allows the possibility of obtaining a more accurate and comprehensive assessment of childhood events than one would be able to obtain after many years. It also would allow a more sensitive untangling of the relationship among various adversities in ways that better explain causal sequences. Although an obvious disadvantage is the inability to assess the long-term effects of childhood adversity on the negative life events and health conditions posited in the ACE Study model, examining more short-term effects in childhood is consistent with the logic of the model. Specifically, the ACE Study model relies strongly on the idea that adverse childhood experiences create a burden of psychological stress that changes behavior, cognitions, emotions, and physical functions in ways that promote subsequent health problems and illness.22 Among the hypothesized pathways, adverse childhood experiences lead to depression and posttraumaticstressdisorder,whichinturncanleadtosubstance abuse, sleep disorders, inactivity, immunosuppression, inflammatory responses, and inconsistent health care use, possibly leading to other medical conditions later in life.23,24 Therefore, childhood behavioral and emotional symptoms verylikelyrepresentacrucialmediatorlinkingadversechildhood experiences and the longer term health-related problems found in the ACE substudies. Thus, in the present study, we tried to replicate the ACE Study findings in a cohort of youth, using psychological distress as an outcome measure, and to explore whether the adversities enumerated by the ACE Study could be improved upon by considering a more comprehensive range of possible adversities, including some of the domains not considered in the ACE Study. maining 1496 of the completed interviews. Sample weights were calculated to adjust for differential probability of selection associated with (1) study design, (2) demographic variations in nonresponse, and (3) variations in within-household eligibility. For this study, we analyzed a subsample of the entire sample of 4549 respondents. This subsample consisted of 2030 youth who were aged 10 to 17 years at the time of the interview and for whom complete data were available on the variables of interest. Analyses in this study are weighted by the sample weights. PROCEDURE A short interview was conducted with an adult caregiver (usually a parent) in each household to obtain family demographic information. One child was randomly selected from all eligible children living in a household by choosing the child with the most recent birthday. If the selected child was aged 10 to 17 years, the main telephone interview was conducted with the child. If the child was younger than 10 years, the interview was completed with the caregiver. However, the current analysis is based only on the 2030 youth aged 10 to 17 years who provided self-report information. Respondents were paid $20 for their participation. The interviews, averaging 45 minutes in both waves, were conducted in either English or Spanish. All procedures were approved by the institutional review board at the University of New Hampshire. RESPONSE RATES AND NONRESPONSE ANALYSES The cooperation rate for the random digit dialing crosssection portion of the survey was 71%, and the response rate was 54%. The cooperation and response rates associated with the smaller oversample were somewhat lower at 63% and 43%, respectively. These are good rates by current survey research standards.26-30 Although the potential for response bias remains an important consideration, several recent studies and our own analysis25 have shown no meaningful association between response rates and response bias.31-34 MEASUREMENT Victimization and Adversity METHODS PARTICIPANTS These analyses use data from the National Survey of Children’s Exposure to Violence (NatSCEV),25 a representative sample of US children and adolescents. The NatSCEV was designed to obtain incidence and prevalence estimates for a wide range of childhood victimizations and other adversities. The survey was conducted between January 2008 and May 2008 with a nationally representative sample of 4549 children aged 0 to 17 years living in the contiguous United States. Interviews with parents and youth were conducted over the telephone by the employees of an experienced survey research firm. The foundation of the design was a nationwide sampling frame of residential telephone numbers from which a sample of telephone households was drawn by random digit dialing. This nationally representative cross section yielded 3053 of the 4549 completed interviews. To ensure that the study included a sizable proportion of racial/ethnic minorities and lowincome respondents for more accurate subgroup analyses, there was also an oversampling of US telephone exchanges that had a population of 70% or more of African American, Hispanic, or low-income households. This oversample yielded the re- This survey used an enhanced version of the Juvenile Victimization Questionnaire, an inventory of childhood victimization.35-37 The Juvenile Victimization Questionnaire obtains reports on 48 forms of youth victimization covering 5 general areas of interest: conventional crime, maltreatment, victimization by peer and siblings, sexual victimization, and witnessing and exposure to violence.38 The survey also contains questions about adverse life events in the parent interview section and in a separate section on adversity. For the present study, which was not originally designed to test the ACE Study model, we selected victimization and adversity items in 2 steps. First, we used screener items and their associated follow-up questions to construct victimization types that most closely matched the abuse and neglect items in the original ACE Study, and we chose family background and adversity items to match the household dysfunction items of the original ACE Study. Using these items, we constructed a replication of the original ACE Study. In the second step, we selected additional types of victimization and adversity items not included in the original ACE Study but that are known to be important correlates of health and well-being outcomes. The measures selected in these 2 steps are described in the next section of this article. Important differences from the ACE Study items are noted in eTable 1 (http://www.jamapeds.com). JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 71 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Measures Used to Replicate Original ACE Study Items The following measures were coded 0 for no and 1 for yes so that they could be summed to create the replicated ACE Study items. All are lifetime measures. v Emotional abuse: One item asked respondents, “At any time in your life, did you get scared or feel really bad because grown-ups in your life called you names, said mean things to you, or said they didn’t want you?” v Physical abuse: Several screeners assessed the child’s experience of physical assault. Children who answered yes to any of these assault screeners were coded as having experienced physical abuse if the incident was perpetrated by parent, an adult relative, or another adult caregiver. v Sexual abuse: Four screeners asked about the child’s experience of sexual assault or attempted rape by a known adult, an adult stranger, or a peer or sibling. v Emotional neglect: Four questions about family social support were used to construct an indicator of emotional neglect. These items are shown in eTable 1. Total scores ranged from 4 to 16. Children whose family support score was 10 or lower were coded as having experienced emotional neglect. v Physical neglect: A single item asked whether the child had ever experienced a time when adults in his or her life “didn’t take care of them the way they should,” including not providing enough food, not taking them to the doctor when they were sick, or not making sure they had a safe place to stay. Children who answered yes were coded as having experienced physical neglect. v Mother treated violently: Twelve screeners asked children whether they had witnessed specific kinds of violence and abuse. Children who answered yes to any of these questions and who reported that their mother was the victim were coded 1 on this item. v Household substance abuse: A single item assessed whether the child had a family member who “drank or used drugs so often that it caused problems.” v Household mental illness: Children who had a parent or sibling with depression, bipolar disorder, anxiety, or “other psychiatric disorder” (information obtained from the parent interview) or children who had “someone close” attempt suicide were coded 1 on household mental illness. v Parental separation or divorce: We coded any respondent who was not currently living with 2 biological or adoptive parents as having experienced parental separation or divorce. v Incarcerated household member: One adversity item asks whether a parent or guardian had ever been sent to prison. Additional Victimization and Adversity Items Not Included in ACE Study The measures listed herein, not included in the ACE Study, were examined as additional correlates of children’s distress. A summary of these items is reported in eTable 2. Unless otherwise specified, questions regarding these items were asked in the child’s portion of the interview: v Peer victimization (assault, physical intimidation, or emotional victimization by a nonsibling peer) v Parents always arguing (respondents were asked whether there was a time in their lives when their parents were always arguing) v Property victimization (experience of a robbery, theft, or vandalism by a nonsibling perpetrator) v Someone close to the child had a bad accident or illness v Exposure to community violence (6 screeners asked whether the child had been exposed to certain types of crime and violence, including witnessing an assault, experiencing a household theft, having someone close murdered, witnessing a murder, experiencing a riot, or being in a war zone) v No good friends (child had no “really good friends at school” at the time of the interview) v Below-average grades (parent reported that the child had “below-average” grades in school) v Someone close to the child died because of an accident or illness v Parent lost job (children reported that there was a time when their “mother, father, or guardian lost a job or couldn’t find work”) v Parent deployed to war zone (parent had to leave the country to fight in a war and was gone for several months or longer) v Disaster (child had experienced a “very bad fire, flood, tornado, hurricane, earthquake, or other disaster”) v Removed from family (child was “sent or taken away from his or her family for any reason”) v Very overweight (parent reported that the child was “quite a bit overweight” compared with other boys/girls his or her age) v Physical disability (parent reported that the child had been diagnosed with a “physical health or medical problem that affects the kinds of activities that he or she can do”) v Ever involved in a bad accident v Neighborhood violence is a “big problem” (asked in the parent interview) v Homelessness (a time when the child’s family “had to live on a street or in a shelter because they had no other place to stay”) v Repeated a grade v Less masculine or feminine than other boys or girls his or her age (asked in the parent interview) Distress Symptoms Distress symptoms were measured using shortened versions of the anger, depression, anxiety, dissociation, and posttraumatic stress scales of the Trauma Symptoms Checklist for Children (TSCC).39 Respondents were asked how often they had experienced each symptom within the past month. Response options were on a 4-point scale from 1 (not at all) to 4 (very often), and responses from the items of all 5 scales were summed to create a total distress score consisting of 28 items. The Cronbach ␣ value for total distress score in this study was 0.93. Demographics Demographic information was obtained in the initial parent interview, including the child’s sex, age (in years), race/ ethnicity (coded into 4 groups: white non-Hispanic, black nonHispanic, other non-Hispanic, and Hispanic any race), socioeconomic status (SES), and place size of the child’s town or city of residence. Socioeconomic status is a continuous composite score based on the sum of the standardized household income and standardized parental educational level (for the parent with the highest educational level) scores, which was then restandardized. For our revised version of the ACE scale, we created a dummy indicator for low SES that flags children whose continuous SES value fell in the bottom, roughly 20%. RESULTS The ACE scale constructed with variables from NatSCEV that mimic the original items is associated with distress levels among youth aged 10 to 17 years, as measured by the Trauma Symptom Checklist for Children. Model 1 in Table 1 reports the regression of distress scores on JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 72 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Table 1. Regression of Wave 1 Trauma Scores on Lifetime Victimization and Adversity Table 2. Items in Original and Revised ACE Scales ACE Scale Adversities (Lifetime) Regression Coefficient, ␤ a Characteristic (n = 2030) Demographics, time 1 b Age, mean, y Male sex Black, non-Hispanic Other, non-Hispanic Hispanic, any race ACE scale items Physical abuse Emotional abuse Emotional neglect Physical neglect Household mental illness Household substance abuse Sexual abuse Mother treated violently Incarcerated household member Parental separation or divorce Additional victimization and adversity items Peer victimization (nonsibling) Parents always arguing Property victimization (nonsibling) Someone close had a bad accident or illness Exposure to community violence No good friends Socioeconomic status Below-average grades Someone close died from illness/accident Parent lost job Parent deployed to war zone Disaster Removed from family Very overweight Physical disability Involved in a bad accident Neighborhood violence is “big problem” Family homeless Repeated a grade Less masculine or feminine than peers Adjusted R 2 % Model 1 Model 2 13.5 51.2 15.1 5.7 17.8 −0.01 −0.03 0.01 −0.05 d −0.02 −0.03 −0.08 c 0.03 −0.05 e −0.03 14.9 17.7 7.7 4.0 27.9 16.8 6.6 13.1 11.1 41.2 0.16 c 0.13 c 0.16 c 0.08 c 0.12 c 0.12 c 0.09 c 0.07 c 0.08 c 0.04 e 0.08 c 0.01 0.08 c 0.05 d 0.05 e −0.02 0.02 −0.01 −0.01 −0.05 e 47.6 22.0 41.0 64.4 0.17 c 0.15 c 0.11 c 0.10 c 63.4 1.8 0.04 6.1 49.3 0.09 c 0.07 c −0.06 d 0.04 e 0.05 e 19.5 9.9 10.9 4.8 3.0 6.9 13.8 4.3 3.2 13.2 8.7 0.04 e 0.04 0.03 0.03 0.02 −0.01 −0.02 −0.02 −0.02 −0.03 −0.03 0.36 0.24 Abbreviation: ACE, Adverse Childhood Experiences. a Change in adjusted R 2 was significant at P ⬍ .001. b Reference category for race/ethnicity is white, non-Hispanic (61.4 % of sample). c Coefficient is significant at P ⬍ .001. d Coefficient is significant at P ⬍ .01. e Coefficient is significant at P ⬍ .05. the items from the replicated ACE scale. The cumulative items were strongly associated with distress, and there was a clear dose-response relationship between the adversities and distress, as has been demonstrated in previous research.1 However, the original ACE scale items did not each make an independent contribution to distress as illustrated in model 1 of Table 1. Two items, parental separation or divorce and incarceration of a household member, were not significant in the regression model of the whole scale. In addition, when other childhood adversi- Original Emotional abuse Physical abuse Sexual abuse Physical neglect Emotional neglect Mother treated violently Household substance abuse Household mental illness Incarcerated household member Parental separation or divorce Emotional abuse Physical abuse Sexual abuse Physical neglect Emotional neglect Household mental illness Property victimization (nonsibling) Peer victimization (nonsibling) Exposure to community violence Socioeconomic status Someone close had a bad accident or illness Below-average grades Parents always arguing No good friends (at time of interview) Abbreviation: ACE, Adverse Childhood Experiences. ties (not considered in the ACE studies) were added to the model (model 2 of Table 1), several ACE scale items dropped below significance. Moreover, several of the added childhood adversities showed strong associations with distress. These included peer victimization, property victimization, parents always arguing, having no good friends, having someone close with a bad illness or accident, SES, and exposure to community violence. A revised ACE scale was then constructed, removing the original items that were no longer significant in the extended model. Significant new items were added to the scale, including parents always arguing, having no good friends, having someone close with a bad illness or accident, peer victimization, property victimization, and exposure to community violence. The old and new scales are contrasted in Table 2. Regression with the new scale determined R2 = 0.34 vs R2 = 0.21 for the original version of the scale. COMMENT In this study, it was possible to improve the value of the original ACE scale considerably by adding some childhood adversities not included in the original scale and excluding others that were in the scale. The value of adding several items not considered in the ACE studies is consistent with several publications showing their harmful effect on child development. In fact, there are likely even more domains of childhood adversity that might be measured and added that could further improve its predictive ability, for example, low IQ,40 parental death, and food scarcity. The present study illustrates that the original ACE scale could likely be improved even more with additional developmental research. However, this analysis also confirms that some of the key ACE scale items, particularly the child maltreatment exposures, remain very important and make discrete independent contributions, even when many other adversities are considered. Moreover, several of the new JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 73 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Revised adversities identified in this study are additional forms of interpersonal victimization—property crime, peer victimization, and exposure to community violence— which reinforce findings from other studies41,42 highlighting the cumulative harm of different forms of childhood victimization. There are several limitations of the current study that bear emphasis. First, this study did not operationalize the adverse childhood events in the same way that the original ACE instrument did. Second, the dependent variable, the TSCC, used in this exercise was not an outcome used in the original ACE Study. The TSCC may be better associated with the impact of some childhood events, such as violence exposure, than others and may not necessarily be reflective of what would best predict long-term health effects. In fact, some childhood adversities may affect later health not through psychological processes, such as distress symptoms, but through other mechanisms, for example, failure to receive proper early health care. Moreover, unlike the ACE Study, the outcome measure was short term and the causal sequence between adversities and outcome cannot be assumed. All the variables in this study come from self-report and, in most cases, from children, which may be inaccurate and introduce method associations. Before additional work on the ACE scale is undertaken, some important issues are worth discussing, even beyond the findings of the current study. One issue concerns what the goal or best use of this or related scales should be. One possible use for this kind of scale is as a risk assessment tool with older adolescents or adults to help health care providers better understand who is most likely to require services and treatment for health problems. However, the goal for which the scale has been most widely used to date is to advocate for and influence prevention policies by highlighting crucial developmental factors that prevention programs should target to improve general health and reduce medical costs and social service expenditures.22,43,44 In many ways the first goal, risk assessment, is a much easier one to accomplish than the second, selection of prevention targets. To successfully satisfy the first goal, research has to find strong associations between risk indicators and later outcomes. The ACE scale seems clearly successful at this. For the second goal, however, a good risk indicator is not sufficient. The indicator has to be a proven causal contributor, which modified would make a difference. Much of the discussion about the ACE scale assumes that its items are causal contributors to the numerous negative adult outcomes, but this may not be the case. Without detailed longitudinal studies and the measurement of many additional variables, it may be very difficult to tease out whether, for example, it is household substance abuse that affects later outcomes or some unmeasured underlying parental emotional problem or lack of self-control. Moreover, a very important, but difficult to test, alternative explanation for many of the ACE Study findings is that inherited genes for health problems or some temperamental qualities create a spurious connection between abuse and neglect by parents or other family context variables and mental and physical health conditions in their offspring. If this were to be the case, it is possible, although not likely, that even preventing child abuse would make modest differences on health outcomes. There are other problems with using an ACE scale even as a long-term risk assessment tool. One is that risk assessment has to factor in social changes regarding the frequency, norms, and impact of different experiences. For older respondents who answered the original ACE Study questionnaire, parental divorce may have been an unusual and stigmatizing event and sexual abuse a hidden experience that one never talked or heard anything about. Among a younger cohort, more cultural awareness and the increased availability of support, including professional intervention, may mean that the experience of sexual abuse or parental divorce might have different consequences. This may be why parental divorce was not a significant predictor in the current study. Another problem is the possibility of reverse causation in which bad later life outcomes induce reports of more negative early childhood experiences. There is some evidence that people recall more negative historical adversity when they have poor adult outcomes, mental health, and physical problems.45 To the degree that this is true, variables identified in later life, such as in the ACE Study, will not prove as predictive of ultimate health outcomes when assessed in earlier life stages. An additional philosophical problem worth considering in discussions about the implications of ACE-type research is whether advocates should use a list of childhood features that are associated with long-term health effects as the primary criterion of what childhood adversities to prioritize for prevention. For example, if sexual abuse were demonstrated to be minimally associated with long-term health effects, would that disqualify it as a priority for primary prevention? No. Many childhood adversities are candidates for prevention not because they create long-term health risks but because they violate the rights of children or cause pain and suffering at the moment. Their contributions to long-term health can be additional evidence to consider but may not be primary. Such adversities illustrate the tension between a utilitarian and human rights perspective in child welfare policy. CONCLUSIONS This research suggests that the goal of identifying childhood adversities that are precursors to long-term health and behavioral outcomes may be improved by considering a wider range of adversities measured in a more contemporaneous way. Such an approach might be well advanced by using longitudinal studies that have been monitoring children into adulthood.12 However, more discussion is needed about the goals and usefulness of such efforts. Although additional efforts to refine an adverse childhood experience checklist that predicts later health outcomes has scientific merit, an argument can be made that enough is known about certain harmful childhood experiences22 that more testing of parts of this model should be carried out through experiment rather than correlation. There is enough consensus that exposure to violence, sexual abuse, and emotional mistreatment are harmful and likely have long- JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 74 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 term health effects; therefore, the next generation of studies should probably focus on preventing and remediating these exposures and following up to determine whether health outcomes improve. Accepted for Publication: June 7, 2012. Published Online: November 26, 2012. doi:10.1001 /jamapediatrics.2013.420 Correspondence: David Finkelhor, PhD, Crimes Against Children Research Center, University of New Hampshire, 126 Horton Social Science Center, 20 Academic Way, Durham, NH 03824 (david.finkelhor@unh.edu). Author Contributions: Study concept and design: Finkelhor, Turner, and Hamby. Analysis and interpretation of data: Finkelhor, Shattuck, Turner, and Hamby. Drafting of the manuscript: Finkelhor and Shattuck. Critical revision of the manuscript for important intellectual content: Finkelhor, Turner, and Hamby. Statistical analysis: Shattuck. Obtained funding: Finkelhor and Turner. Administrative, technical, and material support: Finkelhor and Turner. Study supervision: Finkelhor. Conflict of Interest Disclosures: None reported. Online-Only Material: The eTables are available at http: //www.jamapeds.com. REFERENCES 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 1. Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245258. 2. Anda RF, Croft JB, Felitti VJ, et al. Adverse childhood experiences and smoking during adolescence and adulthood. JAMA. 1999;282(17):1652-1658. 3. Dietz PM, Spitz AM, Anda RF, et al. Unintended pregnancy among adult women exposed to abuse or household dysfunction during their childhood. JAMA. 1999; 282(14):1359-1364. 4. Anda RF, Felitti VJ, Chapman DP, et al. Abused boys, battered mothers, and male involvement in teen pregnancy. Pediatrics. 2001;107(2):E19. doi:10.1542/peds .107.2.e19. 5. Anda RF, Whitfield CL, Felitti VJ, et al. Adverse childhood experiences, alcoholic parents, and later risk of alcoholism and depression. Psychiatr Serv. 2002; 53(8):1001-1009. 6. Dong M, Dube SR, Felitti VJ, Giles WH, Anda RF. Adverse childhood experiences and self-reported liver disease: new insights into the causal pathway. Arch Intern Med. 2003;163(16):1949-1956. 7. Dube SR, Anda RF, Felitti VJ, Croft JB, Edwards VJ, Giles WH. Growing up with parental alcohol abuse: exposure to childhood abuse, neglect, and household dysfunction. Child Abuse Negl. 2001;25(12):1627-1640. 8. Dube SR, Felitti VJ, Dong M, Chapman DP, Giles WH, Anda RF. Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: the Adverse Childhood Experiences Study. Pediatrics. 2003;111(3):564-572. 9. Hillis SD, Anda RF, Felitti VJ, Nordenberg D, Marchbanks PA. Adverse childhood experiences and sexually transmitted diseases in men and women: a retrospective study. Pediatrics. 2000;106(1):E11. http://pediatrics.aappublications .org/content/106/1/e11.long. Accessed February 3, 2012. 10. Dube SR, Anda RF, Felitti VJ, Chapman DP, Williamson DF, Giles WH. Childhood abuse, household dysfunction, and the risk of attempted suicide throughout the life span: findings from the Adverse Childhood Experiences Study. JAMA. 2001;286(24):3089-3096. 11. Dong M, Anda RF, Felitti VJ, et al. The interrelatedness of multiple forms of childhood abuse, neglect, and household dysfunction. Child Abuse Negl. 2004;28 (7):771-784. 12. Melchior M, Moffitt TE, Milne BJ, Poulton R, Caspi A. Why do children from socioeconomically disadvantaged families suffer from poor health when they reach adulthood? a life-course study. Am J Epidemiol. 2007;166(8):966-974. 13. Duncan GJ, Ziol-Guest KM, Kalil A. Early-childhood poverty and adult attainment, behavior, and health. Child Dev. 2010;81(1):306-325. 14. Holzer H, Schanzenbach D, Duncan G, Ludwig J. The Economic Costs of Poverty in the US: Subsequent Effects of Children Growing Up Poor. Washington, DC: Center for American Progress; 2007. 15. Kupersmidt JB, Coie JD, Dodge KA. The role of poor peer relationships in the 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 75 development of disorder. In: Asher SR, Coie JD, eds. Peer Rejection in Childhood. New York, NY: Cambridge University Press; 1990:274-301. Bagwell CL, Newcomb AF, Bukowski WM. Preadolescent friendship and peer rejection as predictors of adult adjustment. Child Dev. 1998;69(1):140-153. Danese A, Moffitt TE, Harrington H, et al. Adverse childhood experiences and adult risk factors for age-related disease: depression, inflammation, and clustering of metabolic risk markers. Arch Pediatr Adolesc Med. 2009;163(12): 1135-1143. Finn JD, Owings J. The Adult Lives of At-Risk Students: The Roles of Attainment and Engagement in High School: Statistical Analysis Report. Washington, DC: National Center for Education Statistics; 2006:2006-2328. Clark C, Ryan L, Kawachi I, Canner MJ, Berkman L, Wright RJ. Witnessing community violence in residential neighborhoods: a mental health hazard for urban women. J Urban Health. 2008;85(1):22-38. Council on Children and Families. Adverse childhood experiences among New York’s adults. 2010. http://ccf.ny.gov/KidsCount/kcResources/ACE_BriefTwo .pdf. Accessed February 3, 2012. Schilling EA, Aseltine RH Jr, Gore S. Adverse childhood experiences and mental health in young adults: a longitudinal survey. BMC Public Health. 2007;7:30. doi:10.1186/1471-2458-7-30. Shonkoff JP, Boyce WT, McEwen BS. Neuroscience, molecular biology, and the childhood roots of health disparities: building a new framework for health promotion and disease prevention. JAMA. 2009;301(21):2252-2259. Kendall-Tackett K. The health effects of childhood abuse: four pathways by which abuse can influence health. Child Abuse Negl. 2002;26(6-7):715-729. Kendall-Tackett K. Psychological trauma and physical health: a psychoneuroimmunology approach to etiology of negative health effects and possible interventions. Psychol Trauma. 2009;1(1):35-48. doi:10.1037/a0015128. Finkelhor D, Hamby SL, Ormrod RK, Turner HA. Violence, abuse, and crime exposure in a national sample of children and youth. Pediatrics. 2009;124(5):1-14. Keeter S, Kennedy C, Dimock M, Best J, Craighill P. Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey. Public Opin Q. 2006;70:759-779. doi:10.1093/poq/nfl035. Babbie E. The Practice of Social Research. 11th ed. Belmont, CA: Wadsworth; 2007. Atrostic BK, Bates N, Burt G, Silberstein A. Nonresponse in US government household surveys: consistent measures, recent trends, and new insights. J Off Stat. 2001;17(2):209-226. Curtin R, Presser S, Singer E. Changes in telephone survey nonresponse over the past quarter century. Public Opin Q. 2005;69:87-98. doi:10.1093/poq/nfi002. Singer E. Introduction: nonresponse bias in household surveys. Public Opin Q. 2006;70:637-645. doi:10.1093/poq/nfl034. Curtin R, Presser S, Singer E. The effects of response rate changes on the index of consumer sentiment. Public Opin Q. 2000;64(4):413-428. Keeter S, Miller C, Kohut A, Groves RM, Presser S. Consequences of reducing nonresponse in a national telephone survey. Public Opin Q. 2000;64(2):125-148. Groves RM. Nonresponse rates and nonresponse bias in household surveys. Public Opin Q. 2006;70:646-675. doi:10.1093/poq/nfl033. Merkle D, Edelman M. Nonresponse in exit polls: a comprehensive analysis. In: Groves RM, Dillman DA, Eltinge JL, Little RJA, eds. Survey Nonresponse. New York, NY: John Wiley & Son Inc; 2002:343-358. Finkelhor D, Hamby SL, Ormrod RK, Turner HA. The Juvenile Victimization Questionnaire: reliability, validity, and national norms. Child Abuse Negl. 2005;29 (4):383-412. Hamby SL, Finkelhor D, Ormrod RK, Turner HA. The Juvenile Victimization Questionnaire ( JVQ): Administration and Scoring Manual. Durham, NH: Crimes Against Children Research Center; 2004. Finkelhor D, Ormrod RK, Turner HA, Hamby SL. Measuring poly-victimization using the Juvenile Victimization Questionnaire. Child Abuse Negl. 2005;29(11): 1297-1312. Finkelhor D, Ormrod RK, Turner HA, Hamby SL. The victimization of children and youth: a comprehensive, national survey. Child Maltreat. 2005;10(1):5-25. Briere J. Trauma Symptoms Checklist for Children (TSCC): Professional Manual. Odessa, FL: Psychological Assessment Resources; 1996. Martin LT, Fitzmaurice GM, Kindlon DJ, Buka SL. Cognitive performance in childhood and early adult illness: a prospective cohort study. J Epidemiol Community Health. 2004;58(8):674-679. Finkelhor D, Ormrod RK, Turner HA. Poly-victimization: a neglected component in child victimization. Child Abuse Negl. 2007;31(1):7-26. Turner HA, Finkelhor D, Ormrod R. Poly-victimization in a national sample of children and youth. Am J Prev Med. 2010;38(3):323-330. Family Policy Council. ACE’s (Adverse Childhood Experiences). http://www.fpc .wa.gov/publications.html#ACEs. Accessed February 28, 2012. World Health Organization. Addressing adverse childhood experiences to improve public health: expert consultation. http://www.who.int/violence_injury _prevention/violence/activities/adverse_childhood_experiences/global_research _network_may_2009.pdf. 2009. Accessed February 3, 2012. Hardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry. 2004;45(2): 260-273. WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016
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Vincent Felitti, MD, pediatrician Robert Anda, MD, MS, and others have studied the relationship of childhood adversity and a variety of lifelong physical and emotional outcomes.1,2 Using a retrospective study design, they surveyed 17 337 adult health maintenance organization members (average age, 57 years) about crucial events during childhood and linked those events in a dose-response manner with cardiovascular disease; cancer; AIDS, and other sexually transmitted diseases; unwanted, often-highrisk pregnancies; chronic obstructive pulmonary disease; and a legacy of self-perpetuating child abuse. While it is hard to believe, many medical and child welfare professionals did not see the links among child abuse and other common social problems with poor health and premature death in adulthood.3 See also page 70 These 8 adverse childhood experiences (or ACEs), as they have come to be called, include exposure of a child before age 18 years to emotional abuse, physical abuse, contact sexual abuse, alcohol/substance abuse, mental illness, criminal behavior, parental separation/divorce, and domestic violence. While there have been questions about the validity of the study design, studies using ACEs have moved to less affluent samples to fit within an accepted universal ecobiodevelopmental framework for understanding health promotion and disease prevention across the lifespan and are supported by recent additional advances in neuroscience, molecular biology, and the social sciences.3-9 In this issue, Finkelhor et al10 seek to improve on this conceptual model and strengthen our understanding of the relationship between childhood adversity and lifelong health. Using data from telephone interviews in 2008 combined with a nationally representative sample of 2020 US children in a study not designed to measure the ACEs (the National Survey of Children’s Exposure to Violence10), the authors obtained incidence and prevalence estimates for a wide range of childhood victimizations and other adversities. They performed a secondary analysis that reconstructed the traditional ACE items and found that the current ACEs do predict current stress among adolescents in a dose-related fashion. Adolescent stress is thought to be a crucial mediator linking ACEs with longer-term health problems and illness and is a likely predictor of long-term negative life events.11 The authors then posit that there are problems methodologically with the retrospective nature of the current ACEs, which also miss things we know are problems associated with adult adversity, such as poor peer relationships, poor school performance, poverty, and unemployment. They then add additional variables to the original ACEs to see what contributes more to psychological distress, choosing new items that have been suggested by relationships of child maltreatment with childhood stress in current research. These additional adverse experiences include having parents who always argue, being friendless, having someone close with a bad illness or serious injury, peer victimization, property victimization, and exposure to community violence. In their models, the authors found that the prediction of current childhood stress was significantly improved by removing some of the original ACEs and adding others in these domains. While this is encouraging, they conclude that “our understanding of the most toxic adversities is still incomplete because of complex interrelationships among them.”10 While there is no doubt that childhood adversity causes and/or contributes to adult adversity, the results of the study by Finkelhor et al10 do help us to better understand toxic stress during childhood and potential critical situations in which we can intervene as families, communities, and a society. Using a study design with more predictive ACEs that measure adversity during childhood will minimize memory error and bias to achieve a more accurate and comprehensive assessment of childhood events. We will then be able to better identify children and families at risk before there is childhood stress or other measurable harm. Finkelhor et al10 are correct to say that we know enough to move to intervention and prevention. The seemingly large costs of child abuse and neglect ($80 billion in the US in 201212) pale in comparison with the economic and human burden of adult poor health and premature death. Some have said “Fight Crime, Invest in Kids,”13 and our response needs to include more than reactionary child welfare and criminal justice responses. Why do we not offer counseling to all children with psychological maltreatment or exposure to domestic violence?14-17 We need to connect the dots in childhood and adolescent trauma to improve the response of all the first responders (including physicians), publicize that these experiences have JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 95 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 downstream poor medical and mental health outcomes, optimize and expand the treatments we know work, and increase public support for these interventions.18 More immediately, we should be appalled if future health care reform does not include universal home visiting for newborns and their families because this has been clearly shown to improve numerous child health and developmental outcomes. As pediatricians, we have unique roles in preventing the adverse consequences of toxic stress using routine anticipatory guidance that strengthens family social supports, encourages positive parenting techniques, and facilitates a child’s social, emotional, and language skills. We should start in our medical home with identification and intervention and then move out of the office and into homes, schools, and the community while advocating for a growing number of evidence-based programs. The American Academy of Pediatrics19 has recommended that we (1) adopt the ecobiodevelopmental framework, (2) incorporate the growing scientific knowledge linking childhood adversity with lifelong health effects into pediatric training, (3) be more proactive in educating parents and other child welfare professionals about the long-term consequences of childhood stress, (4) be vocal advocates for the development and implementation of evidence-based interventions that reduce toxic stress or mitigate its effects, and (5) have our medical homes strengthen anticipatory guidance and screening for children and families at risk, with development of innovative service-provision adaptations and local resources to address the risks of toxic stress. We can use the ACEs to identify children and families now who will suffer later if we fail to act. We need to act now as physicians, professionals, and community leaders to reduce childhood adversity and promote lifelong health. Vincent J. Palusci, MD, MS Published Online: November 26, 2012. doi:10.1001 /jamapediatrics.2013.427 Author Affiliations: New York University School of Medicine, Frances L. Loeb Child Protection and Development Center, Bellevue Hospital, New York, New York. Correspondence: Dr Palusci, New York University School of Medicine, Frances L. Loeb Child Protection and Development Center, Bellevue Hospital, 462 First Ave, Room GC65, New York, NY 10016 (Vincent.palusci@nyumc.org). Conflict of Interest Disclosures: None reported. REFERENCES 1. Centers for Disease Control and Prevention. Adverse Childhood Experiences (ACE) Study: major findings by publication year. http://www.cdc.gov/ace/year.htm. Accessed June 15, 2012. 2. Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245-258. 3. Weiss MJS, Wagner SH. What explains the negative consequences of adverse childhood experiences on adult health? insights from cognitive and neuroscience research. Am J Prev Med. 1998;14(4):356-360. 4. Dube SR, Williamson DF, Thompson T, Felitti VJ, Anda RF. Assessing the reliability of retrospective reports of adverse childhood experiences among adult HMO members attending a primary care clinic. Child Abuse Negl. 2004;28(7):729-737. 5. Anda RF, Felitti VJ, Bremner JD, et al. The enduring effects of abuse and related adverse experiences in childhood: a convergence of evidence from neurobiology and epidemiology. Eur Arch Psychiatry Clin Neurosci. 2006;256(3):174-186. 6. Flaherty EG, Thompson R, Litrownik AJ, et al. Effect of early childhood adversity on child health. Arch Pediatr Adolesc Med. 2006;160(12):1232-1238. 7. Ramiro LS, Madrid BJ, Brown DW. Adverse childhood experiences (ACE) and health-risk behaviors among adults in a developing country setting. Child Abuse Negl. 2010;34(11):842-855. 8. Shonkoff JP, Garner AS; Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics. The lifelong effects of early childhood adversity and toxic stress. Pediatrics. 2012;129(1):e232-e246. 9. Shonkoff JP, Richter L, van der Gaag J, Bhutta ZA. An integrated framework for child survival and early childhood development. Pediatrics. 2012;129(2):e460-e472. 10. Finkelhor D, Shattuck A, Turner H, Hamby S. Improving the Adverse Childhood Experiences Study Scale [published online November 26, 2012]. JAMA Pediatr. 2013;167(1):70-75. 11. Middlebrooks JS, Audage NC. The Effects of Childhood Stress on Health Across the Lifespan. Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; 2008. 12. Gelles RJ, Perlman S. Estimated Annual Cost of Child Abuse and Neglect. Chicago, IL: Prevent Child Abuse America; 2012. 13. Fight Crime. Invest in Kids. http://www.fightcrime.org/. Accessed June 15, 2012. 14. Cohen JA, Mannarino AP, Iyengar S. Community treatment of posttraumatic stress disorder for children exposed to intimate partner violence: a randomized controlled trial. Arch Pediatr Adolesc Med. 2011;165(1):16-21. 15. Layne CM. Developing interventions for trauma-exposed children: a comment on progress to date, and 3 recommendations for further advancing the field. Arch Pediatr Adolesc Med. 2011;165(1):89-90. 16. Palusci VJ, Ondersma SJ. Services and recurrence after psychological maltreatment confirmed by child protective services. Child Maltreat. 2012;17(2):153-163. 17. Perrin EC, Sheldrick RC. The challenge of mental health care in pediatrics. Arch Pediatr Adolesc Med. 2012;166(3):287-288. 18. Asnes AG, Leventhal JM. Connecting the dots in childhood and adolescent trauma. Arch Pediatr Adolesc Med. 2011;165(1):87-89. 19. Garner AS, Shonkoff JP; the American Academy of Pediatrics Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics. Early childhood adversity, toxic stress, and the role of the pediatrician: translating developmental science into lifelong health. Pediatrics. 2012;129 (1):e224-e231 http://pediatrics.aappublications.org/content/129/1/e224. Accessed June 15, 2012. JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 96 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 ARTICLE Improving the Adverse Childhood Experiences Study Scale David Finkelhor, PhD; Anne Shattuck, MA; Heather Turner, PhD; Sherry Hamby, PhD Objective: To test and improve upon the list of adverse childhood experiences from the Adverse Childhood Experiences (ACE) Study scale by examining the ability of a broader range to correlate with mental health symptoms. Design: Nationally representative sample of children and adolescents. Setting and Participants: Telephone interviews with a nationally representative sample of 2030 youth aged 10 to 17 years who were asked about lifetime adversities and current distress symptoms. Main Outcome Measures: Lifetime adversities and participants, but the association was significantly improved (from R2 =0.21 to R2 =0.34) by removing some of the original ACE scale items and adding others in the domains of peer rejection, peer victimization, community violence exposure, school performance, and socioeconomic status. Conclusions: Our understanding of the most harmful childhood adversities is still incomplete because of complex interrelationships among them, but we know enough to proceed to interventional studies to determine whether prevention and remediation can improve long-term outcomes. current distress symptoms. Results: The adversities from the original ACE scale items were associated with mental health symptoms among the JAMA Pediatr. 2013;167(1):70-75. Published online November 26, 2012. doi:10.1001/jamapediatrics.2013.420 T Author Affiliations: Crimes Against Children Research Center, University of New Hampshire, Durham (Drs Finkelhor and Turner and Ms Shattuck); and Psychology Department, Sewanee, the University of the South, Sewanee, Tennessee (Dr Hamby). HE A DVERSE C HILDHOOD Experiences (ACE) Study1 has attracted considerable scientific and policy attention in recent years, in part because it suggests that potentially preventable childhood experiences, particularly physical and sexual abuse and neglect, may increase a person’s risk for serious health problems and higher mortality rates much later in life. The study has demonstrated relationships between adverse childhood experiences and many adult health risks.1-10 These results, which have been published widely in the health sciences, are based on a survey and medical records of more than 17 000 members of the Kaiser Health Plan in San Diego, California.1,11 Nonetheless, research using the ACE Study model has some important limitations, in part because of the retrospective way in which data on childhood adversities have been gathered. The average age of respondents when they supplied information about their childhood experiences was 55 to 57 years. As a result, it is hard to be certain, particularly from such JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 70 a remote vantage, whether it is these particular childhood experiences or unmeasured covariates that are the most important predictors. In addition, the ACE Study list of preventable childhood adversities omits certain domains judged by many developmental researchers to be important in predicting long-term health and well-being outcomes. Among the predictors missing from the ACE Study model are peer rejection, exposure to violence outside the family, low socioeconomic status, and poor academic performance. For editorial comment see page 95 For example, longitudinal studies show that growing up in poverty increases lifelong risk for various negative life events and negative health outcomes.12-14 Peer rejection and lack of friends are associated with the development of many disorders.15-17 Poor school performance in childhood is associated with poor outcomes in adulthood, such as unemployment.18 Witnessing community violence has been WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Author Aff Against Ch Center, Uni Hampshire Finkelhor a Shattuck); Departmen University Sewanee, T Hamby). shown to be a mental health hazard for adults and children.19,20 These major childhood adversities are not currently measured by the ACE scale. In addition, measuring childhood adversities during childhood, rather than later, may offer other improvements to the ACE Study’s early life predictors of health outcomes.21 It allows the possibility of obtaining a more accurate and comprehensive assessment of childhood events than one would be able to obtain after many years. It also would allow a more sensitive untangling of the relationship among various adversities in ways that better explain causal sequences. Although an obvious disadvantage is the inability to assess the long-term effects of childhood adversity on the negative life events and health conditions posited in the ACE Study model, examining more short-term effects in childhood is consistent with the logic of the model. Specifically, the ACE Study model relies strongly on the idea that adverse childhood experiences create a burden of psychological stress that changes behavior, cognitions, emotions, and physical functions in ways that promote subsequent health problems and illness.22 Among the hypothesized pathways, adverse childhood experiences lead to depression and posttraumaticstressdisorder,whichinturncanleadtosubstance abuse, sleep disorders, inactivity, immunosuppression, inflammatory responses, and inconsistent health care use, possibly leading to other medical conditions later in life.23,24 Therefore, childhood behavioral and emotional symptoms verylikelyrepresentacrucialmediatorlinkingadversechildhood experiences and the longer term health-related problems found in the ACE substudies. Thus, in the present study, we tried to replicate the ACE Study findings in a cohort of youth, using psychological distress as an outcome measure, and to explore whether the adversities enumerated by the ACE Study could be improved upon by considering a more comprehensive range of possible adversities, including some of the domains not considered in the ACE Study. maining 1496 of the completed interviews. Sample weights were calculated to adjust for differential probability of selection associated with (1) study design, (2) demographic variations in nonresponse, and (3) variations in within-household eligibility. For this study, we analyzed a subsample of the entire sample of 4549 respondents. This subsample consisted of 2030 youth who were aged 10 to 17 years at the time of the interview and for whom complete data were available on the variables of interest. Analyses in this study are weighted by the sample weights. PROCEDURE A short interview was conducted with an adult caregiver (usually a parent) in each household to obtain family demographic information. One child was randomly selected from all eligible children living in a household by choosing the child with the most recent birthday. If the selected child was aged 10 to 17 years, the main telephone interview was conducted with the child. If the child was younger than 10 years, the interview was completed with the caregiver. However, the current analysis is based only on the 2030 youth aged 10 to 17 years who provided self-report information. Respondents were paid $20 for their participation. The interviews, averaging 45 minutes in both waves, were conducted in either English or Spanish. All procedures were approved by the institutional review board at the University of New Hampshire. RESPONSE RATES AND NONRESPONSE ANALYSES The cooperation rate for the random digit dialing crosssection portion of the survey was 71%, and the response rate was 54%. The cooperation and response rates associated with the smaller oversample were somewhat lower at 63% and 43%, respectively. These are good rates by current survey research standards.26-30 Although the potential for response bias remains an important consideration, several recent studies and our own analysis25 have shown no meaningful association between response rates and response bias.31-34 MEASUREMENT Victimization and Adversity METHODS PARTICIPANTS These analyses use data from the National Survey of Children’s Exposure to Violence (NatSCEV),25 a representative sample of US children and adolescents. The NatSCEV was designed to obtain incidence and prevalence estimates for a wide range of childhood victimizations and other adversities. The survey was conducted between January 2008 and May 2008 with a nationally representative sample of 4549 children aged 0 to 17 years living in the contiguous United States. Interviews with parents and youth were conducted over the telephone by the employees of an experienced survey research firm. The foundation of the design was a nationwide sampling frame of residential telephone numbers from which a sample of telephone households was drawn by random digit dialing. This nationally representative cross section yielded 3053 of the 4549 completed interviews. To ensure that the study included a sizable proportion of racial/ethnic minorities and lowincome respondents for more accurate subgroup analyses, there was also an oversampling of US telephone exchanges that had a population of 70% or more of African American, Hispanic, or low-income households. This oversample yielded the re- This survey used an enhanced version of the Juvenile Victimization Questionnaire, an inventory of childhood victimization.35-37 The Juvenile Victimization Questionnaire obtains reports on 48 forms of youth victimization covering 5 general areas of interest: conventional crime, maltreatment, victimization by peer and siblings, sexual victimization, and witnessing and exposure to violence.38 The survey also contains questions about adverse life events in the parent interview section and in a separate section on adversity. For the present study, which was not originally designed to test the ACE Study model, we selected victimization and adversity items in 2 steps. First, we used screener items and their associated follow-up questions to construct victimization types that most closely matched the abuse and neglect items in the original ACE Study, and we chose family background and adversity items to match the household dysfunction items of the original ACE Study. Using these items, we constructed a replication of the original ACE Study. In the second step, we selected additional types of victimization and adversity items not included in the original ACE Study but that are known to be important correlates of health and well-being outcomes. The measures selected in these 2 steps are described in the next section of this article. Important differences from the ACE Study items are noted in eTable 1 (http://www.jamapeds.com). JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 71 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Measures Used to Replicate Original ACE Study Items The following measures were coded 0 for no and 1 for yes so that they could be summed to create the replicated ACE Study items. All are lifetime measures. v Emotional abuse: One item asked respondents, “At any time in your life, did you get scared or feel really bad because grown-ups in your life called you names, said mean things to you, or said they didn’t want you?” v Physical abuse: Several screeners assessed the child’s experience of physical assault. Children who answered yes to any of these assault screeners were coded as having experienced physical abuse if the incident was perpetrated by parent, an adult relative, or another adult caregiver. v Sexual abuse: Four screeners asked about the child’s experience of sexual assault or attempted rape by a known adult, an adult stranger, or a peer or sibling. v Emotional neglect: Four questions about family social support were used to construct an indicator of emotional neglect. These items are shown in eTable 1. Total scores ranged from 4 to 16. Children whose family support score was 10 or lower were coded as having experienced emotional neglect. v Physical neglect: A single item asked whether the child had ever experienced a time when adults in his or her life “didn’t take care of them the way they should,” including not providing enough food, not taking them to the doctor when they were sick, or not making sure they had a safe place to stay. Children who answered yes were coded as having experienced physical neglect. v Mother treated violently: Twelve screeners asked children whether they had witnessed specific kinds of violence and abuse. Children who answered yes to any of these questions and who reported that their mother was the victim were coded 1 on this item. v Household substance abuse: A single item assessed whether the child had a family member who “drank or used drugs so often that it caused problems.” v Household mental illness: Children who had a parent or sibling with depression, bipolar disorder, anxiety, or “other psychiatric disorder” (information obtained from the parent interview) or children who had “someone close” attempt suicide were coded 1 on household mental illness. v Parental separation or divorce: We coded any respondent who was not currently living with 2 biological or adoptive parents as having experienced parental separation or divorce. v Incarcerated household member: One adversity item asks whether a parent or guardian had ever been sent to prison. Additional Victimization and Adversity Items Not Included in ACE Study The measures listed herein, not included in the ACE Study, were examined as additional correlates of children’s distress. A summary of these items is reported in eTable 2. Unless otherwise specified, questions regarding these items were asked in the child’s portion of the interview: v Peer victimization (assault, physical intimidation, or emotional victimization by a nonsibling peer) v Parents always arguing (respondents were asked whether there was a time in their lives when their parents were always arguing) v Property victimization (experience of a robbery, theft, or vandalism by a nonsibling perpetrator) v Someone close to the child had a bad accident or illness v Exposure to community violence (6 screeners asked whether the child had been exposed to certain types of crime and violence, including witnessing an assault, experiencing a household theft, having someone close murdered, witnessing a murder, experiencing a riot, or being in a war zone) v No good friends (child had no “really good friends at school” at the time of the interview) v Below-average grades (parent reported that the child had “below-average” grades in school) v Someone close to the child died because of an accident or illness v Parent lost job (children reported that there was a time when their “mother, father, or guardian lost a job or couldn’t find work”) v Parent deployed to war zone (parent had to leave the country to fight in a war and was gone for several months or longer) v Disaster (child had experienced a “very bad fire, flood, tornado, hurricane, earthquake, or other disaster”) v Removed from family (child was “sent or taken away from his or her family for any reason”) v Very overweight (parent reported that the child was “quite a bit overweight” compared with other boys/girls his or her age) v Physical disability (parent reported that the child had been diagnosed with a “physical health or medical problem that affects the kinds of activities that he or she can do”) v Ever involved in a bad accident v Neighborhood violence is a “big problem” (asked in the parent interview) v Homelessness (a time when the child’s family “had to live on a street or in a shelter because they had no other place to stay”) v Repeated a grade v Less masculine or feminine than other boys or girls his or her age (asked in the parent interview) Distress Symptoms Distress symptoms were measured using shortened versions of the anger, depression, anxiety, dissociation, and posttraumatic stress scales of the Trauma Symptoms Checklist for Children (TSCC).39 Respondents were asked how often they had experienced each symptom within the past month. Response options were on a 4-point scale from 1 (not at all) to 4 (very often), and responses from the items of all 5 scales were summed to create a total distress score consisting of 28 items. The Cronbach ␣ value for total distress score in this study was 0.93. Demographics Demographic information was obtained in the initial parent interview, including the child’s sex, age (in years), race/ ethnicity (coded into 4 groups: white non-Hispanic, black nonHispanic, other non-Hispanic, and Hispanic any race), socioeconomic status (SES), and place size of the child’s town or city of residence. Socioeconomic status is a continuous composite score based on the sum of the standardized household income and standardized parental educational level (for the parent with the highest educational level) scores, which was then restandardized. For our revised version of the ACE scale, we created a dummy indicator for low SES that flags children whose continuous SES value fell in the bottom, roughly 20%. RESULTS The ACE scale constructed with variables from NatSCEV that mimic the original items is associated with distress levels among youth aged 10 to 17 years, as measured by the Trauma Symptom Checklist for Children. Model 1 in Table 1 reports the regression of distress scores on JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 72 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Table 1. Regression of Wave 1 Trauma Scores on Lifetime Victimization and Adversity Table 2. Items in Original and Revised ACE Scales ACE Scale Adversities (Lifetime) Regression Coefficient, ␤ a Characteristic (n = 2030) Demographics, time 1 b Age, mean, y Male sex Black, non-Hispanic Other, non-Hispanic Hispanic, any race ACE scale items Physical abuse Emotional abuse Emotional neglect Physical neglect Household mental illness Household substance abuse Sexual abuse Mother treated violently Incarcerated household member Parental separation or divorce Additional victimization and adversity items Peer victimization (nonsibling) Parents always arguing Property victimization (nonsibling) Someone close had a bad accident or illness Exposure to community violence No good friends Socioeconomic status Below-average grades Someone close died from illness/accident Parent lost job Parent deployed to war zone Disaster Removed from family Very overweight Physical disability Involved in a bad accident Neighborhood violence is “big problem” Family homeless Repeated a grade Less masculine or feminine than peers Adjusted R 2 % Model 1 Model 2 13.5 51.2 15.1 5.7 17.8 −0.01 −0.03 0.01 −0.05 d −0.02 −0.03 −0.08 c 0.03 −0.05 e −0.03 14.9 17.7 7.7 4.0 27.9 16.8 6.6 13.1 11.1 41.2 0.16 c 0.13 c 0.16 c 0.08 c 0.12 c 0.12 c 0.09 c 0.07 c 0.08 c 0.04 e 0.08 c 0.01 0.08 c 0.05 d 0.05 e −0.02 0.02 −0.01 −0.01 −0.05 e 47.6 22.0 41.0 64.4 0.17 c 0.15 c 0.11 c 0.10 c 63.4 1.8 0.04 6.1 49.3 0.09 c 0.07 c −0.06 d 0.04 e 0.05 e 19.5 9.9 10.9 4.8 3.0 6.9 13.8 4.3 3.2 13.2 8.7 0.04 e 0.04 0.03 0.03 0.02 −0.01 −0.02 −0.02 −0.02 −0.03 −0.03 0.36 0.24 Abbreviation: ACE, Adverse Childhood Experiences. a Change in adjusted R 2 was significant at P ⬍ .001. b Reference category for race/ethnicity is white, non-Hispanic (61.4 % of sample). c Coefficient is significant at P ⬍ .001. d Coefficient is significant at P ⬍ .01. e Coefficient is significant at P ⬍ .05. the items from the replicated ACE scale. The cumulative items were strongly associated with distress, and there was a clear dose-response relationship between the adversities and distress, as has been demonstrated in previous research.1 However, the original ACE scale items did not each make an independent contribution to distress as illustrated in model 1 of Table 1. Two items, parental separation or divorce and incarceration of a household member, were not significant in the regression model of the whole scale. In addition, when other childhood adversi- Original Emotional abuse Physical abuse Sexual abuse Physical neglect Emotional neglect Mother treated violently Household substance abuse Household mental illness Incarcerated household member Parental separation or divorce Emotional abuse Physical abuse Sexual abuse Physical neglect Emotional neglect Household mental illness Property victimization (nonsibling) Peer victimization (nonsibling) Exposure to community violence Socioeconomic status Someone close had a bad accident or illness Below-average grades Parents always arguing No good friends (at time of interview) Abbreviation: ACE, Adverse Childhood Experiences. ties (not considered in the ACE studies) were added to the model (model 2 of Table 1), several ACE scale items dropped below significance. Moreover, several of the added childhood adversities showed strong associations with distress. These included peer victimization, property victimization, parents always arguing, having no good friends, having someone close with a bad illness or accident, SES, and exposure to community violence. A revised ACE scale was then constructed, removing the original items that were no longer significant in the extended model. Significant new items were added to the scale, including parents always arguing, having no good friends, having someone close with a bad illness or accident, peer victimization, property victimization, and exposure to community violence. The old and new scales are contrasted in Table 2. Regression with the new scale determined R2 = 0.34 vs R2 = 0.21 for the original version of the scale. COMMENT In this study, it was possible to improve the value of the original ACE scale considerably by adding some childhood adversities not included in the original scale and excluding others that were in the scale. The value of adding several items not considered in the ACE studies is consistent with several publications showing their harmful effect on child development. In fact, there are likely even more domains of childhood adversity that might be measured and added that could further improve its predictive ability, for example, low IQ,40 parental death, and food scarcity. The present study illustrates that the original ACE scale could likely be improved even more with additional developmental research. However, this analysis also confirms that some of the key ACE scale items, particularly the child maltreatment exposures, remain very important and make discrete independent contributions, even when many other adversities are considered. Moreover, several of the new JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 73 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 Revised adversities identified in this study are additional forms of interpersonal victimization—property crime, peer victimization, and exposure to community violence— which reinforce findings from other studies41,42 highlighting the cumulative harm of different forms of childhood victimization. There are several limitations of the current study that bear emphasis. First, this study did not operationalize the adverse childhood events in the same way that the original ACE instrument did. Second, the dependent variable, the TSCC, used in this exercise was not an outcome used in the original ACE Study. The TSCC may be better associated with the impact of some childhood events, such as violence exposure, than others and may not necessarily be reflective of what would best predict long-term health effects. In fact, some childhood adversities may affect later health not through psychological processes, such as distress symptoms, but through other mechanisms, for example, failure to receive proper early health care. Moreover, unlike the ACE Study, the outcome measure was short term and the causal sequence between adversities and outcome cannot be assumed. All the variables in this study come from self-report and, in most cases, from children, which may be inaccurate and introduce method associations. Before additional work on the ACE scale is undertaken, some important issues are worth discussing, even beyond the findings of the current study. One issue concerns what the goal or best use of this or related scales should be. One possible use for this kind of scale is as a risk assessment tool with older adolescents or adults to help health care providers better understand who is most likely to require services and treatment for health problems. However, the goal for which the scale has been most widely used to date is to advocate for and influence prevention policies by highlighting crucial developmental factors that prevention programs should target to improve general health and reduce medical costs and social service expenditures.22,43,44 In many ways the first goal, risk assessment, is a much easier one to accomplish than the second, selection of prevention targets. To successfully satisfy the first goal, research has to find strong associations between risk indicators and later outcomes. The ACE scale seems clearly successful at this. For the second goal, however, a good risk indicator is not sufficient. The indicator has to be a proven causal contributor, which modified would make a difference. Much of the discussion about the ACE scale assumes that its items are causal contributors to the numerous negative adult outcomes, but this may not be the case. Without detailed longitudinal studies and the measurement of many additional variables, it may be very difficult to tease out whether, for example, it is household substance abuse that affects later outcomes or some unmeasured underlying parental emotional problem or lack of self-control. Moreover, a very important, but difficult to test, alternative explanation for many of the ACE Study findings is that inherited genes for health problems or some temperamental qualities create a spurious connection between abuse and neglect by parents or other family context variables and mental and physical health conditions in their offspring. If this were to be the case, it is possible, although not likely, that even preventing child abuse would make modest differences on health outcomes. There are other problems with using an ACE scale even as a long-term risk assessment tool. One is that risk assessment has to factor in social changes regarding the frequency, norms, and impact of different experiences. For older respondents who answered the original ACE Study questionnaire, parental divorce may have been an unusual and stigmatizing event and sexual abuse a hidden experience that one never talked or heard anything about. Among a younger cohort, more cultural awareness and the increased availability of support, including professional intervention, may mean that the experience of sexual abuse or parental divorce might have different consequences. This may be why parental divorce was not a significant predictor in the current study. Another problem is the possibility of reverse causation in which bad later life outcomes induce reports of more negative early childhood experiences. There is some evidence that people recall more negative historical adversity when they have poor adult outcomes, mental health, and physical problems.45 To the degree that this is true, variables identified in later life, such as in the ACE Study, will not prove as predictive of ultimate health outcomes when assessed in earlier life stages. An additional philosophical problem worth considering in discussions about the implications of ACE-type research is whether advocates should use a list of childhood features that are associated with long-term health effects as the primary criterion of what childhood adversities to prioritize for prevention. For example, if sexual abuse were demonstrated to be minimally associated with long-term health effects, would that disqualify it as a priority for primary prevention? No. Many childhood adversities are candidates for prevention not because they create long-term health risks but because they violate the rights of children or cause pain and suffering at the moment. Their contributions to long-term health can be additional evidence to consider but may not be primary. Such adversities illustrate the tension between a utilitarian and human rights perspective in child welfare policy. CONCLUSIONS This research suggests that the goal of identifying childhood adversities that are precursors to long-term health and behavioral outcomes may be improved by considering a wider range of adversities measured in a more contemporaneous way. Such an approach might be well advanced by using longitudinal studies that have been monitoring children into adulthood.12 However, more discussion is needed about the goals and usefulness of such efforts. Although additional efforts to refine an adverse childhood experience checklist that predicts later health outcomes has scientific merit, an argument can be made that enough is known about certain harmful childhood experiences22 that more testing of parts of this model should be carried out through experiment rather than correlation. There is enough consensus that exposure to violence, sexual abuse, and emotional mistreatment are harmful and likely have long- JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 74 WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016 term health effects; therefore, the next generation of studies should probably focus on preventing and remediating these exposures and following up to determine whether health outcomes improve. Accepted for Publication: June 7, 2012. Published Online: November 26, 2012. doi:10.1001 /jamapediatrics.2013.420 Correspondence: David Finkelhor, PhD, Crimes Against Children Research Center, University of New Hampshire, 126 Horton Social Science Center, 20 Academic Way, Durham, NH 03824 (david.finkelhor@unh.edu). Author Contributions: Study concept and design: Finkelhor, Turner, and Hamby. Analysis and interpretation of data: Finkelhor, Shattuck, Turner, and Hamby. Drafting of the manuscript: Finkelhor and Shattuck. Critical revision of the manuscript for important intellectual content: Finkelhor, Turner, and Hamby. Statistical analysis: Shattuck. Obtained funding: Finkelhor and Turner. Administrative, technical, and material support: Finkelhor and Turner. Study supervision: Finkelhor. Conflict of Interest Disclosures: None reported. Online-Only Material: The eTables are available at http: //www.jamapeds.com. REFERENCES 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 1. Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245258. 2. Anda RF, Croft JB, Felitti VJ, et al. Adverse childhood experiences and smoking during adolescence and adulthood. JAMA. 1999;282(17):1652-1658. 3. Dietz PM, Spitz AM, Anda RF, et al. Unintended pregnancy among adult women exposed to abuse or household dysfunction during their childhood. JAMA. 1999; 282(14):1359-1364. 4. Anda RF, Felitti VJ, Chapman DP, et al. Abused boys, battered mothers, and male involvement in teen pregnancy. Pediatrics. 2001;107(2):E19. doi:10.1542/peds .107.2.e19. 5. Anda RF, Whitfield CL, Felitti VJ, et al. Adverse childhood experiences, alcoholic parents, and later risk of alcoholism and depression. Psychiatr Serv. 2002; 53(8):1001-1009. 6. Dong M, Dube SR, Felitti VJ, Giles WH, Anda RF. Adverse childhood experiences and self-reported liver disease: new insights into the causal pathway. Arch Intern Med. 2003;163(16):1949-1956. 7. Dube SR, Anda RF, Felitti VJ, Croft JB, Edwards VJ, Giles WH. Growing up with parental alcohol abuse: exposure to childhood abuse, neglect, and household dysfunction. Child Abuse Negl. 2001;25(12):1627-1640. 8. Dube SR, Felitti VJ, Dong M, Chapman DP, Giles WH, Anda RF. Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: the Adverse Childhood Experiences Study. Pediatrics. 2003;111(3):564-572. 9. Hillis SD, Anda RF, Felitti VJ, Nordenberg D, Marchbanks PA. Adverse childhood experiences and sexually transmitted diseases in men and women: a retrospective study. Pediatrics. 2000;106(1):E11. http://pediatrics.aappublications .org/content/106/1/e11.long. Accessed February 3, 2012. 10. Dube SR, Anda RF, Felitti VJ, Chapman DP, Williamson DF, Giles WH. Childhood abuse, household dysfunction, and the risk of attempted suicide throughout the life span: findings from the Adverse Childhood Experiences Study. JAMA. 2001;286(24):3089-3096. 11. Dong M, Anda RF, Felitti VJ, et al. The interrelatedness of multiple forms of childhood abuse, neglect, and household dysfunction. Child Abuse Negl. 2004;28 (7):771-784. 12. Melchior M, Moffitt TE, Milne BJ, Poulton R, Caspi A. Why do children from socioeconomically disadvantaged families suffer from poor health when they reach adulthood? a life-course study. Am J Epidemiol. 2007;166(8):966-974. 13. Duncan GJ, Ziol-Guest KM, Kalil A. Early-childhood poverty and adult attainment, behavior, and health. Child Dev. 2010;81(1):306-325. 14. Holzer H, Schanzenbach D, Duncan G, Ludwig J. The Economic Costs of Poverty in the US: Subsequent Effects of Children Growing Up Poor. Washington, DC: Center for American Progress; 2007. 15. Kupersmidt JB, Coie JD, Dodge KA. The role of poor peer relationships in the 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. JAMA PEDIATR/ VOL 167 (NO. 1), JAN 2013 75 development of disorder. In: Asher SR, Coie JD, eds. Peer Rejection in Childhood. New York, NY: Cambridge University Press; 1990:274-301. Bagwell CL, Newcomb AF, Bukowski WM. Preadolescent friendship and peer rejection as predictors of adult adjustment. Child Dev. 1998;69(1):140-153. Danese A, Moffitt TE, Harrington H, et al. Adverse childhood experiences and adult risk factors for age-related disease: depression, inflammation, and clustering of metabolic risk markers. Arch Pediatr Adolesc Med. 2009;163(12): 1135-1143. Finn JD, Owings J. The Adult Lives of At-Risk Students: The Roles of Attainment and Engagement in High School: Statistical Analysis Report. Washington, DC: National Center for Education Statistics; 2006:2006-2328. Clark C, Ryan L, Kawachi I, Canner MJ, Berkman L, Wright RJ. Witnessing community violence in residential neighborhoods: a mental health hazard for urban women. J Urban Health. 2008;85(1):22-38. Council on Children and Families. Adverse childhood experiences among New York’s adults. 2010. http://ccf.ny.gov/KidsCount/kcResources/ACE_BriefTwo .pdf. Accessed February 3, 2012. Schilling EA, Aseltine RH Jr, Gore S. Adverse childhood experiences and mental health in young adults: a longitudinal survey. BMC Public Health. 2007;7:30. doi:10.1186/1471-2458-7-30. Shonkoff JP, Boyce WT, McEwen BS. Neuroscience, molecular biology, and the childhood roots of health disparities: building a new framework for health promotion and disease prevention. JAMA. 2009;301(21):2252-2259. Kendall-Tackett K. The health effects of childhood abuse: four pathways by which abuse can influence health. Child Abuse Negl. 2002;26(6-7):715-729. Kendall-Tackett K. Psychological trauma and physical health: a psychoneuroimmunology approach to etiology of negative health effects and possible interventions. Psychol Trauma. 2009;1(1):35-48. doi:10.1037/a0015128. Finkelhor D, Hamby SL, Ormrod RK, Turner HA. Violence, abuse, and crime exposure in a national sample of children and youth. Pediatrics. 2009;124(5):1-14. Keeter S, Kennedy C, Dimock M, Best J, Craighill P. Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey. Public Opin Q. 2006;70:759-779. doi:10.1093/poq/nfl035. Babbie E. The Practice of Social Research. 11th ed. Belmont, CA: Wadsworth; 2007. Atrostic BK, Bates N, Burt G, Silberstein A. Nonresponse in US government household surveys: consistent measures, recent trends, and new insights. J Off Stat. 2001;17(2):209-226. Curtin R, Presser S, Singer E. Changes in telephone survey nonresponse over the past quarter century. Public Opin Q. 2005;69:87-98. doi:10.1093/poq/nfi002. Singer E. Introduction: nonresponse bias in household surveys. Public Opin Q. 2006;70:637-645. doi:10.1093/poq/nfl034. Curtin R, Presser S, Singer E. The effects of response rate changes on the index of consumer sentiment. Public Opin Q. 2000;64(4):413-428. Keeter S, Miller C, Kohut A, Groves RM, Presser S. Consequences of reducing nonresponse in a national telephone survey. Public Opin Q. 2000;64(2):125-148. Groves RM. Nonresponse rates and nonresponse bias in household surveys. Public Opin Q. 2006;70:646-675. doi:10.1093/poq/nfl033. Merkle D, Edelman M. Nonresponse in exit polls: a comprehensive analysis. In: Groves RM, Dillman DA, Eltinge JL, Little RJA, eds. Survey Nonresponse. New York, NY: John Wiley & Son Inc; 2002:343-358. Finkelhor D, Hamby SL, Ormrod RK, Turner HA. The Juvenile Victimization Questionnaire: reliability, validity, and national norms. Child Abuse Negl. 2005;29 (4):383-412. Hamby SL, Finkelhor D, Ormrod RK, Turner HA. The Juvenile Victimization Questionnaire ( JVQ): Administration and Scoring Manual. Durham, NH: Crimes Against Children Research Center; 2004. Finkelhor D, Ormrod RK, Turner HA, Hamby SL. Measuring poly-victimization using the Juvenile Victimization Questionnaire. Child Abuse Negl. 2005;29(11): 1297-1312. Finkelhor D, Ormrod RK, Turner HA, Hamby SL. The victimization of children and youth: a comprehensive, national survey. Child Maltreat. 2005;10(1):5-25. Briere J. Trauma Symptoms Checklist for Children (TSCC): Professional Manual. Odessa, FL: Psychological Assessment Resources; 1996. Martin LT, Fitzmaurice GM, Kindlon DJ, Buka SL. Cognitive performance in childhood and early adult illness: a prospective cohort study. J Epidemiol Community Health. 2004;58(8):674-679. Finkelhor D, Ormrod RK, Turner HA. Poly-victimization: a neglected component in child victimization. Child Abuse Negl. 2007;31(1):7-26. Turner HA, Finkelhor D, Ormrod R. Poly-victimization in a national sample of children and youth. Am J Prev Med. 2010;38(3):323-330. Family Policy Council. ACE’s (Adverse Childhood Experiences). http://www.fpc .wa.gov/publications.html#ACEs. Accessed February 28, 2012. World Health Organization. Addressing adverse childhood experiences to improve public health: expert consultation. http://www.who.int/violence_injury _prevention/violence/activities/adverse_childhood_experiences/global_research _network_may_2009.pdf. 2009. Accessed February 3, 2012. Hardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry. 2004;45(2): 260-273. WWW.JAMAPEDS.COM ©2013 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by George Morris on 04/20/2016
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Assignment 1: Technology Assessment and Government Regulations

Assignment 1: Technology Assessment and Government Regulations

Assignment 1: Technology Assessment and Government Regulations Due Week 3 and worth 150 points You are the

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senior manager of a large healthcare organization. The senior management team must decide on a Health Information Management Systems (HIMS) for the organization that will encompass several clinical and administrative departments. You will need to create a PowerPoint presentation that will persuade your CEO to purchase your chosen HIMS. Your presentation should also contain some important aspects of HIMS (EMR) such as, implementation, interoperability, productivity, and support challenges. Create a twenty to twenty five (20-25) slide PowerPoint presentation in which you: 1. Create an argument to be presented to the CIO the need to integrate all clinical and administrative departments using a Health Information Management System in your health care organization. Note: Your title slide is considered as one (1) slide. 2. Identify and analyze the most significant EHI, EHR, HIPPA, and HITECH current regulations in your state. Next, determine two (2) ways they could impact the integration of HIMS in your health care organization. Be sure to include three (3) potential solutions to address these regulation challenges. 3. Propose three (3) privacy and security measure that will help health care providers avoid security breaches, data loss, and better allow them to concentrate on caring for their patients. Next, develop an action plan to protect patient information that complies with EHI, HER, PHI, HIPAA legal requirements. 4. Suggest three (3) key actions you could take to monitor privacy and security violations that may occur after the implementation of HIMS in your health care organization. 5. Use at least three (3) quality resources in this assignment. Note: Wikipedia and similar Websites do not qualify as quality resources. Note: Your references slides is considered as one (1) slide. The specific course learning outcomes associated with this assignment are: • • • • Demonstrate an understanding of the basic technology underlying health care information systems. Apply senior management’s role in information technology management. Use technology and information resources to research issues in health information systems. Write clearly and concisely about health information systems using proper writing mechanics.
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How do I make a powerpoint about How Does Race Affect Quality of Healthcare?

How do I make a powerpoint about How Does Race Affect Quality of Healthcare?

The final part of the power point project is the actual power point presentation.

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You should create at least 20 slides for the final power point.
In the power point, you will want to make sure you include the social theory (functionalism, conflict theory, interactionism, feminist, or queer theory) you have chosen and how it connects to your topic.

All sources should be listed on the final slide(s) in the power point, in APA format.
The final power point will be submitted through the Power Point Project Final Submission Assignment in Module 7.

Refer to the Power Point Project Rubric in the Course Resources tab for further information on grading requirements.

Rubric
Power Point Project Rubric (1)

Power Point Project Rubric (1)

Criteria Ratings Pts
This criterion is linked to a Learning OutcomeSociological Understanding & Application

70.0 pts
Exceptional

The presentation is lively, well-paced, interesting, and even exciting. The language has style. Looking at the presentation, we can feel a mind at work. The presentation is proof that the author has a true mastery of the sociological concepts pertaining to the topic.

56.0 pts
Proficient

The audience knows exactly what the author wants to say. It is well organized, it presents a worthwhile and interesting idea, that idea is supported by sound evidence, and contains discussion of core concepts in sociology, all presented in a neat and orderly way.

49.0 pts
Adequate

The presentation rarely uses evidence or core sociological concepts well; sometimes it does not use evidence at all. The audience feels that the author has only a moderate grasp of the topic at hand.

42.0 pts
Limited

There is little indication that the author understands the material being presented, but there are some attempts at incorporating core concepts in sociology to the topic at hand

35.0 pts
Insufficient

There is no evidence that the presenter has any comprehension of the topic at hand. There is no application of sociological understanding in the presentation

70.0 pts

This criterion is linked to a Learning OutcomeNotes and Sources

15.0 pts
Exceptional

All sources are provided, along with links to the sources. All sources are reliable, and most are from peer-reviewed journals and books. Detailed notes are provided that correlate with the presentation.

12.0 pts
Proficient

Good sources are provided and the notes contain references to all points presented.

10.5 pts
Adequate

A mixture of reliable and questionable sources is provided. The notes provided correlate with the presentation, but do not cover all points presented.

9.0 pts
Limited

Sources are provided, but they are not good, reliable sources. Notes correlate only slightly with presentation.

7.5 pts
Insufficient

There are no sources provided, and the notes do not correlate with t

WALDEN Healthcare Leadership Features And Challenges Discussion

WALDEN Healthcare Leadership Features And Challenges Discussion

Review this week’s Learning Resources. Select two contemporary theories of leadership that are relevant to the

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demands of the complex healthcare environment.
https://web-a-ebscohost-com.ezp.waldenulibrary.org…
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Identify specific health care organization challenges where these theories can be applied. How do these leadership theories offer approaches to overcome these challenges?
Post a cohesive response to the following:

Describe the two contemporary theories of leadership you selected. Analyze health care organization challenges where these theories can be applied. Recommend strategies to overcome these challenges. Defend or argue your recommendations.

Healthcare Mission Statement Business Plan and Recommendation Assignmen

Healthcare Mission Statement Business Plan and Recommendation Assignmen

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Instructions

This assignment should be researched using a minimum of three scholarly resources. It should be written using APA formatting and be a minimum of 550 words.

Select a business you would like to go into, in your field of interest (healthcare administration Imagine that you have been hired in a management position. The company is looking to expand and wishes to apply for a loan of $2,000,000 to help them set up a satellite office. The first task you have been assigned is to prepare a business plan to show the bank.

For the first part of this business plan:

Describe the business including the mission statement, the products and services the company offers, and who you consider to be the company’s competition.
What would you recommend your company do so that it stands out from the competition?
How will you help this business to accommodate a global business environment?
What talents will you be looking for when you hire employees?
What technologies are imperative to maintaining the business?
What does the company currently charge for its products and/or services they offer?

Chapter 1 Marketing Initiatives to Improve Clinical Workload Assignment

Chapter 1 Marketing Initiatives to Improve Clinical Workload Assignment

First, review the case study that preceded Chapter 1 in the textbook. Then respond to the following: After investigating the declining performance of CMC, the new CEO believes that a new marketing plan is necessary to gain market share. Develop a list of five marketing initiatives to improve clinical workload. Who should be involved in developing the CMC marketing plan?

Your initial posting should be 250-500 words

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