EHR Errors Essay
EHR Errors Essay
Read the following article:
The following quote from the article mentions a problem with data entry errors that directly affect the performance of the EHR system.
“If information is entered incorrectly on the front end the HIM department has additional clean-up on the back end, ‘It is “garbage in, garbage out,’ Bell notes.”
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Questions for discussion:
- How do you think “garbage in, garbage out” can be avoided?
- How can the source of the inaccurate data be identified? EHR Errors Essay
Performance of the EHR System
How I think “garbage in, garbage out” can be avoided
“Garbage in, garbage out” is a phrase severally used to express the fact that, input that is of poor quality or incorrect will always result in faulty output as related to computing or other spheres of day to activities. However, it is possible to avoid “garbage in, garbage out” more so in relation to the field of computing. The first initiative to avoid “garbage in, garbage out” is by individuals expressing and selling the benefits of a clean data set EHR Errors Essay. Basically, a clean dataset ensures that the process of cleansing data in not only possible but also effective in producing desired outcomes. Performing regular data cleansing exercises through software and hardware updates assure the integrity of data hence accurate results (Wiedemann, 2010).
Another way in which “garbage in, garbage out” can be avoided is through working within existing processes. There is a specific procedure in which specific operations have to be executed before receiving final outcomes. It is essential that computer users follow these procedures depending on specific computer applications and operations they would like to perform. In this manner, computer users are able to prioritize operations, identify possibilities of errors and correct before execution hence avoiding possibilities of the occurrence of “garbage in, garbage out”(Bjokaman, 2014).
“Garbage in, garbage out” is highly attributable to human and system errors although the former largely contribute in comparison with the latter. For this reason, it should be an initiative by computer users to countercheck data and information before inputting to check for possible errors and inaccuracies that may result in undesired outcomes. This has to be done just before or at the point of data entry as it helps to avoid occurrences of “garbage in, garbage out” (Thomson, 2009) EHR Errors Essay.
How the Source of the Inaccurate Data Can Be Identified
Right from the entry point, it is possible to identify sources of incorrect data especially if the person who enters the data knows what type of data to expect before entry. In this manner, an individual is able to identify inaccuracy sources which may include misspellings, human errors and even system errors during the process of data entry. The most common type of error in that largely contributes to the inaccuracy of data is attributed to human errors which are likely associated with ignorance of individuals EHR Errors Essay. However, sources of human errors are easily identified through a series of steps that range from inspecting the data collection process to the center of data output. Through this initiative, it is possible to identify if data inaccuracy is attributable to human errors, system errors or both (Nickle, 2012).
References
Bjokaman, P. (2014). Avoiding the ‘Garbage in Garbage Out’ trap – Snow Software
Blog.Software Asset Management & License Optimization Blog.Mc
Nickle, M. (2012) 5 reasons data inaccuracies occur in EMRs. Healthcare IT News.
Thomson, V. E. (2009). Garbage in, garbage out: Solving the problems with long-distance trash
transport Charlottesville: University of Virginia Press EHR Errors Essay.
Wiedemann. Lou Ann. (2010). Completing Charts in EHRs Journal of AHIMA, 81, no.1,
January 2010: 40-41. Available at https://content.learntoday.info/Learn/HIM2652fw_Spring_16/site/Media/Completing_Charts_in_EHRs.docx Accessed on 30/10/2017
Completing Charts in EHRs
By Lou Ann Wiedemann, MS, RHIA, CPEHR This issue the Journal introduces a new “Working Smart” column offering best practices for working in the e-HIM environment. Since the advent of the HIM profession many have struggled with the chart completion process. In the paper environment, the process began with assembling mountains of paper into a logical order and sequence. From there clerical staff spent countless hours reviewing pages for signatures and missing documentation EHR Errors Essay. Many of these processes still remain in the EHR. “It really comes down to a process that is shorter, but sometimes more time-consuming,” says Bonnie Irzyk, RHIT, HIM manager at VNS Home Health Services in Rhode Island. This column outlines practice guidance for completing a record in an electronic environment. Defining Chart Completion Policies and Procedures The first step in the chart completion process is to review regulatory guidelines, including any state-specific, Joint Commission, or Centers for Medicare and Medicaid Services guidelines regarding record completion. Most organizations require that each entry within a record be signed. State regulations may further outline that entities include the date and time with the signature. These requirements, and any other requirements, should be outlined in an organization’s chart completion policies and procedures EHR Errors Essay. Organizations should ensure that their policies and procedures are up-to-date as processes change. Irzyk recommends keying in on specific terms such as “paper” when reviewing specific department policies and procedures. In such an instance, organizations can simply change references from “paper” to “electronic.” Policies and procedures should define when a record is complete. For most organizations, a record is complete once all applicable signatures and reports are verified to be part of the record. The organization should then define which signatures and reports the HIM department will confirm. For example, at OU Medical Center in Oklahoma City, HIM manager Valerie Bell, RHIA, considers a record complete when the clerical staff has confirmed that it contains a “history and physical, discharge summary, applicable consultations or operative notes as well as signatures on each report and all physician orders.” If one physician order is missing, the record remains incomplete until that order is signed EHR Errors Essay. This is the same policy that was in place when the record was completely comprised of paper. The only process that has changed is the process by which reports and signatures are obtained. Irzyk also recommends that every department define its legal electronic health record. A documentation crosswalk can provide guidance on the components of the legal health record EHR Errors Essay. It will also help HIM professionals address other issues, such as electronic signature, within other policies. For example, an organization that has implemented electronic signature no longer must obtain manual signatures. Instead of reviewing and placing a manual deficiency into an HIM tracking module, EHR systems have built-in queues that recognize the author and the need for a cosignature. The order is automatically sent to the appropriate physician for counter signature. No manual review is needed. Chart Completion Challenges A major challenge for HIM professionals is learning an EHR system’s functionality. Irzyk found that “understanding the logic of the software” was a major hurdle to overcome at VNS. The software VNS chose allowed providers to enter clinical notes; however, it did not provide e-signature functionality for all modules. The issue was quickly recognized by working closely with providers and IT. The HIM and IT departments were able to adapt a system “task” function as a workaround EHR Errors Essay. The HIM department completes the task, which sends a notification to the clinician to complete the record deficiency. Once the physician completes the deficiency, an edit list is reviewed in the HIM department to complete the record. HIM professionals should not be afraid to ask system questions, nor should they assume that if a system has electronic data entry it automatically allows e-signatures. In addition, the number of people entering data on the front end increases as more modules are moved to the electronic environment. If information is entered incorrectly on the front end the HIM department has additional clean-up on the back end. “It is ‘garbage in, garbage out,’” Bell notes. For example, if a nurse enters a verbal order and links it to the incorrect physician the HIM department usually finds out after discharge. The system assigns the signature to the incorrect physician, who then comes to HIM to have the order corrected. HIM professionals must understand the functionality of the software and how physicians are assigned in these instances. EHR Errors Essay “If we [HIM] don’t understand, the number of incorrect deficiencies continues to increase and physicians get frustrated with a system that does not appear to work correctly,” Bell says. Another major challenge for HIM professionals is job responsibilities. Many providers feel that record completion activities are clerical functions and do not fall within their scope of services. However, these functions are no longer black and white in an electronic environment. For example, when implementing computerized physician order entry, a key process in the paper world was the transcription of the order. Many times a ward clerk reviewed the order and then transcribed the order into the different ancillary modules (e.g., medications to the pharmacy or chest x-ray to the radiology department). As ward clerks entered the order they answered key questions such as “Is the patient required to have nothing by mouth?” prior to the test. In the electronic world these questions are flagged for the provider entering the order to answer. Physicians may feel overwhelmed at the beginning of the electronic order implementation because they are not accustomed to answering these types of questions. Another challenge for HIM professionals during the transition is the hybrid process that occurs while modules are being implemented. During this time period providers may be completing records electronically and manually EHR Errors Essay. Clerical staff must then identify which providers are signing electronically and which are signing manually.
In a facility with a large medical staff this process can bring HIM processes to a screeching halt. “It is a huge problem that is often overlooked,” Bell says. The HIM department should be aware of chart completion concerns before beginning the transition. “Just go into the implementation being aware of back-end difficulties,” she recommends. As HIM professionals move toward an electronic record there are several lessons to be learned. Completing health records and maintaining the integrity of the information is a fundamental HIM function that cannot be lost in the transition to an EHR. “Just when you think you have it down, something new happens,” says Irzyk. “However, the end product is more accurate, and the documentation is better.” HIM professionals can take advantage of the EHR to streamline record completion processes and minimize duplication of effort. Lou Ann Wiedemann is a director of practice resources at AHIMA.
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How I think “garbage in, garbage out” can be avoided
“Garbage in, garbage out” is a phrase severally used to express the fact that, input that is of poor quality or incorrect will always result in faulty output as related to computing or other spheres of day to activities. However, it is possible to avoid “garbage in, garbage out” more so in relation to the field of computing. The first initiative to avoid “garbage in, garbage out” is by individuals expressing and selling the benefits of a clean data set EHR Errors Essay. Basically, a clean dataset ensures that the process of cleansing data in not only possible but also effective in producing desired outcomes. Performing regular data cleansing exercises through software and hardware updates assure the integrity of data hence accurate results (Wiedemann, 2010).
ORDER A PLAGIARISM-FREE PAPER NOW
Another way in which “garbage in, garbage out” can be avoided is through working within existing processes. There is a specific procedure in which specific operations have to be executed before receiving final outcomes. It is essential that computer users follow these procedures depending on specific computer applications and operations they would like to perform. In this manner, computer users are able to prioritize operations, identify possibilities of errors and correct before execution hence avoiding possibilities of the occurrence of “garbage in, garbage out”(Bjokaman, 2014).
“Garbage in, garbage out” is highly attributable to human and system errors although the former largely contribute in comparison with the latter. For this reason, it should be an initiative by computer users to countercheck data and information before inputting to check for possible errors and inaccuracies that may result in undesired outcomes. This has to be done just before or at the point of data entry as it helps to avoid occurrences of “garbage in, garbage out” (Thomson, 2009) EHR Errors Essay.
How the Source of the Inaccurate Data Can Be Identified
Right from the entry point, it is possible to identify sources of incorrect data especially if the person who enters the data knows what type of data to expect before entry. In this manner, an individual is able to identify inaccuracy sources which may include misspellings, human errors and even system errors during the process of data entry. The most common type of error in that largely contributes to the inaccuracy of data is attributed to human errors which are likely associated with ignorance of individuals. EHR Errors Essay However, sources of human errors are easily identified through a series of steps that range from inspecting the data collection process to the center of data output. Through this initiative, it is possible to identify if data inaccuracy is attributable to human errors, system errors or both (Nickle, 2012).
References
Bjokaman, P. (2014). Avoiding the ‘Garbage in Garbage Out’ trap – Snow Software
Blog.Software Asset Management & License Optimization Blog.Mc
Nickle, M. (2012) 5 reasons data inaccuracies occur in EMRs. Healthcare IT News.
Thomson, V. E. (2009). Garbage in, garbage out: Solving the problems with long-distance trash
transport Charlottesville: University of Virginia Press.
Wiedemann. Lou Ann. (2010). Completing Charts in EHRs Journal of AHIMA, 81, no.1,
January 2010: 40-41. Available at https://content.learntoday.info/Learn/HIM2652fw_Spring_16/site/Media/Completing_Charts_in_EHRs.docx Accessed on 30/10/2017 EHR Errors Essay