Big Data Risks and Rewards in Healthcare Clinical System Essay

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Big data in healthcare

Potential Benefit of Big Data in Healthcare Clinical System

Big data analytics is fast becoming a promising field in the provision of insights into data sets of large magnitude while simultaneously minimizing healthcare costs. Thew (2016) points out that for big data to be utilized in influencing meaningful outcomes within the nursing field, nurse executives need to take up their role as architects and visionaries of data.One of the potential benefit of using big data is dexcribed in the article by Thew, the local hospital mentioned using Meditech, a software program that allows physicians remote access to patients’ charts. By using Meditech, it is less time consuming and easier in comparison to making medical rounds. Meditech allows physicians to view a patient’s lab tests, CT scans, ultrasounds, notes on the patients from all attending or attended physicians, among other vital information, Stware such as Meditech is beneficial to a clinical sytem as it primarily saves time through remote patient assessment by physicians. Big Data Risks and Rewards in Healthcare Clinical System Essay

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Potential Risk of Big Data Use in a Clinical System

One example of a potential challenge of using big data is in accessing and capturing data that is correctly formatted, accurate, complete and clean for utilization in multiple systems. This is because data comes from different sources and some of the sources lack impeccable governance (Bresnick, 2017).  A recent study by Valikodath, Newman, Lee, et al., (2017) depicted one such challenge. The researchers conducted a study in an ophthalmology clinic where the patient-reported data from 23.5% of EHR was analyzed. The study revealed that when patients reported three or more ocular problem symptoms, the EHR data did not reconcile the same. This was an example of poor reconciliation of data despite the accurate presentation of information by patients. Asri, Mousannif, Moatassim, et al., (2015) assert that poor usability of EHR, convoluted workflows and a failure to completely understand the importance of capturing big data well, can add to the quality issues that compromise data throughout the entire lifecycle. Big Data Risks and Rewards in Healthcare Clinical System Essay.

Strategy to Mitigate the Challenge

To ensure that data sourced by a healthcare facility is reliable, clean, and accurate, quality assurance measures need tobe put in place. More specifically policies that enforce the validation of data should be enforced in a healhtcare facility. Additionally, data on patients should be comprehensive which means that patient records should be complete with their care events as well as in the information that is of relevance regarding individual patients. Comprehensiveness will require for a healthcare faciiltiy to have accurate information on the patient’s every encounter with the system over time. Big Data Risks and Rewards in Healthcare Clinical System Essay. To achieve this, a patient seeking medical assistance in a new healthcare facility will be required to inform on whether they have had other hospital visits. The information availed by the patient will be counter-checked in the state and federal healthcare system for clarification and reconciliation. Doing so will ensure that a patient receives the right treatment and avoid medical errors.

References

Asri, H., Mousannif, H., Al Moatassime, H., & Noel, T. (2015, June). Big data in healthcare: Challenges and opportunities. In 2015 International Conference on Cloud Technologies and Applications (CloudTech) (pp. 1-7). IEEE.

Bresnick, J. (2017). Top 10 Challenges of Big Data Analytics in Healthcare. Health IT Analytics. Available online at: https://healthitanalytics. com/news/top-10-challenges-of-big-data-analytics-in-healthcare (AccessedJun20, 2018). Big Data Risks and Rewards in Healthcare Clinical System Essay

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs

Valikodath, N. G., Newman-Casey, P. A., Lee, P. P., Musch, D. C., Niziol, L. M., & Woodward, M. A. (2017). Agreement of ocular symptom reporting between patient-reported outcomes and medical records. JAMA ophthalmology, 135(3), 225-231.

Big Data Risks and Rewards
When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.

From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth. Big Data Risks and Rewards in Healthcare Clinical System Essay

As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.

To Prepare:

Review the Resources and reflect on the web article Big Data Means Big Potential, Challenges for Nurse Execs.
Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.

Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples. Big Data Risks and Rewards in Healthcare Clinical System Essay

Learning Resources
Note: To access this week’s required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.

Required Readings
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Chapter 25, “The Art of Caring in Technology-Laden Environments” (pp. 525–535)
Chapter 26, “Nursing Informatics and the Foundation of Knowledge” (pp. 537–551)
American Nurses Association. (2018). Inclusion of recognized terminologies supporting nursing practice within electronic health records and other health information technology solutions. Retrieved from https://www.nursingworld.org/practice-policy/nursing-excellence/official-position-statements/id/Inclusion-of-Recognized-Terminologies-Supporting-Nursing-Practice-within-Electronic-Health-Records/

Macieria, T. G. R., Smith, M. B., Davis, N., Yao, Y., Wilkie, D. J., Lopez, K. D., & Keenan, G. (2017). Evidence of progress in making nursing practice visible using standardized nursing data: A systematic review. AMIA Annual Symposium Proceedings, 2017, 1205–1214. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977718/ Big Data Risks and Rewards in Healthcare Clinical System Essay

Office of the National Coordinator for Health Information Technology. (2017). Standard nursing terminologies: A landscape analysis. Retrieved from https://www.healthit.gov/sites/default/files/snt_final_05302017.pdf

Rutherford, M. A. (2008). Standardized nursing language: What does it mean for nursing practice? Online Journal of Issues in Nursing, 13(1), 1–12. doi:10.3912/OJIN.Vol13No01PPT05.

Note: You will access this article from the Walden Library databases.

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Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs

Topaz, M. (2013). The hitchhiker’s guide to nursing theory: Using the Data-Knowledge-Information-Wisdom framework to guide informatics research. Online Journal of Nursing Informatics, 17(3).

Note: You will access this article from the Walden Library databases. Big Data Risks and Rewards in Healthcare Clinical System Essay

Wang, Y. Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3–13. doi:10.1016/j.techfore.2015.12.019.

Note: You will access this article from the Walden Library databases.

Required Media
Laureate Education (Executive Producer). (2012). Data, information, knowledge and wisdom continuum [Multimedia file]. Baltimore, MD: Author. Retrieved from http://mym.cdn.laureate-media.com/2dett4d/Walden/NURS/6051/03/mm/continuum/index.html

Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success [Video file]. Baltimore, MD: Author.

Transcript for video
Analyzing Data for Clinical Success
Program Transcript
GRANT SHEVCHIK: Probably the one disorder/disease where information
technology has had the biggest impact and really done a great job is in the
management of diabetes. Diabetes has a lot of complications too it, a lot of
different things that can go wrong. But on the surface, what you\’re managing for
the most part are numbers. Obviously, information technology is very conducive
to measuring numbers. Big Data Risks and Rewards in Healthcare Clinical System Essay
So you can pull up Joe, and you can see Joe. And you can see his numbers. You
can see the trend over time. You can see all sorts of things. This was magic. This
was one of the reasons why, way back when, we wanted to get an electronic
record, because we were able to look at that.
But the most important thing is not looking at the numbers in isolation, but looking
at them over time and being able to say to you, hey Joe, you\’re doing a great job.
You went from a hemoglobin A1C of 15. Normal is supposed to be 7. You\’re
down to 9. Most people would be unhappy with you. I\’m ecstatic, because 9 is a
lot better than 15.
By saying it in that fashion, Joe has an incentive to get down to 8. Joe\’s last
doctor never even knew what his A1C was the time before, the time before that.
In the paper chart, the chart was never there when Joe was there.
But it also makes a difference if this person shows up in the emergency room
and needs emergency surgery. Is this diabetic a diabetic under good control? Is
this a diabetic that has a lot of problems?
In the past, all we\’ve done is coded them as being diabetes. And we patted the
doctor on the back and said, good job. You let us know they have diabetes.
Now we\’re really asking for the more specific detail. What else is going on? What
else is there? Having some data is good. But then taking that data and looking
and making it more accurate is a more desirable goal and would make a big
difference in that patient in the long run.
The advantages of the whole community– meaning patients, physicians, et
cetera– becoming electronic and communicating over the internet via
smartphones, via whatever– that\’s what\’s going to really change medicine,
especially in chronic diseases. If you\’re talking about somebody\’s arthritis, they
need to be able to tell you, where does it hurt? How much does it hurt– that sort
of thing. So it\’s not as straightforward. But if you build effective questionnaires,
you can have questionnaires that the computer is smart enough to answer and
analyze for you.
© 2018 Laureate Education, Inc. 1

Analyzing Data for Clinical Success
So the future is great if you take what\’s out there and available, have the
computer work for you, design effective questionnaires, design effective things,
reach out to patients on a regular basis, know who communicates back to you,
but also know the ones who you\’ve lost. It\’s like anything else. The most
important patients are the ones that somehow got lost to follow-up. They\’re the
ones that are going to come back and be the train wreck. They\’re going to be the
ones that come back and show up in the hospital in the emergency room.
IT mean makes it a whole lot better than it used to be with just paper cards,
where he pull the cards out and see who needs to be reminded this month.
However, you still need to have people on your end, meaning the physician\’s
office end, who\’s looking at this and managing this to be able to make sure that
you\’re communicating with your patients, they\’re getting back to you, and you\’re
seeing what needs to be done. Big Data Risks and Rewards in Healthcare Clinical System Essay
As we get farther along, and more and more people sign onto a patient portal–
that sort of thing– that\’s where the magic comes in, because now, I can reach out
to all my diabetics through the portal. I can remind 1,000 people in 10 minutes by
just writing what I want to write, and send it all 1,000 of them. We didn\’t have that
ability before.
The part that really makes it easier is we\’re now actually getting to people
through their smartphones. And so we need to use these things that are out
there, the things that are available to us, that we can begin to take advantage
and really reach out to our patients. They love the convenience. And most
importantly, they appreciate that we care.
Analyzing Data for Clinical Success
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Analyzing Data for Clinical Success
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Accessible player
Vinay Shanthagiri. (2014). Big Data in Health Informatics [Video file]. Retrieved from https://www.youtube.com/watch?v=4W6zGmH_pOw. Big Data Risks and Rewards in Healthcare Clinical System Essay