Journal:Creating learning health systems and the emerging role of biomedical informatics
| Full article title | Creating learning health systems and the emerging role of biomedical informatics |
|---|---|
| Journal | Learning Health Systems |
| Author(s) | Kohn, Martin S.; Topaloglu, Umit; Kirkendall, Eric S.; Dharod, Ahay; Wells, Brian J.; Gurcan, Metin |
| Primary contact | Email: mkohn at wakehealth dot edu |
| Editors | Wake Forest School of Medicine Center for Biomedical Informatics |
| Year published | 2022 |
| Volume and issue | 6(1) |
| Article # | e10259 |
| DOI | 10.1002/lrh2.10259 |
| ISSN | 2379-6146 |
| Distribution license | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International |
| Website | https://onlinelibrary.wiley.com/doi/10.1002/lrh2.10259 |
| Download | https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.10259 (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Introduction: The nature of information used in medicine has changed. In the past, we were limited to routine clinical data and published clinical trials. Today, we deal with massive, multiple data streams and easy access to new tests, ideas, and capabilities to process them. Whereas in the past getting information for decision-making was a challenge, today's clinicians have readily available access to information and data through the multitude of data-collecting devices, though it remains a challenge at times to analyze, evaluate, and prioritize it. As such, clinicians must become adept with the tools needed to deal with the era of big data, requiring a major change in how we learn to make decisions. Major change is often met with resistance and questions about value. A "learning health system" is an enabler to encourage the development of such tools and demonstrate value in improved decision-making.
Methods: In this work, we describe how we are developing a biomedical informatics program to help our medical institution's evolution as an academic learning health system, including strategy, training for house staff, and examples of the role of informatics from operations to research.
Results: We highlight an array of learning health system implementations and educational programs to improve healthcare and prepare a cadre of physicians with basic information technology (IT) skills. The programs have been well accepted with, for example, increasing interest and enrollment in the educational programs.
Conclusions: We are now in an era when large volumes of a wide variety of data are readily available. The challenge is not so much in the acquisition of data, but in assessing the quality, relevance, and value of the data. The data we can get may not be the data we need. In the past, sources of data were limited, and trial results published in journals were the major source of evidence for decision making. The advent of powerful analytics systems has changed the concept of evidence. Clinicians will have to develop the skills necessary to work in the era of big data. It is not reasonable to expect that all clinicians will also be data scientists. However, understanding the role of artificial intelligence (AI) and predictive analytics, and how to apply them, will become progressively more important. Programs such as the one being implemented at Wake Forest fill that need.
Keywords: biomedical informatics, learning health systems, physician education
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This presentation is faithful to the original, with only a few minor changes to presentation, spelling, and grammar. In some cases important information was missing from the references, and that information was added. Everything else remains true to the original article, per the "NoDerivatives" portion of the distribution license.
