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RESOURCE: Informatics Professor: Implementing the Learning Healthcare System Can Be Facilitated Using the Principles of Evidence-Based Medicine

The enthusiasm for big data and for the use of analytics and business intelligence with that data is reaching a fevered pitch. I share that enthusiasm, but also know from both my clinical and my informatics experience that knowledge will not emanate just by turning on the data spigot from the growing number of electronic health record (EHR) systems now in operational use. However, if we approach the problem properly, I believe we can achieve the goals of the learning healthcare system as eloquently laid out in various reports from the Institute of Medicine (IOM) [1, 2]

A complementary approach to learning from EHR and other clinical data can be to apply the basic approach of evidence-based medicine (EBM) [4]. In some ways, EBM is antagonistic to EHR data analytics, with the former giving the most value to evidence from controlled experiments, especially randomized controlled trials (RCTs), while the latter makes use of real-world observational data that may be incomplete, incorrect, and inconsistent.

But I maintain that we can look to the process of EBM to guide us in how to best approach the “evidence” of EHR data analytics and the learning health system. EBM is not just about finding RCTs. Rather, it uses a principled approach to find and apply the best evidence to make clinical decisions. In particular, EBM done most effectively uses four steps:

  1. Ask an answerable question
  2. Find the best evidence
  3. Critically appraise the evidence
  4. Apply it to the patient situation

By: Dr. William Hersch

Written by

Joel is a digital innovation leader who has spent the past 15 years improving access to information and data across the life science and healthcare industries as an entrepreneur, board member, and advisor. He co-founded and currently leads ArcheMedX, which applies behavioral science to transform learning and generate actionable insights for Healthcare and Life Science organizations.

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