Physicians Search For Best Treatment Plan Based On Outcomes Of Similar Patients In Hospital Records System, Not Medical Literature
This time, House, M.D. fans, it was lupus. The article “Evidence-Based Medicine in the EMR Era” published in the Nov. 10 issue of the New England Journal of Medicine might have read like a House television script, but it was a real-life glimpse of what the most optimistic health IT advocates are hoping will become commonplace in U.S. health care: Mining EHR data to arrive at treatment decisions.
In a Health IT Exchange piece (on TechTarget) EHR data spurs real-time evidence-based medicine, Don Fluckinger summarizes (and dramatizes, accurately) this early specimen of care being transformed – beyond the literature – by looking at past records. Faced with a 13 year old lupus patient with a complex problem (see article for details)…
In four hours, they did a retrospective study of similar patients in the hospital’s data warehouse…, and decided to move ahead with the treatment based on the previous results of 98 [similar patients] … The authors said they will never know if they made the “correct” decision, but they did know that — in absence of randomized trial research to support their decision — they acted on the evidence of the best data available, coupled with their experience.
“Our case is but one example of a situation in which the existing literature is insufficient to guide the clinical care of a patient,” the authors wrote. …
What are we waiting for, people?? Imagine if doctors were able to access all of our records, or at least those of us who opt in, so your doctors (your kids’ doctors, your mom’s) can go beyond the limitations of peer reviewed literature – and provide better care. Make better use of their training and experience.
So often we’re all hampered because the ideal information doesn’t exist. When the information does exist, isn’t it a tragedy to limit the quality of care because the frickin’ data is isolated in silos?? Let’s connect ‘em! Health information exchange! Aggregate! Summarize! Analyze!
Let’s get to work! Data liberación, as Todd says!
Congrats to these Stanford docs – and thanks yet again to @ICMCC for spotlighting this in their excellent daily newsletter. This was in their 10 Most Read for the week of 11/13.
p.s. And now let’s see House welcome contributions from engaged patients and families, bringing in the results of their research!
*This blog post was originally published at e-Patients.net*