tag:blogger.com,1999:blog-1443178381846934312.post6100400390478025675..comments2023-11-23T01:21:38.194-08:00Comments on Mission: Health Equity : From randomized trials to the real worldsorayahttp://www.blogger.com/profile/14780792746786453756noreply@blogger.comBlogger2125tag:blogger.com,1999:blog-1443178381846934312.post-49860694196625318052014-09-25T11:14:53.892-07:002014-09-25T11:14:53.892-07:00Urmimala: Thank you for this insightful comment, A...Urmimala: Thank you for this insightful comment, Andy. I absolutely agree that we have newer, better, observational data and should treat it separately from its less rigorous predecessors.courtneyhttps://www.blogger.com/profile/03807667038134284531noreply@blogger.comtag:blogger.com,1999:blog-1443178381846934312.post-62518145329456596612014-09-19T17:07:08.711-07:002014-09-19T17:07:08.711-07:00I would like to second your thoughtful and importa...I would like to second your thoughtful and important statement! When it comes to evidence-based clinical decisions, observational evidence has historically been ranked as a second rate citizen (at best) and often ignored. We need to acknowledge, however, that much of the published observational research is poorly designed to make causal inferences (e.g., cross-sectional studies)...and their inclusion may have given observational research a lousy reputation among policy and guideline makers. However, the ability to make valid causal inferences in observational research has made substantial advances. There are now several, rigorous causal methods such as difference-in-difference models, (e.g., the one used in your recent paper: Use of the Refill Function Through an Online Patient Portal is Associated With Improved Adherence to Statins in an Integrated Health System. Medical Care 2014 Mar;52(3):194-201), marginal structural models (MSM), instrumental variables, and directed acyclic graph-guided model specification. Systematic reviews should consider evidence based on these more rigorous approaches as a separate, special class, rather than pooling their evidence with causally inferior observational methods. Most guidelines committees continue to base decisions on primarily RCTs (considered strong evidence)....despite RCTs being often not predictive of real-world effectiveness in the end. Instead, I believe (when possible) we should base policy decisions on evidence from both experimental and observational studies; they have complementary strengths and weaknesses (e.g., internal vs external validity). In many cases, RCTs will never be performed (e.g., questions of addressing health disparities), and in such instances, we will need to inform policy and guideline decisions on rigorous observational research alone. (Andrew Karter, PhD, Division of Research, Kaiser Permanente)Anonymoushttps://www.blogger.com/profile/04102920981967028590noreply@blogger.com