Bench to Behavior Translation: Association of Evidence Generated by Comparative Efficacy and Effectiveness Research on Physician Prescribin

Background: Comparative Efficacy (CE) and Comparative Effectiveness Research (CER) constitute Evidence Based Medicine (EBM), which is a strong tool to aid the clinical decision-making process. The FDA doesn't mandate the generation of CE evidence and it can take up to a decade for CER evidence to be translated into clinical practice. The lack of adoption of EBM is one of the reasons for the cost and quality imbalance in the US health care system. There is no past research assessing the association of scientific evidence (CE and CER) with clinical practice as it relates to prescribing of drugs.;Aims: The primary aim of this study was to analyze the association of CE and CER evidence with physician prescribing in selected markets for Diabetes Mellitus and Hypertension. The secondary aim was to explore the cost burden of prescription drugs to patients to explain the prescribing trends in the selected markets.;Methods: The three different kinds of markets, GLP-1 agonist (CE market), DPP4 inhibitor (non-CE market), ARBs (mixed market) were identified under Diabetes Mellitus and Hypertension based on the availability of CE data. Within each market, systematic review was conducted to identify and assess the CER evidence. To assess the association of the identified CE and CER evidence with physician prescribing and to assess the cost burden in each market, a retrospective longitudinal analysis was conducted using Medical Expenditure Panel Survey (MEPS) data from 1996-2014. All of the estimates were weighted using the MEPS survey weights and clustered standard errors to represent the U.S. non-institutionalized population, using STATA 14 and presented in a graphical form. Time series plots of the estimates were created to show trends in the study variables.;Results: In the CE market (i.e. GLP-1 agonist market), the CE evidence suggested superiority of Liraglutide to Exenatide twice a day (BID). The CER evidence suggests that Liraglutide and Exenatide once a week (QW) have similar efficacy and are superior to Exenatide BID. The overall trends in annual drug prescribing rates were in concordance with this evidence. However, the trends in the cost burden didn't support the prescribing rates. In the non-CE market (i.e. DPP4 inhibitor market), the CER evidence suggested non-inferiority of all the drugs i.e. Sitagliptin, Saxagliptin and Linagliptin. In the absence of any CE evidence or conclusive superiority CER evidence, the prescribing rates could be explained by the cost burden incurred by the patients in terms of out-of-pocket payments. In the mixed market (i.e. ARBs market), the CE and CER evidence suggested superiority of Azilsartan to the comparators i.e. Olmesartan and Valsartan. However, the influence of the scientific evidence was not reflective in the prescribing trends due to the crowdedness of the ARBs market, Losartan becoming generically available, and choice of comparators used to generate the scientific evidence.;Conclusion: CE and CER evidence appear to be associated with physician prescribing, however, the association can vary depending on the type of therapeutic market. Stricter policies could be devised for the therapeutic markets which exhibited unsubstantial correlation of scientific evidence and prescribing. Regulations mandating CE evidence generation are needed for the drug approval process and stricter policies around the choice of comparators used to generate CE and CER evidence are required. In the absence of CE or CER evidence, physician prescribing or payer's formulary decision making might be guided by other factors such as pharmaceutical advertisements, rebates and patients' cost burden. Adoption of EBM will help quantify the value of different treatment therapies or drugs, which would lead to faster bench-to behavior translation in the US healthcare system.