Improving Hypertension Management Through Preference List Defaults

Choice Behavior, Clinical Decision Support, Hypertension, Quality Improvement

Hypertension, Clinical Decision Support, Choice Behavior, Quality Improvement

This study aims to evaluate whether modifying the EPIC preference list to display combination blood pressure (BP) medications at the top and/or adding "(PREFERRED)" to the beginning of the medication listing increases prescribing of these medications. Combination BP medications are aligned with value-based care guidelines and may improve patient adherence and reduce pill burden. Currently, these medications may be under-prescribed in part due to their low visibility in the EPIC prescribing interface.

In this study, 50 primary care clinics at Geisinger will be randomized to a re-ordered preference list with combination BP medications at the top and/or adding "(PREFERRED)" to the beginning of the medication listing, or to have no change to the preference list. This intervention works by adding a special character ( i.e., "(" ) to the beginning of a medication name in EPIC, which moves it to the top of the preference list. However, this only works when the provider searches for the first medication in a combination medication. For example, if a provider in the intervention group searches for "Amlodipine," the combination "(PREFERRED) Amlodipine-Benazepril" will appear at the top of the preference list. However, a special character is NOT prioritized in the preference list when the second medication in a combination medication name is searched. For example, if the provider searches "Benazepril," the combination "(PREFERRED) Amlodipine-Benazepril" will be shown after single-class Benazepril prescriptions. The "(PREFERRED)" prefix will still be shown, which may encourage prescribing even without the medication listed first. The study will employ a three-level hierarchical design, clustering patients within providers and providers within clinics. The study will run for 3 months or until enrollment reaches 12,150 unique patients, whichever comes second. Clinic randomization will be stratified by variables that may affect response to the intervention including: clinic type (community medicine, senior medicine, internal medicine, FQHC), baseline prescribing rate for combination medications (\<8%, 8%-13%, \>13%), and number of providers (1-4, 5-9, 10-29, 30+). One exception to the above stratification is internal medicine, where there are only two clinics. These are also the only two clinics with 30+ providers, but baseline combination medication prescribing rates fall in different stratification categories. These two clinics will be kept in the same stratum because they are still similar in culture, procedures, and size. Stratified randomization was simulated 1000 times. Because strata are randomized independently and some strata include uneven numbers of clinics, overall assignment of the 50 clinics to treatment and control was uneven (e.g., 26 in treatment and 24 in control) on 709 of the 1000 iterations. To ensure a balance in clinic allocation to study arms, one of the 291 evenly randomized iterations will be randomly selected for implementation in the study.

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