Impact of star ratings on Medicare health plan enrollment: A systematic literature review.

BACKGROUND: The Medicare star ratings program was developed by the Centers for Medicare and Medicaid Services in 2007 as an approach to evaluate health plan performance and quality. OBJECTIVE: This study aimed to identify and narratively describe studies that attempted to quantitatively assess the impact that Medicare star ratings have on health plan enrollment. METHODS: A systematic literature review (SLR) was conducted of PubMed MEDLINE, Embase, and Google to identify articles that quantitatively assessed the impact of Medicare star ratings on health plan enrollment. Inclusion criteria consisted of studies that conducted quantitative analyses to estimate the potential impact. Exclusion criteria consisted of qualitative studies and studies that did not directly assess plan enrollment. RESULTS: This SLR identified 10 studies that sought to measure the impact of Medicare star ratings on plan enrollment. Nine of the studies found that plan enrollment increased in accordance with increases in star ratings or that plan disenrollment increased with decreases in star ratings. One study conducted of data before the implementation of the Medicare quality bonus payment found contradictory results from one year to the next, whereas all the studies that assessed data after implementation found increases in enrollment in accordance to increases in star ratings or increases in disenrollment for decreases in star ratings. One concerning finding from some of the articles included in the SLR is that increases in star ratings had less of an impact on enrollment in higher-rated plans for ethnic and racial minorities and older adults. CONCLUSIONS: Increases in Medicare star ratings led to statistically significant increases in health plan enrollment and decreases in health plan disenrollment. Future studies are needed to assess whether this increase has a causal association or is caused by additional factors outside of or in addition to increases in overall star rating.

Successful deployment of drug-disease interaction clinical decision support across multiple Kaiser Permanente regions.

OBJECTIVE: The study sought to develop a criteria-based scoring tool for assessing drug-disease knowledge base content and creation of a subset and to implement the subset across multiple Kaiser Permanente (KP) regions. MATERIALS AND METHODS: In Phase I, the scoring tool was developed, used to create a drug-disease alert subset, and validated by surveying physicians and pharmacists from KP Northern California. In Phase II, KP enabled the alert subset in July 2015 in silent mode to collect alert firing rates and confirmed that alert burden was adequately reduced. The alert subset was subsequently rolled out to users in KP Northern California. Alert data was collected September 2015 to August 2016 to monitor relevancy and override rates. RESULTS: Drug-disease alert scoring identified 1211 of 4111 contraindicated drug-disease pairs for inclusion in the subset. The survey results showed clinician agreement with subset examples 92.3%-98.5% of the time. Postsurvey adjustments to the subset resulted in KP implementation of 1189 drug-disease alerts. The subset resulted in a decrease in monthly alerts from 32 045 to 1168. Postimplementation monthly physician alert acceptance rates ranged from 20.2% to 29.8%. DISCUSSION: Our study shows that drug-disease alert scoring resulted in an alert subset that generated acceptable interruptive alerts while decreasing overall potential alert burden. Following the initial testing and implementation in its Northern California region, KP successfully implemented the disease interaction subset in 4 regions with additional regions planned. CONCLUSIONS: Our approach could prevent undue alert burden when new alert categories are implemented, circumventing the need for trial live activations of full alert category knowledge bases.