How hospitals can improve their public quality metrics: a decision-theoretic model.

The public reporting of hospitals' quality of care is providing additional motivation for hospitals to deliver high-quality patient care. Hospital Compare, a consumer-oriented website by the Centers for Medicare and Medicaid Services (CMS), provides patients with detailed quality of care data on most US hospitals. Given that many quality metrics are the aggregate result of physicians' individual clinical decisions, the question arises if and how hospitals could influence their physicians so that their decisions positively contribute to hospitals' quality goals. In this paper, we develop a decision-theoretic model to explore how three different hospital interventions-incentivization, training, and nudging-may affect physicians' decisions. We focus our analysis on Outpatient Measure 14 (OP-14), which is an imaging quality metric that reports the percentage of outpatients with a brain computed tomography (CT) scan, who also received a same-day sinus CT scan. In most cases, same-day brain and sinus CT scans are considered unnecessary, and high utilizing hospitals aim to reduce their OP-14 metric. Our model captures the physicians' imaging decision process accounting for medical and behavioral factors, in particular the uncertainty in clinical assessment and a physician's diagnostic ability. Our analysis shows how hospital interventions of incentivization, training, and nudging affect physician decisions and consequently OP-14. This decision-theoretic model provides a foundation to develop insights for policy makers on the multi-level effects of their policy decisions.

Determinants of outcomes following outpatient placement of implantable cardioverter defibrillators in a Medicare Advantage population.

BACKGROUND: Recipients of ICD are likely to have several risk factors that could interfere with successful use of implantable cardioverter defibrillators (ICDs). HYPOTHESIS: Age, sex, and factors indicated in claims are associated with one-year mortality and complications after ICD placement. METHODS: Adult Medicare Advantage patients who underwent outpatient ICD implantation from January 2014 to September 2015 were included. Age, sex, Charlson Comorbidity Index (CCI), prior year hospitalization and emergency department (ED) visit, diabetes, heart failure, ischemic heart disease, and indicators of the need for pacing were evaluated as risk factors. Mortality and device-related complications (lead and nonlead) were assessed at one-year post-procedure using Kaplan-Meier and Cox Proportional Hazard analysis. RESULTS: Among 8450 patients who underwent implantation, 1-year event-free survival was 80.1%, based on an overall composite measure of complications and mortality. Adjusted survival analysis showed that age ≥ 65, male sex, incremental increase in CCI, heart failure, prior year hospitalization, ED visit, and prior year pacing procedure were significant predictors of mortality. Age ≥ 65, male sex, and prior year hospitalization were significant predictors of a composite measure of device-related complications. CCI and prior hospitalization were significant predictors of a composite measure of any adverse outcome. CONCLUSIONS: Results suggest most patients in an older population do not experience adverse outcomes in the year following ICD implantation. The risk of mortality may be greater in men, patients over the age of 65, and patients with greater general morbidity, heart failure, or a history of a pacing procedure.

A Bold Goal: More Healthy Days Through Improved Community Health.

Humana, a large health care company, has set a goal of 20% improvement in health in the communities it serves by 2020. The metric chosen for the Bold Goal initiative was the HRQOL-4 version of the Centers for Disease Control and Prevention (CDC) Healthy Days survey. This paper presents the methods for measuring progress, reports results for the first year of tracking, and describes Humana's community-based interventions. Across 7 specially designated "Bold Goal" communities, mean unhealthy days declined from 10.98 in 2015 to 10.64 in 2016, which represented a 3.1% relative, or 0.34 absolute, decline. This compares with a 0.17 absolute unhealthy days decline in Humana's national population overall. The paper also describes how additional work identifying associations between social determinants of health (SDOH) and Healthy Days is influencing Humana's strategy. Lastly, a strategy of community engagement is illustrated through 2 case examples: San Antonio and Knoxville. In the San Antonio area, the community in which Humana has been involved the longest, unhealthy days dropped by 9.0% (-0.95 absolute) from a mean 10.52 to 9.57 unhealthy days. In Knoxville, one of the newer areas of engagement, mean unhealthy days declined by 4.8% (-0.61 absolute), representing declines in both physically and mentally unhealthy days. Overall, results are encouraging, and Humana expects declines to accelerate over time as initiatives are launched and scaled in Bold Goal communities.