Although the Centers for Medicare and Medicaid Services (CMS) spends over $18 billion annually to care for 3.5 million home health (HH) beneficiaries, we know very little about how these beneficiaries select home health agencies (HHAs), or the impact of their choices on their health care outcomes. To facilitate HHA selection, CMS introduced technical quality and patient experience summary star ratings on the HH Compare website in July 2015 and January 2016. Currently, there is no information about the value of the HH star ratings in terms of driving patient selection, representing patient priorities, or predicting patient outcomes. The long-term goal of this research is to develop meaningful measures of HH quality that patients, families, and referring clinicians can use to make informed decisions about HH care. The first step towards this goal, and the immediate objective of this application, is to understand and compare the impact and effectiveness of the publicly reported quality and patient experience star ratings for HHAs. Our central hypothesis is that both technical quality and patient experience star ratings will be related to agency selection, patient outcomes, and satisfaction (represented by returning, rather than switching HHAs, for future episodes). We further hypothesize that patient experience will have a greater influence on selection and satisfaction, while technical quality will be more strongly associated with outcomes. To evaluate our hypotheses, we propose the following specific aims: 1) Compare the impact of the introduction of technical quality and patient experience star ratings on HHA selection, 2) Assess the relationship between HHA star ratings and individual patient outcomes, and 3) Evaluate the relationship between HHA star ratings and switching HHAs amongst individuals with more than one HH episode. To achieve these objectives, we propose to study Medicare Fee-for-Service beneficiaries who received HH care between 2014 and 2016 using Medicare claims linked to data from the Home Health Outcome and Assessment Information Set (OASIS).
The first aim will utilize a conditional logit discreet choice model to compare the likelihood of selecting an HHA of each star rating before and after the introduction of star ratings.
Aims 2 and 3 will utilize instrumental variable (IV) analyses to estimate the likelihoods of experiencing ten outcomes (Aim 2), and the likelihood of switching HHAs (Aim 3) among HHAs of different star ratings. The proposed work is innovative because it is the first study to evaluate the impact and effectiveness of the newly released HH star ratings and the first in-depth exploration of patient focused effects of quality reporting in HH. Additionally, we utilize a novel IV to conduct a causal analysis of the relationship between HHA selection and outcomes. This work is significant because understanding HH selection and enabling HH patients and their families to make informed comparisons of providers is critical to ensuring accessible, high quality, and patient-centered care for this vulnerable population. Insights gained through this work may motivate HHAs to improve the quality of their care and inform policymakers regarding future changes to HH public reporting and value-based purchasing programs.
The proposed research is relevant to public health because selecting a low quality home health agency puts patients at increased risk for adverse outcomes such as hospitalizations, medication errors, falls, and functional decline. These negative outcomes are particularly detrimental to the elderly and chronically ill individuals that utilize home health care. This work is relevant to the mission of AHRQ because enabling patients and their families to make informed comparisons of home health providers is critical to achieving the goals of accessible, high quality, and patient centered care, as described in AHRQ's mission and the national quality strategy.
