Deprescribing research in nursing home residents using routinely collected healthcare data: a conceptual framework.

BACKGROUND: Efforts are needed to strengthen evidence and guidance for appropriate deprescribing for older nursing home (NH) residents, who are disproportionately affected by polypharmacy and inappropriate prescribing. Given the challenges of conducting randomized drug withdrawal studies in this population, data from observational studies of routinely collected healthcare data can be used to identify patients who are apparent candidates for deprescribing and evaluate subsequent health outcomes. To improve the design and interpretation of observational studies examining determinants, risks, and benefits of deprescribing specific medications in older NH residents, we sought to propose a conceptual framework of the determinants of deprescribing in older NH residents. METHODS: We conducted a scoping review of observational studies examining patterns and potential determinants of discontinuing or de-intensifying (i.e., reducing) medications for NH residents. We searched PubMed through September 2021 and included studies meeting the following criteria: conducted among adults aged 65 + in the NH setting; (2) observational study designs; (3) discontinuation or de-intensification as the primary outcome with key determinants as independent variables. We conceptualized deprescribing as a behavior through a social-ecological lens, potentially influenced by factors at the intrapersonal, interpersonal, organizational, community, and policy levels. RESULTS: Our search in PubMed identified 250 potentially relevant studies published through September 2021. A total of 14 studies were identified for inclusion and were subsequently synthesized to identify and group determinants of deprescribing into domains spanning the five core social-ecological levels. Our resulting framework acknowledges that deprescribing is strongly influenced by intrapersonal, patient-level clinical factors that modify the expected benefits and risks of deprescribing, including index condition attributes (e.g., disease severity), attributes of the medication being considered for deprescribing, co-prescribed medications, and prognostic factors. It also incorporates the hierarchical influences of interpersonal differences relating to healthcare providers and family caregivers, NH facility and health system organizational structures, community trends and norms, and finally healthcare policies. CONCLUSIONS: Our proposed framework will serve as a useful tool for future studies seeking to use routinely collected healthcare data sources and observational study designs to evaluate determinants, risks, and benefits of deprescribing for older NH residents.