Factors influencing central nervous system medication deprescribing and behavior change in hospitalized older adults.

BACKGROUND: Central nervous system (CNS) medications are linked to higher morbidity and mortality in older adults. Hospitalization allows for deprescribing opportunities. This qualitative study investigates clinician and patient perspectives on CNS medication deprescribing during hospitalization using a behavioral change framework, aiming to inform interventions and identify recommendations to enhance hospital deprescribing processes. METHODS: This qualitative study focused on hospitalists, primary care providers, pharmacists, and patients aged ≥60 years hospitalized on a general medicine service and prescribed ≥1 CNS medications. Using semi-structured interviews and focus groups, we aimed to evaluate patient medication knowledge, prior deprescribing experiences, and decision-making preferences, as well as provider processes and tools for medication evaluation and deprescribing. Rapid qualitative analysis applying the Capability, Opportunity, Motivation, and Behavior (COM-B) framework revealed themes influencing deprescribing behavior in patients and providers. RESULTS: A total of 52 participants (20 patients and 32 providers) identified facilitators and barriers across deprescribing steps and generated recommended strategies to address them. Clinicians and patients highlighted the opportunity for CNS medication deprescribing during hospitalizations, facilitated by multidisciplinary teams enhancing clinicians' capability to make medication changes. Both groups also stressed the importance of intensive patient engagement, education, and monitoring during hospitalizations, acknowledging challenges in timing and extent of deprescribing, with some patients preferring decisions deferred to outpatient clinicians. Hospitalist and pharmacist recommendations centered on early pharmacist involvement for medication reconciliation, expanding pharmacy consultation and clinician education on deprescribing, whereas patients recommended enhancing shared decision-making through patient education on medication adverse effects, tapering plans, and alternatives. Hospitalists and PCPs also emphasized standardized discharge instructions and transitional care calls to improve medication review and feedback during care transitions. CONCLUSIONS: Clinicians and patients highlighted the potential advantages of hospital interventions for CNS medication deprescribing, emphasizing the necessity of addressing communication, education, and coordination challenges between inpatient and outpatient settings.

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.

OBJECTIVE: The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution's approach to evaluation and governance of algorithmic technologies used in clinical care and operations by creating an Implementation Guide that standardizes evaluation criteria so that local oversight is performed in an objective fashion. MATERIALS AND METHODS: Building on a framework that applies key ethical and quality principles (clinical value and safety, fairness and equity, usability and adoption, transparency and accountability, and regulatory compliance), we created concrete guidelines for evaluating algorithmic technologies at our institution. RESULTS: An Implementation Guide articulates evaluation criteria used during review of algorithmic technologies and details what evidence supports the implementation of ethical and quality principles for trustworthy health AI. Application of the processes described in the Implementation Guide can lead to algorithms that are safer as well as more effective, fair, and equitable upon implementation, as illustrated through 4 examples of technologies at different phases of the algorithmic lifecycle that underwent evaluation at our academic medical center. DISCUSSION: By providing clear descriptions/definitions of evaluation criteria and embedding them within standardized processes, we streamlined oversight processes and educated communities using and developing algorithmic technologies within our institution. CONCLUSIONS: We developed a scalable, adaptable framework for translating principles into evaluation criteria and specific requirements that support trustworthy implementation of algorithmic technologies in patient care and healthcare operations.

Development of a Community Hospital Medicine Affiliated Inpatient Rotation for Family Medicine Residents-A Collaborative Success.

Background: Hospitalists perform key roles as inpatient educators for family medicine residents. For the past decade, Duke University Family Medicine Residency Program had its inpatient family medicine resident rotation at non-Duke facilities. Objective: The authors describe the steps taken in 2020 to develop an inpatient Duke family medicine rotation at a North Carolina community hospital, Duke Regional Hospital, and provide outcomes data. Methods: Duke Family Medicine Residency and Duke Regional Hospital Medicine collaborated in addressing key issues to develop an inpatient rotation for family medicine residents. Performance metrics of patients cared for by both the family medicine inpatient resident team and internal medicine teams were compared. Resident satisfaction survey results were reviewed. Results: Retrospective cohort evaluation comparing the two inpatient services (internal medicine and family medicine) revealed the family medicine resident inpatient service performed comparatively in length of stay and 30-day readmission rates. Resident evaluation surveys of the family medicine inpatient rotation showed overall satisfaction with learning objectives. Conclusions: This new family medicine inpatient rotation has benefitted all parties. Key quality performance metrics such as LOS and readmissions are comparable to internal medicine, hospitalists have more teaching opportunities, and Duke family medicine has its residents training in a Duke-affiliated community hospital for their core inpatient rotation.