Challenges in Deprescribing among Older Adults in Post-Acute Care Transitions to Home.

OBJECTIVES: Medications with a higher risk of harm or that are unlikely to be beneficial are used by nearly all older patients in home health care (HHC). The objective of this study was to understand stakeholders' perspectives on challenges in deprescribing these medications for post-acute HHC patients. DESIGN: Qualitative individual interviews were conducted with stakeholders involved with post-acute deprescribing. SETTING AND PARTICIPANT: Older HHC patients, HHC nurses, pharmacists, and primary/acute care/post-acute prescribers from 9 US states participated in individual qualitative interviews. MEASURES: Interview questions were focused on the experience, processes, roles, training, workflow, and challenges of deprescribing in hospital-to-home transitions. We used the constant comparison approach to identify and compare findings among patient, prescriber, and pharmacist and HHC nurse stakeholders. RESULTS: We interviewed 9 older patients, 11 HHC nurses, 5 primary care physicians (PCP), 3 pharmacists, 1 hospitalist, and 1 post-acute nurse practitioner. Four challenges were described in post-acute deprescribing for HHC patients. First, PCPs' time constraints, the timing of patient encounters after hospital discharge, and the lack of prioritization of deprescribing make it difficult for PCPs to initiate post-acute deprescribing. Second, patients are often confused about their medications, despite the care team's efforts in educating the patients. Third, communication is challenging between HHC nurses, PCPs, specialists, and hospitalists. Fourth, the roles of HHC nurses and pharmacists are limited in care team collaboration and discussion about post-acute deprescribing. CONCLUSIONS AND IMPLICATIONS: Post-acute deprescribing relies on multiple parties in the care team yet it has challenges. Interventions to align the timing of deprescribing and that of post-acute care visits, prioritize deprescribing and allow clinicians more time to complete related tasks, improve medication education for patients, and ensure effective communication in the care team with synchronized electronic health record systems are needed to advance deprescribing during the transition from hospital to home.

Antipsychotic use among older patients with dementia receiving home health care services: Prevalence, predictors, and outcomes.

BACKGROUND: Antipsychotic use is a safety concern among older patients in home health care (HHC), particularly for those with Alzheimer's disease and related dementias (ADRD). The objective of this study was to examine the prevalence and predictors of antipsychotic use among older adults with and without ADRD who received HHC, and the association of antipsychotic use with outcomes among patients living with ADRD. METHODS: In this secondary analysis of adults ≥65 years receiving care from an HHC agency in New York in 2019 (N = 6684), we used data from the Outcome and Assessment Information Set, Medicare HHC claims, and home medication review results in the electronic HHC records during a 60-day HHC episode. ADRD was identified by diagnostic codes. Functional outcome was the change in the composite activities of daily living (ADL) score from HHC admission to HHC discharge (measured in 5833 patients), where a positive score means improvement and a negative score means decline. Data were analyzed using logistic (predictors) and linear regression (association with outcome) analyses. RESULTS: The point prevalence of antipsychotic use was 17.2% and 6.6% among patients with and without ADRD, respectively. Among patients living with ADRD, predictors of antipsychotic use included having greater ADL limitations (odds ratio [OR] = 1.30, p = 0.01), taking more medications (OR = 1.04, p = 0.02), having behavioral and psychological symptoms (OR = 5.26, p = 0.002), and living alone (OR = 0.52, p = 0.06). Among patients living with ADRD, antipsychotic use was associated with having less ADL improvement at HHC discharge (ß = -0.70, p < 0.001). CONCLUSIONS: HHC patients living with ADRD were more likely to use antipsychotics and to experience worse functional outcomes when using antipsychotics. Antipsychotics should be systematically reviewed and, if contraindicated or unnecessary, deprescribed. Efforts are needed to improve HHC patients' access to nonpharmacological interventions and to provide education for caregivers regarding behavioral approaches to manage symptoms in ADRD.

How to Deprescribe Potentially Inappropriate Medications During the Hospital-to-Home Transition: Stakeholder Perspectives on Essential Tasks.

PURPOSE: Nearly all older patients receiving postacute home health care (HHC) use potentially inappropriate medications (PIMs) that carry a risk of harm. Deprescribing can reduce and optimize the use of PIMs, yet it is often not conducted among HHC patients. The objective of this study was to gather perspectives from patient, practitioner, and HHC clinician stakeholders on tasks that are essential to postacute deprescribing in HHC. METHODS: A total of 44 stakeholders, including 14 HHC patients, 15 practitioners (including 9 primary care physicians, 4 pharmacists, 1 hospitalist, and 1 nurse practitioner), and 15 HHC nurses, participated. The stakeholders were from 12 US states, including New York (n = 29), Colorado (n = 2), Connecticut (n = 1), Illinois (n = 2), Kansas (n = 2), Massachusetts (n = 1), Minnesota (n = 1), Mississippi (n = 1), Nebraska (n = 1), Ohio (n = 1), Tennessee (n = 1), and Texas (n = 2). First, individual interviews were conducted by experienced research staff via video conference or telephone. Second, the study team reviewed all interview transcripts and selected interview statements regarding stakeholders' suggestions for important tasks needed for postacute deprescribing in HHC. Third, concept mapping was conducted in which stakeholders sorted and rated selected interview statements regarding importance and feasibility. A content analysis was conducted of data collected in the individual interviews, and a mixed-method analysis was conducted of data collected in the concept mapping. FINDINGS: Four essential tasks were identified for postacute deprescribing in HHC: (1) ongoing review and assessment of medication use, (2) patent-centered and individualized plan of deprescribing, (3) timely and efficient communication among members of the care team, and (4) continuous and tailored medication education to meet patient needs. Among these tasks, developing patient-centered deprescribing considerations was considered the most important and feasible, followed by medication education, review and assessment of medication use, and communication. IMPLICATIONS: Deprescribing during the transition of care from hospital to home requires the following: continuous medication education for patients, families, and caregivers; ongoing review and assessment of medication use; patient-centered deprescribing considerations; and effective communication and collaboration among the primary care physician, HHC nurse, and pharmacist.

How "age-friendly" are deprescribing interventions? A scoping review of deprescribing trials.

OBJECTIVE: To assess how age-friendly deprescribing trials are regarding intervention design and outcome assessment. Reduced use of potentially inappropriate medications (PIMs) can be addressed by deprescribing-a systematic process of discontinuing and/or reducing the use of PIMs. The 4Ms-"Medication", "Mentation", "Mobility", and "What Matters Most" to the person-can be used to guide assessment of age-friendliness of deprescribing trials. DATA SOURCE: Published literature. STUDY DESIGN: Scoping review. DATA EXTRACTION METHODS: The literature was identified using keywords related to deprescribing and polypharmacy in PubMed, EMBASE, Web of Science, ProQuest, CINAHL, and Cochrane and snowballing. Study characteristics were extracted and evaluated for consideration of 4Ms. PRINCIPAL FINDINGS: Thirty-seven of the 564 trials identified met the review eligibility criteria. Intervention design: "Medication" was considered in the intervention design of all trials; "Mentation" was considered in eight trials; "Mobility" (n = 2) and "What Matters Most" (n = 6) were less often considered in the design of intervention. Most trials targeted providers without specifying how matters important to older adults and their families were aligned with deprescribing decisions. OUTCOME ASSESSMENT: "Medication" was the most commonly assessed outcome (n = 33), followed by "Mobility" (n = 13) and "Mentation" (n = 10) outcomes, with no study examining "What Matters Most" outcomes. CONCLUSIONS: "Mentation" and "Mobility", and "What Matters Most" have been considered to varying degrees in deprescribing trials, limiting the potential of deprescribing evidence to contribute to improved clinical practice in building an age-friendly health care system.

Implementation considerations of deprescribing interventions: A scoping review.

Over half of older adults experience polypharmacy, including medications that may be inappropriate or unnecessary. Deprescribing, which is the process of discontinuing or reducing inappropriate and/or unnecessary medications, is an effective way to reduce polypharmacy. This review summarizes (1) the process of deprescribing and conceptual models and tools that have been developed to facilitate deprescribing, (2) barriers, enablers, and factors associated with deprescribing, and (3) characteristics of deprescribing interventions in completed trials, as well as (4) implementation considerations for deprescribing in routine practice. In conceptual models of deprescribing, multilevel factors of the patient, clinician, and health-care system are all related to the efficacy of deprescribing. Numerous tools have been developed for clinicians to facilitate deprescribing, yet most require substantial time and, thus, may be difficult to implement during routine health-care encounters. Multiple deprescribing interventions have been evaluated, which mostly include one or more of the following components: patient education, medication review, identification of deprescribing targets, and patient and/or provider communication about high-risk medications. Yet, there has been limited consideration of implementation factors in prior deprescribing interventions, especially with regard to the personnel and resources in existing health-care systems and the feasibility of incorporating components of deprescribing interventions into the routine care processes of clinicians. Future trials require a more balanced consideration of both effectiveness and implementation when designing deprescribing interventions.

Medications Associated With Geriatric Syndromes (MAGS) and Hospitalization Risk in Home Health Care Patients.

OBJECTIVES: Polypharmacy is common in home health care (HHC). This study examined the prevalence of medications associated with geriatric syndromes (MAGS), its predictors, and association with subsequent hospitalization in HHC. DESIGN: Analysis of HHC electronic medical records, the Outcome and Assessment Information Set (OASIS), and Medicare HHC claims. SETTING AND PARTICIPANTS: A total of 6882 adults ≥65 years old receiving HHC in 2019 from a large, not-for-profit home health agency serving multiple counties in New York State. MEASURES: MAGS use was identified from active medications reconciled during HHC visits (HHC electronic medical records). MAGS use was operationalized as count and in quartiles. Hospitalization during the HHC episode was operationalized as a time-to-event variable (ie, number of days from HHC admission to hospitalization). We used regression analyses to identify predictors of MAGS use, and survival analyses to examine the association between MAGS and hospitalization. RESULTS: Nearly all (98%) of the HHC patients used at least 1 MAGS and 41% of all active medications used by the sample were MAGS. More MAGS use was found in HHC patients who were community-referred, taking more medications, and having more diagnoses, depressive symptoms, and functional limitations. Adjusted for covariates, higher MAGS quartiles were not independently associated with the risk of hospitalization, but higher MAGS quartiles combined with multimorbidity (ie, having ≥10 diagnoses) were associated with a 2.3-fold increase in hospitalization risk (hazard ratio 2.24; 95% confidence interval: 1.61-3.13; P < .001), relative to the lowest quartile of MAGS use and having <10 diagnoses. CONCLUSIONS AND IMPLICATIONS: More than 40% of medications taken by HHC patients are MAGS. Multimorbidity and MAGS use collectively increased the risk of hospitalization by up to 2.3 times. HHC clinicians should carefully review patients' medications and use information about MAGS to facilitate discussion about deprescribing with patients and their prescribers.

Machine learning-assisted screening for cognitive impairment in the emergency department.

BACKGROUND/OBJECTIVES: Despite a high prevalence and association with poor outcomes, screening to identify cognitive impairment (CI) in the emergency department (ED) is uncommon. Identification of high-risk subsets of older adults is a critical challenge to expanding screening programs. We developed and evaluated an automated screening tool to identify a subset of patients at high risk for CI. METHODS: In this secondary analysis of existing data collected for a randomized control trial, we developed machine-learning models to identify patients at higher risk of CI using only variables available in electronic health record (EHR). We used records from 1736 community-dwelling adults age > 59 being discharged from three EDs. Potential CI was determined based on the Blessed Orientation Memory Concentration (BOMC) test, administered in the ED. A nested cross-validation framework was used to evaluate machine-learning algorithms, comparing area under the receiver-operator curve (AUC) as the primary metric of performance. RESULTS: Based on BOMC scores, 121 of 1736 (7%) participants screened positive for potential CI at the time of their ED visit. The best performing algorithm, an XGBoost model, predicted BOMC positivity with an AUC of 0.72. With a classification threshold of 0.4, this model had a sensitivity of 0.73, a specificity of 0.64, a negative predictive value of 0.97, and a positive predictive value of 0.13. In a hypothetical ED with 200 older adult visits per week, the use of this model would lead to a decrease in the in-person screening burden from 200 to 77 individuals in order to detect 10 of 14 patients who would fail a BOMC. CONCLUSION: This study demonstrates that an algorithm based on EHR data can define a subset of patients at higher risk for CI. Incorporating such an algorithm into a screening workflow could allow screening efforts and resources to be focused where they have the most impact.

Anticholinergic medication: Related dry mouth and effects on the salivary glands.

OBJECTIVE: Salivary glands are among the most sensitive target organs of medications with anticholinergic (AC) properties, interrupting the neural stimulation of saliva secretion and reducing saliva flow. Hyposalivation results in dry mouth, leading to dental caries, intraoral infection, orofacial pain, problems with speaking and swallowing, and diminished oral health--related quality of life. Current understanding of the pharmacokinetics of AC medications and their effect on muscarinic receptors in the salivary glands were reviewed to assist clinicians in predicting salivary damage in patients with AC medication-induced dry mouth. STUDY DESIGN: We summarized the literature related to the mechanisms and properties of AC medications, anticholinergic adverse effects, and their effect on salivary function and management strategies to prevent oral health damage. RESULTS: Although a large number of studies reported on the frequencies of medication-induced dry mouth, we found very limited data on predicting individual susceptibility to AC medication--caused hyposalivation and no prospective clinical studies addressing this issue. CONCLUSION: Dry mouth is most frequently caused by medications with AC properties, which interrupt the neural stimulation of saliva secretion. Interdisciplinary care should guide pharmacotherapeutics and dental interventions should aim in preventing AC salivary adverse effects and reducing the oral health burden from AC medication-induced dry mouth.

Staff Experiences Forming and Sustaining Palliative Care Teams in Nursing Homes.

Background and Objectives: Building palliative care (PC) capacity in nursing homes (NH) is a national priority and essential to providing high quality care for residents with advanced illness. We report on NH staff experiences in developing and sustaining Palliative Care Teams (PCTeams) as part of a randomized clinical trial to "Improve Palliative Care through Teamwork" (IMPACTT). Research Design and Methods: We conducted rapid ethnographic assessments of all NH (N = 14) in the intervention arm. Data included semistructured interviews with direct care and administrative staff (n = 41), field observations, and written materials. We used a phased approach to data analysis including open coding and comparative analyses within and across homes. Results: We found four key structural themes in our analysis including: administrative support, financial considerations, turnover and staffing, and competing priorities. The development and sustainability of the nascent PCTeams were constantly threatened by competing priorities and the key factor in their success was consistent and tangible administrative support. Discussion and Implications: While improving PC in NHs is a recognized priority, lack of stable infrastructure and unintended consequences of reimbursement policies created conditions which often thwarted the sustainability of the PCTeams.

Impact of Nursing Home Palliative Care Teams on End-of-Life Outcomes: A Randomized Controlled Trial.

BACKGROUND: Deficits in end-of-life care in nursing homes (NHs) are reported, but the impact of palliative care teams (PCTeams) on resident outcomes remains largely untested. OBJECTIVE: Test the impact of PCTeams on end-of-life outcomes. RESEARCH DESIGN: Multicomponent strategy employing a randomized, 2-arm controlled trial with a difference-in-difference analysis, and a nonrandomized second control group to assess the intervention's placebo effect. SUBJECTS: In all, 25 New York State NHs completed the trial (5830 decedent residents) and 609 NHs were in the nonrandomized group (119,486 decedents). MEASURES: Four risk-adjusted outcome measures: place of death, number of hospitalizations, self-reported moderate-to-severe pain, and depressive symptoms. The Minimum Data Set, vital status files, staff surveys, and in-depth interviews were employed. For each outcome, a difference-in-difference model compared the pre-post intervention periods using logistic and Poisson regressions. RESULTS: Overall, we found no statistically significant effect of the intervention. However, independent analysis of the interview data found that only 6 of the 14 treatment facilities had continuously working PCTeams throughout the study period. Decedents in homes with working teams had significant reductions in the odds of in-hospital death compared to the other treatment [odds ratio (OR), 0.400; P<0.001), control (OR, 0.482; P<0.05), and nonrandomized control NHs (0.581; P<0.01). Decedents in these NHs had reduced rates of depressive symptoms (OR, 0.191; P≤0.01), but not pain or hospitalizations. CONCLUSIONS: The intervention was not equally effective for all outcomes and facilities. As homes vary in their ability to adopt new care practices, and in their capacity to sustain them, reforms to create the environment in which effective palliative care can become broadly implemented are needed.