Drug Burden Index is a Modifiable Predictor of 30-Day-Hospitalization in Community-Dwelling Older Adults with Complex Care Needs:Machine Learning Analysis of InterRAI Data

BACKGROUND: Older adults (≥ 65 years) account for a disproportionately high proportion of hospitalization and in-hospital mortality, some of which may be avoidable. Although machine learning (ML) models have already been built and validated for predicting hospitalization and mortality, there remains a significant need to optimise ML models further. Accurately predicting hospitalization may tremendously impact the clinical care of older adults as preventative measures can be implemented to improve clinical outcomes for the patient.METHODS: In this retrospective cohort study, a dataset of 14,198 community-dwelling older adults (≥ 65 years) with complex care needs from the Inter-Resident Assessment Instrument database was used to develop and optimise three ML models to predict 30-day-hospitalization. The models developed and optimized were Random Forest (RF), XGBoost (XGB), and Logistic Regression (LR). Variable importance plots were generated for all three models to identify key predictors of 30-day-hospitalization.RESULTS: The area under the receiver operating characteristics curve for the RF, XGB and LR models were 0.97, 0.90 and 0.72, respectively. Variable importance plots identified the Drug Burden Index and alcohol consumption as important, immediately potentially modifiable variables in predicting 30-day-hospitalization.CONCLUSIONS: Identifying immediately potentially modifiable risk factors such as the Drug Burden Index and alcohol consumption is of high clinical relevance. If clinicians can influence these variables, they could proactively lower the risk of 30-day-hospitalization. ML holds promise to improve the clinical care of older adults. It is crucial that these models undergo extensive validation through large-scale clinical studies before being utilized in the clinical setting.</p

Frailty knowledge, training and barriers to frailty management: A national cross-sectional survey of health professionals in Australia

Objective(s): To understand Australian health professionals\u27 perceptions of their knowledge and previous training about frailty, as well as barriers to frailty assessment and management in their practice. Methods: A cross-sectional online survey was developed and distributed to health professionals (medical, nursing and allied health) engaged in clinical practice in Australia through convenience and snowball sampling techniques from March to May 2022. The survey consisted of five sections: frailty training and knowledge; confidence in recognising and managing adults with frailty; the importance and relevance of frailty; barriers to assessing and managing frailty in practice; and interest in further frailty training. Responses were analysed using descriptive statistics. Results: The survey was taken by 736 health professionals. Less than half of respondents (44%, 321/733) reported receiving any training on frailty, with 14% (105/733) receiving training specifically focussed on frailty. Most respondents (78%, 556/712) reported ‘good’ or ‘fair’ understanding of frailty. The majority (64%, 448/694) reported being ‘fairly’ or ‘somewhat’ confident with identifying frailty. Almost all respondents ( \u3e 90%) recognised frailty as having an important impact on outcomes and believed that there are beneficial interventions for frailty. Commonly reported barriers to frailty assessment in practice included ‘lack of defined protocol for managing frailty’ and ‘lack of consensus about which frailty assessment tool to use’. Most respondents (88%, 521/595) were interested in receiving further education on frailty, with a high preference for online training. Conclusions: The findings suggest frailty is important to health professionals in Australia, and there is a need for and interest in further frailty education

Caregivers’ experiences of medication management advice for people living with dementia at discharge

Acknowledgments: StepUp for Dementia Research, which is funded by the Australian Government Department of Health and implemented by a dedicated team at the University of Sydney. Journal of Evaluation in Clinical Practice Funding : The project and DG was supported by the Australian National Health and Medical Research Council Dementia Leadership Fellowship.Peer reviewedPostprin

Development of a tool to evaluate medication management guidance provided to carers of people living with dementia at hospital discharge : a mixed methods study

Acknowledgements We thank our research advisory group and the members of the Sydney Dementia Network Lived Experience Expert Advisory Panel for their valuable feedback, and StepUp for Dementia Research, which is funded by the Australian Government Department of Health and implemented by a dedicated team at the University of Sydney. Funding This article was supported by a grant from the National Health and Medical Research Council Dementia Leadership Fellowship (grant number 1136849) and Dementia Centre for Research Postdoctoral Fellowship.Peer reviewedPublisher PD

Drug Burden Index and Cognitive and Physical Function in Aged Care Residents:A Longitudinal Study

Objectives: Anticholinergic/antimuscarinic and sedative medications (eg, benzodiazepines) have been found to be associated with poorer cognitive and physical function and mobility impairment in older age. However, previous studies were mostly conducted among community-dwelling older individuals and had often a cross-sectional design. Accordingly, our aim was to examine longitudinal associations between cumulative exposure to anticholinergic and sedative medications and cognitive and physical function among residents from aged care homes. Design: Longitudinal study. Setting and Participants: A total of 4624 residents of Dutch aged care homes of whom data were collected between June 2005 and April 2014. Methods: Outcome measures were collected with the Long-Term Care Facilities assessment from the international Residential Assessment Instrument (interRAI-LTCF) and included the Cognitive Performance Scale, the Activities of Daily Living (ADL) Hierarchy scale, a timed 4-meter walk test, distance walked, hours of physical activity, and days being outside. Cumulative exposure to anticholinergic and sedative medications was calculated with the Drug Burden Index (DBI), a linear additive pharmacological dose-response model. Associations were examined with linear mixed models to take the potential dependence of observations into account (ie, data were collected at repeated assessment occasions of residents who were clustered in aged care homes). Analyses were adjusted for sex, age, dementia, comorbidity (neurological, psychiatric, cardiovascular, oncological, and pulmonary), fractures, depressive symptoms, and medications excluded from the DBI. Results: We observed significant longitudinal associations between a higher DBI and poorer ADLs, fewer hours of physical activity, and fewer days being outside. We found no significant longitudinal association between a higher DBI and poorer cognitive function. Conclusions and Implications: Over time, cumulative exposure to anticholinergic and sedative medications is associated with poorer physical but not cognitive function in aged care residents. Careful monitoring of aged care residents with high cumulative anticholinergic and sedative medication exposure is needed

The Drug Burden Index and Level of Frailty as Determinants of Healthcare Costs in a Cohort of Older Frail Adults in New Zealand

OBJECTIVES: Frailty is common in older people and is associated with increased use of healthcare services and ongoing use of multiple medications. This study provides insights into the healthcare cost structure of a frail group of older adults in Aotearoa, New Zealand. Furthermore, we investigated the relationship between participants' anticholinergic and sedative medication burden and their total healthcare costs to explore the viability of deprescribing interventions within this cohort.METHODS: Healthcare cost analysis was conducted using data collected during a randomized controlled trial within a frail, older cohort. The collected information included participant demographics, medications used, frailty, cost of service use of aged residential care and outpatient hospital services, hospital admissions, and dispensed medications.RESULTS: Data from 338 study participants recruited between 25 September 2018 and 30 October 2020 with a mean age of 80 years were analyzed. The total cost of healthcare per participant ranged from New Zealand $15 (US dollar$10) to New Zealand $270 681 (US dollar$175 943) over 6 months postrecruitment into the study. Four individuals accounted for 26% of this cohort's total healthcare cost. We found frailty to be associated with increased healthcare costs, whereas the drug burden was only associated with increased pharmaceutical costs, not overall healthcare costs.CONCLUSIONS: With no relationship found between a patient's anticholinergic and sedative medication burden and their total healthcare costs, more research is required to understand how and where to unlock healthcare cost savings within frail, older populations.</p

Anticholinergic and Sedative Medications and Dynamic Gait Parameters in Older Patients

BACKGROUND: Anticholinergic and sedative medications are associated with poorer physical function in older age. Gait and physical function have traditionally been assessed with the time needed to execute objective function tests. Accelerometer-based gait parameters provide a precise capturing of gait dynamics and patterns and as such have added value. OBJECTIVES: This study examined the associations between cumulative exposure to anticholinergic and sedative medications and gait dimensions as assessed with accelerometer-based dynamic gait parameters. METHODS: Data were collected from outpatients of a diagnostic geriatric day clinic who underwent a comprehensive geriatric assessment (CGA). Cumulative exposure to anticholinergic and sedative medications was quantified with the Drug Burden Index (DBI), a linear additive pharmacological dose-response model. From a total of 22 dynamic gait parameters, the gait dimensions 'Regularity', 'Complexity', 'Stability', 'Pace', and 'Postural Control' were derived using factor analysis (and standardized total scores for these dimensions were calculated accordingly). Data were analyzed with multivariable linear regression analysis, in which adjustment was made for the covariates age, gender, body mass index (BMI), Mini Mental State Examination (MMSE) score, Charlson Comorbidity Index (CCI) including dementia, and number of medications not included in the DBI. RESULTS: A total of 184 patients participated, whose mean age was 79.8 years (± SD 5.8), of whom 110 (60%) were women and of whom 88 (48%) had polypharmacy (i.e., received treatment with ≥5 medications). Of the 893 medications that were prescribed in total, 157 medications (17.6%) had anticholinergic and/or sedative properties. Of the patients, 100 (54%) had no exposure (DBI = 0), 42 (23%) had moderate exposure (0 > DBI ≤ 1), while another 42 (23%) had high exposure (DBI >1) to anticholinergic and sedative medications. Findings showed that high cumulative exposure to anticholinergic and sedative medications was related with poorer function on the Regularity and Pace dimensions. Furthermore, moderate and high exposure were associated with poorer function on the Complexity dimension. CONCLUSIONS: These findings show that in older patients with comorbidities, cumulative anticholinergic and sedative exposure is associated with poorer function on multiple gait dimensions