Symptomatic and Preventive Medication Use before and after Alzheimer's Disease Diagnosis: A 10-Year Matched Cohort Study.

OBJECTIVE: To investigate longitudinal changes in symptomatic and preventive medication use among community-dwelling people with and without Alzheimer's disease (AD) 5 years pre- and post-AD diagnosis. DESIGN: Retrospective matched cohort study. SETTINGS AND PARTICIPANTS: The sample comprised 58,496 people with a geriatrician/neurologist-verified AD diagnosis matched 1:1 for age, sex, and region to people without AD in Finland. METHODS: Medication dispensing data were obtained from the Finnish Prescription Register. Prevalence of symptomatic and preventive medication use was evaluated every 6 months from 5 years pre- to post-AD diagnosis. Longitudinal changes in medication use between people with and without AD were compared using ordinal logistic regression. RESULTS: During the 5 years pre- and post-diagnosis, there were differences in symptomatic (P < .001) and preventive (P = .006) medication use between people with and without AD. Over the 5 years pre-diagnosis, prevalence of symptomatic and preventive medications increased in both people with and without AD. During the 1 year pre-diagnosis, people with AD had a higher increase in use of ≥3 symptomatic medications (+4.4% vs +2.2%) and ≥3 preventive medications (+6.4% vs +2.9%) compared to people without AD. Over the 5 years post-diagnosis, symptomatic medication use plateaued in both people with and without AD. Meanwhile, people using ≥3 preventive medications decreased (-6.0%) in those with AD, but increased (+6.1%) in those without AD. During the follow-up period, people with AD had a larger absolute percentage increase in prevalence of antipsychotics (+22.7% vs +1.8%) and antidepressants (+19.1% vs +5.0%) than people without AD. During the same period, paracetamol and calcium supplement use increased by 31.1% and 20.4%, respectively, among people with AD. The largest absolute percentage decrease in prevalence of preventive medications over the 5 years post-diagnosis were beta-blockers (-9.8%) and statins (-7.0%) in people with AD. CONCLUSIONS AND IMPLICATIONS: At the point of and following diagnosis, there were population-level changes in medication use among people with AD. Medication assessments during this period appear to coincide with discontinuation of preventive medications whereas minimal changes were observed in symptomatic medication use.

Deprescribing Opportunities for Frail Residents of Nursing Homes: A Multicenter Study in Australia, China, Japan, and Spain.

OBJECTIVE: Deprescribing opportunities may differ across health care systems, nursing home settings, and prescribing cultures. The objective of this study was to compare the prevalence of STOPPFrail medications according to frailty status among residents of nursing homes in Australia, China, Japan, and Spain. DESIGN: Secondary cross-sectional analyses of data from 4 cohort studies. SETTING AND PARTICIPANTS: A total of 1142 residents in 31 nursing homes. METHODS: Medication data were extracted from resident records. Frailty was assessed using the FRAIL-NH scale (non-frail 0-2; frail 3-6; most-frail 7-14). Chi-square tests and prevalence ratios (PRs) were used to compare STOPPFrail medication use across cohorts. RESULTS: In total, 84.7% of non-frail, 95.6% of frail, and 90.6% of most-frail residents received ≥1 STOPPFrail medication. Overall, the most prevalent STOPPFrail medications were antihypertensives (53.0% in China to 73.3% in Australia, P < .001), vitamin D (nil in China to 52.7% in Australia, P < .001), lipid-lowering therapies (11.1% in Japan to 38.9% in Australia, P < .001), aspirin (13.5% in Japan to 26.2% in China, P < .001), proton pump inhibitors (2.1% in Japan to 32.0% in Australia, P < .001), and antidiabetic medications (12.3% in Japan to 23.5% in China, P = .010). Overall use of antihypertensives (PR, 1.15; 95% CI, 1.06-1.25), lipid-lowering therapies (PR, 1.78; 95% CI, 1.45-2.18), aspirin (PR, 1.31; 95% CI, 1.04-1.64), and antidiabetic medications (PR, 1.31; 95% CI, 1.00-1.72) were more prevalent among non-frail and frail residents compared with most-frail residents. Antihypertensive use was more prevalent with increasing frailty in China and Japan, but less prevalent with increasing frailty in Australia. Antidiabetic medication use was less prevalent with increasing frailty in China and Spain but was consistent across frailty groups in Australia and Japan. CONCLUSIONS AND IMPLICATIONS: There were overall and frailty-specific variations in prevalence of different STOPPFrail medications across cohorts. This may reflect differences in prescribing cultures, application of clinical practice guidelines in the nursing home setting, and clinician or resident attitudes toward deprescribing.

Symptomatic and preventive medication use according to age and frailty in Australian and Japanese nursing homes.

OBJECTIVE: To investigate symptomatic and preventive medication use according to age and frailty in Australian and Japanese nursing homes (NHs). METHODS: Secondary cross-sectional analyses of two prospective cohort studies involving 12 Australian NHs and four Japanese NHs. Frailty was measured using the FRAIL-NH scale (non-frail 0-2; frail 3-6; most-frail 7-14). Regular medications were classified as symptomatic or preventive based on published lists and expert consensus. Descriptive statistics were used to compare the prevalence and ratio of symptomatic to preventive medications. RESULTS: Overall, 550 Australian residents (87.7 ± 7.3 years; 73.3% females) and 333 Japanese residents (86.5 ± 7.0 years; 73.3% females) were included. Australian residents used a higher mean number of medications than Japanese residents (9.8 ± 4.0 vs 7.7 ± 3.7, p < 0.0001). Australian residents used more preventive than symptomatic medications (5.5 ± 2.5 vs 4.3 ± 2.6, p < 0.0001), while Japanese residents used more symptomatic than preventive medications (4.7 ± 2.6 vs 3.0 ± 2.2, p < 0.0001). In Australia, symptomatic medications were more prevalent with increasing frailty (non-frail 3.4 ± 2.6; frail 4.0 ± 2.6; most-frail 4.8 ± 2.6, p < 0.0001) but less prevalent with age (< 80 years 5.0 ± 2.9; 80-89 years 4.4 ± 2.6; ≥ 90 years 3.9 ± 2.5, p = 0.0042); while preventive medications remained similar across age and frailty groups. In Japan, there was no significant difference in the mean number of symptomatic and preventive medications irrespective of age and frailty. CONCLUSIONS: The ratio of symptomatic to preventive medications was higher with increasing frailty but lower with age in Australia; whereas in Japan, the ratio remained consistent across age and frailty groups. Preventive medications remained prevalent in most-frail residents in both cohorts, albeit at lower levels in Japan.

Cohort profile: Using primary care data to understand Opioid Prescribing, Policy Impacts and Clinical Outcomes (OPPICO) in Victoria, Australia.

PURPOSE: The OPPICO cohort is a population-based cohort based on non-identifiable electronic health records routinely collected from 464 general practices in Victoria, Australia, created with the aim of understanding opioid prescribing, policy impacts and clinical outcomes. The aim of this paper is to provide a profile of the study cohort by summarising available demographic, clinical and prescribing characteristics. PARTICIPANTS: The cohort described in this paper comprises people who were aged at least 14 years at cohort entry, and who were prescribed an opioid analgesic at least once at participating practices for a total of 1 137 728 person-years from 1 January 2015 to 31 December 2020. The cohort was formed using the data collected from electronic health records through the Population Level Analysis and Reporting (POLAR) system. The POLAR data primarily consist of patient demographics, clinical measurements, Australian Medicare Benefits Scheme item numbers, diagnoses, pathology testing and prescribed medications. FINDING TO DATE: In total, the cohort consists of 676 970 participants with 4 389 185 opioid prescription records from 1 January 2015 to 31 December 2020. Approximately half (48.7%) received a single opioid prescription, and 0.9% received more than 100 opioid prescriptions. The mean number of opioid prescriptions per patient was 6.5 (SD=20.9); prescriptions for strong opioids accounted for 55.6% of all opioid prescriptions. FUTURE PLANS: The OPPICO cohort data will be used for various types of pharmacoepidemiological research, including examining the impact of policy changes on coprescription of opioids with benzodiazepines and gabapentin, and monitoring trends and patterns of other medication utilisation. Through data-linkage between our OPPICO cohort and hospital outcome data, we will examine whether policy changes for opioid prescribing lead to changes in prescription opioid-related harms, and other drug and mental health-related outcomes. TRIAL REGISTRATION NUMBER: EU PAS Register (EUPAS43218, prospectively registered).

Medication Management in Frail Older People: Consensus Principles for Clinical Practice, Research, and Education.

Frailty is a geriatric condition associated with increased vulnerability to adverse drug events and medication-related harm. Existing clinical practice guidelines rarely provide medication management recommendations specific to frail older people. This report presents international consensus principles, generated by the Optimizing Geriatric Pharmacotherapy through Pharmacoepidemiology Network, related to medication management in frail older people. This consensus comprises 7 principles for clinical practice, 6 principles for research, and 4 principles for education. Principles for clinical practice include (1) perform medication reconciliation and maintain an up-to-date medication list; (2) assess and plan based on individual's capacity to self-manage medications; (3) ensure appropriate prescribing and deprescribing; (4) simplify medication regimens when appropriate to reduce unnecessary burden; (5) be alert to the contribution of medications to geriatric syndromes; (6) regularly review medication regimens to align with changing goals of care; and (7) facilitate multidisciplinary communication among patients, caregivers, and healthcare teams. Principles for research include (1) include frail older people in randomized controlled trials; (2) consider frailty status as an effect modifier; (3) ensure collection and reporting of outcome measures important in frailty; (4) assess impact of frailty on pharmacokinetics and pharmacodynamics; (5) encourage frailty research in under-researched settings; and (6) utilize routinely collected linked health data. Principles for education include (1) provide undergraduate and postgraduate education on frailty; (2) minimize low-value care related to medication management; (3) improve health and medication literacy; and (4) incorporate evidence in relation to frailty into clinical practice guidelines. These principles for clinical practice, research and education highlight different considerations for optimizing medication management in frail older people. These principles can be used in conjunction with existing best practice guidelines to help achieve optimal health outcomes for this vulnerable population. Implementation of the principles will require multidisciplinary collaboration between healthcare professionals, researchers, educators, organizational leaders, and policymakers.

The role of medication advisory committees in residential aged care services.

BACKGROUND: There is increasing international interest in initiatives to reduce medication-related harm and preventable hospitalizations in residential aged care services (RACS). The Australian Government recommends that RACS establish multidisciplinary Medication Advisory Committees (MACs). No previous research has specifically investigated the structures and functioning of MACs. OBJECTIVES: To explore the current structures and functioning of MACs, and identify opportunities for MACs to better promote safe and effective medication use. METHODS: Semi-structured interviews and focus groups were conducted with a maximum variation sample of health professionals (n = 44) across four health services operating across 27 RACS in rural and regional Victoria, Australia. Qualitative data were analyzed using deductive and inductive content analyses. Results were presented to a multidisciplinary expert panel (n = 13) to identify opportunities for improvement. RESULTS: Deductively coded themes included composition and functioning of the MAC, education and information needs and support to better manage polypharmacy. Emergent inductively coded themes included general medical practitioner (GP) and pharmacist engagement, collaboration and effectiveness. Participation by GPs and pharmacists was variable, while no MACs involved residents or family carers. Aged care specific and multidisciplinary MACs were generally more proactive in addressing potential medication-related harm. Education to identify and report adverse drug events with high risk medications was identified as a priority. The multidisciplinary panel made 12 recommendations to promote safe and effective medication use. CONCLUSION: Despite all MACs having a strong commitment to medication safety, opportunities exist to improve the composition and structure, proactive identification and response to emerging issues, and systems for staff, resident and family carer training.

Transition to high-dose or strong opioids: a population-based study of people initiating opioids in Australia.

BACKGROUND AND AIMS: Strong and high-dose opioids are associated with opioid overdose and death. The objective of this study was to determine the rate and predictors of transitioning to high-dose or strong opioids among people initiating opioids. DESIGN: Retrospective cohort study. SETTING: Australia. PARTICIPANTS: People initiating opioid analgesics from July 2013 to January 2018 were identified from a random 10% sample of Australia's Pharmaceutical Benefits Scheme eligible population. MEASUREMENTS: Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for the predictors of escalating to ≥ 50 mg oral morphine equivalents (OMEs)/day (cohort 1); ≥ 90 mg OMEs/day (cohort 2) and transitioning from weak opioids to strong opioids (cohort 3) over 12 months of follow-up. Predictors included age, sex, number of comorbidities, history of depression, prior treatment for cancer and selected other medication use. FINDINGS: In total, 861 691 people initiated opioids at average doses < 50 mg OMEs/day (cohort 1), 874 401 at < 90 mg OMEs/day (cohort 2) and 603 884 initiated weak opioids (cohort 3). Overall, 1.4% of people escalated to doses ≥ 50 mg OMEs/day, 0.8% to doses ≥ 90 mg OMEs/day and 7.3% transitioned to strong opioids. The strongest predictors of transitioning included prior treatment for cancer [cohort 1: HR = 3.19, 95% CI = 3.00-3.40; cohort 2: HR = 4.19, 95% CI = 3.90-4.51; cohort 3: HR = 2.07, 95% CI = 1.95-2.18] and age ≥ 75 years (cohort 1: HR = 3.04, 95% CI = 2.73-3.38; cohort 2: HR = 2.51, 95% CI = 2.17-2.89; cohort 3: HR = 1.88, 95% CI = 1.80-1.96). Females transitioned to high doses and strong opioids less rapidly than males (cohort 1: HR = 0.79, 95% CI = 0.76-0.82; cohort 2: HR = 0.70, 95% CI = 0.66-0.73; cohort 3: HR = 0.95, 95% CI = 0.93-0.96). CONCLUSIONS: In Australia, more than one in every 13 people initiating weak opioids transition to strong opioids. By extrapolation, more than 26 000 Australian adults initiating opioids escalate to high doses each year. People with cancer treatment history, older people and males transition to strong and high-dose opioids more rapidly than others.

Trajectories of sickness absence and disability pension before and after opioid initiation for noncancer pain: a 10-year population-based study.

Chronic noncancer pain is a leading cause of sickness absence (SA) and disability pension (DP). The objectives of this study were to identify trajectories of SA/DP before and after strong and weak opioid initiation for noncancer pain and the factors associated with these trajectories. A longitudinal population-based study of 201,641 people (24-59 years) without cancer who initiated opioid analgesics in 2009 in Sweden was conducted. Trajectories of net annual SA/DP days in the 5 years before/after opioid initiation were estimated with group-based trajectory modelling. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for factors associated with trajectory groups. Among the 6.9% of people initiating strong opioids, 12.5% had persistent high SA/DP (estimated 320 days/year) before and after opioid initiation and 72.9% had persistent low/minimum SA/DP (estimated 30 days/year). Approximately 8.6% of people had increasing SA/DP, and 6.1% had decreasing SA/DP after opioid initiation, although this seemed to reflect continuation of preinitiation patterns. Trajectories were similar at lower SA/DP days/year among those initiating weak opioids. Persistent high SA/DP among strong opioid initiators were associated with ≥5 comorbidities (OR = 8.72, 95% CI 5.61-13.56), ≤9 years of education (OR = 5.83, 95% CI 4.84-7.03), and previous use of antidepressants (OR = 4.57, 95% CI 3.89-5.37) and antipsychotics (OR = 4.49, 95% CI 2.93-6.88). Three-quarters of people initiating opioids for noncancer pain had persistent low/minimum levels of SA/DP 5 years before and after initiation. Increasing and decreasing SA/DP after opioid initiation seemed to reflect a continuation of preinitiation patterns. Our findings highlight the complex range of sociodemographic and medication-related factors associated with persistent SA/DP.

Prevalence and incidence of prescription opioid analgesic use in Australia.

AIMS: The aims of the current study were to determine the prevalence and incidence of prescription opioid analgesic use in Australia and compare the characteristics of people with and without cancer initiating prescription opioid analgesics. METHODS: A retrospective population-based study was conducted using the random 10% sample of adults who were dispensed prescription opioid analgesics in Australia between July 2013 and June 2017 through the Pharmaceutical Benefits Scheme. Poisson regression was used to calculate rate ratios (RR) for opioid prevalence and incidence. The characteristics of people initiating opioids, including type of opioid initiated, total oral morphine equivalents dispensed, prescriber speciality, medical comorbidities, and past analgesic and benzodiazepine use, were compared for people with and without cancer. RESULTS: Opioid prevalence increased {RR = 1.006 [95% confidence interval (CI) 1.004, 1.008]}, while incidence decreased [RR = 0.977 (95% CI 0.975,0.979)] from 2013/2014 to 2016/2017. There were between 287 677 and 307 772 prevalent users each year. In total, 769 334 adults initiated opioids between 2013/2014 and 2016/2017, and half of these initiations were by general practitioners. Initiation with a strong opioid occurred in 55.8% of those with cancer and 28.2% of those without cancer. CONCLUSION: Rates of opioid use have remained high since 2013, with approximately 3 million adults using opioids and over 1.9 million adults initiating opioids each year. Between 2013 and 2017, opioid prevalence has slightly increased but incidence has decreased. People without cancer account for the majority of opioid use and are more likely to be initiated on short-acting and weak opioids. Initiation of strong opioids has increased over time, reinforcing concerns about increased use and the harms associated with strong opioids in the community.

Harms associated with extramedical use of prescription opioid analgesics in Australia: A scoping review.

BACKGROUND: Evidence is accumulating globally on harms from extramedical prescription opioid analgesic (POA) use. OBJECTIVE: The aim of this scoping review was to explore harms and documented risk factors associated with extramedical POA use in Australia. METHODS: MEDLINE, EMBASE, PsycINFO and CINAHL were searched for original studies published between January 2000 and February 2018. Studies were eligible for inclusion if: 1) POA use was explicitly reported, 2) extramedical use was evident 3) harm was explicitly reported, 4) data were collected in/after 2000, 5) conducted in adults and 6) undertaken in Australia. RESULTS: We identified 560 articles and 16 met the inclusion criteria. Harms reported from extramedical POA use included: increased health service utilization (n = 5), non-fatal overdose (n = 6), fatal overdose (n = 5), injection-related injuries or diseases (n = 4), engagement in crime (n = 2), loss of employment (n = 1), and foreign body pulmonary embolization (n = 1). Multiple drug toxicity was reported as the cause of death in up to 83% of fatal overdose cases. Risk factors for harm included being male, aged 31-49 years, a history of chronic non-cancer pain, mental health disorders and/or substance abuse, and concomitant use of benzodiazepines, antidepressants or other centrally-acting substances. CONCLUSION: Extramedical use of POAs is associated with a range of harms, including fatal and non-fatal overdose. Polysubstance use with other centrally-acting substances was often implicated. No published studies used linked data sources to provide a comprehensive overview of the extent of POA use or harm in Australia. Future research should focus on undertaking longitudinal cohort studies with linked data sources.

Predictors of persistent prescription opioid analgesic use among people without cancer in Australia.

AIMS: To identify patterns of opioid analgesic use and determine predictors of persistent opioid use among people without cancer. METHODS: A population-based cohort study of Australians initiating prescription opioids from July 2013 to December 2015 was conducted using data from a random 10% sample of people who accessed medicines through Australia's Pharmaceutical Benefits Scheme. A 12-month retrospective period was used to define opioid initiation, exclude people with cancer and determine comorbidities. Persistent use over 12 months since initiation was identified through group-based trajectory modelling. Odds ratios (OR) and 95% confidence intervals (CIs) for predictors of opioid persistence were estimated using logistic regression. RESULTS: The cohort consisted of 431 963 people without cancer who initiated opioids. A total of 11 323 (2.6%) persistent opioid users were identified. Predictors of persistence included initiation with transdermal formulations (OR 4.2, 95% CI 3.9-4.5), or initiation with total oral morphine equivalents (OME) ≥ 750 mg (3.7, 3.3-4.1), having depression (1.6, 1.5-1.7) or psychotic illness (2.0, 1.9-2.2). Previous dispensing of paracetamol (2.0, 1.9-2.1), pregabalin (2.0, 1.8-2.1) and benzodiazepines (1.53, 1.4-1.6) predicted persistence. Compared to people aged 18-44 years, those ≥75 years were 2.5 (2.3-2.6) times more likely to be persistent users. CONCLUSIONS: Patient-specific characteristics (older age, prior history of mental health comorbidities and use of non-opioid analgesics) and prescriber choice of initial opioid (transdermal formulation and higher total OMEs) were found to strongly predict persistent use. This information may help prescribers target monitoring and early intervention efforts in order to prevent harms associated with the long-term use of opioids.

Prioritizing interventions to manage polypharmacy in Australian aged care facilities.

BACKGROUND: Polypharmacy is highly prevalent in residential aged care facilities (RACFs). Although polypharmacy is sometimes unavoidable, polypharmacy has been associated with increased morbidity and mortality. OBJECTIVE: To identify and prioritize a range of potential interventions to manage polypharmacy in RACFs from the perspectives of health care professionals, health policy and consumer representatives. METHODS: Two nominal group technique (NGT) sessions were convened in August 2015. A purposive sample (n = 19) of clinicians, researchers, managers and representatives of consumer, professional and health policy organizations were asked to nominate interventions to address the prevalence and appropriateness of medication use. Participants were then asked to prioritize five interventions suitable for possible implementation at the system level. RESULTS: Six of 16 potential interventions were prioritized highest for possible implementation in clinical practice, with two interventions prioritized as second highest. The top interventions in rank order were 'implementation of a pharmacist-led medication reconciliation service for new residents,' 'conduct facility-level audits and feedback to staff and health care professionals,' 'develop deprescribing scripts to assist clinician-resident discussion,' 'develop or revise prescribing guidelines specific to older people with multimorbidity in RACFs,' 'implement electronic medication charts and records' and 'better support Medication Advisory Committees (MACs) to address medication appropriateness.' CONCLUSION: This study prioritized a range of potential interventions that may be used to assist clinicians and policy makers develop a comprehensive strategy to manage polypharmacy in RACFs.

Polypharmacy and Medication Regimen Complexity as Risk Factors for Hospitalization Among Residents of Long-Term Care Facilities: A Prospective Cohort Study.

OBJECTIVES: To investigate the association between polypharmacy and medication regimen complexity with time to first hospitalization, number of hospitalizations, and number of hospital days over a 12-month period. DESIGN: A 12-month prospective cohort study. PARTICIPANTS AND SETTING: A total of 383 residents of 6 Australian long-term care facilities (LTCFs). MEASUREMENTS: The primary exposures were polypharmacy (≥9 regular medications) and the 65-item Medication Regimen Complexity Index (MRCI). Cox proportional hazards regression was used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between polypharmacy and MRCI with time to first hospitalization. Poisson regression was used to compute incident rate ratios (IRR) and 95% CIs for the association between polypharmacy and MRCI with number of hospitalizations and number of hospital days. Models were adjusted for age, sex, length of stay in LTCF, comorbidities, activities of daily living, and dementia severity. RESULTS: There were 0.56 (95% CI 0.49-0.65) hospitalizations per person-year and 4.52 (95% CI 4.31-4.76) hospital days per person-year. In adjusted analyses, polypharmacy was associated with time to first hospitalization (HR 1.84; 95% CI 1.21-2.79), number of hospitalizations (IRR 1.51; 95% CI 1.09-2.10), and hospital days per person-year (IRR 1.39; 95% CI 1.24-1.56). Similarly, in adjusted analyses a 10-unit increase in MRCI was associated with time to first hospitalization (HR 1.17; 95% CI 1.06-1.29), number of hospitalizations (IRR 1.15; 95% CI 1.06-1.24), and hospital days per person-year (IRR 1.19; 95% CI 1.16-1.23). CONCLUSIONS: Polypharmacy and medication regimen complexity are associated with hospitalizations from LTCFs. This highlights the importance of regular medication review for residents of LTCFs and the need for further research into the risk-to-benefit ratio of prescribing in this setting.

Polypharmacy and medication regimen complexity as factors associated with staff informant rated quality of life in residents of aged care facilities: a cross-sectional study.

PURPOSE: The purpose of this study is to investigate the association between polypharmacy with health-related quality of life (HRQoL) and medication regimen complexity with HRQoL in residential aged care facilities (RACFs). METHODS: A cross-sectional study of 383 residents from six Australian RACFs was conducted. The primary exposures were polypharmacy (≥9 regular medications) and the validated Medication Regimen Complexity Index (MRCI). The outcome measure was staff informant rated quality of life assessed using the Quality of Life Alzheimer's disease (QoL-AD) scale. Covariates included age, sex, Charlson's comorbidity index, activities of daily living, and dementia severity. Logistic quantile regression was used to characterize the association between polypharmacy and QoL-AD (model 1) and MRCI and QoL-AD (model 2). RESULTS: The median age of the 383 residents was 88 years and 297 (78 %) residents were female. In total, 63 % of residents were exposed to polypharmacy and the median MRCI score (range) was 43.5 (4-113). After adjusting for the covariates, polypharmacy was not associated with either higher or lower QoL-AD scores (estimate -0.02; 95 % confidence interval (CI) -0.165, 0.124; p = 0.78). Similarly, after adjusting for the covariates, MRCI was not associated with either higher or lower QoL-AD scores (estimate -0.0009, 95 % CI -0.005, 0.003; p = 0.63). CONCLUSIONS: These findings suggest that polypharmacy and medication regimen complexity are not associated with staff informant rated HRQoL. Further research is needed to investigate how specific medication classes may impact change in quality of life over time.