Analysis of Medication Management System Data to Determine Potentially Inappropriate Medication Use and Hospitalization Among Older Adults Living in Residential Care Homes for the Elderly Population

Analysis of Medication Management System Data to Determine Potentially Inappropriate Medication Use and Hospitalization Among Older Adults Living in Residential Care Homes for the Elderly Population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of Medication Management System Data to Determine Potentially Inappropriate Medication Use and Hospitalization Among Older Adults Living in Residential Care Homes for the Elderly Population Ho Cheung Chau, Kexin Zhang, Bik-Wai Bilvick Tai, Isaac Shing Yan Hui, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5733476/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 May, 2025 Read the published version in BMC Geriatrics → Version 1 posted 9 You are reading this latest preprint version Abstract Objectives Many older adults living in Resident Care Homes for the Elderly (RCHEs) are at risk of polypharmacy and the use of potentially inappropriate medication (PIM). Few studies have evaluated the prevalence and consequences of PIM use among older adults living in RCHEs. The objectives of this study are (1) to evaluate the prevalence of PIM use in 29 RCHEs in Hong Kong, and (2) to investigate the association between PIM use and hospitalization in this population. Methods This is a prospective, observational, cohort study which utilized final-administered medication data from RCHEs that participated in a medication management program. Data on the medications administered to all residents living in the participating RCHEs were extracted from the SafeMed Medication Management System (SMMS®), which is a purpose-built Information Technology supporting the entire medication management process at RCHEs. The outcome of interest is the 12-month period prevalence of PIM use (January 1 to December 31, 2023), which was obtained by comparing the medication data with the 2023 Beers criteria. Hospital admissions during the study period were extracted from the SMMS®.Multivariable logistic regression was conducted to investigate the association between PIM use and hospital admissions. Results We included 6,346 residents (age 82.9 ± 8.6 years; female 61.9%). The average number of current medications was 6.8 ± 7.4. Over half (51.5%) of residents had polypharmacy (≥ 5 medications). The 12-month period prevalence of PIM use was 34.5%. Among the residents with PIMs, 65.1%, 25.5% and 9.4% used 1, 2 and > 2 PIMs, respectively. Residents with PIMs were associated with higher rates of hospitalization (Odds Ratio [OR] 1.73, 95% confidence interval [CI] 1.54 to 1.69), after adjusting for age, sex and comorbidities. The number of PIMs was significantly associated with higher risk of hospitalization (OR: 2.17, 95% CI: 1.82 to 2.59 for > 1 PIMs vs 0). Conclusions The use of PIM was observed in one-third of older adults living in RCHEs, and was associated with an increased risk of hospitalization. Our findings highlighted the urgent need for strategies to improve clinicians’ awareness of PIMs and their adverse impact, and to implement pharmacist-led medication reviews in RCHEs. Figures Figure 1 Introduction Physiological changes associated with aging can alter the pharmacokinetics and pharmacodynamic properties of drugs. These factors play a significant role in augmenting drug toxicity in adults aged 65 or over (hereinafter, “older adults”), increasing their susceptibility to adverse drug reactions (ADRs) associated with the use of multiple drugs. 1 , 2 Moreover, older adults may take potentially inappropriate medications (PIMs), which are “ drugs with… risks [that] outweigh potential benefits, especially when effective alternatives are available. ” 3 To reduce older adults’ exposure to PIMs, the American Geriatrics Society (AGS) developed the Beers Criteria for PIM Use in Older Adults as a safe-prescribing reference for clinicians. 4 Although the Beers criteria were designed for use in the US, they have been widely used to assess the prevalence of PIM use by older populations in various settings in other countries, including Hong Kong. 5 – 8 Many older adults living in residential care homes for the elderly (RCHEs) have multiple chronic diseases and thus have a higher probability of having polypharmacy (i.e. receiving five or more medications concurrently). 9 , 10 For example, it has been reported that over 10% of the Slovenian population had polypharmacy, and 4% with over ten medications concomitantly (i.e., with hyper-polypharmacy). 11 A systematic review of 17 studies found that according to the Beers criteria, the prevalence of PIM use by RCHE residents ranged from 18.5–82.6%. 12 It has been shown that compared with appropriate medication use, inappropriate medication and PIM use by older adults is associated with more frequent hospital visits and hospitalization. 12 , 13 In particular, inappropriate use of medications in older adults with psychiatric conditions may lead to increased risk of developing major cardiopulmonary and neurological adverse drug reactions. 14 Furthermore, a Korean study reported that residents who used ≥ 4 PIMs (according to the Beers and Korean criteria) at the time of RCHE admission had a 30% increased risk of an emergency department visit. 15 In Hong Kong, older adults comprised 20.5% of the population in 2021, and this percentage is expected to increase to 36.0% of the population by 2046. 16 The 2021 Hong Kong Population Census reported that 95.2% of older adults were living in domestic households, while the remaining 4.8% were living in non-domestic households, such as RCHEs. 17 Thus, improving medication safety and management has become a priority of the Hong Kong healthcare agenda. 18 An analysis of data obtained from the Hospital Authority, a statutory body that governs all public healthcare services in Hong Kong, reported that the 12-month prevalence of PIM use was 55.5% in 2006 and reduced to 47.5% in 2014. 19 However, there remains a lack of information regarding the risk of hospitalization due to the use of PIMs in older adults living in RCHEs in metropolitan cities like Hong Kong. Furthermore, the accuracy of the medication exposure data in this study was limited, as these data were obtained from a repository that captured information on dispensed medications rather than administered medications. Study Objectives The objectives of this study are (1) to describe the prevalence of PIM use according to the 2023 Beers criteria in older adults living in RCHEs of Hong Kong, and (2) to investigate the association between their PIM use and risk of hospitalization. Methods Study design This is a prospective, observational, cohort study that analyzed data collected from the Integrated Old Age Home Medication Management Program, which was initiated by the Hong Kong Pharmaceutical Care Foundation Ltd (HKPCF), a non-governmental organization. The medication management program employs various technologies and automated methods to develop a medication management system for participating RCHEs in Hong Kong. 20 Approval was obtained from the Survey and Behavioral Research Ethics (SBRE) Committee of the Chinese University of Hong Kong (reference number: SBRE-19-106). All participating RCHEs provided consent for the use of de-identified data for research purposes. The implementation and use of the SMMS® at the participating RCHEs is funded by a philanthropic organization, which played no role in investigating, analyzing or interpreting the results of this study. Base cohort This study analyzed medication and clinical data of the residents living in 29 RCHEs that participated in the medication management program from January 1 to December 31, 2023 (the study period) across various geographical regions of Hong Kong. These RCHEs met the SMMS® criteria, i.e., they (1) had a Wi-fi network, (2) received sustained operational funding from the government, the private sector, or philanthropic organizations, and (3) consented in writing to provide de-identified data for medication management program evaluation and research purposes. To ensure generalizability to older adults living in RCHEs of Hong Kong, the data of all residents who were aged 65 years or older and living in the participating RCHEs (n = 6,346) was analyzed in this study, regardless of their medication status (Supplemental Fig. 1) . Data source All data of the base cohort were extracted from the SafeMed Medication Management System (SMMS®), which is an electronic medication system developed by HKPCF with diverse applications for RCHEs to integrate patients’ medication data from different sources. In Hong Kong, RCHE residents are prescribed medications by physicians at hospitals or outpatient clinics (i.e. General Out-patient Clinic [GOPC]) under the Hospital Authority, which is a public health system funded by the Government and is responsible for more than 90% of the in-patient service in Hong Kong. To a lesser extent, general practitioners and clinicians from private clinics or hospitals may also prescribe medications for patients. The medications were collected by RCHE staff, who also entered patients’ information and medications into the database of the SMMS® 20 . Unique among systems for RCHEs in Hong Kong, the SMMS has included a comprehensive drug database that covers all medications commonly prescribed by clinicians from the Hospital Authority. The database includes the details of each medication as follows: trade name, dosage form, strength, legal classification, therapeutic class (according to the Anatomical Therapeutic Chemical Classification 21 ), precautions, common instructions for use, Hong Kong registration number, and manufacturer. This drug database enables the systematic built up of medication profiles for individual residents with detailed appropriate drug administration schedules. Moreover, the system supports electronic records of medications that are administered to the residents of RCHEs at the scheduled times in a real-time manner. Thus, the administered medication data for the base cohort were extracted from the backend of the SMMS® database. The SMMS® database also contains updated information on RCHE residents’ personal information, and follow-up consultations at hospitals or clinics, hospital admissions and discharges. These data are reliable and comprehensive, as the SMMS® is the sole medication management system for all 29 participating RCHEs. Our previous study determined that the amount of data missing from the SMMS® database is negligible. 20 For major comorbidities and medical conditions, the nursing staff of RCHEs manually entered the residents’ existing health conditions from the medical records of the Hospital Authority (including hospitals and outpatient clinics) upon initiation of a profile for each new resident, and updated the list periodically based on the latest health status of the resident. For the purpose of the current analysis, coding of the health conditions was conducted by one investigator (ISYH) and independently verified by two other investigators (KZ and YTC). In addition, all records in the SMMS® database are anonymized and de-identified for research purposes. Operational definition of PIM use The 12-month prevalence of PIM use was calculated by dividing the number of members of the base cohort with at least one PIM use from January 1 to December 31, 2023 by the total number of residents in the 29 RCHEs during the study period. The 2023 AGS Beers criteria contain five categories of PIM use, 4 of which four of these were excluded from the current study. The updated Beers criteria involved an expert panel of highly experienced specialists with a robust internal review and external public comment processes. 4 Specifically, the categories of “medications potentially inappropriate in patients with certain diseases or syndromes” and “potentially inappropriate drug-drug interactions” were excluded due to concerns regarding their lack of comprehensiveness, as disclaimed by the developers, 4 and because diagnosis information and the exact indications of medications are not available in the SMMS® database. In addition, the category of “medications to be used with caution” was excluded, as such medications can be used under specific circumstances. Moreover, the category of “medication with dosage adjustments based on renal function” was excluded, as assessment of kidney function requires clinical data that are not available in the SMMS® database. Therefore, the only category included in this analysis was “medications considered potentially inappropriate independent of diagnosis.” Subsequently, the drugs in this category were examined in the context of their registration status in Hong Kong. 22 PIMs that are not commercially registered in Hong Kong (such as meclizine, amoxapine, and desipramine) were excluded. In addition, PIMs with inappropriateness defined by their indication, dose, or therapy duration were excluded, because the SMMS® database does not capture the aforementioned data. Thus, the final PIM assessment criteria were adapted to Hong Kong and contained 36 PIMs independent of diagnosis ( Supplemental Table 1 ). This approach of defining PIMs and the 36 PIMs in this analysis are consistent with previous studies that have investigated drug utilization among older adults in Hong Kong. 19 , 23 Hospitalization data To examine the association between PIM use and hospitalization rates, another cohort was constructed from the base cohort, consisting of residents ≥ 65 years old in the 29 RCHEs who were administered at least one medication between January 1 and December 31, 2023 (Supplemental Fig. 1) . Residents not taking any medications were excluded from this analysis as they might be in better health state and had fewer severe comorbidities; including these healthier individuals could cloud the observed rate of hospitalization in non-PIM users, potentially leading to biased results. From this sub-cohort, information on hospitalization between January 1 and December 31, 2023, comprising the dates of admission and discharge, as well as the type of care received were extracted from the SMMS®. Only hospital admission(s) that occurred after the start date of any PIM and before the end date (if any) for each resident was coded as a “case” in this analysis. All types of hospitalization, regardless of planned or unplanned admissions and length of stay, were included. Statistical analysis Descriptive statistics were used to summarize the characteristics of the base cohort and medications they were administered. The association between the use of PIM and hospitalization in the base cohort was evaluated using multivariable logistic regression. The main predictors of interest were the use of any PIMs (yes vs no) and the number of PIMs used (0 or 1 vs ≥ 2) and were analyzed in separate models to prevent multicollinearity. The other covariates included in the model were clinically relevant factors that have been reported to be associated with hospitalization in institutionalized older adults, 24 – 26 namely sex, age (65–74, 75–84, or 85–94 vs ≥ 95 years), number of concurrent medications (0–4 or 5–9 vs ≥ 10), and number of comorbidities (0–2, 3–5, or 6–8 vs ≥ 9). The magnitude of associations was quantified by calculating the odds ratios (ORs) and 95% confidence intervals (CIs). A P value of less than 0.05 was considered to indicate a statistically significant difference. R V.4.4.0 software was used for all statistical analyses. As our study did not capture the actual ADRs experienced by the study population, an exploratory descriptive analysis was conducted to estimate the cumulative burden of ADRs due to PIMs in each member of the base cohort. The estimated ADR burden was quantified using the Cumulative Toxicity Tool in Polypharmacy Guidance Realistic Prescribing 2018, which cross-tabulates 32 classes of medication (including PIMs) and 15 ADR risks. 27 A risk score was used to quantify the cumulative risk of each ADR. Specifically, members of the base cohort who took a drug associated with an ADR were assigned a risk score of 1, and if they took multiple drugs associated with the ADR, the corresponding risk scores were summed to obtain a total risk score. A higher risk score indicated a high risk of experiencing a given ADR and represented the cumulative burden of the ADR in a given member of the base cohort. Results Characteristics of the base cohort The mean age of the base cohort was 82.9 (standard deviation (SD) = 8.6) years, and 61.9% were women (Table 1 ). The average number of concurrent medications was 6.8 (SD = 7.4), and polypharmacy (i.e. receiving five or more medications concurrently) was present in approximately 51.5% (n = 3,266) of the base cohort using medications most often for comorbid hypertension (n = 3,290, 51.8%), dementia (n = 2,201, 34.7%), or acute infection (n = 2,095, 33.0%). The prevalence of the 32 comorbidities in the base cohort are shown in Supplemental Table 2. The medications used in the 12-month study period by the base cohort are shown in Supplemental Table 3 . The most commonly used medications were those that act on the gastrointestinal system (n = 4,381, 69.0%), central nervous system (CNS; n = 4,350, 68.5%), and cardiovascular system (n = 4,081, 64.3%). The three most commonly used medications that act on the gastrointestinal system were bisacodyl (n = 2,999, 47.3%), senna (n = 2,811, 44.3%), and lactulose (n = 2,595, 40.9%). Table 1 Characteristics of the base cohort (N = 6,346) Characteristics n (%) Sex Female 3,931 (61.9) Male 2,415 (38.1) Age (years), mean ± SD 82.9 ± 8.6 65–74 860 (13.6) 75–84 1,649 (26.0) 85–94 2,893 (45.6) ≥ 95 944 (14.9) Major comorbidities Hypertension 3,290 (51.8) Dementia 2,201 (34.7) Acute infection 2,095 (33.0) Stroke 1,985 (31.3) Eye disease 1,799 (28.3) Renal disease 1,671 (26.3) Diabetes 1,648 (26.0) Cholesterol 1,431 (22.5) Fractures 1,336 (21.1) Psychiatric 1,051 (16.6) Arthritis 989 (15.6) Cancer 727 (11.5) Anemia 682 (10.7) Ischemic heart disease 659 (10.4) No. of concurrent medications, (mean ± SD) 6.8 ± 7.4 0 2,786 (43.9) 1–4 294 (4.6) 5–9 879 (13.9) 10–14 1,273 (20.1) ≥ 15 1,114 (17.6) No. of classes of concurrent medications, (mean ± SD) 5.2 ± 6.3 0 2,786 (43.9) 1–5 527 (8.3) 6–10 1,354 (21.3) 11–15 1,193 (18.8) ≥ 16 486 (7.7) Prescribing sources of medications* Public hospitals only 3062 (86.0) Private hospitals only 147 (4.1) Public and private hospitals 351 (9.9) SD: standard deviation *Include only 3,560 residents who were prescribed at least 1 medication. Prevalence of PIM use At least one PIM was taken by one-third (n = 2,189, 34.5%) of the base cohort, with 65.1% (n = 1,425) taking one PIM, 25.5% (n = 558) taking two PIMs, and 9.4% (n = 206) taking more than two PIMs. Table 2 presents the PIMs that were taken by over 1% of the base cohort. The most frequently used PIMs were chlorpheniramine (n = 1,031, 16.2%), lorazepam (n = 382, 6.0%), promethazine (n = 288, 4.5%), and gliclazide (n = 280, 4.4%). A full list of the prevalence of PIM use is presented in Supplemental Table 4 . Table 2 Top 10 most frequently administered potentially inappropriate medications in the base cohort (N = 6,346) Medication Therapeutic category No. of users Prevalence of PIM use (%) Chlorpheniramine First-generation antihistamines 1,031 16.2 Lorazepam Benzodiazepines 382 6.0 Promethazine First-generation antihistamines 288 4.5 Gliclazide Sulphonylureas 280 4.4 Clonazepam Benzodiazepines 175 2.8 Diphenhydramine First-generation antihistamines 171 2.7 Trihexyphenidyl Antiparkinsonian agents 125 2.0 Hydroxyzine First-generation antihistamines 109 1.7 Zolpidem Nonbenzodiazepine 105 1.7 Scopolamine (Hyoscine) Gastrointestinal antispasmodics 102 1.6 Cyproheptadine First-generation antihistamines 81 1.3 Association between PIM use and hospitalization In the study period, 4,686 members of the base cohort were administered at least one medication, and 2,563 (54.6%) were also hospitalized. The characteristics of those who were and were not hospitalized are presented in Supplement Table 5 . In the multivariable model (Table 3 ), compared with those who did not use PIMs, those who did use PIMs had higher rates of hospitalization (OR: 1.73, 95% CI: 1.54 to 1.69), and the number of PIMs they used was positively associated with their risk of hospitalization (OR: 2.17, 95% CI: 1.82 to 2.59 for > 1 PIMs vs 0). Those with a high comorbidity burden had a greater risk of hospitalization than those without comorbidity (OR: 1.72, 95% CI: 1.45 to 2.06 for ≥ nine comorbidities vs one comorbidity). Compared with those who received zero to four medications, those who received five to nine medications had lower risk of hospitalization (OR: 0.72, 95% CI: 0.60 to 0.86) while those who received ten or more medications was not associated with hospitalization (OR: 1.00, 95% CI 0.87 to 1.14). Table 3 Factors associated with hospitalization risk Model 1 Model 2 Variables OR (95% CI) P OR (95% CI) P PIM use in 2023 No Reference --- Yes 1.73 (1.54–1.96) <0.001 --- No. of PIMs in 2023 0 --- Reference 1 --- 1.56 (1.36–1.78) <0.001 ≥ 2 --- 2.17 (1.82–2.59) <0.001 Sex Male Reference Reference Female 0.79 (0.69–0.90) <0.001 0.79 (0.69–0.90) <0.001 Age 65–74 Reference Reference 75–84 0.93 (0.76–1.14) 0.50 0.94 (0.77–1.16) 0.5860 85–94 1.22 (1.00-1.47) 0.046 1.23 (1.02–1.49) 0.032 ≥ 95 1.41 (1.12–1.77) 0.003 1.44 (1.15–1.82) 0.002 No. of concurrent medications 0–4 Reference Reference 5–9 0.72 (0.60–0.86) <0.001 0.72 (0.61–0.86) <0.001 ≥ 10 1.00 (0.87–1.14) 0.98 0.99 (0.86–1.13) 0.83 No. of comorbidities 0–2 Reference Reference 3–5 1.16 (0.99–1.36) 0.063 1.16 (0.99–1.36) 0.065 6–8 1.33 (1.13–1.57) <0.001 1.32 (1.12–1.56) <0.001 ≥ 9 1.72 (1.45–2.06) <0.001 1.71 (1.43–2.04) <0.001 OR: odds ratio; PIM: potentially inappropriate medication; 95% CI: 95% confidence interval Model 1: Multivariable logistic regression model with PIM use, sex, age, number of concurrent medications and number of comorbidities as independent variables. Model 2: Multivariable logistic regression model with number of PIMs, sex, age, number of concurrent medications and number of comorbidities as independent variables. Exploratory Analysis: Estimating the Cumulative burden of ADRs in PIMs The risk scores for 15 distinct ADRs among the 2,387 members of the base cohort who had hyper-polypharmacy (concurrent use of ≥ 10 medications) were calculated based on the Cumulative Toxicity Tool in Polypharmacy Guidance Realistic Prescribing 2018, and the estimated cumulative burden of each ADR was visualized in the form of a heatmap (Fig. 1 ). The six ADRs with the highest cumulative burdens (individuals with a projected risk score of ≥ 5) were falls and fractures (n = 497, 20.8%), constipation (n = 275, 11.5%), CNS depression (n = 5.2%), and cardiovascular (CV) events (n = 101, 4.2%). The average projected risk scores were calculated for the 15 ADRs, and the highest risk scores were observed for falls and fractures (3.08), constipation (2.55), CV events (1.87), and CNS depression (1.70). Discussion This large-scaled study was the first to investigate the burden of PIM use and risk of hospitalization among older adults living in RCHEs in Hong Kong. Moreover, this study adopted a more precise and pragmatic classification of PIMs than the 2023 AGS Beers criteria and exploited data on administered medications extracted from the SMMS® database. Therefore, the descriptive findings of this study are reliable and accurately reflect the medications taken by the base cohort. It was found that more than a third (34.5%) of the base cohort took at least one PIM, particularly first-generation antihistamines and benzodiazepines. In addition, the use of a PIM was associated with 1.73 higher odds of hospitalization. Those who took at least two PIMs had 2.17-fold higher odds of hospitalization than those who did not take any PIM. These findings highlight the imminent need to develop local practical and sustainable measures to minimize the use of PIMs in older adults living in RCHEs. Moreover, there is a pressing need to engage pharmacists to review medication utilization among RCHE residents. Such a review may be more feasible if it is to lay focus on those who take the most common PIMs and who are at risk of the highest ADR burden from PIMs rather than include all those who take a PIM. Within the study period, about 1 in 3 older adults of the base cohort took a PIM. Similarly, it has been found that 30.3–38.6% of community-dwelling older adults in Hong Kong have used a PIM. 23 , 28 We acknowledge that some patient-related factors (e.g., age, sex, and comorbidity burden) are known unmodifiable risk factors for PIM use. For example, the majority of the current study population who took zolpidem and clonazepam received their prescriptions from a psychiatry hospital in Kowloon. This finding echoes with a study by Stuhec that reported high prevalence (25%) of potentially inappropriate antipsychotic use in nursing homes, and the need for collaborative strategies with pharmacists to ensure rational prescription of antipsychotics in older adults. 29 However, prescriber-related variables may also account for the high prevalence of PIM use by our cohort. Nevertheless, the prevalence of PIM use in our base cohort is lower than that reported by Zhang et al., i.e., 45.5%, in an investigation of PIM use among older adults visiting GOPCs in Hong Kong public healthcare system. These researchers outlined the underlying factors contributing to PIM use, including the highly subsidized services that led to a heavy patient load in the GOPCs and the absence of mandatory training on geriatric medicine for physicians practicing in the GOPCs. 19 We postulate that PIM use by the current study population is lower than that reported by Zhang et al. because our cohort mostly visited specialist outpatient clinics, which may have more well-trained physicians in geriatrics than GOPCs. Our findings reinforce the importance in increasing the competency of the physicians and RCHE staff through continuing professional education. Future work should be focused on collaborating with health administrators of the Hong Kong public healthcare system to adopt computerized decision-support tools to reduce potentially inappropriate prescriptions and the use of PIMs. Consistent with previous findings 15 , 30 , 31 , this study found that the use of PIMs in older adults at RCHEs was strongly associated with an increased risk of hospitalization, which increased with the number of PIMs used. This finding should be interpreted cautiously because PIM use and hospital admission data were both captured within the same study period. Although the analysis only counted hospital admissions after the start date of any PIM as a “case”, the cross-sectional design of this study meant that a causal relationship between PIM use and the risk of hospitalization could not be determined. We were also unable to differentiate between planned or unplanned admission due to limitations of the SMMS®. Nevertheless, based on previous studies, it is reasonable to postulate that drug–drug or drug–disease interactions and adverse events may be mechanisms by which PIMs can increase the risk of hospitalization. 30 , 32 In addition, our exploratory analysis used the Cumulative Toxicity Tool in Polypharmacy Guidance Realistic Prescribing 27 to estimate the potential ADR risk associated each PIM. Although this estimation is hypothetical in nature and may not reflect the actual ADRs that the residents experienced, the analysis shows the highest ADR risk score for falls and fractures, which may logically be associated with a higher risk of hospitalization based on evidence from the literature. 33 , 34 The strong association of PIMs with hospitalization and the “dose–response” increase in the risk of hospitalization observed in those of the study population who took at least two PIMs are further evidence of the detrimental effect of PIMs on older adults in RCHEs in Hong Kong. Another finding of this study was that compared with those in the study population who took up to four medications, those who took from five to nine medications exhibited a lower risk of hospitalization, despite this number of medications traditionally being classified as polypharmacy. This finding is inconsistent with the findings in a review of previous studies 35 but could be explained by the concept of “appropriate polypharmacy.” 36 This is a term for medicines prescribed according to best evidence to an individual who has complex conditions or multiple conditions and uses the medicines in an optimized fashion. 37 Therefore, we posit that in older adults with multiple comorbidities, the appropriateness and necessity of the medications prescribed are significant, in addition to the number of medications prescribed. However, this finding should be interpreted cautiously given that the concept of “appropriate polypharmacy” still requires validation and supporting evidence from the literature, and that the sample size of older adults who took five to nine medications is small. In summary, the clinical context in which multiple medications are prescribed should be considered to ensure that patients use only medications that are necessary for treating or managing their diseases and, if possible, that these medications are not PIMs. 38 Our findings reinforce the importance of regular medication review and reconciliation for residents in nursing homes. A recent review found that pharmacist-led services significantly reduced the mean number of falls among residents in RCHEs, although they did not uniformly reduce overall mortality and hospitalization rates. 39 However, most local RCHEs do not have in-house pharmacists who provide medication reviews for residents. To address this service gap, the recent Primary Healthcare Blueprint released by the Hong Kong government recommended that community geriatric assessment teams regularly visit RCHEs for older adults to provide medical and nursing care to frail residents. 40 We also found potentially inappropriate psychiatric medications prescribed to older adults in our study cohort. Several reports have demonstrated that including a clinical pharmacist in the interdisciplinary ward rounds and medication reconciliation reviews could significantly reduce potential drug-related problems in Slovenia 41 , 42 ; this has eventually led to the first national-level reimbursed medication review program in the primary care settings in Central Europe. 11 In Germany, interdisciplinary pharmacist-led medication reviews have effectively led to increased recommendations in dose reductions and temporary or permanent discontinuation of PIMs in older adults with psychiatric conditions. 43 Similarly, countries such as Singapore and Australia have achieved cost savings and other positive outcomes by engaging community pharmacists from both public and private sectors to conduct regular medication reviews in RCHEs. 44 , 45 The involvement of pharmacists in a multidisciplinary team is important for promoting the safe use of medications and implementing deprescribing practices in RCHEs. A key strength of the current study is the use of an electronic medication management system to capture the medications administered to the study population. This approach allowed us to overcome several limitations reported in other studies using claims databases or dispensing records, such as a failure to account for drug adherence, incomplete medication data, and inaccurate coding. 46 , 47 However, the current study also has several limitations. First, although the Beers Criteria is an internationally recognized criteria to categorize PIMs, the prevalence of PIM use might have been underestimated because as not all categories of the Beers criteria were assessed in the study. For example, PIMs related to indication, renal impairment, and drug-drug interactions were unaddressed because such information is not available in the SMMS®. To illustrate, a study by Kummer et al. has reported that more than a quarter (28%) of older adults living in RCHEs of Croatia were inappropriately prescribed with benzodiazepines higher than recommended geriatric doses and nearly half (48%) were prescribed concomitant interacting medications. 48 Therefore, the actual rate of PIM use may be even higher than what is reported in this study. Second, the use of the SMMS® database restricted the assessment of medications to prescribed drugs, meaning that over-the-counter medications or supplements that the members of the base cohort might have been taking of their own accord were not assessed. Third, data on certain potential residual confounding factors, such as frailty status, disease severity, and disability, were not available to be included in our analyses. Furthermore, as medical diagnoses data in the Hospital Authority is currently not linked with the SMMS®, our manual approach to coding the diagnoses data may lead to errors in characterizing the comorbidities of the study population. Fourth, as this study leveraged on data collected from the Integrated Old Age Home Medication Management Program (a community service improvement project), there is no prior sample size calculation. However, we reckoned a study population consisting of 6,346 residents from 29 RCHEs may still be reasonably generalizable to the RCHE community in Hong Kong, as well as adequate to estimate the prevalence of PIM use and interpret the significant associations observed between PIM use and hospitalization. As the SMMS® database does not contain information on resident mortality, we were unable to determine the survival status of a subgroup of residents (8.2%) who had been discharged before June 2024 due to death or other reasons. However, these residents comprised a small proportion of the base cohort, and thus it is unlikely that their discharge status significantly impacted the results. Conclusion According to an assessment based on the latest version of the Beers criteria, there was a high burden of PIM use among older adults living in 29 RCHEs in Hong Kong during the study period. In addition, the use of PIMs by these older adults was associated with an increased risk of hospitalization, particularly for those who were taking at least two PIMs and had multiple comorbidities. Effective interventions should be implemented and strengthened in these RCHEs, particularly interventions that focus on educating physicians about PIMs and the use of computer-assisted technology in identifying PIMs. Future studies should examine the causes of PIMs in various settings and devise strategies that may ameliorate PIM-related healthcare burden. Declarations Clinical trial number: Not applicable Ethics approval and consent to participate: Approval was obtained from the Survey and Behavioral Research Ethics (SBRE) Committee of the Chinese University of Hong Kong (reference number: SBRE-19-106). All participating RCHEs provided consent for the use of de-identified data for research purposes. Written informed consent from individual participants was waived due to the following reasons: (1) this study involved de-identified data from the routine users of a medication management system (SMMS ® ), (2) there is minimal risk posted to the patient and concerns with data privacy as the analyzed data was all de-identified and anonymized in the analysis, and (3) it was not practicable to obtain individual consent from all residents who are routine users of the SMMS ® . The study is conducted in accordance with the ethical considerations and compliance with the principles enunciated in the Declaration of Helsinki. Consent for publication: All participating RCHEs provided consent for the publication of aggregated and anonymized (unidentifiable) data for research purposes. Availability of data and material: The data that support the findings of this study are available on request from the corresponding authors, YTC and SCC. The data are not publicly available due to information that could compromise the privacy of research participants. Competing interests: All authors declare no conflict of interest. Funding: The implementation and use of the SMMS ® at the participating RCHEs is funded by the Vera Ruttonjee Desai Charitable Fund, a philanthropic organization, which played no role in investigating, analyzing or interpreting the results of this study. Authors' contributions: All authors made substantial contributions to the conception and study design. H.C.C and S.C.C conducted data collection. K.Z and Y.T.C conducted the data analysis. All authors interpreted the data. K.Z and Y.T.C drafted the manuscript. All authors substantively revised it. All authors have approved the submitted version. All authors have agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work. Acknowledgements: NA References Zazzara MB, Palmer K, Vetrano DL, Carfì A, Onder G. Adverse drug reactions in older adults: a narrative review of the literature. Eur Geriatr Med Jun. 2021;12(3):463–73. 10.1007/s41999-021-00481-9 . Davies EA, O'Mahony MS. Adverse drug reactions in special populations – the elderly. Br J Clin Pharmacol. 2015;80(4):796–807. https://doi.org/10.1111/bcp.12596 . Motter FR, Fritzen JS, Hilmer SN, Paniz ÉV, Paniz VMV. Potentially inappropriate medication in the elderly: a systematic review of validated explicit criteria. Eur J Clin Pharmacol Jun. 2018;74(6):679–700. 10.1007/s00228-018-2446-0 . Panel BtAGSBCUE. American Geriatrics Society 2023 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052–81. https://doi.org/10.1111/jgs.18372 . Tian F, Chen Z, Zeng Y, Feng Q, Chen X. Prevalence of Use of Potentially Inappropriate Medications Among Older Adults Worldwide: A Systematic Review and Meta-Analysis. JAMA Netw Open. 2023;6(8):e2326910–2326910. 10.1001/jamanetworkopen.2023.26910 . Morin L, Laroche ML, Texier G, Johnell K. Prevalence of Potentially Inappropriate Medication Use in Older Adults Living in Nursing Homes: A Systematic Review. J Am Med Dir Assoc. Sep 2016;1(9):e8621–9. 10.1016/j.jamda.2016.06.011 . Opondo D, Eslami S, Visscher S, et al. Inappropriateness of medication prescriptions to elderly patients in the primary care setting: a systematic review. PLoS ONE. 2012;7(8):e43617. 10.1371/journal.pone.0043617 . Jokanovic N, Tan EC, Dooley MJ, Kirkpatrick CM, Bell JS. Prevalence and factors associated with polypharmacy in long-term care facilities: a systematic review. J Am Med Dir Assoc. Jun 2015;1(6):e5351–12. 10.1016/j.jamda.2015.03.003 . Díez R, Cadenas R, Susperregui J, et al. Drug-Related Problems and Polypharmacy in Nursing Home Residents: A Cross-Sectional Study. Int J Environ Res Public Health Apr. 2022;4(7). 10.3390/ijerph19074313 . MacRae C, Henderson DA, Mercer SW, et al. Excessive polypharmacy and potentially inappropriate prescribing in 147 care homes: a cross-sectional study. BJGP Open. 2021;5(6). 10.3399/bjgpo.2021.0167 . Stuhec M. Clinical pharmacist consultant in primary care settings in Slovenia focused on elderly patients on polypharmacy: successful national program from development to reimbursement. Int J Clin Pharm Dec. 2021;43(6):1722–7. 10.1007/s11096-021-01306-2 . Storms H, Marquet K, Aertgeerts B, Claes N. Prevalence of inappropriate medication use in residential long-term care facilities for the elderly: A systematic review. Eur J Gen Pract Dec. 2017;23(1):69–77. 10.1080/13814788.2017.1288211 . Wong J, Marr P, Kwan D, Meiyappan S, Adcock L. Identification of inappropriate medication use in elderly patients with frequent emergency department visits. Can Pharm J (Ott) Jul. 2014;147(4):248–56. 10.1177/1715163514536522 . Heck J, Noltemeyer N, Schulze Westhoff M, et al. Adverse drug reactions in geriatric psychiatry—retrospective cohort study of a 6-year period. Ir J Med Sci. 1971 -;192(6):2917–27. 10.1007/s11845-023-03300-1 . 2023/12/01 2023. Chae H-W, Zhao J, Ah Y-M, Choi KH, Lee J-Y. Potentially inappropriate medication use as predictors of hospitalization for residents in nursing home. BMC Geriatrics . 2023/08/02 2023;23(1):467. 10.1186/s12877-023-04165-w Hong Kong Population Projections 2022–2046. Census and Statistics Department. URL: https://www.censtatd.gov.hk/en/data/stat_report/product/B1120015/att/B1120015092023XXXXB01.pdf . Accessed on November 1, 2024. Census and Statistics Department. Hong Kong Special Administrative Region. 2021 Population Census. Thematic Report: Older Persons. URL: https://www.censtatd.gov.hk/en/data/stat_report/product/B1120118/att/B11201182021XXXXB0100.pdf . Accessed on November 1, 2024. Legislative Council Panel on Welfare Services. LC Paper No. CB(1)1311/2024(05): Drug Management of Residential Care Homes for the Elderly. URL: https://www.legco.gov.hk/yr2024/english/panels/ws/papers/ws20241014cb1-1311-5-e.pdf . Accessed on November 1, 2024. Zhang H, Wong EL, Wong SY, et al. Prevalence and determinants of potentially inappropriate medication use in Hong Kong older patients: a cross-sectional study. BMJ Open Jul. 2021;22(7):e051527. 10.1136/bmjopen-2021-051527 . So KH, Ting CW, Lee CP, Lam TT, Chiang SC, Cheung YT. Medication Management Service for Old Age Homes in Hong Kong Using Information Technology, Automation Technology, and the Internet of Things: Pre-Post Interventional Study. JMIR Med Inf Feb. 2021;10(2):e24280. 10.2196/24280 . ATC/DDD classification (final).(ATC/DDD Classification)(anatomical therapeutic chemical (ATC) classifications and defined daily doses). WHO drug Inform. 2011;25(1):43. HA Drug Formulary. Hospital Authority. URL: https://www.ha.org.hk/hadf/en-us/Updated-HA-Drug-Formulary/Drug-Formulary.html . Accessed on November 1, 2024. Lam DP, Mak CF, Chan SM, Yao RW, Leung SS, You JH. Polypharmacy and inappropriate prescribing in elderly Hong Kong Chinese patients. J Am Geriatr Soc Jan. 2010;58(1):203–5. 10.1111/j.1532-5415.2009.02656.x . Bick I, Dowding D. Hospitalization risk factors of older cohorts of home health care patients: A systematic review. Home Health Care Serv Q Jul-Sep. 2019;38(3):111–52. 10.1080/01621424.2019.1616026 . Grabowski DC, Stewart KA, Broderick SM, Coots LA. Predictors of nursing home hospitalization: a review of the literature. Med Care Res Rev Feb. 2008;65(1):3–39. 10.1177/1077558707308754 . Zhang S, Zhang K, Chen Y, Wu C. Prediction models of all-cause mortality among older adults in nursing home setting: A systematic review and meta-analysis. Health Sci Rep Jun. 2023;6(6):e1309. 10.1002/hsr2.1309 . Polypharmacy Guidance Realistic Prescribing, 3rd Edition. 2018. URL: https://www.therapeutics.scot.nhs.uk/wp-content/uploads/2018/04/Polypharmacy-Guidance-2018.pdf . Accessed November 1, 2024. Lam MP, Cheung BM, Wong IC. Beers 2012, and Screening Tool of Older Person's Prescriptions and Screening Tool to Alert doctors to Right Treatment Criteria. J Am Geriatr Soc Jul. 2015;63(7):1471–2. 10.1111/jgs.13555 . Prevalence of Potentially Inappropriate Prescribing Among Hong Kong Older Adults: A Comparison of the Beers 2003. Stuhec M. Antipsychotic treatment in elderly patients on polypharmacy with schizophrenia. Curr Opin Psychiatry Sep. 2022;1(5):332–7. 10.1097/yco.0000000000000808 . Albert SM, Colombi A, Hanlon J. Potentially inappropriate medications and risk of hospitalization in retirees: analysis of a US retiree health claims database. Drugs Aging May. 2010;27(5):407–15. 10.2165/11315990-000000000-00000 . Lau DT, Kasper JD, Potter DE, Lyles A, Bennett RG. Hospitalization and death associated with potentially inappropriate medication prescriptions among elderly nursing home residents. Arch Intern Med Jan. 2005;10(1):68–74. 10.1001/archinte.165.1.68 . Reinhild Haerig T, Krause D, Klaassen-Mielke R, Rudolf H, Trampisch HJ, Thuermann P. Potentially inappropriate medication including drug-drug interaction and the risk of frequent falling, hospital admission, and death in older adults - results of a large cohort study (getABI). Front Pharmacol. 2023;14:1062290. 10.3389/fphar.2023.1062290 . Moon A, Jang S, Kim J-H, Jang S. Risk of falls or fall-related injuries associated with potentially inappropriate medication use among older adults with dementia. BMC Geriatrics . 2024/08/23 2024;24(1):699. 10.1186/s12877-024-05300-x Berdot S, Bertrand M, Dartigues JF, et al. Inappropriate medication use and risk of falls–a prospective study in a large community-dwelling elderly cohort. BMC Geriatr Jul. 2009;23:9:30. 10.1186/1471-2318-9-30 . Fried TR, O'Leary J, Towle V, Goldstein MK, Trentalange M, Martin DK. Health outcomes associated with polypharmacy in community-dwelling older adults: a systematic review. J Am Geriatr Soc Dec. 2014;62(12):2261–72. 10.1111/jgs.13153 . Cadogan CA, Ryan C, Hughes CM. Appropriate Polypharmacy and Medicine Safety: When Many is not Too Many. Drug Saf Feb. 2016;39(2):109–16. 10.1007/s40264-015-0378-5 . World Health Organization. Medication Safety in Polypharmacy. URL: https://www.who.int/docs/default-source/patient-safety/who-uhc-sds-2019-11-eng.pdf . Accessed on November 1, 2024. Hughes C. Appropriate and inappropriate polypharmacy-Choosing the right strategy. Br J Clin Pharmacol Jan. 2021;87(1):84–6. 10.1111/bcp.14589 . Lee SWH, Mak VSL, Tang YW. Pharmacist services in nursing homes: A systematic review and meta-analysis. Br J Clin Pharmacol Dec. 2019;85(12):2668–88. 10.1111/bcp.14101 . Health Bureau. The Government of the Hong Kong Special Administrative Region. Primary Healthcare Blueprint Supplement. URL: https://www.primaryhealthcare.gov.hk/bp/cms-assets/Primary_Healthcare_Blueprint_Supplement_Perfect_Binding_Eng_291a55714a.pdf . Accessed on November 1, 2024. Stuhec M, Tement V. Positive evidence for clinical pharmacist interventions during interdisciplinary rounding at a psychiatric hospital. Sci Rep Jul. 2021;1(1):13641. 10.1038/s41598-021-92909-2 . Stuhec M, Batinic B. Clinical pharmacist interventions in the transition of care in a mental health hospital: case reports focused on the medication reconciliation process. Front Psychiatry. 2023;14:1263464. 10.3389/fpsyt.2023.1263464 . Schröder S, Schulze Westhoff M, Pfister T, et al. Characteristics of clinical-pharmacological recommendations in psychiatry in Germany. Int J Psychiatry Med. May 2024;59(3):393–405. 10.1177/00912174231177230 . Haider I, Kosari S, Naunton M, et al. The role of on-site pharmacist in residential aged care facilities: findings from the PiRACF study. J Pharm Policy Pract. 2023;2023/07/03(1):82. 10.1186/s40545-023-00587-4 . Chia HS, Ho JA, Lim BD. Pharmacist review and its impact on Singapore nursing homes. Singap Med J Sep. 2015;56(9):493–501. 10.11622/smedj.2015133 . Tyree PT, Lind BK, Lafferty WE. Challenges of using medical insurance claims data for utilization analysis. Am J Med Qual Jul-Aug. 2006;21(4):269–75. 10.1177/1062860606288774 . Rasmussen L, Wettermark B, Steinke D, Pottegård A. Core concepts in pharmacoepidemiology: Measures of drug utilization based on individual-level drug dispensing data. Pharmacoepidemiol Drug Saf Oct. 2022;31(10):1015–26. 10.1002/pds.5490 . Kummer I, Reissigová J, Lukačišinová A, et al. Polypharmacy and potentially inappropriate prescribing of benzodiazepines in older nursing home residents. Ann Med Dec. 2024;56(1):2357232. 10.1080/07853890.2024.2357232 . Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials10Apr25.docx Cite Share Download PDF Status: Published Journal Publication published 06 May, 2025 Read the published version in BMC Geriatrics → Version 1 posted Editorial decision: Accepted 25 Apr, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 22 Apr, 2025 Reviews received at journal 18 Apr, 2025 Reviewers agreed at journal 18 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers invited by journal 16 Apr, 2025 Submission checks completed at journal 16 Apr, 2025 First submitted to journal 11 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5733476","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":444015617,"identity":"5c715889-d426-4002-95ff-ad92487288e9","order_by":0,"name":"Ho Cheung Chau","email":"","orcid":"","institution":"Hong Kong Pharmaceutical Care Foundation Limited","correspondingAuthor":false,"prefix":"","firstName":"Ho","middleName":"Cheung","lastName":"Chau","suffix":""},{"id":444015618,"identity":"96bd61f4-8614-4be8-84d4-a6e36fdb3246","order_by":1,"name":"Kexin Zhang","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Kexin","middleName":"","lastName":"Zhang","suffix":""},{"id":444015620,"identity":"eccdedef-e394-479d-924c-ed19434ca2df","order_by":2,"name":"Bik-Wai Bilvick Tai","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Bik-Wai","middleName":"Bilvick","lastName":"Tai","suffix":""},{"id":444015622,"identity":"074c6962-5182-47de-8d74-142d8d7ae140","order_by":3,"name":"Isaac Shing Yan Hui","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"Shing Yan","lastName":"Hui","suffix":""},{"id":444015624,"identity":"2f02463e-e3cd-4eb0-8c5d-5012daeab331","order_by":4,"name":"Hon Ming Ma","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Hon","middleName":"Ming","lastName":"Ma","suffix":""},{"id":444015625,"identity":"6634c10f-abb7-4a0d-926f-ed621d8a6ec0","order_by":5,"name":"Martin Chi Sang Wong","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"Chi Sang","lastName":"Wong","suffix":""},{"id":444015626,"identity":"ccce55d7-00dc-48ac-8635-a587014d3f61","order_by":6,"name":"Sau Chu Chiang","email":"","orcid":"","institution":"Hong Kong Pharmaceutical Care Foundation Limited","correspondingAuthor":false,"prefix":"","firstName":"Sau","middleName":"Chu","lastName":"Chiang","suffix":""},{"id":444015627,"identity":"e1288ecb-ad0c-4a78-8311-5d00270b5935","order_by":7,"name":"Yin Ting Cheung","email":"data:image/png;base64,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","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":true,"prefix":"","firstName":"Yin","middleName":"Ting","lastName":"Cheung","suffix":""}],"badges":[],"createdAt":"2024-12-30 07:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5733476/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5733476/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-025-05989-4","type":"published","date":"2025-05-06T15:56:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80823692,"identity":"70676789-6b53-4ae9-a33c-0d671b71e107","added_by":"auto","created_at":"2025-04-17 12:41:31","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":326409,"visible":true,"origin":"","legend":"\u003cp\u003eThe risk scores for 15 distinct adverse drug reactions (ADR) among 2,387 residents with hyper-polypharmacy (i.e. taking ≥10 medications)\u003c/p\u003e\n\u003cp\u003e*The x-axis represents the 15 types of adverse drug reactions as outlined by the Cumulative Toxicity Tool of the Polypharmacy Guidance 2018, while the y-axis represents the cumulative risk scores. Each square denotes the specific risk score, and the number within each square indicates the number of patients at that risk score level. A darker color indicates a higher number of residents bearing that risk score level.\u003c/p\u003e\n\u003cp\u003eCNS depression: \u003ca href=\"https://en.wikipedia.org/wiki/Central_nervous_system_depression\" target=\"_blank\"\u003ecentral nervous system depression\u003c/a\u003e; CV events: cardiovascular events.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5733476/v1/826ac7363bdd36db88a579af.jpeg"},{"id":82537614,"identity":"393e603f-b569-4c3b-8d3a-c596f9eb14a7","added_by":"auto","created_at":"2025-05-12 16:09:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1254552,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5733476/v1/59b1263a-030b-470e-b05c-aa1862afe152.pdf"},{"id":80822702,"identity":"bfda8d44-72d2-4873-8b2c-e0c38430611a","added_by":"auto","created_at":"2025-04-17 12:33:31","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":70117,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials10Apr25.docx","url":"https://assets-eu.researchsquare.com/files/rs-5733476/v1/a3a22702c469fe699c31b81c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of Medication Management System Data to Determine Potentially Inappropriate Medication Use and Hospitalization Among Older Adults Living in Residential Care Homes for the Elderly Population","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePhysiological changes associated with aging can alter the pharmacokinetics and pharmacodynamic properties of drugs. These factors play a significant role in augmenting drug toxicity in adults aged 65 or over (hereinafter, \u0026ldquo;older adults\u0026rdquo;), increasing their susceptibility to adverse drug reactions (ADRs) associated with the use of multiple drugs.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Moreover, older adults may take potentially inappropriate medications (PIMs), which are \u0026ldquo;\u003cem\u003edrugs with\u0026hellip; risks [that] outweigh potential benefits, especially when effective alternatives are available.\u003c/em\u003e\u0026rdquo;\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e To reduce older adults\u0026rsquo; exposure to PIMs, the American Geriatrics Society (AGS) developed the Beers Criteria for PIM Use in Older Adults as a safe-prescribing reference for clinicians.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Although the Beers criteria were designed for use in the US, they have been widely used to assess the prevalence of PIM use by older populations in various settings in other countries, including Hong Kong.\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMany older adults living in residential care homes for the elderly (RCHEs) have multiple chronic diseases and thus have a higher probability of having polypharmacy (i.e. receiving five or more medications concurrently).\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e For example, it has been reported that over 10% of the Slovenian population had polypharmacy, and 4% with over ten medications concomitantly (i.e., with hyper-polypharmacy).\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e A systematic review of 17 studies found that according to the Beers criteria, the prevalence of PIM use by RCHE residents ranged from 18.5\u0026ndash;82.6%.\u003csup\u003e12\u003c/sup\u003e It has been shown that compared with appropriate medication use, inappropriate medication and PIM use by older adults is associated with more frequent hospital visits and hospitalization.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e In particular, inappropriate use of medications in older adults with psychiatric conditions may lead to increased risk of developing major cardiopulmonary and neurological adverse drug reactions.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Furthermore, a Korean study reported that residents who used\u0026thinsp;\u0026ge;\u0026thinsp;4 PIMs (according to the Beers and Korean criteria) at the time of RCHE admission had a 30% increased risk of an emergency department visit.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn Hong Kong, older adults comprised 20.5% of the population in 2021, and this percentage is expected to increase to 36.0% of the population by 2046.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The 2021 Hong Kong Population Census reported that 95.2% of older adults were living in domestic households, while the remaining 4.8% were living in non-domestic households, such as RCHEs.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Thus, improving medication safety and management has become a priority of the Hong Kong healthcare agenda.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e An analysis of data obtained from the Hospital Authority, a statutory body that governs all public healthcare services in Hong Kong, reported that the 12-month prevalence of PIM use was 55.5% in 2006 and reduced to 47.5% in 2014.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e However, there remains a lack of information regarding the risk of hospitalization due to the use of PIMs in older adults living in RCHEs in metropolitan cities like Hong Kong. Furthermore, the accuracy of the medication exposure data in this study was limited, as these data were obtained from a repository that captured information on dispensed medications rather than administered medications.\u003c/p\u003e\n\u003ch3\u003eStudy Objectives\u003c/h3\u003e\n\u003cp\u003eThe objectives of this study are (1) to describe the prevalence of PIM use according to the 2023 Beers criteria in older adults living in RCHEs of Hong Kong, and (2) to investigate the association between their PIM use and risk of hospitalization.\u003c/p\u003e"},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis is a prospective, observational, cohort study that analyzed data collected from the Integrated Old Age Home Medication Management Program, which was initiated by the Hong Kong Pharmaceutical Care Foundation Ltd (HKPCF), a non-governmental organization. The medication management program employs various technologies and automated methods to develop a medication management system for participating RCHEs in Hong Kong.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e Approval was obtained from the Survey and Behavioral Research Ethics (SBRE) Committee of the Chinese University of Hong Kong (reference number: SBRE-19-106). All participating RCHEs provided consent for the use of de-identified data for research purposes. The implementation and use of the SMMS\u0026reg; at the participating RCHEs is funded by a philanthropic organization, which played no role in investigating, analyzing or interpreting the results of this study.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eBase cohort\u003c/h3\u003e\n\u003cp\u003eThis study analyzed medication and clinical data of the residents living in 29 RCHEs that participated in the medication management program from January 1 to December 31, 2023 (the study period) across various geographical regions of Hong Kong. These RCHEs met the SMMS\u0026reg; criteria, i.e., they (1) had a Wi-fi network, (2) received sustained operational funding from the government, the private sector, or philanthropic organizations, and (3) consented in writing to provide de-identified data for medication management program evaluation and research purposes. To ensure generalizability to older adults living in RCHEs of Hong Kong, the data of all residents who were aged 65 years or older and living in the participating RCHEs (n\u0026thinsp;=\u0026thinsp;6,346) was analyzed in this study, regardless of their medication status \u003cb\u003e(Supplemental Fig.\u0026nbsp;1)\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eData source\u003c/h3\u003e\n\u003cp\u003eAll data of the base cohort were extracted from the SafeMed Medication Management System (SMMS\u0026reg;), which is an electronic medication system developed by HKPCF with diverse applications for RCHEs to integrate patients\u0026rsquo; medication data from different sources. In Hong Kong, RCHE residents are prescribed medications by physicians at hospitals or outpatient clinics (i.e. General Out-patient Clinic [GOPC]) under the Hospital Authority, which is a public health system funded by the Government and is responsible for more than 90% of the in-patient service in Hong Kong. To a lesser extent, general practitioners and clinicians from private clinics or hospitals may also prescribe medications for patients. The medications were collected by RCHE staff, who also entered patients\u0026rsquo; information and medications into the database of the SMMS\u0026reg;\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUnique among systems for RCHEs in Hong Kong, the SMMS has included a comprehensive drug database that covers all medications commonly prescribed by clinicians from the Hospital Authority. The database includes the details of each medication as follows: trade name, dosage form, strength, legal classification, therapeutic class (according to the Anatomical Therapeutic Chemical Classification\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e), precautions, common instructions for use, Hong Kong registration number, and manufacturer. This drug database enables the systematic built up of medication profiles for individual residents with detailed appropriate drug administration schedules. Moreover, the system supports electronic records of medications that are administered to the residents of RCHEs at the scheduled times in a real-time manner. Thus, the administered medication data for the base cohort were extracted from the backend of the SMMS\u0026reg; database. The SMMS\u0026reg; database also contains updated information on RCHE residents\u0026rsquo; personal information, and follow-up consultations at hospitals or clinics, hospital admissions and discharges. These data are reliable and comprehensive, as the SMMS\u0026reg; is the sole medication management system for all 29 participating RCHEs. Our previous study determined that the amount of data missing from the SMMS\u0026reg; database is negligible.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e For major comorbidities and medical conditions, the nursing staff of RCHEs manually entered the residents\u0026rsquo; existing health conditions from the medical records of the Hospital Authority (including hospitals and outpatient clinics) upon initiation of a profile for each new resident, and updated the list periodically based on the latest health status of the resident. For the purpose of the current analysis, coding of the health conditions was conducted by one investigator (ISYH) and independently verified by two other investigators (KZ and YTC). In addition, all records in the SMMS\u0026reg; database are anonymized and de-identified for research purposes.\u003c/p\u003e\n\u003ch3\u003eOperational definition of PIM use\u003c/h3\u003e\n\u003cp\u003eThe 12-month prevalence of PIM use was calculated by dividing the number of members of the base cohort with at least one PIM use from January 1 to December 31, 2023 by the total number of residents in the 29 RCHEs during the study period.\u003c/p\u003e \u003cp\u003eThe 2023 AGS Beers criteria contain five categories of PIM use,\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e of which four of these were excluded from the current study. The updated Beers criteria involved an expert panel of highly experienced specialists with a robust internal review and external public comment processes.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Specifically, the categories of \u0026ldquo;medications potentially inappropriate in patients with certain diseases or syndromes\u0026rdquo; and \u0026ldquo;potentially inappropriate drug-drug interactions\u0026rdquo; were excluded due to concerns regarding their lack of comprehensiveness, as disclaimed by the developers,\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and because diagnosis information and the exact indications of medications are not available in the SMMS\u0026reg; database. In addition, the category of \u0026ldquo;medications to be used with caution\u0026rdquo; was excluded, as such medications can be used under specific circumstances. Moreover, the category of \u0026ldquo;medication with dosage adjustments based on renal function\u0026rdquo; was excluded, as assessment of kidney function requires clinical data that are not available in the SMMS\u0026reg; database. Therefore, the only category included in this analysis was \u0026ldquo;medications considered potentially inappropriate independent of diagnosis.\u0026rdquo;\u003c/p\u003e \u003cp\u003eSubsequently, the drugs in this category were examined in the context of their registration status in Hong Kong.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e PIMs that are not commercially registered in Hong Kong (such as meclizine, amoxapine, and desipramine) were excluded. In addition, PIMs with inappropriateness defined by their indication, dose, or therapy duration were excluded, because the SMMS\u0026reg; database does not capture the aforementioned data. Thus, the final PIM assessment criteria were adapted to Hong Kong and contained 36 PIMs independent of diagnosis (\u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e). This approach of defining PIMs and the 36 PIMs in this analysis are consistent with previous studies that have investigated drug utilization among older adults in Hong Kong.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHospitalization data\u003c/h2\u003e \u003cp\u003eTo examine the association between PIM use and hospitalization rates, another cohort was constructed from the base cohort, consisting of residents\u0026thinsp;\u0026ge;\u0026thinsp;65 years old in the 29 RCHEs who were administered at least one medication between January 1 and December 31, 2023 \u003cb\u003e(Supplemental Fig.\u0026nbsp;1)\u003c/b\u003e. Residents not taking any medications were excluded from this analysis as they might be in better health state and had fewer severe comorbidities; including these healthier individuals could cloud the observed rate of hospitalization in non-PIM users, potentially leading to biased results. From this sub-cohort, information on hospitalization between January 1 and December 31, 2023, comprising the dates of admission and discharge, as well as the type of care received were extracted from the SMMS\u0026reg;. Only hospital admission(s) that occurred after the start date of any PIM and before the end date (if any) for each resident was coded as a \u0026ldquo;case\u0026rdquo; in this analysis. All types of hospitalization, regardless of planned or unplanned admissions and length of stay, were included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize the characteristics of the base cohort and medications they were administered.\u003c/p\u003e \u003cp\u003eThe association between the use of PIM and hospitalization in the base cohort was evaluated using multivariable logistic regression. The main predictors of interest were the use of any PIMs (yes vs no) and the number of PIMs used (0 or 1 vs\u0026thinsp;\u0026ge;\u0026thinsp;2) and were analyzed in separate models to prevent multicollinearity. The other covariates included in the model were clinically relevant factors that have been reported to be associated with hospitalization in institutionalized older adults,\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e namely sex, age (65\u0026ndash;74, 75\u0026ndash;84, or 85\u0026ndash;94 vs\u0026thinsp;\u0026ge;\u0026thinsp;95 years), number of concurrent medications (0\u0026ndash;4 or 5\u0026ndash;9 vs\u0026thinsp;\u0026ge;\u0026thinsp;10), and number of comorbidities (0\u0026ndash;2, 3\u0026ndash;5, or 6\u0026ndash;8 vs\u0026thinsp;\u0026ge;\u0026thinsp;9). The magnitude of associations was quantified by calculating the odds ratios (ORs) and 95% confidence intervals (CIs). A P value of less than 0.05 was considered to indicate a statistically significant difference. R V.4.4.0 software was used for all statistical analyses.\u003c/p\u003e \u003cp\u003eAs our study did not capture the actual ADRs experienced by the study population, an exploratory descriptive analysis was conducted to estimate the cumulative burden of ADRs due to PIMs in each member of the base cohort. The estimated ADR burden was quantified using the Cumulative Toxicity Tool in Polypharmacy Guidance Realistic Prescribing 2018, which cross-tabulates 32 classes of medication (including PIMs) and 15 ADR risks.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e A risk score was used to quantify the cumulative risk of each ADR. Specifically, members of the base cohort who took a drug associated with an ADR were assigned a risk score of 1, and if they took multiple drugs associated with the ADR, the corresponding risk scores were summed to obtain a total risk score. A higher risk score indicated a high risk of experiencing a given ADR and represented the cumulative burden of the ADR in a given member of the base cohort.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the base cohort\u003c/h2\u003e \u003cp\u003eThe mean age of the base cohort was 82.9 (standard deviation (SD)\u0026thinsp;=\u0026thinsp;8.6) years, and 61.9% were women (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The average number of concurrent medications was 6.8 (SD\u0026thinsp;=\u0026thinsp;7.4), and polypharmacy (i.e. receiving five or more medications concurrently) was present in approximately 51.5% (n\u0026thinsp;=\u0026thinsp;3,266) of the base cohort using medications most often for comorbid hypertension (n\u0026thinsp;=\u0026thinsp;3,290, 51.8%), dementia (n\u0026thinsp;=\u0026thinsp;2,201, 34.7%), or acute infection (n\u0026thinsp;=\u0026thinsp;2,095, 33.0%). The prevalence of the 32 comorbidities in the base cohort are shown in Supplemental Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eThe medications used in the 12-month study period by the base cohort are shown in \u003cb\u003eSupplemental Table\u0026nbsp;3\u003c/b\u003e. The most commonly used medications were those that act on the gastrointestinal system (n\u0026thinsp;=\u0026thinsp;4,381, 69.0%), central nervous system (CNS; n\u0026thinsp;=\u0026thinsp;4,350, 68.5%), and cardiovascular system (n\u0026thinsp;=\u0026thinsp;4,081, 64.3%). The three most commonly used medications that act on the gastrointestinal system were bisacodyl (n\u0026thinsp;=\u0026thinsp;2,999, 47.3%), senna (n\u0026thinsp;=\u0026thinsp;2,811, 44.3%), and lactulose (n\u0026thinsp;=\u0026thinsp;2,595, 40.9%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the base cohort (N\u0026thinsp;=\u0026thinsp;6,346)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,931 (61.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,415 (38.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e860 (13.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,649 (26.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e85\u0026ndash;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,893 (45.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e944 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,290 (51.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDementia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,201 (34.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,095 (33.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,985 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEye disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,799 (28.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,671 (26.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,648 (26.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,431 (22.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFractures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,336 (21.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,051 (16.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e989 (15.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e727 (11.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e682 (10.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e659 (10.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of concurrent medications, (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,786 (43.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e294 (4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e879 (13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,273 (20.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,114 (17.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of classes of concurrent medications, (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,786 (43.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e527 (8.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,354 (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,193 (18.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e486 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescribing sources of medications*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic hospitals only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3062 (86.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate hospitals only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e147 (4.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic and private hospitals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e351 (9.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSD: standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Include only 3,560 residents who were prescribed at least 1 medication.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of PIM use\u003c/h2\u003e \u003cp\u003eAt least one PIM was taken by one-third (n\u0026thinsp;=\u0026thinsp;2,189, 34.5%) of the base cohort, with 65.1% (n\u0026thinsp;=\u0026thinsp;1,425) taking one PIM, 25.5% (n\u0026thinsp;=\u0026thinsp;558) taking two PIMs, and 9.4% (n\u0026thinsp;=\u0026thinsp;206) taking more than two PIMs. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the PIMs that were taken by over 1% of the base cohort. The most frequently used PIMs were chlorpheniramine (n\u0026thinsp;=\u0026thinsp;1,031, 16.2%), lorazepam (n\u0026thinsp;=\u0026thinsp;382, 6.0%), promethazine (n\u0026thinsp;=\u0026thinsp;288, 4.5%), and gliclazide (n\u0026thinsp;=\u0026thinsp;280, 4.4%). A full list of the prevalence of PIM use is presented in \u003cb\u003eSupplemental Table\u0026nbsp;4\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 most frequently administered potentially inappropriate medications in the base cohort (N\u0026thinsp;=\u0026thinsp;6,346)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTherapeutic category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of users\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevalence of PIM use (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChlorpheniramine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-generation antihistamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLorazepam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenzodiazepines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePromethazine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-generation antihistamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGliclazide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSulphonylureas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClonazepam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenzodiazepines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiphenhydramine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-generation antihistamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrihexyphenidyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntiparkinsonian agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydroxyzine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-generation antihistamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZolpidem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonbenzodiazepine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScopolamine (Hyoscine)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGastrointestinal antispasmodics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCyproheptadine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-generation antihistamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between PIM use and hospitalization\u003c/h2\u003e \u003cp\u003eIn the study period, 4,686 members of the base cohort were administered at least one medication, and 2,563 (54.6%) were also hospitalized. The characteristics of those who were and were not hospitalized are presented in \u003cb\u003eSupplement Table\u0026nbsp;5\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eIn the multivariable model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), compared with those who did not use PIMs, those who did use PIMs had higher rates of hospitalization (OR: 1.73, 95% CI: 1.54 to 1.69), and the number of PIMs they used was positively associated with their risk of hospitalization (OR: 2.17, 95% CI: 1.82 to 2.59 for \u0026gt;\u0026thinsp;1 PIMs vs 0). Those with a high comorbidity burden had a greater risk of hospitalization than those without comorbidity (OR: 1.72, 95% CI: 1.45 to 2.06 for \u0026ge;\u0026thinsp;nine comorbidities vs one comorbidity). Compared with those who received zero to four medications, those who received five to nine medications had lower risk of hospitalization (OR: 0.72, 95% CI: 0.60 to 0.86) while those who received ten or more medications was not associated with hospitalization (OR: 1.00, 95% CI 0.87 to 1.14).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with hospitalization risk\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIM use in 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.73 (1.54\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of PIMs in 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56 (1.36\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.17 (1.82\u0026ndash;2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.79 (0.69\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 (0.69\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.76\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 (0.77\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e85\u0026ndash;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22 (1.00-1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.23 (1.02\u0026ndash;1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41 (1.12\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.44 (1.15\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of concurrent medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72 (0.60\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72 (0.61\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.87\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.86\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.16 (0.99\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16 (0.99\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.33 (1.13\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32 (1.12\u0026ndash;1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.72 (1.45\u0026ndash;2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.71 (1.43\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eOR: odds ratio; PIM: potentially inappropriate medication; 95% CI: 95% confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eModel 1: Multivariable logistic regression model with PIM use, sex, age, number of concurrent medications and number of comorbidities as independent variables.\u003c/p\u003e \u003cp\u003eModel 2: Multivariable logistic regression model with number of PIMs, sex, age, number of concurrent medications and number of comorbidities as independent variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eExploratory Analysis: Estimating the Cumulative burden of ADRs in PIMs\u003c/h2\u003e \u003cp\u003eThe risk scores for 15 distinct ADRs among the 2,387 members of the base cohort who had hyper-polypharmacy (concurrent use of \u0026ge;\u0026thinsp;10 medications) were calculated based on the Cumulative Toxicity Tool in Polypharmacy Guidance Realistic Prescribing 2018, and the estimated cumulative burden of each ADR was visualized in the form of a heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The six ADRs with the highest cumulative burdens (individuals with a projected risk score of \u0026ge;\u0026thinsp;5) were falls and fractures (n\u0026thinsp;=\u0026thinsp;497, 20.8%), constipation (n\u0026thinsp;=\u0026thinsp;275, 11.5%), CNS depression (n\u0026thinsp;=\u0026thinsp;5.2%), and cardiovascular (CV) events (n\u0026thinsp;=\u0026thinsp;101, 4.2%). The average projected risk scores were calculated for the 15 ADRs, and the highest risk scores were observed for falls and fractures (3.08), constipation (2.55), CV events (1.87), and CNS depression (1.70).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis large-scaled study was the first to investigate the burden of PIM use and risk of hospitalization among older adults living in RCHEs in Hong Kong. Moreover, this study adopted a more precise and pragmatic classification of PIMs than the 2023 AGS Beers criteria and exploited data on administered medications extracted from the SMMS\u0026reg; database. Therefore, the descriptive findings of this study are reliable and accurately reflect the medications taken by the base cohort. It was found that more than a third (34.5%) of the base cohort took at least one PIM, particularly first-generation antihistamines and benzodiazepines. In addition, the use of a PIM was associated with 1.73 higher odds of hospitalization. Those who took at least two PIMs had 2.17-fold higher odds of hospitalization than those who did not take any PIM. These findings highlight the imminent need to develop local practical and sustainable measures to minimize the use of PIMs in older adults living in RCHEs. Moreover, there is a pressing need to engage pharmacists to review medication utilization among RCHE residents. Such a review may be more feasible if it is to lay focus on those who take the most common PIMs and who are at risk of the highest ADR burden from PIMs rather than include all those who take a PIM.\u003c/p\u003e \u003cp\u003eWithin the study period, about 1 in 3 older adults of the base cohort took a PIM. Similarly, it has been found that 30.3\u0026ndash;38.6% of community-dwelling older adults in Hong Kong have used a PIM.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e We acknowledge that some patient-related factors (e.g., age, sex, and comorbidity burden) are known unmodifiable risk factors for PIM use. For example, the majority of the current study population who took zolpidem and clonazepam received their prescriptions from a psychiatry hospital in Kowloon. This finding echoes with a study by Stuhec that reported high prevalence (25%) of potentially inappropriate antipsychotic use in nursing homes, and the need for collaborative strategies with pharmacists to ensure rational prescription of antipsychotics in older adults.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e However, prescriber-related variables may also account for the high prevalence of PIM use by our cohort. Nevertheless, the prevalence of PIM use in our base cohort is lower than that reported by Zhang et al., i.e., 45.5%, in an investigation of PIM use among older adults visiting GOPCs in Hong Kong public healthcare system. These researchers outlined the underlying factors contributing to PIM use, including the highly subsidized services that led to a heavy patient load in the GOPCs and the absence of mandatory training on geriatric medicine for physicians practicing in the GOPCs.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e We postulate that PIM use by the current study population is lower than that reported by Zhang et al. because our cohort mostly visited specialist outpatient clinics, which may have more well-trained physicians in geriatrics than GOPCs. Our findings reinforce the importance in increasing the competency of the physicians and RCHE staff through continuing professional education. Future work should be focused on collaborating with health administrators of the Hong Kong public healthcare system to adopt computerized decision-support tools to reduce potentially inappropriate prescriptions and the use of PIMs.\u003c/p\u003e \u003cp\u003eConsistent with previous findings\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, this study found that the use of PIMs in older adults at RCHEs was strongly associated with an increased risk of hospitalization, which increased with the number of PIMs used. This finding should be interpreted cautiously because PIM use and hospital admission data were both captured within the same study period. Although the analysis only counted hospital admissions after the start date of any PIM as a \u0026ldquo;case\u0026rdquo;, the cross-sectional design of this study meant that a causal relationship between PIM use and the risk of hospitalization could not be determined. We were also unable to differentiate between planned or unplanned admission due to limitations of the SMMS\u0026reg;. Nevertheless, based on previous studies, it is reasonable to postulate that drug\u0026ndash;drug or drug\u0026ndash;disease interactions and adverse events may be mechanisms by which PIMs can increase the risk of hospitalization.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e In addition, our exploratory analysis used the Cumulative Toxicity Tool in Polypharmacy Guidance Realistic Prescribing\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e to estimate the potential ADR risk associated each PIM. Although this estimation is hypothetical in nature and may not reflect the actual ADRs that the residents experienced, the analysis shows the highest ADR risk score for falls and fractures, which may logically be associated with a higher risk of hospitalization based on evidence from the literature.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e The strong association of PIMs with hospitalization and the \u0026ldquo;dose\u0026ndash;response\u0026rdquo; increase in the risk of hospitalization observed in those of the study population who took at least two PIMs are further evidence of the detrimental effect of PIMs on older adults in RCHEs in Hong Kong.\u003c/p\u003e \u003cp\u003eAnother finding of this study was that compared with those in the study population who took up to four medications, those who took from five to nine medications exhibited a lower risk of hospitalization, despite this number of medications traditionally being classified as polypharmacy. This finding is inconsistent with the findings in a review of previous studies\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e but could be explained by the concept of \u0026ldquo;appropriate polypharmacy.\u0026rdquo;\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e This is a term for medicines prescribed according to best evidence to an individual who has complex conditions or multiple conditions and uses the medicines in an optimized fashion.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Therefore, we posit that in older adults with multiple comorbidities, the appropriateness and necessity of the medications prescribed are significant, in addition to the number of medications prescribed. However, this finding should be interpreted cautiously given that the concept of \u0026ldquo;appropriate polypharmacy\u0026rdquo; still requires validation and supporting evidence from the literature, and that the sample size of older adults who took five to nine medications is small. In summary, the clinical context in which multiple medications are prescribed should be considered to ensure that patients use only medications that are necessary for treating or managing their diseases and, if possible, that these medications are not PIMs.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur findings reinforce the importance of regular medication review and reconciliation for residents in nursing homes. A recent review found that pharmacist-led services significantly reduced the mean number of falls among residents in RCHEs, although they did not uniformly reduce overall mortality and hospitalization rates.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e However, most local RCHEs do not have in-house pharmacists who provide medication reviews for residents. To address this service gap, the recent Primary Healthcare Blueprint released by the Hong Kong government recommended that community geriatric assessment teams regularly visit RCHEs for older adults to provide medical and nursing care to frail residents.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e We also found potentially inappropriate psychiatric medications prescribed to older adults in our study cohort. Several reports have demonstrated that including a clinical pharmacist in the interdisciplinary ward rounds and medication reconciliation reviews could significantly reduce potential drug-related problems in Slovenia\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e; this has eventually led to the first national-level reimbursed medication review program in the primary care settings in Central Europe.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e In Germany, interdisciplinary pharmacist-led medication reviews have effectively led to increased recommendations in dose reductions and temporary or permanent discontinuation of PIMs in older adults with psychiatric conditions.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Similarly, countries such as Singapore and Australia have achieved cost savings and other positive outcomes by engaging community pharmacists from both public and private sectors to conduct regular medication reviews in RCHEs.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e The involvement of pharmacists in a multidisciplinary team is important for promoting the safe use of medications and implementing deprescribing practices in RCHEs.\u003c/p\u003e \u003cp\u003eA key strength of the current study is the use of an electronic medication management system to capture the medications administered to the study population. This approach allowed us to overcome several limitations reported in other studies using claims databases or dispensing records, such as a failure to account for drug adherence, incomplete medication data, and inaccurate coding.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e However, the current study also has several limitations. First, although the Beers Criteria is an internationally recognized criteria to categorize PIMs, the prevalence of PIM use might have been underestimated because as not all categories of the Beers criteria were assessed in the study. For example, PIMs related to indication, renal impairment, and drug-drug interactions were unaddressed because such information is not available in the SMMS\u0026reg;. To illustrate, a study by Kummer et al. has reported that more than a quarter (28%) of older adults living in RCHEs of Croatia were inappropriately prescribed with benzodiazepines higher than recommended geriatric doses and nearly half (48%) were prescribed concomitant interacting medications.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Therefore, the actual rate of PIM use may be even higher than what is reported in this study. Second, the use of the SMMS\u0026reg; database restricted the assessment of medications to prescribed drugs, meaning that over-the-counter medications or supplements that the members of the base cohort might have been taking of their own accord were not assessed. Third, data on certain potential residual confounding factors, such as frailty status, disease severity, and disability, were not available to be included in our analyses. Furthermore, as medical diagnoses data in the Hospital Authority is currently not linked with the SMMS\u0026reg;, our manual approach to coding the diagnoses data may lead to errors in characterizing the comorbidities of the study population. Fourth, as this study leveraged on data collected from the Integrated Old Age Home Medication Management Program (a community service improvement project), there is no prior sample size calculation. However, we reckoned a study population consisting of 6,346 residents from 29 RCHEs may still be reasonably generalizable to the RCHE community in Hong Kong, as well as adequate to estimate the prevalence of PIM use and interpret the significant associations observed between PIM use and hospitalization. As the SMMS\u0026reg; database does not contain information on resident mortality, we were unable to determine the survival status of a subgroup of residents (8.2%) who had been discharged before June 2024 due to death or other reasons. However, these residents comprised a small proportion of the base cohort, and thus it is unlikely that their discharge status significantly impacted the results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAccording to an assessment based on the latest version of the Beers criteria, there was a high burden of PIM use among older adults living in 29 RCHEs in Hong Kong during the study period. In addition, the use of PIMs by these older adults was associated with an increased risk of hospitalization, particularly for those who were taking at least two PIMs and had multiple comorbidities. Effective interventions should be implemented and strengthened in these RCHEs, particularly interventions that focus on educating physicians about PIMs and the use of computer-assisted technology in identifying PIMs. Future studies should examine the causes of PIMs in various settings and devise strategies that may ameliorate PIM-related healthcare burden.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eClinical trial number: Not applicable\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate:\u0026nbsp;Approval was obtained from the Survey and Behavioral Research Ethics (SBRE) Committee of the Chinese University of Hong Kong (reference number: SBRE-19-106). All participating RCHEs provided consent for the use of de-identified data for research purposes. Written informed consent from individual participants was waived due to the following reasons: (1) this study involved de-identified data from the routine users of a medication management system (SMMS\u003csup\u003e\u0026reg;\u003c/sup\u003e), (2) there is minimal risk posted to the patient and concerns with data privacy as the analyzed data was all de-identified and anonymized in the analysis, and (3) it was not practicable to obtain individual consent from all residents who are routine users of the SMMS\u003csup\u003e\u0026reg;\u003c/sup\u003e.\u0026nbsp;The study is conducted in accordance with the ethical considerations and compliance with the principles enunciated in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eConsent for publication:\u0026nbsp;All participating RCHEs provided consent for the publication of aggregated and anonymized (unidentifiable) data for research purposes.\u003c/p\u003e\n\u003cp\u003eAvailability of data and material: The data that support the findings of this study are available on request from the corresponding authors, YTC and SCC. The data are not publicly available due to information that could compromise the privacy of research participants.\u003c/p\u003e\n\u003cp\u003eCompeting interests: All authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding:\u0026nbsp;The implementation and use of the SMMS\u003csup\u003e\u0026reg;\u0026nbsp;\u003c/sup\u003eat the participating RCHEs is funded by\u0026nbsp;the Vera Ruttonjee Desai Charitable Fund,\u0026nbsp;a philanthropic organization, which played no role in investigating, analyzing or interpreting the results of this study.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions:\u003c/p\u003e\n\u003cp\u003eAll authors made substantial contributions to the conception and study design.\u003c/p\u003e\n\u003cp\u003eH.C.C and S.C.C conducted data collection.\u003c/p\u003e\n\u003cp\u003eK.Z and Y.T.C conducted the data analysis. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors interpreted the data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eK.Z and Y.T.C drafted the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors substantively revised it.\u003c/p\u003e\n\u003cp\u003eAll authors have approved the submitted version.\u003c/p\u003e\n\u003cp\u003eAll authors have agreed both to be personally accountable for the author\u0026apos;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: NA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZazzara MB, Palmer K, Vetrano DL, Carf\u0026igrave; A, Onder G. Adverse drug reactions in older adults: a narrative review of the literature. Eur Geriatr Med Jun. 2021;12(3):463\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s41999-021-00481-9\u003c/span\u003e\u003cspan address=\"10.1007/s41999-021-00481-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies EA, O'Mahony MS. Adverse drug reactions in special populations \u0026ndash; the elderly. Br J Clin Pharmacol. 2015;80(4):796\u0026ndash;807. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/bcp.12596\u003c/span\u003e\u003cspan address=\"10.1111/bcp.12596\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMotter FR, Fritzen JS, Hilmer SN, Paniz \u0026Eacute;V, Paniz VMV. Potentially inappropriate medication in the elderly: a systematic review of validated explicit criteria. Eur J Clin Pharmacol Jun. 2018;74(6):679\u0026ndash;700. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00228-018-2446-0\u003c/span\u003e\u003cspan address=\"10.1007/s00228-018-2446-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanel BtAGSBCUE. American Geriatrics Society 2023 updated AGS Beers Criteria\u0026reg; for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jgs.18372\u003c/span\u003e\u003cspan address=\"10.1111/jgs.18372\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian F, Chen Z, Zeng Y, Feng Q, Chen X. Prevalence of Use of Potentially Inappropriate Medications Among Older Adults Worldwide: A Systematic Review and Meta-Analysis. JAMA Netw Open. 2023;6(8):e2326910\u0026ndash;2326910. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamanetworkopen.2023.26910\u003c/span\u003e\u003cspan address=\"10.1001/jamanetworkopen.2023.26910\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorin L, Laroche ML, Texier G, Johnell K. Prevalence of Potentially Inappropriate Medication Use in Older Adults Living in Nursing Homes: A Systematic Review. J Am Med Dir Assoc. Sep 2016;1(9):e8621\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jamda.2016.06.011\u003c/span\u003e\u003cspan address=\"10.1016/j.jamda.2016.06.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpondo D, Eslami S, Visscher S, et al. Inappropriateness of medication prescriptions to elderly patients in the primary care setting: a systematic review. PLoS ONE. 2012;7(8):e43617. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0043617\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0043617\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJokanovic N, Tan EC, Dooley MJ, Kirkpatrick CM, Bell JS. Prevalence and factors associated with polypharmacy in long-term care facilities: a systematic review. J Am Med Dir Assoc. Jun 2015;1(6):e5351\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jamda.2015.03.003\u003c/span\u003e\u003cspan address=\"10.1016/j.jamda.2015.03.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD\u0026iacute;ez R, Cadenas R, Susperregui J, et al. Drug-Related Problems and Polypharmacy in Nursing Home Residents: A Cross-Sectional Study. Int J Environ Res Public Health Apr. 2022;4(7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph19074313\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19074313\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacRae C, Henderson DA, Mercer SW, et al. Excessive polypharmacy and potentially inappropriate prescribing in 147 care homes: a cross-sectional study. BJGP Open. 2021;5(6). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3399/bjgpo.2021.0167\u003c/span\u003e\u003cspan address=\"10.3399/bjgpo.2021.0167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStuhec M. Clinical pharmacist consultant in primary care settings in Slovenia focused on elderly patients on polypharmacy: successful national program from development to reimbursement. Int J Clin Pharm Dec. 2021;43(6):1722\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11096-021-01306-2\u003c/span\u003e\u003cspan address=\"10.1007/s11096-021-01306-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStorms H, Marquet K, Aertgeerts B, Claes N. Prevalence of inappropriate medication use in residential long-term care facilities for the elderly: A systematic review. Eur J Gen Pract Dec. 2017;23(1):69\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13814788.2017.1288211\u003c/span\u003e\u003cspan address=\"10.1080/13814788.2017.1288211\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong J, Marr P, Kwan D, Meiyappan S, Adcock L. Identification of inappropriate medication use in elderly patients with frequent emergency department visits. Can Pharm J (Ott) Jul. 2014;147(4):248\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1715163514536522\u003c/span\u003e\u003cspan address=\"10.1177/1715163514536522\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeck J, Noltemeyer N, Schulze Westhoff M, et al. Adverse drug reactions in geriatric psychiatry\u0026mdash;retrospective cohort study of a 6-year period. Ir J Med Sci. 1971 -;192(6):2917\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11845-023-03300-1\u003c/span\u003e\u003cspan address=\"10.1007/s11845-023-03300-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. 2023/12/01 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChae H-W, Zhao J, Ah Y-M, Choi KH, Lee J-Y. Potentially inappropriate medication use as predictors of hospitalization for residents in nursing home. \u003cem\u003eBMC Geriatrics\u003c/em\u003e. 2023/08/02 2023;23(1):467. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12877-023-04165-w\u003c/span\u003e\u003cspan address=\"10.1186/s12877-023-04165-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong Kong Population Projections 2022\u0026ndash;2046. Census and Statistics Department. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.censtatd.gov.hk/en/data/stat_report/product/B1120015/att/B1120015092023XXXXB01.pdf\u003c/span\u003e\u003cspan address=\"https://www.censtatd.gov.hk/en/data/stat_report/product/B1120015/att/B1120015092023XXXXB01.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCensus and Statistics Department. Hong Kong Special Administrative Region. 2021 Population Census. Thematic Report: Older Persons. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.censtatd.gov.hk/en/data/stat_report/product/B1120118/att/B11201182021XXXXB0100.pdf\u003c/span\u003e\u003cspan address=\"https://www.censtatd.gov.hk/en/data/stat_report/product/B1120118/att/B11201182021XXXXB0100.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegislative Council Panel on Welfare Services. LC Paper No. CB(1)1311/2024(05): Drug Management of Residential Care Homes for the Elderly. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.legco.gov.hk/yr2024/english/panels/ws/papers/ws20241014cb1-1311-5-e.pdf\u003c/span\u003e\u003cspan address=\"https://www.legco.gov.hk/yr2024/english/panels/ws/papers/ws20241014cb1-1311-5-e.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, Wong EL, Wong SY, et al. Prevalence and determinants of potentially inappropriate medication use in Hong Kong older patients: a cross-sectional study. BMJ Open Jul. 2021;22(7):e051527. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2021-051527\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2021-051527\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSo KH, Ting CW, Lee CP, Lam TT, Chiang SC, Cheung YT. Medication Management Service for Old Age Homes in Hong Kong Using Information Technology, Automation Technology, and the Internet of Things: Pre-Post Interventional Study. JMIR Med Inf Feb. 2021;10(2):e24280. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/24280\u003c/span\u003e\u003cspan address=\"10.2196/24280\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eATC/DDD classification (final).(ATC/DDD Classification)(anatomical therapeutic chemical (ATC) classifications and defined daily doses). WHO drug Inform. 2011;25(1):43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHA Drug Formulary. Hospital Authority. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ha.org.hk/hadf/en-us/Updated-HA-Drug-Formulary/Drug-Formulary.html\u003c/span\u003e\u003cspan address=\"https://www.ha.org.hk/hadf/en-us/Updated-HA-Drug-Formulary/Drug-Formulary.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLam DP, Mak CF, Chan SM, Yao RW, Leung SS, You JH. Polypharmacy and inappropriate prescribing in elderly Hong Kong Chinese patients. J Am Geriatr Soc Jan. 2010;58(1):203\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1532-5415.2009.02656.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1532-5415.2009.02656.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBick I, Dowding D. Hospitalization risk factors of older cohorts of home health care patients: A systematic review. Home Health Care Serv Q Jul-Sep. 2019;38(3):111\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/01621424.2019.1616026\u003c/span\u003e\u003cspan address=\"10.1080/01621424.2019.1616026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrabowski DC, Stewart KA, Broderick SM, Coots LA. Predictors of nursing home hospitalization: a review of the literature. Med Care Res Rev Feb. 2008;65(1):3\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1077558707308754\u003c/span\u003e\u003cspan address=\"10.1177/1077558707308754\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang S, Zhang K, Chen Y, Wu C. Prediction models of all-cause mortality among older adults in nursing home setting: A systematic review and meta-analysis. Health Sci Rep Jun. 2023;6(6):e1309. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hsr2.1309\u003c/span\u003e\u003cspan address=\"10.1002/hsr2.1309\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolypharmacy Guidance Realistic Prescribing, 3rd Edition. 2018. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.therapeutics.scot.nhs.uk/wp-content/uploads/2018/04/Polypharmacy-Guidance-2018.pdf\u003c/span\u003e\u003cspan address=\"https://www.therapeutics.scot.nhs.uk/wp-content/uploads/2018/04/Polypharmacy-Guidance-2018.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLam MP, Cheung BM, Wong IC. Beers 2012, and Screening Tool of Older Person's Prescriptions and Screening Tool to Alert doctors to Right Treatment Criteria. J Am Geriatr Soc Jul. 2015;63(7):1471\u0026ndash;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jgs.13555\u003c/span\u003e\u003cspan address=\"10.1111/jgs.13555\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Prevalence of Potentially Inappropriate Prescribing Among Hong Kong Older Adults: A Comparison of the Beers 2003.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStuhec M. Antipsychotic treatment in elderly patients on polypharmacy with schizophrenia. Curr Opin Psychiatry Sep. 2022;1(5):332\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/yco.0000000000000808\u003c/span\u003e\u003cspan address=\"10.1097/yco.0000000000000808\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlbert SM, Colombi A, Hanlon J. Potentially inappropriate medications and risk of hospitalization in retirees: analysis of a US retiree health claims database. Drugs Aging May. 2010;27(5):407\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2165/11315990-000000000-00000\u003c/span\u003e\u003cspan address=\"10.2165/11315990-000000000-00000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLau DT, Kasper JD, Potter DE, Lyles A, Bennett RG. Hospitalization and death associated with potentially inappropriate medication prescriptions among elderly nursing home residents. Arch Intern Med Jan. 2005;10(1):68\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archinte.165.1.68\u003c/span\u003e\u003cspan address=\"10.1001/archinte.165.1.68\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReinhild Haerig T, Krause D, Klaassen-Mielke R, Rudolf H, Trampisch HJ, Thuermann P. Potentially inappropriate medication including drug-drug interaction and the risk of frequent falling, hospital admission, and death in older adults - results of a large cohort study (getABI). Front Pharmacol. 2023;14:1062290. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fphar.2023.1062290\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2023.1062290\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoon A, Jang S, Kim J-H, Jang S. Risk of falls or fall-related injuries associated with potentially inappropriate medication use among older adults with dementia. \u003cem\u003eBMC Geriatrics\u003c/em\u003e. 2024/08/23 2024;24(1):699. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12877-024-05300-x\u003c/span\u003e\u003cspan address=\"10.1186/s12877-024-05300-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerdot S, Bertrand M, Dartigues JF, et al. Inappropriate medication use and risk of falls\u0026ndash;a prospective study in a large community-dwelling elderly cohort. BMC Geriatr Jul. 2009;23:9:30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2318-9-30\u003c/span\u003e\u003cspan address=\"10.1186/1471-2318-9-30\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFried TR, O'Leary J, Towle V, Goldstein MK, Trentalange M, Martin DK. Health outcomes associated with polypharmacy in community-dwelling older adults: a systematic review. J Am Geriatr Soc Dec. 2014;62(12):2261\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jgs.13153\u003c/span\u003e\u003cspan address=\"10.1111/jgs.13153\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCadogan CA, Ryan C, Hughes CM. Appropriate Polypharmacy and Medicine Safety: When Many is not Too Many. Drug Saf Feb. 2016;39(2):109\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40264-015-0378-5\u003c/span\u003e\u003cspan address=\"10.1007/s40264-015-0378-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Medication Safety in Polypharmacy. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/docs/default-source/patient-safety/who-uhc-sds-2019-11-eng.pdf\u003c/span\u003e\u003cspan address=\"https://www.who.int/docs/default-source/patient-safety/who-uhc-sds-2019-11-eng.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHughes C. Appropriate and inappropriate polypharmacy-Choosing the right strategy. Br J Clin Pharmacol Jan. 2021;87(1):84\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bcp.14589\u003c/span\u003e\u003cspan address=\"10.1111/bcp.14589\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SWH, Mak VSL, Tang YW. Pharmacist services in nursing homes: A systematic review and meta-analysis. Br J Clin Pharmacol Dec. 2019;85(12):2668\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bcp.14101\u003c/span\u003e\u003cspan address=\"10.1111/bcp.14101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHealth Bureau. The Government of the Hong Kong Special Administrative Region. Primary Healthcare Blueprint Supplement. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.primaryhealthcare.gov.hk/bp/cms-assets/Primary_Healthcare_Blueprint_Supplement_Perfect_Binding_Eng_291a55714a.pdf\u003c/span\u003e\u003cspan address=\"https://www.primaryhealthcare.gov.hk/bp/cms-assets/Primary_Healthcare_Blueprint_Supplement_Perfect_Binding_Eng_291a55714a.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on November 1, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStuhec M, Tement V. Positive evidence for clinical pharmacist interventions during interdisciplinary rounding at a psychiatric hospital. Sci Rep Jul. 2021;1(1):13641. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-021-92909-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-021-92909-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStuhec M, Batinic B. Clinical pharmacist interventions in the transition of care in a mental health hospital: case reports focused on the medication reconciliation process. Front Psychiatry. 2023;14:1263464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyt.2023.1263464\u003c/span\u003e\u003cspan address=\"10.3389/fpsyt.2023.1263464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchr\u0026ouml;der S, Schulze Westhoff M, Pfister T, et al. Characteristics of clinical-pharmacological recommendations in psychiatry in Germany. Int J Psychiatry Med. May 2024;59(3):393\u0026ndash;405. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/00912174231177230\u003c/span\u003e\u003cspan address=\"10.1177/00912174231177230\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaider I, Kosari S, Naunton M, et al. The role of on-site pharmacist in residential aged care facilities: findings from the PiRACF study. J Pharm Policy Pract. 2023;2023/07/03(1):82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40545-023-00587-4\u003c/span\u003e\u003cspan address=\"10.1186/s40545-023-00587-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChia HS, Ho JA, Lim BD. Pharmacist review and its impact on Singapore nursing homes. Singap Med J Sep. 2015;56(9):493\u0026ndash;501. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11622/smedj.2015133\u003c/span\u003e\u003cspan address=\"10.11622/smedj.2015133\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTyree PT, Lind BK, Lafferty WE. Challenges of using medical insurance claims data for utilization analysis. Am J Med Qual Jul-Aug. 2006;21(4):269\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1062860606288774\u003c/span\u003e\u003cspan address=\"10.1177/1062860606288774\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRasmussen L, Wettermark B, Steinke D, Potteg\u0026aring;rd A. Core concepts in pharmacoepidemiology: Measures of drug utilization based on individual-level drug dispensing data. Pharmacoepidemiol Drug Saf Oct. 2022;31(10):1015\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/pds.5490\u003c/span\u003e\u003cspan address=\"10.1002/pds.5490\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKummer I, Reissigov\u0026aacute; J, Lukačišinov\u0026aacute; A, et al. Polypharmacy and potentially inappropriate prescribing of benzodiazepines in older nursing home residents. Ann Med Dec. 2024;56(1):2357232. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/07853890.2024.2357232\u003c/span\u003e\u003cspan address=\"10.1080/07853890.2024.2357232\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5733476/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5733476/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eMany older adults living in Resident Care Homes for the Elderly (RCHEs) are at risk of polypharmacy and the use of potentially inappropriate medication (PIM). Few studies have evaluated the prevalence and consequences of PIM use among older adults living in RCHEs. The objectives of this study are (1) to evaluate the prevalence of PIM use in 29 RCHEs in Hong Kong, and (2) to investigate the association between PIM use and hospitalization in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis is a prospective, observational, cohort study which utilized final-administered medication data from RCHEs that participated in a medication management program. Data on the medications administered to all residents living in the participating RCHEs were extracted from the SafeMed Medication Management System (SMMS\u0026reg;), which is a purpose-built Information Technology supporting the entire medication management process at RCHEs. The outcome of interest is the 12-month period prevalence of PIM use (January 1 to December 31, 2023), which was obtained by comparing the medication data with the 2023 Beers criteria. Hospital admissions during the study period were extracted from the SMMS\u0026reg;.Multivariable logistic regression was conducted to investigate the association between PIM use and hospital admissions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe included 6,346 residents (age 82.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6 years; female 61.9%). The average number of current medications was 6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4. Over half (51.5%) of residents had polypharmacy (\u0026ge;\u0026thinsp;5 medications). The 12-month period prevalence of PIM use was 34.5%. Among the residents with PIMs, 65.1%, 25.5% and 9.4% used 1, 2 and \u0026gt;\u0026thinsp;2 PIMs, respectively. Residents with PIMs were associated with higher rates of hospitalization (Odds Ratio [OR] 1.73, 95% confidence interval [CI] 1.54 to 1.69), after adjusting for age, sex and comorbidities. The number of PIMs was significantly associated with higher risk of hospitalization (OR: 2.17, 95% CI: 1.82 to 2.59 for \u0026gt;\u0026thinsp;1 PIMs vs 0).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe use of PIM was observed in one-third of older adults living in RCHEs, and was associated with an increased risk of hospitalization. Our findings highlighted the urgent need for strategies to improve clinicians\u0026rsquo; awareness of PIMs and their adverse impact, and to implement pharmacist-led medication reviews in RCHEs.\u003c/p\u003e","manuscriptTitle":"Analysis of Medication Management System Data to Determine Potentially Inappropriate Medication Use and Hospitalization Among Older Adults Living in Residential Care Homes for the Elderly Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 12:33:26","doi":"10.21203/rs.3.rs-5733476/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-25T09:03:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T08:33:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132559747102864383048452300186991721447","date":"2025-04-22T07:51:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-18T08:48:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209850249397799927308225193511364783979","date":"2025-04-18T08:45:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203344052128630247710138527541989273844","date":"2025-04-16T14:19:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-16T14:11:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-16T09:36:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-04-11T13:11:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2bd0b8fa-91a4-48ca-860d-a6307cc3055c","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:05:53+00:00","versionOfRecord":{"articleIdentity":"rs-5733476","link":"https://doi.org/10.1186/s12877-025-05989-4","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2025-05-06 15:56:53","publishedOnDateReadable":"May 6th, 2025"},"versionCreatedAt":"2025-04-17 12:33:26","video":"","vorDoi":"10.1186/s12877-025-05989-4","vorDoiUrl":"https://doi.org/10.1186/s12877-025-05989-4","workflowStages":[]},"version":"v1","identity":"rs-5733476","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5733476","identity":"rs-5733476","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}