Drugs Aging DOI 10.1007/s40266-014-0185-1
ORIGINAL RESEARCH ARTICLE
Polypharmacy and Medication Regimen Complexity as Factors Associated with Hospital Discharge Destination Among Older People: A Prospective Cohort Study Barbara Caecilia Wimmer • Elsa Dent • Renuka Visvanathan • Michael David Wiese • Kristina Johnell • Ian Chapman • J. Simon Bell
Ó Springer International Publishing Switzerland 2014
Abstract Background Older people often take multiple medications. It is a policy priority to facilitate older people to stay at home longer. Three-quarters of nursing home placements in the US are preceded by a hospitalization. Objective To investigate the association between polypharmacy and medication regimen complexity with hospital discharge destination among older people. Methods This prospective cohort study comprised patients aged C70 years consecutively admitted to the Geriatric Evaluation and Management unit at a tertiary hospital in Adelaide, Australia, between October 2010 and December B. C. Wimmer M. D. Wiese J. S. Bell Sansom Institute, School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA, Australia B. C. Wimmer (&) J. S. Bell Faculty of Pharmacy and Pharmaceutical Sciences, Centre for Medicine Use and Safety, Monash University, 381 Royal Parade, Parkville, Melbourne, VIC 3052, Australia e-mail: [email protected] E. Dent R. Visvanathan I. Chapman Discipline of Medicine, University of Adelaide, Adelaide, SA, Australia
2011. Medication regimen complexity at discharge was calculated using the 65-item validated Medication Regimen Complexity Index (MRCI). Unadjusted and adjusted relative risks (RRs) with 95 % confidence intervals (CIs) were calculated for medication-related factors associated with discharge directly to home versus non-community settings (rehabilitation, transition care, and residential aged care). Results From 163 eligible patients, 87 were discharged directly to home (mean age 84.6 years, standard deviation [SD] 6.9; mean MRCI 26.1, SD 9.7), while 76 were discharged to non-community settings (mean age 85.8 years, SD 5.8; mean MRCI 29.9, SD 13.2). After adjusting for age, sex, comorbidity, and activities of daily living, having a high medication regimen complexity (MRCI [35) was inversely associated with discharge directly to home (RR 0.39; 95 % CI 0.20–0.73), whereas polypharmacy (C9 medications) was not significantly associated with discharge directly to home (RR 0.97; 95 % CI 0.53–1.58). Conclusion Having high medication regimen complexity was inversely associated with discharge directly to home, while polypharmacy was not associated with discharge destination.
E. Dent Discipline of Public Health, University of Adelaide, Adelaide, SA, Australia
Key Points
R. Visvanathan Aged and Extended Care Services, The Queen Elizabeth Hospital and the Adelaide Geriatrics Training and Research with Aged Care (GTRAC) Centre, University of Adelaide, Adelaide, SA, Australia
A high medication regimen complexity in older people discharged from a Geriatric Evaluation and Management unit was inversely associated with discharge directly to home whereas polypharmacy was not.
K. Johnell Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
Simplifying medication regimens in older people discharged from hospital may be beneficial.
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1 Introduction Facilitating older people to stay at home longer is a policy priority, and interventions to support discharge to home from hospital should be a research priority [1, 2]. The National Hospital Discharge Survey in the US reported that 5 million of 32 million non-newborn hospital discharges in 2010 were to short- or long-term care institutions [3]. It is common for patients to be discharged to another institution such as a nursing home following hospitalization. Three-quarters of nursing home placements in the US are directly preceded by a hospitalization, with discharge to a skilled nursing facility being strongly predictive of subsequent long-term care placement [4]. The percentage of patients aged 65 years and older discharged from hospital to a nursing home, residential home, or hospice doubled in the UK between 1996 and 1997, and 2001 and 2002 [5]. In Australia, 14 % of females and 10 % of males aged C85 years were discharged to residential aged care in 2004–2005 [6]. Factors associated with placement in a nursing home include dementia, decline in activities of daily living (ADLs), older age, living alone, and female sex [4, 7]. Hospital-based Geriatric Evaluation and Management (GEM) units are designed to provide multidisciplinary care following a short acute care episode so that older people can resume living independently in the community [8]. However, hospital discharge to non-community settings from these units still occur as discharge destination and can be influenced by factors such as a person’s physical condition and the availability of social and environmental support [9]. GEM units represent a potentially important location to optimize patients’ medication regimens. A person’s medication regimen has not traditionally been recognized as having an impact on hospital discharge destination. To our knowledge, no previous studies have investigated whether medication regimen complexity is associated with discharge directly to home or to noncommunity settings. Medication-related problems are a leading cause of preventable hospital admission [10]. Polypharmacy is commonly defined as use of five or more medications in general adult populations [11], although the definition of nine or more medications is often used in long-term care facilities [12, 13]. However, polypharmacy is only one component of medication regimen complexity [14]. Other factors that contribute to regimen complexity include the number of daily doses, types of different dose forms, and special instructions for medication use. These additional factors may be important in determining whether or not a person can manage their medication regimen at home. Studying characteristics of discharge medication regimens is important because medication regimens may
change substantially during hospitalization [15]. Reducing medication regimen complexity may have a positive impact on post-discharge adherence and may reduce adverse drug events and thereby improve patients’ quality of life [16]. We hypothesized that there would be an inverse association between both polypharmacy and medication regimen complexity with discharge directly to home. The objective of the study was to investigate the association between polypharmacy and medication regimen complexity with hospital discharge destination among older people.
2 Methods 2.1 Design and Context This was a prospective cohort study of patients consecutively admitted to the GEM unit at The Queen Elizabeth Hospital (TQEH), Adelaide, Australia. TQEH is a 327-bed tertiary-referral hospital located in the western suburbs of metropolitan Adelaide, Australia. The GEM unit provides comprehensive geriatric assessment, multidisciplinary management and rehabilitation to maximize the likelihood that patients can return to living independently in the community [17]. It comprises 20 beds, and during the study period one full-time equivalent clinical pharmacist worked at the GEM unit. It is an aim of the service to return responsibility for care to the primary care provider postdischarge, therefore outpatient follow-up is not common. 2.2 Data Collection All patients aged C70 years admitted to the GEM unit between 22 October 2010 and 23 December 2011 were invited to participate in the study by a member of the research team (n = 427). Potential participants were excluded if a proxy was required but unavailable [e.g. in case of dementia, unresolved delirium within 72 h (n = 77), or language barriers (n = 67)], if their treating clinician recommended exclusion [e.g. due to elder abuse, physical aggression, or due to being medically unwell (n = 33)], they were deemed infectious (n = 11), missed by the researcher (n = 4), if they declined to participate (n = 63), were transferred to another hospital (n = 2), to palliative care service (n = 1) or died during hospital stay (n = 6). This study investigated discharge destination of 163 participants discharged from the GEM unit (Fig. 1). 2.3 Main Outcome Measure Data concerning discharge destination were extracted from Open Architecture Clinical Information System (OACIS,
Polypharmacy, Medication Regimen Complexity and Hospital Discharge Destination Fig.1 Flow of participants through the study
166 eligible participants
Transfer to - another hospital (n=2) - palliative care service (n=1) 163 participants included in the study
Discharge directly to home (n=87)
Discharge to non-community settings (n=76)
Low level or high level residential aged care (n=31)
South Australia Health Department, 2009). Patients were considered to have been ‘discharged directly to home’ if they returned to their own home immediately following hospitalization either with or without new community services such as ‘Meals on Wheels’, domiciliary care, or home and community care services. Patients were considered ‘discharged to non-community settings’ if they were discharged to either high- or low-level residential aged care, transition care (i.e. restorative care in a residential aged care facility), or off-site inpatient rehabilitation. 2.4 Medication Assessment Each patient’s medication regimen was assessed at hospital discharge. Discharge medication data were extracted directly from the separation summary prepared predominantly by medical doctors and recorded in OACIS. We included prescription, non-prescription, and complementary and alternative medications (CAMs) when computing polypharmacy and medication regimen complexity. This was because all medications taken by a patient can contribute to the complexity of their medication regimen. At the GEM unit, discharge medication lists are routinely provided to both the patient and their primary care physician to inform about ongoing prescribing. All medication data were extracted by the same pharmacist researcher. Medications were categorized according to the Anatomical Therapeutic Chemical (ATC) Classification System recommended by the World Health Organization [18]. Polypharmacy was defined as use of nine or more medications on a regular or as-needed basis. This definition was consistent with that recommended for use in long-term facilities [12] and used in previous research [13]. It was
Transition care (i.e. restorative care in a residential aged care facility, n=16)
Off-site inpatient rehabilitation (n=29)
impractical to use the more traditional cutoff of five or more medications because almost all participants (n = 155) took five or more medications. Each patient’s regimen complexity was computed using the 65-item validated Medication Regimen Complexity Index (MRCI) developed by George et al. [19]. In short, the Index provides scores for dosage forms, dosing frequencies, and additional directions. The MRCI has both convergent (Spearman’s rho = 0.9; p \ 0.0001) and discriminate validity (Spearman’s rho = 0.34; p = 0.1 for age and p = 0.487 for sex) [19]. Higher MRCI scores reflect more complex medication regimens. Prescription and non-prescription medications, nutritional supplements, health products, dermatologicals and short-term medications (e.g. antibiotics) were all considered when computing the MRCI. The inclusion of non-prescription medications was consistent with other recent studies utilizing the MRCI [20, 21]. In the absence of recognized cutoffs for MRCI, we defined a high MRCI as [35 because this represented the highest quartile of regimen complexity in our cohort. 2.5 Covariates Comorbidity was calculated for each patient using the Charlson’s Comorbidity Index, a weighted index that is suitable for use with medical records [22, 23]. ADLs were assessed using the 10-item Barthel’s ADL index, a performance scale giving a maximum score of 100 [24]. 2.6 Statistical Analyses Data were tested for normality using the Kolmogorov– Smirnov and Shapiro–Wilk test. Normally distributed
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characteristics were summarized using means with standard deviations. Non-normally distributed variables (Barthel’s ADL index, Charlson’s Comorbidity Index) were reported using medians and ranges. Logistic regression analyses were used to compute unadjusted and adjusted odds ratios (ORs) with 95 % confidence intervals (CIs) for medication-related factors associated with discharge destination. The ORs were converted to relative risks (RRs) using the method described by Zhang and Fai because ORs are a poor estimate of the RRs when the prevalence of outcome is [10 % [25]. Two logistic regression models were computed. The first model investigated the association between polypharmacy and discharge destination and the second model investigated the association between high regimen complexity (MRCI [35) and discharge destination. Variables that were significantly associated with discharge destination in the unadjusted analyses (defined as p \ 0.1), or those deemed clinically relevant on the basis of previous research [9, 26], were included in the multivariate models. The same covariates were used in each regression model. Age, ADLs and comorbidities were analyzed as continuous variables, whereas sex was analyzed as a dichotomized variable. Three sets of sensitivity analyses were also performed. The first sensitivity analyses excluded medications that were prescribed for a short duration (e.g. antibiotics) when calculating MRCI. The second sensitivity analyses adjusted the models investigating MRCI using the number of prescribed medications. The third sensitivity analyses investigated polypharmacy and MRCI as continuous rather than categorical variables. In the third sensitivity analyses,
MRCI was analyzed as a continuous variable in 10-unit steps. Data were analyzed using the Statistical Package for the Social Sciences (SPSS), version 21 (IBM Corporation, Armonk, NY, USA). A p-value of \0.05 was considered statistically significant. 2.7 Ethical Considerations All potential participants were provided with written information about the study. Written informed consent to participate was obtained from all participants themselves or their health proxy. The study was approved by the Human Research Ethics Committees at TQEH and the University of South Australia.
3 Results Patients were mostly female (72.4 %; n = 118) and the mean age was 85.2 ± 6.4 years (range 71–101 years). The median length of stay of eligible patients was 12 days. The most prevalent medications were calcium (76.7 % of participants), antithrombotic agents, including aspirin (65.0 %), laxatives (59.5 %), and paracetamol (58.9 %). The most prevalent dose forms were oral (98.2 % of participants), topical applications (33.7 %), and eye drops (22.7 %). The most prevalent diagnoses documented in the separation summary were cardiovascular disease (82.2 %), gastrointestinal disorders (47.2 %), and arthritis (36.8 %) [Table 1]. The study cohort comprised 163 eligible patients, of whom 87 (53.4 %) were discharged directly to home
Table 1 Characteristics of the cohort Age [years; mean (± SD)]
Total cohort (n = 163)
DD directly to home (n = 87)
DD non-community setting (n = 76)
85.2 (± 6.4)
84.6 (± 6.9)
85.8 (± 5.8)
Male sex [n (%)]
45 (27.6)
28 (32.2)
17 (22.4)
MRCI [35 [n (%)]
40 (24.5)
13 (14.9)
27 (35.5)
Polypharmacy C9 medications (%)
98 (60.1)
53 (60.9)
45 (59.2)
Barthel’s ADL index [median (range)]
67.3 (8–100)
73.0 (21–100)
60.7 (8–100)
Charlson’s Comorbidity Index [median (range)]
2.93 (0–10)
2.85 (0–10)
3.03 (0–9)
134 (82.2)
71 (81.6)
63 (82.9)
GI disorders
77 (47.2)
48 (55.2)
29 (38.2)
Arthritis
60 (36.8)
29 (33.3)
31 (40.8)
Diabetes UTI/urological disorders
54 (33.1) 46 (28.8)
32 (36.8) 24 (27.6)
22 (28.9) 22 (28.9)
Osteoporosis
45 (27.6)
23 (26.4)
22 (28.9)
Airways disease
35 (21.5)
20 (23.0)
15 (19.7)
Cancer
34 (20.9)
17 (19.5)
17 (22.4)
Renal impairment/disease
34 (20.9)
15 (17.2)
19 (25.0)
Dementia
34 (20.9)
14 (16.1)
20 (26.3)
Documented diagnoses [n (%)] CVD
ADL activities of daily living, CVD cardiovascular disease, DD discharge destination, GI gastrointestinal, MRCI Medication Regimen Complexity Index, SD standard deviation, UTI urinary tract infection
Polypharmacy, Medication Regimen Complexity and Hospital Discharge Destination Table 2 Unadjusted and adjusted relative risks for the association between polypharmacy and medication regimen complexity (MRCI [35) with discharge directly to home Unadjusted RR (95 % CI)
Adjusteda RR (95 % CI)
Polypharmacy C9 medications
1.05 (0.64–1.59)
0.97 (0.53–1.58)
Age
0.98 (0.94–1.01)
0.99 (0.95–1.03)
Male sex
1.41 (0.86–2.07)
1.45 (0.79–2.34)
Charlson’s Comorbidity Index
0.97 (0.87–1.08)
0.96 (0.84–1.09)
Barthel’s ADL
1.03 (1.01–1.04)
1.03 (1.02–1.05)
High MRCI [35
0.39 (0.19–0.74)
0.39 (0.20–0.73)
Age
0.98 (0.94–1.01)
0.98 (0.94–1.02)
Male sex
1.41 (0.86–2.07)
1.15 (0.71–1.57)
Charlson’s Comorbidity Index
0.97 (0.87–1.08)
0.99 (0.91–1.09)
Barthel’s ADL
1.03 (1.01–1.04)
1.02 (1.01–1.03)
ADLs activities of daily living, CI confidence interval, MRCI Medication Regimen Complexity Index, RR relative risk a
Adjusted for age, Barthel’s ADL, Charlson’s comorbidity index, and sex
(Fig. 1). Of the 76 people discharged to non-community settings, 74 were admitted directly from home. After adjusting for age, sex, comorbidity, and ADLs, polypharmacy was not associated with discharge destination (RR 0.97; 95 % CI 0.53–1.58) [Table 2]. After adjusting for age, sex, comorbidity, and ADLs, there was an inverse association between having a high medication regimen complexity and discharge directly to home (RR 0.39; 95 % CI 0.20–0.73). In the first sensitivity analyses, the RR for discharge directly to home was unchanged when medications prescribed for a short duration only were excluded when calculating the MRCI (RR 0.36; 95 % CI 0.17–0.72). In the second sensitivity analyses, the association between high MRCI and discharge destination was unchanged when the model was adjusted for the number of medications in addition to age, sex, comorbidities, and ADLs (RR 0.28; 95 % CI 0.10–0.69). In the third sensitivity analyses, there was no association between polypharmacy and discharge directly to home (RR 0.96; 95 % CI 0.91–1.02) when polypharmacy was analyzed as a continuous variable. When MRCI was analyzed as a continuous variable in 10-unit steps, there was an inverse association with discharge directly to home in adjusted analyses (RR 0.81; 95 % CI 0.65–0.98).
4 Discussion The main finding of this study was that medication regimen complexity was inversely associated with discharge directly to home. Participants with a high medication
regimen complexity were less likely to be discharged directly to home than those without a high medication regimen complexity. Polypharmacy, which is often used as a surrogate for inappropriate medication use [27, 28], was not associated with discharge destination. Our results suggest that medication regimen complexity may be an under-recognized factor associated with discharge destination from geriatric units. A recent systematic review on factors associated with institutionalization did not list specific medications or the complexity of medication regimens as a factor [26]. Factors associated with institutionalization included older age, dementia, cognitive or functional impairment, low self-rated health, and a high number of prescriptions [26]. A qualitative study conducted in New Zealand concluded that the reasons for admission to non-community settings were multifactorial, and included physical condition and social/community support [9]. However, in the study mentioned above, medications were not mentioned as contributing to institutionalization. Previous studies have suggested medication regimen complexity is associated with lower medication adherence [14], hospital readmission [29], and lower quality of life [30]. To our knowledge this is the first study that has reported the association between medication regimen complexity and hospital discharge destination. The possible reasons for association between regimen complexity and discharge destination are multifactorial. During periods of hospitalization, medication regimens are often modified [31]. The number of prescribed medications and regimen complexity may even increase [32–35]. This could contribute to people who are unable to manage their medication regimen at home being discharged to a noncommunity setting. Highly complex medication regimens often comprise a range of dose forms and formulations [36]. Handling dose administration aids (DAAs) or blister packs, opening child-resistant bottles, and splitting tablets requires a level of physical dexterity [37]. Visual impairment can lead to an inability to distinguish colors of tablets or capsules [37]. Clinicians may have considered all these factors when determining discharge destination. Medication regimen complexity might consciously or unconsciously influence prescribing behavior. Moreover, clinicians’ decisions to prescribe complex medication regimens may have been impacted by their perception of medication support available to the patient. Clinical implications of our findings include the potential importance of reducing complexity where possible. Complex regimens include those with a combination of different dose forms (e.g. metered dose inhalers for asthma/ chronic obstructive pulmonary disease, transdermal analgesics, subcutaneous insulin), dose frequencies, and additional directions (e.g. weekly or monthly oral bisphosphonates). Potential strategies to reduce medication
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regimen complexity include reducing the need for multiple daily dosing by prescribing sustained-release formations, avoiding the need for tablet splitting by prescribing a lower-strength tablet (e.g. a low-dose tablet rather than half a full-strength tablet), and standardizing dose timing (e.g. suggesting all once-daily tablets and capsules be taken at the same time of day if possible) [38]. The MRCI may be suitable for inclusion in prescribing and dispensing software as a prompt for clinicians to minimize regimen complexity, although the suitability of the MRCI for this purpose has not yet been demonstrated. Unlike medication regimen complexity, polypharmacy was not associated with discharge destination. This highlights the importance of considering dose forms and formulations, dose timing, and special instructions for medication use. Medication regimen complexity may be more useful than polypharmacy for predicting discharge destination. This has important implications because polypharmacy is often used by clinicians and policy makers to help identify the need for medication review [39]. One previous study reported that polypharmacy was associated with care home admission [40]. However, the authors of this study defined polypharmacy according to the use of potentially inappropriate medications rather than the number of medications, which means this finding is not comparable with our results. Nevertheless, use of multiple medications has been associated with a range of other adverse events, including length of hospital stay, mortality, and hospital readmission [27, 32, 41]. Further longitudinal research is needed to investigate whether MRCI predicts mortality or rehospitalization. 4.1 Strengths and Limitations As with all observational studies, there is the possibility of confounding by indication and disease severity. Medication regimen complexity may reflect patients’ overall health condition because people who are sicker, less independent, or otherwise in need of institutionalization may be prescribed more complex regimens. However, we accounted for this by adjusting our logistic regression models for age, sex, ADLs, and comorbidities. Strengths of this study include the medication data being extracted by an experienced pharmacist researcher in order to minimize the likelihood of error [42]. Validated scales were used to assess the cohort regarding comorbidities [23], ADLs [24], and medication regimen complexity [19]. Patients discharged from the GEM unit were generally provided with 2 weeks’ supply of their medications in DAAs regardless of their discharge destination. It was a limitation of the study that information was not available on the actual long-term use or availability of DAAs
post-discharge [43]. In Australia, DAAs are widely available through community pharmacies for both people living at home and in residential aged care facilities. This means that availability and use of DAAs were unlikely to have impacted the results. Study participants were discharged from a single GEM unit which might limit the generalizability. However, the MRCI scores, sex distribution, and Charlson’s Comorbidity Index were similar to those reported in previous research [20]. This suggests that the study sample was similar to samples included in earlier research studies. Another limitation was the relatively small sample size of 163 people, and this restricted the number of adjustment variables in the multivariate models. We did not analyze change in polypharmacy or regimen complexity during hospitalization or whether polypharmacy or regimen complexity was associated with other hospital discharge outcomes. It is possible that clinicians had already attempted to simplify patients’ medication regimens during their inpatient stay. Moreover, we did not investigate whether living alone, housing quality, or access to a paid or unpaid caregiver post-discharge impacted patients’ discharge destination. We did not assess whether each patient’s pre-admission level of home support was sufficient for the patient to resume living independently in the community given that the required level of support may have changed. Nevertheless, patients were admitted to the GEM unit with a view to them being able to resume living independently in the community. An additional potential limitation was the reliance on patients’ hospital medical records since these are often incomplete [44]. However, data utilized in the study were the same data forwarded to the patients’ primary care physicians for the purpose of medical decision making and repeat prescribing post-discharge. A prospective intervention study is required to determine whether simplification of regimens leads to a higher percentage of patients being discharged directly to home.
5 Conclusion High medication regimen complexity was inversely associated with discharge directly to home in older people, whereas polypharmacy was not. While a controlled intervention study is needed to determine whether reducing medication regimen complexity would permit a greater proportion of patients to be discharged directly to home, our findings highlight the potential importance of simplifying medication regimens in older people discharged from hospital. This finding is of particular relevance because several previous studies have reported an increase in polypharmacy when patients are admitted to hospital.
Polypharmacy, Medication Regimen Complexity and Hospital Discharge Destination Acknowledgments No external sources of funding were used for this study. Barbara C. Wimmer received an International President’s Scholarship from the University of South Australia to undertake the research reported in this manuscript. Barbara C. Wimmer, Elsa Dent, Renuka Visvanathan, Michael D. Wiese, Kristina Johnell, Ian Champan, and J. Simon Bell have no conflicts of interest that are directly relevant to the content of this study.
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43. Bell JS, Johnell K, Wimmer BC, et al. Multidose drug dispensing and optimising drug use in older people. Age Ageing. 2013;42(5):556–8. 44. Lau HS, Florax C, Porsius AJ, et al. The completeness of medication histories in hospital medical records of patients admitted to general internal medicine wards. Br J Clin Pharmacol. 2000;49(6):597–603.
ORIGINAL RESEARCH ARTICLE
Polypharmacy and Medication Regimen Complexity as Factors Associated with Hospital Discharge Destination Among Older People: A Prospective Cohort Study Barbara Caecilia Wimmer • Elsa Dent • Renuka Visvanathan • Michael David Wiese • Kristina Johnell • Ian Chapman • J. Simon Bell
Ó Springer International Publishing Switzerland 2014
Abstract Background Older people often take multiple medications. It is a policy priority to facilitate older people to stay at home longer. Three-quarters of nursing home placements in the US are preceded by a hospitalization. Objective To investigate the association between polypharmacy and medication regimen complexity with hospital discharge destination among older people. Methods This prospective cohort study comprised patients aged C70 years consecutively admitted to the Geriatric Evaluation and Management unit at a tertiary hospital in Adelaide, Australia, between October 2010 and December B. C. Wimmer M. D. Wiese J. S. Bell Sansom Institute, School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA, Australia B. C. Wimmer (&) J. S. Bell Faculty of Pharmacy and Pharmaceutical Sciences, Centre for Medicine Use and Safety, Monash University, 381 Royal Parade, Parkville, Melbourne, VIC 3052, Australia e-mail: [email protected] E. Dent R. Visvanathan I. Chapman Discipline of Medicine, University of Adelaide, Adelaide, SA, Australia
2011. Medication regimen complexity at discharge was calculated using the 65-item validated Medication Regimen Complexity Index (MRCI). Unadjusted and adjusted relative risks (RRs) with 95 % confidence intervals (CIs) were calculated for medication-related factors associated with discharge directly to home versus non-community settings (rehabilitation, transition care, and residential aged care). Results From 163 eligible patients, 87 were discharged directly to home (mean age 84.6 years, standard deviation [SD] 6.9; mean MRCI 26.1, SD 9.7), while 76 were discharged to non-community settings (mean age 85.8 years, SD 5.8; mean MRCI 29.9, SD 13.2). After adjusting for age, sex, comorbidity, and activities of daily living, having a high medication regimen complexity (MRCI [35) was inversely associated with discharge directly to home (RR 0.39; 95 % CI 0.20–0.73), whereas polypharmacy (C9 medications) was not significantly associated with discharge directly to home (RR 0.97; 95 % CI 0.53–1.58). Conclusion Having high medication regimen complexity was inversely associated with discharge directly to home, while polypharmacy was not associated with discharge destination.
E. Dent Discipline of Public Health, University of Adelaide, Adelaide, SA, Australia
Key Points
R. Visvanathan Aged and Extended Care Services, The Queen Elizabeth Hospital and the Adelaide Geriatrics Training and Research with Aged Care (GTRAC) Centre, University of Adelaide, Adelaide, SA, Australia
A high medication regimen complexity in older people discharged from a Geriatric Evaluation and Management unit was inversely associated with discharge directly to home whereas polypharmacy was not.
K. Johnell Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
Simplifying medication regimens in older people discharged from hospital may be beneficial.
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1 Introduction Facilitating older people to stay at home longer is a policy priority, and interventions to support discharge to home from hospital should be a research priority [1, 2]. The National Hospital Discharge Survey in the US reported that 5 million of 32 million non-newborn hospital discharges in 2010 were to short- or long-term care institutions [3]. It is common for patients to be discharged to another institution such as a nursing home following hospitalization. Three-quarters of nursing home placements in the US are directly preceded by a hospitalization, with discharge to a skilled nursing facility being strongly predictive of subsequent long-term care placement [4]. The percentage of patients aged 65 years and older discharged from hospital to a nursing home, residential home, or hospice doubled in the UK between 1996 and 1997, and 2001 and 2002 [5]. In Australia, 14 % of females and 10 % of males aged C85 years were discharged to residential aged care in 2004–2005 [6]. Factors associated with placement in a nursing home include dementia, decline in activities of daily living (ADLs), older age, living alone, and female sex [4, 7]. Hospital-based Geriatric Evaluation and Management (GEM) units are designed to provide multidisciplinary care following a short acute care episode so that older people can resume living independently in the community [8]. However, hospital discharge to non-community settings from these units still occur as discharge destination and can be influenced by factors such as a person’s physical condition and the availability of social and environmental support [9]. GEM units represent a potentially important location to optimize patients’ medication regimens. A person’s medication regimen has not traditionally been recognized as having an impact on hospital discharge destination. To our knowledge, no previous studies have investigated whether medication regimen complexity is associated with discharge directly to home or to noncommunity settings. Medication-related problems are a leading cause of preventable hospital admission [10]. Polypharmacy is commonly defined as use of five or more medications in general adult populations [11], although the definition of nine or more medications is often used in long-term care facilities [12, 13]. However, polypharmacy is only one component of medication regimen complexity [14]. Other factors that contribute to regimen complexity include the number of daily doses, types of different dose forms, and special instructions for medication use. These additional factors may be important in determining whether or not a person can manage their medication regimen at home. Studying characteristics of discharge medication regimens is important because medication regimens may
change substantially during hospitalization [15]. Reducing medication regimen complexity may have a positive impact on post-discharge adherence and may reduce adverse drug events and thereby improve patients’ quality of life [16]. We hypothesized that there would be an inverse association between both polypharmacy and medication regimen complexity with discharge directly to home. The objective of the study was to investigate the association between polypharmacy and medication regimen complexity with hospital discharge destination among older people.
2 Methods 2.1 Design and Context This was a prospective cohort study of patients consecutively admitted to the GEM unit at The Queen Elizabeth Hospital (TQEH), Adelaide, Australia. TQEH is a 327-bed tertiary-referral hospital located in the western suburbs of metropolitan Adelaide, Australia. The GEM unit provides comprehensive geriatric assessment, multidisciplinary management and rehabilitation to maximize the likelihood that patients can return to living independently in the community [17]. It comprises 20 beds, and during the study period one full-time equivalent clinical pharmacist worked at the GEM unit. It is an aim of the service to return responsibility for care to the primary care provider postdischarge, therefore outpatient follow-up is not common. 2.2 Data Collection All patients aged C70 years admitted to the GEM unit between 22 October 2010 and 23 December 2011 were invited to participate in the study by a member of the research team (n = 427). Potential participants were excluded if a proxy was required but unavailable [e.g. in case of dementia, unresolved delirium within 72 h (n = 77), or language barriers (n = 67)], if their treating clinician recommended exclusion [e.g. due to elder abuse, physical aggression, or due to being medically unwell (n = 33)], they were deemed infectious (n = 11), missed by the researcher (n = 4), if they declined to participate (n = 63), were transferred to another hospital (n = 2), to palliative care service (n = 1) or died during hospital stay (n = 6). This study investigated discharge destination of 163 participants discharged from the GEM unit (Fig. 1). 2.3 Main Outcome Measure Data concerning discharge destination were extracted from Open Architecture Clinical Information System (OACIS,
Polypharmacy, Medication Regimen Complexity and Hospital Discharge Destination Fig.1 Flow of participants through the study
166 eligible participants
Transfer to - another hospital (n=2) - palliative care service (n=1) 163 participants included in the study
Discharge directly to home (n=87)
Discharge to non-community settings (n=76)
Low level or high level residential aged care (n=31)
South Australia Health Department, 2009). Patients were considered to have been ‘discharged directly to home’ if they returned to their own home immediately following hospitalization either with or without new community services such as ‘Meals on Wheels’, domiciliary care, or home and community care services. Patients were considered ‘discharged to non-community settings’ if they were discharged to either high- or low-level residential aged care, transition care (i.e. restorative care in a residential aged care facility), or off-site inpatient rehabilitation. 2.4 Medication Assessment Each patient’s medication regimen was assessed at hospital discharge. Discharge medication data were extracted directly from the separation summary prepared predominantly by medical doctors and recorded in OACIS. We included prescription, non-prescription, and complementary and alternative medications (CAMs) when computing polypharmacy and medication regimen complexity. This was because all medications taken by a patient can contribute to the complexity of their medication regimen. At the GEM unit, discharge medication lists are routinely provided to both the patient and their primary care physician to inform about ongoing prescribing. All medication data were extracted by the same pharmacist researcher. Medications were categorized according to the Anatomical Therapeutic Chemical (ATC) Classification System recommended by the World Health Organization [18]. Polypharmacy was defined as use of nine or more medications on a regular or as-needed basis. This definition was consistent with that recommended for use in long-term facilities [12] and used in previous research [13]. It was
Transition care (i.e. restorative care in a residential aged care facility, n=16)
Off-site inpatient rehabilitation (n=29)
impractical to use the more traditional cutoff of five or more medications because almost all participants (n = 155) took five or more medications. Each patient’s regimen complexity was computed using the 65-item validated Medication Regimen Complexity Index (MRCI) developed by George et al. [19]. In short, the Index provides scores for dosage forms, dosing frequencies, and additional directions. The MRCI has both convergent (Spearman’s rho = 0.9; p \ 0.0001) and discriminate validity (Spearman’s rho = 0.34; p = 0.1 for age and p = 0.487 for sex) [19]. Higher MRCI scores reflect more complex medication regimens. Prescription and non-prescription medications, nutritional supplements, health products, dermatologicals and short-term medications (e.g. antibiotics) were all considered when computing the MRCI. The inclusion of non-prescription medications was consistent with other recent studies utilizing the MRCI [20, 21]. In the absence of recognized cutoffs for MRCI, we defined a high MRCI as [35 because this represented the highest quartile of regimen complexity in our cohort. 2.5 Covariates Comorbidity was calculated for each patient using the Charlson’s Comorbidity Index, a weighted index that is suitable for use with medical records [22, 23]. ADLs were assessed using the 10-item Barthel’s ADL index, a performance scale giving a maximum score of 100 [24]. 2.6 Statistical Analyses Data were tested for normality using the Kolmogorov– Smirnov and Shapiro–Wilk test. Normally distributed
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characteristics were summarized using means with standard deviations. Non-normally distributed variables (Barthel’s ADL index, Charlson’s Comorbidity Index) were reported using medians and ranges. Logistic regression analyses were used to compute unadjusted and adjusted odds ratios (ORs) with 95 % confidence intervals (CIs) for medication-related factors associated with discharge destination. The ORs were converted to relative risks (RRs) using the method described by Zhang and Fai because ORs are a poor estimate of the RRs when the prevalence of outcome is [10 % [25]. Two logistic regression models were computed. The first model investigated the association between polypharmacy and discharge destination and the second model investigated the association between high regimen complexity (MRCI [35) and discharge destination. Variables that were significantly associated with discharge destination in the unadjusted analyses (defined as p \ 0.1), or those deemed clinically relevant on the basis of previous research [9, 26], were included in the multivariate models. The same covariates were used in each regression model. Age, ADLs and comorbidities were analyzed as continuous variables, whereas sex was analyzed as a dichotomized variable. Three sets of sensitivity analyses were also performed. The first sensitivity analyses excluded medications that were prescribed for a short duration (e.g. antibiotics) when calculating MRCI. The second sensitivity analyses adjusted the models investigating MRCI using the number of prescribed medications. The third sensitivity analyses investigated polypharmacy and MRCI as continuous rather than categorical variables. In the third sensitivity analyses,
MRCI was analyzed as a continuous variable in 10-unit steps. Data were analyzed using the Statistical Package for the Social Sciences (SPSS), version 21 (IBM Corporation, Armonk, NY, USA). A p-value of \0.05 was considered statistically significant. 2.7 Ethical Considerations All potential participants were provided with written information about the study. Written informed consent to participate was obtained from all participants themselves or their health proxy. The study was approved by the Human Research Ethics Committees at TQEH and the University of South Australia.
3 Results Patients were mostly female (72.4 %; n = 118) and the mean age was 85.2 ± 6.4 years (range 71–101 years). The median length of stay of eligible patients was 12 days. The most prevalent medications were calcium (76.7 % of participants), antithrombotic agents, including aspirin (65.0 %), laxatives (59.5 %), and paracetamol (58.9 %). The most prevalent dose forms were oral (98.2 % of participants), topical applications (33.7 %), and eye drops (22.7 %). The most prevalent diagnoses documented in the separation summary were cardiovascular disease (82.2 %), gastrointestinal disorders (47.2 %), and arthritis (36.8 %) [Table 1]. The study cohort comprised 163 eligible patients, of whom 87 (53.4 %) were discharged directly to home
Table 1 Characteristics of the cohort Age [years; mean (± SD)]
Total cohort (n = 163)
DD directly to home (n = 87)
DD non-community setting (n = 76)
85.2 (± 6.4)
84.6 (± 6.9)
85.8 (± 5.8)
Male sex [n (%)]
45 (27.6)
28 (32.2)
17 (22.4)
MRCI [35 [n (%)]
40 (24.5)
13 (14.9)
27 (35.5)
Polypharmacy C9 medications (%)
98 (60.1)
53 (60.9)
45 (59.2)
Barthel’s ADL index [median (range)]
67.3 (8–100)
73.0 (21–100)
60.7 (8–100)
Charlson’s Comorbidity Index [median (range)]
2.93 (0–10)
2.85 (0–10)
3.03 (0–9)
134 (82.2)
71 (81.6)
63 (82.9)
GI disorders
77 (47.2)
48 (55.2)
29 (38.2)
Arthritis
60 (36.8)
29 (33.3)
31 (40.8)
Diabetes UTI/urological disorders
54 (33.1) 46 (28.8)
32 (36.8) 24 (27.6)
22 (28.9) 22 (28.9)
Osteoporosis
45 (27.6)
23 (26.4)
22 (28.9)
Airways disease
35 (21.5)
20 (23.0)
15 (19.7)
Cancer
34 (20.9)
17 (19.5)
17 (22.4)
Renal impairment/disease
34 (20.9)
15 (17.2)
19 (25.0)
Dementia
34 (20.9)
14 (16.1)
20 (26.3)
Documented diagnoses [n (%)] CVD
ADL activities of daily living, CVD cardiovascular disease, DD discharge destination, GI gastrointestinal, MRCI Medication Regimen Complexity Index, SD standard deviation, UTI urinary tract infection
Polypharmacy, Medication Regimen Complexity and Hospital Discharge Destination Table 2 Unadjusted and adjusted relative risks for the association between polypharmacy and medication regimen complexity (MRCI [35) with discharge directly to home Unadjusted RR (95 % CI)
Adjusteda RR (95 % CI)
Polypharmacy C9 medications
1.05 (0.64–1.59)
0.97 (0.53–1.58)
Age
0.98 (0.94–1.01)
0.99 (0.95–1.03)
Male sex
1.41 (0.86–2.07)
1.45 (0.79–2.34)
Charlson’s Comorbidity Index
0.97 (0.87–1.08)
0.96 (0.84–1.09)
Barthel’s ADL
1.03 (1.01–1.04)
1.03 (1.02–1.05)
High MRCI [35
0.39 (0.19–0.74)
0.39 (0.20–0.73)
Age
0.98 (0.94–1.01)
0.98 (0.94–1.02)
Male sex
1.41 (0.86–2.07)
1.15 (0.71–1.57)
Charlson’s Comorbidity Index
0.97 (0.87–1.08)
0.99 (0.91–1.09)
Barthel’s ADL
1.03 (1.01–1.04)
1.02 (1.01–1.03)
ADLs activities of daily living, CI confidence interval, MRCI Medication Regimen Complexity Index, RR relative risk a
Adjusted for age, Barthel’s ADL, Charlson’s comorbidity index, and sex
(Fig. 1). Of the 76 people discharged to non-community settings, 74 were admitted directly from home. After adjusting for age, sex, comorbidity, and ADLs, polypharmacy was not associated with discharge destination (RR 0.97; 95 % CI 0.53–1.58) [Table 2]. After adjusting for age, sex, comorbidity, and ADLs, there was an inverse association between having a high medication regimen complexity and discharge directly to home (RR 0.39; 95 % CI 0.20–0.73). In the first sensitivity analyses, the RR for discharge directly to home was unchanged when medications prescribed for a short duration only were excluded when calculating the MRCI (RR 0.36; 95 % CI 0.17–0.72). In the second sensitivity analyses, the association between high MRCI and discharge destination was unchanged when the model was adjusted for the number of medications in addition to age, sex, comorbidities, and ADLs (RR 0.28; 95 % CI 0.10–0.69). In the third sensitivity analyses, there was no association between polypharmacy and discharge directly to home (RR 0.96; 95 % CI 0.91–1.02) when polypharmacy was analyzed as a continuous variable. When MRCI was analyzed as a continuous variable in 10-unit steps, there was an inverse association with discharge directly to home in adjusted analyses (RR 0.81; 95 % CI 0.65–0.98).
4 Discussion The main finding of this study was that medication regimen complexity was inversely associated with discharge directly to home. Participants with a high medication
regimen complexity were less likely to be discharged directly to home than those without a high medication regimen complexity. Polypharmacy, which is often used as a surrogate for inappropriate medication use [27, 28], was not associated with discharge destination. Our results suggest that medication regimen complexity may be an under-recognized factor associated with discharge destination from geriatric units. A recent systematic review on factors associated with institutionalization did not list specific medications or the complexity of medication regimens as a factor [26]. Factors associated with institutionalization included older age, dementia, cognitive or functional impairment, low self-rated health, and a high number of prescriptions [26]. A qualitative study conducted in New Zealand concluded that the reasons for admission to non-community settings were multifactorial, and included physical condition and social/community support [9]. However, in the study mentioned above, medications were not mentioned as contributing to institutionalization. Previous studies have suggested medication regimen complexity is associated with lower medication adherence [14], hospital readmission [29], and lower quality of life [30]. To our knowledge this is the first study that has reported the association between medication regimen complexity and hospital discharge destination. The possible reasons for association between regimen complexity and discharge destination are multifactorial. During periods of hospitalization, medication regimens are often modified [31]. The number of prescribed medications and regimen complexity may even increase [32–35]. This could contribute to people who are unable to manage their medication regimen at home being discharged to a noncommunity setting. Highly complex medication regimens often comprise a range of dose forms and formulations [36]. Handling dose administration aids (DAAs) or blister packs, opening child-resistant bottles, and splitting tablets requires a level of physical dexterity [37]. Visual impairment can lead to an inability to distinguish colors of tablets or capsules [37]. Clinicians may have considered all these factors when determining discharge destination. Medication regimen complexity might consciously or unconsciously influence prescribing behavior. Moreover, clinicians’ decisions to prescribe complex medication regimens may have been impacted by their perception of medication support available to the patient. Clinical implications of our findings include the potential importance of reducing complexity where possible. Complex regimens include those with a combination of different dose forms (e.g. metered dose inhalers for asthma/ chronic obstructive pulmonary disease, transdermal analgesics, subcutaneous insulin), dose frequencies, and additional directions (e.g. weekly or monthly oral bisphosphonates). Potential strategies to reduce medication
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regimen complexity include reducing the need for multiple daily dosing by prescribing sustained-release formations, avoiding the need for tablet splitting by prescribing a lower-strength tablet (e.g. a low-dose tablet rather than half a full-strength tablet), and standardizing dose timing (e.g. suggesting all once-daily tablets and capsules be taken at the same time of day if possible) [38]. The MRCI may be suitable for inclusion in prescribing and dispensing software as a prompt for clinicians to minimize regimen complexity, although the suitability of the MRCI for this purpose has not yet been demonstrated. Unlike medication regimen complexity, polypharmacy was not associated with discharge destination. This highlights the importance of considering dose forms and formulations, dose timing, and special instructions for medication use. Medication regimen complexity may be more useful than polypharmacy for predicting discharge destination. This has important implications because polypharmacy is often used by clinicians and policy makers to help identify the need for medication review [39]. One previous study reported that polypharmacy was associated with care home admission [40]. However, the authors of this study defined polypharmacy according to the use of potentially inappropriate medications rather than the number of medications, which means this finding is not comparable with our results. Nevertheless, use of multiple medications has been associated with a range of other adverse events, including length of hospital stay, mortality, and hospital readmission [27, 32, 41]. Further longitudinal research is needed to investigate whether MRCI predicts mortality or rehospitalization. 4.1 Strengths and Limitations As with all observational studies, there is the possibility of confounding by indication and disease severity. Medication regimen complexity may reflect patients’ overall health condition because people who are sicker, less independent, or otherwise in need of institutionalization may be prescribed more complex regimens. However, we accounted for this by adjusting our logistic regression models for age, sex, ADLs, and comorbidities. Strengths of this study include the medication data being extracted by an experienced pharmacist researcher in order to minimize the likelihood of error [42]. Validated scales were used to assess the cohort regarding comorbidities [23], ADLs [24], and medication regimen complexity [19]. Patients discharged from the GEM unit were generally provided with 2 weeks’ supply of their medications in DAAs regardless of their discharge destination. It was a limitation of the study that information was not available on the actual long-term use or availability of DAAs
post-discharge [43]. In Australia, DAAs are widely available through community pharmacies for both people living at home and in residential aged care facilities. This means that availability and use of DAAs were unlikely to have impacted the results. Study participants were discharged from a single GEM unit which might limit the generalizability. However, the MRCI scores, sex distribution, and Charlson’s Comorbidity Index were similar to those reported in previous research [20]. This suggests that the study sample was similar to samples included in earlier research studies. Another limitation was the relatively small sample size of 163 people, and this restricted the number of adjustment variables in the multivariate models. We did not analyze change in polypharmacy or regimen complexity during hospitalization or whether polypharmacy or regimen complexity was associated with other hospital discharge outcomes. It is possible that clinicians had already attempted to simplify patients’ medication regimens during their inpatient stay. Moreover, we did not investigate whether living alone, housing quality, or access to a paid or unpaid caregiver post-discharge impacted patients’ discharge destination. We did not assess whether each patient’s pre-admission level of home support was sufficient for the patient to resume living independently in the community given that the required level of support may have changed. Nevertheless, patients were admitted to the GEM unit with a view to them being able to resume living independently in the community. An additional potential limitation was the reliance on patients’ hospital medical records since these are often incomplete [44]. However, data utilized in the study were the same data forwarded to the patients’ primary care physicians for the purpose of medical decision making and repeat prescribing post-discharge. A prospective intervention study is required to determine whether simplification of regimens leads to a higher percentage of patients being discharged directly to home.
5 Conclusion High medication regimen complexity was inversely associated with discharge directly to home in older people, whereas polypharmacy was not. While a controlled intervention study is needed to determine whether reducing medication regimen complexity would permit a greater proportion of patients to be discharged directly to home, our findings highlight the potential importance of simplifying medication regimens in older people discharged from hospital. This finding is of particular relevance because several previous studies have reported an increase in polypharmacy when patients are admitted to hospital.
Polypharmacy, Medication Regimen Complexity and Hospital Discharge Destination Acknowledgments No external sources of funding were used for this study. Barbara C. Wimmer received an International President’s Scholarship from the University of South Australia to undertake the research reported in this manuscript. Barbara C. Wimmer, Elsa Dent, Renuka Visvanathan, Michael D. Wiese, Kristina Johnell, Ian Champan, and J. Simon Bell have no conflicts of interest that are directly relevant to the content of this study.
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