Investigating the association between medication regimen complexity, medication adherence and treatment satisfaction among Malaysian older adult patients: a cross-sectional study.

BACKGROUND: The prevalence of medication nonadherence among Malaysian older adults is approximately 60%. However, there is a lack of studies assessing the factors associated with medication nonadherence among this population. This research aims to explore the association between medication regimen complexity (MRC), treatment satisfaction and medication adherence among Malaysian older adults. METHOD: A cross-sectional study was conducted in outpatient clinics of a teaching hospital in Pahang, Malaysia, between April 2023 and September 2023. MRC Index (MRCI), Treatment Satisfaction for Medication version II (TSQM v.II), and the Malaysian Medication Adherence Assessment Tool (MyMAAT) were used. Multivariate linear and logistic regression models were performed to test the factors affecting treatment satisfaction and medication adherence. Mediator analysis was implemented to assess the mediating role of treatment satisfaction. RESULT: The study involved 429 Malaysian older adult patients, with a prevalence of nonadherence of 51.0% (n = 219) and an MRCI mean score of 17.37 (SD = 7.07). The mean overall treatment satisfaction score was 73.91 (SD = 15.23). Multivariate logistic regression analysis expressed four significant predictors associated with nonadherence: MRC (AOR = 1.179, p = 0.002), overall treatment satisfaction (AOR = 0.847, p < 0.001), partially self-managed medication (AOR = 2.675, p = 0.011) and fully managed medication by family members/caregivers (AOR = 8.436, p = 0.004). Multivariate linear regression shows three predictors of treatment satisfaction: MRC (ß = -1.395, p < 0.001), Charlson Comorbidity Index (CCI) (ß = -0.746, p = 0.009) and self-managed medication (ß = 5.554, p = 0.006). Mediator analysis indicated that treatment satisfaction partially mediated the association between MRC and nonadherence. CONCLUSION: Nonadherence was quite prevalent among Malaysian older outpatients and was associated with regimen complexity, treatment satisfaction and patient dependence on others to manage their medications. Future studies should focus on interventions to control the factors that negatively affect patients' medication adherence.

Medication burden in patients with dialysis-dependent CKD: a systematic review.

This systematic review aimed to statistically profile the medication burden and associated influencing factors, and outcomes in patients with dialysis-dependent chronic kidney disease (DD-CKD). Studies of medication burden in patients with DD-CKD in the last 10 years from 1 January 2013 to 31 March 2024 were searched from PubMed, Embase, and Cochrane databases. Newcastle-Ottawa Scale (NOS) or Agency for Healthcare Research and Quality (AHRQ) methodology checklist was used to evaluate quality and bias. Data extraction and combining from multiple groups of number (n), mean, and standard deviation (SD) were performed using R programming language (version4.3.1; R Core Team, Vienna, Austria). A total of 10 studies were included, and the results showed a higher drug burden in patients with DD-CKD. The combined pill burden was 14.57 ± 7.56 per day in hemodialysis (HD) patients and 14.63 ± 6.32 in peritoneal dialysis (PD) patients. The combined number of medications was 9.74 ± 3.37 in HD and 8 ± 3 in PD. Four studies described the various drug classes and their proportions, in general, antihypertensives and phosphate binders were the most commonly used drugs. Five studies mentioned factors associated with medication burden. A total of five studies mentioned medication burden-related outcomes, with one study finding that medication-related burden was associated with increased treatment burden, three studies finding that poor medication adherence was associated with medication burden, and another study finding that medication complexity was not associated with self-reported medication adherence. Limitations: meta-analysis was not possible due to the heterogeneity of studies.

Implications of the medication regimen complexity index score on hospital readmissions in elderly patients with heart failure: a retrospective cohort study.

BACKGROUND: The likelihood of elderly patients with heart failure (HF) being readmitted to the hospital is higher if they have a higher medication regimen complexity index (MRCI) compared to those with a lower MRCI. The objective of this study was to investigate whether there is a correlation between the MRCI score and the frequency of hospital readmissions (30-day, 90-day, and 1-year) among elderly patients with HF. METHODS: In this single-center retrospective cohort study, MRCI scores were calculated using a well-established tool. Patients were categorized into high (≥ 15) or low (< 15) MRCI score groups. The primary outcome examined the association between MRCI scores and 30-day hospital readmission rates. Secondary outcomes included the relationships between MRCI scores and 90-day readmission, one-year readmission, and mortality rates. Multivariate logistic regression was employed to assess the 30- and 90-day readmission rates, while Kaplan-Meier analysis was utilized to plot mortality. RESULTS: A total of 150 patients were included. The mean MRCI score for all patients was 33.43. 90% of patients had a high score. There was no link between a high MCRI score and a high 30-day readmission rate (OR 1.02; 95% CI 0.99-1.05; p < 0.13). A high MCRI score was associated with an initial significant increase in the 90-day readmission rate (odd ratio, 1.03; 95% CI, 1.00-1.07; p < 0.022), but not after adjusting for independent factors (odd ratio, 0.99; 95% CI, 0.95-1.03; p < 0.487). There was no significant difference between high and low MRCI scores in their one-year readmission rate. CONCLUSION: The study's results indicate that there is no correlation between a higher MRCI score and the rates of hospital readmission or mortality among elderly patients with HF. Therefore, it can be concluded that the medication regimen complexity index does not appear to be a significant predictor of hospital readmission or mortality in this population.

Evaluation of potentially inappropriate medications use and medication complexity in elderly patients applying to community pharmacy in Turkey.

BACKGROUND: Older adults often use multiple medicines to manage comorbidities well or to prevent associated complications. This study aims to determine polypharmacy, the use of potentially inappropriate medications (PIMs) using the 2019 Beers Criteria and to determine the Medication Regimen Complexity Index (MRCI) score. It also aims to identify factors associated with the presence of PIMs and the MRCI score. METHODS: This cross-sectional study was carried out between 6 and 2023 and 5 May 2023 in a community pharmacy in Turkey. Elderly patients over 65 years of age, who used at least one drug, and who came to the pharmacy for any reason were included in the study. PIMs were determined according to the 2019 Beers Criteria. The Turkish validated version of the MRCI was used to determine the medication complexity score. RESULTS: 200 patients were included in this study. 59.5% of the patients were female and the median age was 70 (IQR, 66-74.75). Polypharmacy was detected in 33% of patients. The use of PIMs was determined in 63.5% of the patients. The median of the MRCI score was 11 (IQR, 7-15). The number of chronic diseases and drugs, presence of polypharmacy, MRCI score and mental disorders were found to be significantly higher in those with PIMs than in those without (p < 0.05). Having less than eight years of education, presence of polypharmacy, the presence of comorbidity (diabetes mellitus, cardiovascular disease, thyroid, chronic obstructive pulmonary disease (COPD), asthma and mental disorders) were associated with significantly higher MRCI scores (p < 0.05). CONCLUSIONS: According to the results of our study, it was found that the elderly patients who came to the pharmacy had low MRCI scores, but had high PIMs use. Community pharmacists have an important role in identifying inappropriate drug use, so they should be trained to develop skills in identifying and reducing PIMs in older patients.

Attitude towards deprescribing and its association with frailty and complexity of medication regimen: A survey of older inpatients in a district health board in New Zealand.

BACKGROUND: Older inpatients, particularly those with frailty, have increased exposure to complex medication regimens. It is not known whether frailty and complexity of medication regimens influence attitudes toward deprescribing. This study aimed to investigate (1) older inpatients' attitudes toward deprescribing; (2) if frailty and complexity of medication regimen influence attitudes and willingness to deprescribe - a relationship that has not been investigated in previous studies. METHODS: In this cross-sectional study, older adults (≥ 65 years) recruited from general medicine and geriatric services in a New Zealand hospital completed the revised Patients' Attitudes Towards Deprescribing (rPATD) questionnaire. Hospital frailty risk score (HFRS) was calculated using diagnostic codes and other relevant information present at the time of index hospital admission; higher scores indicate higher frailty risk. Medication regimen complexity was quantified using the medication regimen complexity index (MRCI); higher scores indicate greater complexity. Logistic regression analysis was used to identify predictors of attitudes and willingness to deprescribe. RESULTS: A total of 222 patients were included in the study, the median age was 83 years and 63% were female. One in two patients reported feeling they were taking too many medications, and 1 in 5 considered their medications burdensome. Almost 3 in 4 (73%) wanted to be involved in decision-making about their medications, and 4 in 5 (84%) were willing to stop one or more of their medications if their prescriber said it was possible. Patients with higher MRCI had increased self-reported medication burden (adjusted odds ratio (AOR) 2.6, 95% CI 1.29, 5.29) and were more interested in being involved in decision-making about their medications (AOR 1.8, CI 0.99, 3.42) than those with lower MRCI. Patients with moderate HFRS had lower odds of willingness to deprescribe (AOR 0.45, CI 0.22,0.92) compared to the low-risk group. Female patients had a lower desire to be involved in decision-making. The oldest old age group( > 80 years) had lower self-reported medication burden and were less likely to want to try stopping their medications. CONCLUSION: Most older inpatients wanted to be involved in decision-making about their medications and were willing to stop one or more medications if proposed by their prescriber. Medication complexity and frailty status influence patients' attitudes toward deprescribing and thus should be taken into consideration when making deprescribing decisions. Further research is needed to investigate the relationship between frailty and the complexity of medication regimens.

Medication regimen complexity (MRC-ICU) for in-hospital mortality prediction in COVID-19 patients.

Purpose: The medication regimen complexity-intensive care unit (MRC-ICU) score was developed prior to the existence of COVID-19. The purpose of this study was to assess if MRC-ICU could predict in-hospital mortality in patients with COVID-19. Methods: A single-center, observational study was conducted from August 2020 to January 2021. The primary outcome of this study was the area under the receiver operating characteristic (AUROC) for in-hospital mortality for the 48-hour MRC-ICU. Age, sequential organ failure assessment (SOFA), and World Health Organization (WHO) COVID-19 Severity Classification were assessed. Logistic regression was performed to predict in-hospital mortality as well as WHO Severity Classification at 7 days. Results: A total of 149 patients were included. The median SOFA score was 8 (IQR 5-11) and median MRC-ICU score at 48 hours was 15 (IQR 7-21). The in-hospital mortality rate was 36% (n = 54). The AUROC for MRC-ICU was 0.71 (95% Confidence Interval (CI), 0.62-0.78) compared to 0.66 for age, 0.81 SOFA, and 0.72 for the WHO Severity Classification. In univariate analysis, age, SOFA, MRC-ICU, and WHO Severity Classification all demonstrated significant association with in-hospital mortality, while SOFA, MRC-ICU, and WHO Severity Classification demonstrated significant association with WHO Severity Classification at 7 days. In univariate analysis, all 4 characteristics showed significant association with mortality; however, only age and SOFA remained significant following multivariate analysis. Conclusion: In the first analysis of medication-related variables as a predictor of severity and in-hospital mortality in COVID-19, MRC-ICU demonstrated acceptable predictive ability as represented by AUROC; however, SOFA was the strongest predictor in both AUROC and regression analysis.

An Evaluation of the Relationship Between Medication Regimen Complexity as Measured by the MRC-ICU to Medication Errors in Critically Ill Patients.

Purpose: The purpose of this study was to determine the relationship between medication regimen complexity-intensive care unit (MRC-ICU) score at 24 hours and medication errors identified throughout the ICU. Methods: A single-center, observational study was conducted from August to October 2021. The primary outcome was the association between MRC-ICU at 24 hours and total medication errors identified. During the prospective component, ICU pharmacists recorded medication errors identified over an 8-week period. During the retrospective component, the electronic medical record was reviewed to collect patient demographics, outcomes, and MRC-ICU score at 24 hours. The primary outcome of the relationship of MRC-ICU at 24 hours to medication errors was assessed using Pearson correlation. Results: A total of 150 patients were included. There were 2 pharmacists who recorded 634 errors during the 8-week study period. No significant relationship between MRC-ICU and medication errors was observed (r2 = .13, P = .11). Exploratory analyses of MRC-ICU relationship to major interventions and harm scores showed that MRC-ICU scores >10 had more major interventions (27 vs 14, P = .27) and higher harm scores (15 vs 7, P = .33), although these values were not statistically significant. Conclusion: Medication errors appear to occur independently of medication regimen complexity. Critical care pharmacists were responsible for mitigating a large number of medication errors.

Prevalence and patient-rated relevance of complexity factors in medication regimens of community-dwelling patients with polypharmacy.

PURPOSE: To describe the prevalence of complexity factors in the medication regimens of community-dwelling patients with more than five drugs and to evaluate the relevance of these factors for individual patients. METHODS: Data were derived from the HIOPP-6 trial, a controlled study conducted in 9 general practices which evaluated an electronic tool to detect and reduce complexity of drug treatment. The prevalence of complexity factors was based on the results of the automated analysis of 139 patients' medication data. The relevance assessment was based on the patients' rating of each factor in an interview (48 patients included for analysis). RESULTS: A median of 5 (range 0-21) complexity factors per medication regimen were detected and at least one factor was observed in 131 of 139 patients. Almost half of these patients found no complexity factor in their medication regimen relevant. CONCLUSION: In most medication regimens, complexity factors could be identified automatically, yet less than 15% of factors were indeed relevant for patients as judged by themselves. When assessing complexity of medication regimens, one should especially consider factors that are both particularly frequent and often challenging for patients, such as use of inhalers or tablet splitting. TRIAL REGISTRATION: The HIOPP-6 trial was registered retrospectively on May 17, 2021, in the German Clinical Trials register under DRKS-ID DRKS00025257.

Are Clinical Outcomes Associated With Medication Regimen Complexity? A Systematic Review and Meta-analysis.

Background: Current evidence of the influence of the medication regimen complexity (MRC) on the patients' clinical outcomes are not conclusive. Objective: To systematically and analytically assess the association between MRC measured by the Medication Regimen Complexity Index (MRCI) and clinical outcomes. Methods: A search was carried out in the databases Cochrane Library, LILACS, PubMed, Scopus, EMBASE, Open Thesis, and Web of Science to identify studies evaluating the association between MRC and clinical outcomes that were published from January 1, 2004, to April 2, 2018. The search terms included outcome assessment, drug therapy, and medication regimen complexity index and their synonyms in different combinations for case-control and cohort studies that used the MRCI to measure MRC and related the MRCI with clinical outcomes. Odds ratios (ORs), hazard ratios (HRs), and mean differences (WMDs) were calculated, and heterogeneity was assessed using the I2 test. Results: A total of 12 studies met the eligibility criteria. The meta-analysis showed that MRC is associated with the following clinical outcomes: hospitalization (HR = 1.20; 95% CI = 1.14 to 1.27;I2 = 0%) in cohort studies, hospital readmissions (WMD = 7.72; 95% CI = 1.19 to 14.25; I2 = 84%) in case-control studies, and medication nonadherence (adjusted OR = 1.05; 95% CI = 1.02 to 1.07; I2 = 0%) in cohort studies. Conclusion and Relevance: This systematic review and meta-analysis gathered relevant scientific evidence and quantified the combined estimates to show the association of MRC with clinical outcomes: hospitalization, hospital readmission, and medication adherence.

Medication Regimen Complexity Index Prediction of Adverse Drug Reaction-Related Hospital Admissions.

BACKGROUND: The relationship between the medication regimen complexity index (MRCI) and adverse drug reaction (ADR)-related hospital admissions has not yet specifically been investigated. OBJECTIVE: To evaluate the MRCI and compare with medication count for prediction of ADR-related hospital admissions in older patients. METHODS: This was a retrospective analysis of a prospectively collected convenience sample of 768 unplanned medical admissions of Australians aged 65 years old and older. The sample consisted of 115 (15.0%) ADR-related unplanned hospital admissions and 653 (85.0%) non-ADR-related unplanned medical admissions. The MRCI score was calculated from the medical records and analyzed to predict ADR-related hospital admissions. RESULTS: The cohort had a median age of 81 years, 5 comorbidities, and 11 medications, with a slight majority of women. The MRCI score was not significantly different in patients who had ADR-related admissions compared with other medical admissions-38.5 versus 34.0, respectively; Wilcoxon Rank Sum test W = 33 522; P = 0.067. The medication count was significantly different between the ADR-related admissions compared with other medical admissions: 12 versus 10; W = 32 508; P = 0.021. However, the medication count was not a strong predictor of ADR-related admissions; unadjusted odds ratio = 1.044; 95% CI = 1.006-1.084. CONCLUSION AND RELEVANCE: The MRCI score did not discriminate between ADR-related admissions and other medical admissions despite taking time to calculate with potential for inconsistent application. Medication count is more readily applicable with marginally greater relevance in this cohort; however, both measures do not appear to be useful when used alone for clinicians to identify patients at risk of ADRs.

Development of an algorithm to detect and reduce complexity of drug treatment and its technical realisation.

BACKGROUND: The increasing complexity of current drug therapies jeopardizes patient adherence. While individual needs to simplify a medication regimen vary from patient to patient, a straightforward approach to integrate the patients' perspective into decision making for complexity reduction is still lacking. We therefore aimed to develop an electronic, algorithm-based tool that analyses complexity of drug treatment and supports the assessment and consideration of patient preferences and needs regarding the reduction of complexity of drug treatment. METHODS: Complexity factors were selected based on literature and expert rating and specified for integration in the automated assessment. Subsequently, distinct key questions were phrased and allocated to each complexity factor to guide conversation with the patient and personalize the results of the automated assessment. Furthermore, each complexity factor was complemented with a potential optimisation measure to facilitate drug treatment (e.g. a patient leaflet). Complexity factors, key questions, and optimisation strategies were technically realized as tablet computer-based application, tested, and adapted iteratively until no further technical or content-related errors occurred. RESULTS: In total, 61 complexity factors referring to the dosage form, the dosage scheme, additional instructions, the patient, the product, and the process were considered relevant for inclusion in the tool; 38 of them allowed for automated detection. In total, 52 complexity factors were complemented with at least one key question for preference assessment and at least one optimisation measure. These measures included 29 recommendations for action for the health care provider (e.g. to suggest a dosage aid), 27 training videos, 44 patient leaflets, and 5 algorithms to select and suggest alternative drugs. CONCLUSIONS: Both the set-up of an algorithm and its technical realisation as computer-based app was successful. The electronic tool covers a wide range of different factors that potentially increase the complexity of drug treatment. For the majority of factors, simple key questions could be phrased to include the patients' perspective, and, even more important, for each complexity factor, specific measures to mitigate or reduce complexity could be defined.

Medication Regimen Complexity and Hospital Readmission in Older Adults With Chronic Kidney Disease.

BACKGROUND: Chronic kidney disease (CKD) is characterized by high rates of hospital admissions and readmissions. However, there is a scarcity of research into medication-related factors predicting such outcomes in this patient group. OBJECTIVE: To evaluate the effect of medication regimen complexity at hospital discharge on subsequent readmissions and their timing in older adults with CKD. METHODS: This was a 12-month retrospective cohort study of 204 older (⩾65 years) CKD patients in an Australian tertiary care hospital. Medication regimen complexity was quantified using the 65-item medication regimen complexity index (MRCI). The outcomes were the occurrence of readmission in 30 days and time to readmission within 12 months. Logistic regression was used to identify factors predicting 30-day readmission, and a competing risks proportional subdistribution hazard model, accounting for deaths, was used for factors predicting time to readmission. RESULTS: Overall, 50 (24%) patients, predominantly men (72%), were readmitted within 30 days of follow-up. MRCI was not significantly associated with 30-day readmission (odds ratio [OR] = 1.27; 95% CI = 0.94-1.73). The median (interquartile range) time to readmission within 12 months was 145 (31-365) days. On a multivariate analysis, a 10-unit increase in MRCI was associated with a shorter time to readmission within 12 months (subdistribution HR = 1.18; 95% CI = 1.01-1.36). Conclusion and Relevance: Medication regimen complexity was not significantly associated with 30-day readmission; however, it was associated with a significantly shorter time to 12-month readmission in older CKD patients. This finding highlights the importance of medication regimen complexity as a potential target for medical interventions to reduce readmission risks.

Therapeutic burden in interstitial lung disease: Lessons to learn.

BACKGROUND AND OBJECTIVE: Patients with interstitial lung disease (ILD) are often prescribed disease-targeted and symptomatic therapies, both of which can cause significant treatment burden due to polypharmacy and drug-disease interactions. This study aimed to evaluate medication regimen complexity before and after introduction of ILD-specific therapies. Potential drug-disease interactions were evaluated for patients who were prescribed prednisolone. METHODS: In this study, 214 patients with ILD were assessed for demographic information, co-morbidities and medication use. Medication lists were reviewed prior to and after the introduction of ILD-specific therapies. Complexity of treatment regimen was examined using the validated Medication Regimen Complexity Index (MRCI). RESULTS: Of the 214 patients, 75 had idiopathic pulmonary fibrosis (IPF) while the rest had inflammatory ILD (chronic hypersensitivity pneumonitis: 45; connective tissue disease-related ILD: 41). Polypharmacy was common at baseline (IPF: 51%, inflammatory ILD: 63%). Following introduction of ILD-specific therapies, median total MRCI scores significantly increased from 8 (interquartile range (IQR) = 8-15) to 22.5 (17.5-27.5) and 14.5 (8.5-21) to 21.5 (16-30) for IPF and inflammatory ILD groups, respectively (P < 0.0001 for both). Complex dosing instructions contributed the most to total MRCI scores for ILD-specific therapies. Among patients receiving prednisolone (n = 113), 88% had ≥1 co-morbidity which may be impacted. Common co-morbidities included gastrointestinal diseases (56%), obesity (37%), osteoporosis (24%) and diabetes mellitus (18%). CONCLUSION: Polypharmacy and complex medication regimen are common in patients with ILD of different aetiologies. There is a high frequency of potential drug-disease interactions among patients who are prescribed systemic corticosteroids. These findings highlight the need for careful evaluation of the impact of therapeutic complexity and burden in patients with ILD.

Medication Regimen Complexity Measured by MRCI: A Systematic Review to Identify Health Outcomes.

OBJECTIVE: To perform a systematic review to identify health outcomes related to medication regimen complexity as measured by the Medication Regimen Complexity Index (MRCI) instrument. DATA SOURCES: Cochrane Library, LILACS, PubMed, Scopus, EMBASE, Open Thesis, and Web of Science were searched from January 1, 2004, until April 02, 2018, using the following search terms: outcome assessment, drug therapy, and Medication Regimen Complexity Index and their synonyms in different combinations. STUDY SELECTION AND DATA EXTRACTION: Studies that used the MRCI instrument to measure medication regimen complexity and related it to clinical, humanistic, and/or economic outcomes were evaluated. Two reviewers independently carried out the analysis of the titles, abstracts, and complete texts according to the eligibility criteria, performed data extraction, and evaluated study quality. DATA SYNTHESIS: A total of 23 studies met the inclusion criteria; 18 health outcomes related to medication regimen complexity were found. The health outcomes most influenced by medication regimen complexity were hospital readmission, medication adherence, hospitalization, adverse drug events, and emergency sector visit. Only one study related medication regimen complexity with humanistic outcomes, and no study related medication regimen complexity to economic outcomes. Most of the studies were of good methodological quality. Relevance to Patient Care and Clinical Practice: Health care professionals should pay attention to medication regimen complexity of the patients because this may influence health outcomes. CONCLUSION: This study identified some health outcomes that may be influenced by medication regimen complexity: hospitalization, hospital readmission, and medication adherence were more prevalent, showing a significant association between MRCI increase and these health outcomes.

Association between medication regimen complexity and pharmacotherapy adherence: a systematic review.

PURPOSE: The purpose of this study was to systematically review evidence regarding the association between regimen complexity and adherence. METHODS: Articles were searched in MEDLINE, LILACS, Cochrane, CINAHL, PsycINFO and references of included studies. Search terms included medication regimen complexity, medication adherence and their synonyms. Randomized clinical trials, cross-sectional, cohort or case-control studies published until March 2016 in English, Portuguese or Spanish were eligible if quantitatively examined the association between complexity and adherence in patients of any age and sex, under any type of medication therapy. Complexity was defined according to the strategy used to assess it in the individual studies. All types of instruments used to assess complexity and adherence were considered. Data extraction was performed using an electronic spreadsheet. Quality assessment was conducted independently using standard scales. The data were qualitatively synthesized. RESULTS: Fifty-four studies were included: 37 cross-sectional and 17 cohorts. Most were conducted in outpatient setting. Most frequently, studies were carried out with HIV-infected individuals or patients with chronic conditions. The most frequent methods used to assess complexity and adherence were complexity index (19) and self-report (27), respectively. Complexity was associated with adherence in 35 studies. Most of them (28) identified that participants with more complex regimens were less likely to adhere to pharmacotherapy; seven studies found a direct correlation. The others found inconclusive results or no association between complexity and adherence. The studies had low to moderate-methodological quality. CONCLUSION: Although there was variability regarding the association between complexity and adherence, most studies showed that an increased regimen complexity reduces medication adherence.

Cross-cultural Adaptation and Validation of the Medication Regimen Complexity Index Adapted to Spanish.

BACKGROUND: The most widely used validated instrument to assess the complexity of medication regimens is the Medication Regimen Complexity Index (MRCI). OBJECTIVE: This study aimed to translate, adapt, and validate a reliable version of the MRCI adapted to Spanish (MRCI-E). METHODS: The cross-cultural adaptation process consisted of an independent translation by 3 clinical pharmacists and a backtranslation by 2 native English speakers. A reliability analysis was conducted on 20 elderly randomly selected patients. Two clinical pharmacists calculated the MRCI-E from discharge treatments and 2 months later. For the validity analysis, the sample was augmented to 60 patients. Convergent validity was assessed by analyzing the correlation between the number of medications; discriminant validity was stratified by gender; and predictive validity was determined by analyzing the ability to predict readmission and mortality at 3 and 6 months. RESULTS: The MRCI-E retained the original structure of 3 sections. The reliability analysis demonstrated an excellent internal consistency (Cronbach's α=0.83), and the intraclass correlation coefficient exceeded 0.9 in all cases. The correlation coefficient with the number of medications was 0.883 ( P<0.001). No significant differences were found when stratified by gender (3.6; 95%CI=-2.9 to 10.2; P=0.27). Patients who were readmitted at 3 months had a higher MRCI-E score (10.7; 95%CI=4.4 to 17.2; P=0.001). The differences remained significant in patients readmitted at 6 months, but differences in mortality were not detected. CONCLUSIONS: The MRCI-E retains the reliability and validity of the original index and provides a suitable tool to assess the complexity of medication regimens in Spanish.

Medication Regimen Complexity and Polypharmacy as Factors Associated With All-Cause Mortality in Older People: A Population-Based Cohort Study.

OBJECTIVES: To investigate whether medication regimen complexity and/or polypharmacy are associated with all-cause mortality in older people. METHODS: This was a population-based cohort study among community-dwelling and institutionalized people ≥60 years old (n = 3348). Medication regimen complexity was assessed using the 65-item Medication Regimen Complexity Index (MRCI) in 10-unit steps. Polypharmacy was assessed as a continuous variable (number of medications). Mortality data were obtained from the Swedish National Cause of Death Register. Cox proportional hazard models were used to compute unadjusted and adjusted hazard ratios (HRs) and 95% CIs for the association between regimen complexity and polypharmacy with all-cause mortality over a 3-year period. Subanalyses were performed stratifying by age (≤80 and>80 years), sex, and cognition (Mini-Mental State Examination [MMSE] <26 and ≥26). RESULTS: During follow-up, 14% of the participants (n = 470) died. After adjusting for age, sex, comorbidity, educational level, activities of daily living, MMSE, and residential setting, a higher MRCI was associated with mortality (adjusted HR = 1.12; 95% CI = 1.01-1.25). Polypharmacy was not associated with mortality (adjusted HR = 1.03; 95% CI = 0.99-1.06). When stratifying by sex, both MRCI and polypharmacy were associated with mortality in men but not in women. MRCI was associated with mortality in participants ≤80 years old and in participants with MMSE ≥26 but not in participants >80 years old or with MMSE <26. CONCLUSION: Regimen complexity was a better overall predictor of mortality than polypharmacy. However, regimen complexity was not predictive of mortality in women, in participants >80 years old, or in those with MMSE<26. These different associations with mortality deserve further investigation.

Clinical Outcomes Associated With a Collaborative Pharmacist-Endocrinologist Diabetes Intense Medical Management "Tune Up" Clinic in Complex Patients.

BACKGROUND: No previous studies exist examining the impact of a short-term pharmacist-endocrinologist collaborative practice model on glycemic control in complex patients. OBJECTIVE: Evaluate outcomes associated with a PharmD-Endocrinologist Diabetes Intense Medical Management (DIMM) "tune up" clinic for complex patients. METHODS: A retrospective cohort study of 99 patients referred to DIMM clinic versus a comparator group of 56 primary care provider (PCP) patients meeting the same criteria (adult type 2 diabetes patients, glycosylated hemoglobin [A1C] ≥ 8%, follow-up visit within 6 months) in a Veterans Affairs Medical Center. DIMM clinic used a short-term model that coupled personalized clinical care with real-time, patient-specific diabetes education during two to four 60-minute visits over 6 months. PCP patients received usual care. Primary outcome was mean A1C change after 6 months. Secondary measures included fasting blood glucose, lipids, blood pressure, weight, body mass index, and percentage of patients meeting goals. RESULTS: Patients in each group had an average of 8 and were taking 12 to 14 medications daily. Mean A1C (%) improvement in DIMM group was significantly greater at 6 months (-2.4 [SD = 2.1] vs -0.8 [SD = 1.7]; P < 0.001), than PCP group. Percentage meeting A1C goal levels (<7%, <8%, and <9%) was significantly greater at 3 and 6 months compared with baseline in the DIMM group (P < 0.001) versus (only <8%) at 3 and 6 months compared with baseline in PCP group. CONCLUSIONS: The DIMM clinic "tune up" model demonstrates a successful collaborative practice which helped complex diabetes patients achieve glycemic control in a 6-month period.

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

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

Medication Regimen Complexity and Unplanned Hospital Readmissions in Older People.

BACKGROUND: Medication-related problems and adverse drug events are leading causes of preventable hospitalizations. Few previous studies have investigated the possible association between medication regimen complexity and unplanned rehospitalization. OBJECTIVE: To investigate the association between discharge medication regimen complexity and unplanned rehospitalization over a 12-month period. METHOD: The prospective study comprised patients aged ≥70 years old consecutively admitted to a Geriatrics Evaluation and Management (GEM) unit between October 2010 and December 2011. Medication regimen complexity at discharge was calculated using the 65-item validated Medication Regimen Complexity Index (MRCI). Cox proportional-hazards regression was used to compute unadjusted and adjusted hazard ratios (HRs) with 95% CIs for factors associated with rehospitalization over a 12-month follow-up period. RESULT: Of 163 eligible patients, 99 patients had one or more unplanned hospital readmissions. When adjusting for age, sex, activities of daily living, depression, comorbidity, cognitive status, and discharge destination, MRCI (HR = 1.01; 95% CI = 0.81-1.26), number of discharge medications (HR = 1.01; 95% CI = 0.94-1.08), and polypharmacy (≥9 medications; HR = 1.12; 95% CI = 0.69-1.80) were not associated with rehospitalization. In patients discharged to nonhome settings, there was an association between rehospitalization and the number of discharge medications (HR = 1.12; 95% CI = 1.01-1.25) and polypharmacy (HR = 2.24; 95% CI = 1.02-4.94) but not between rehospitalization and MRCI (HR = 1.32; 95% CI = 0.98-1.78). CONCLUSION: Medication regimen complexity was not associated with unplanned hospital readmission in older people. However, in patients discharged to nonhome settings, the number of discharge medications and polypharmacy predicted rehospitalization. A patient's discharge destination is an important factor in unplanned medication-related readmissions.