Preprint
Article

Potentially Inappropriate Medication: A Pilot Study in Institutionalized Older Adults

Submitted:

20 May 2024

Posted:

21 May 2024

You are already at the latest version

A peer-reviewed article of this preprint also exists.

Abstract
Institutionalized older adults often face complex medication regimens, increasing their risk of adverse drug events due to polypharmacy, overprescribing, medication interactions or the use of Potentially Inappropriate Medications (PIM). However, data on medication use and associated risks in this population remain scarce. This pilot study aimed to characterize the sociodemographic, clinical and pharmacotherapeutic profiles and the use of PIM among institutionalized elders residing in Residential Structures for Elderly People (ERPI) in the Faro municipality, located in the Portuguese region of the Algarve. We conducted a cross-sectional study in a non-randomized sample of 96 participants (mean age: 86.6 ±7.86 years) where trained researchers reviewed medication profiles and identified potentially inappropriate medications using the EU(7)-PIM list. Over 90% of participants exhibited polypharmacy (≥5 medications), with an average of 9.1 ± 4.15 medications per person. About 92% had potential drug interactions, including major and moderate interactions. More than 86% used at least one potentially inappropriate medication, most commonly central nervous system drugs. This pilot study demonstrates that institutionalized older adults may be at high risk of potential medication-related problems. Implementing comprehensive medication review programs and promoting adapted prescribing practices are crucial to optimize medication use and improve the well-being of this vulnerable population.
Keywords: 
;  ;  ;  ;  

1. Introduction

Advancements in healthcare and medicine have significantly improved quality of life and life expectancy, contributing to an increase in the global population ageing. Europe is notably the continent with the oldest population, inhabited by around 25% of the world’s population aged over 60 [1]. Portugal reflects this demographic trend, showing an rate of ageing of 183.5% in 2022 [2], with 29.7% of the population aged 60 or over and projected to rise to around 40.3% by 2050 [3]. Globally, according to the United Nations, the number of elderly people aged 60 or over could double by 2050, from 962 million in 2017 to 2.1 billion in 2050 [1].
As physical and cognitive capacities decline with age, the elderly face diminished self-care abilities [4,5]. This problem, further complicated by the fragility of the family environment and social, economic, and cultural challenges, jeopardizes legally guaranteed basic rights. Residential Structures for the Elderly (ERPI) play a crucial role in upholding these rights by providing health care, psychosocial support, and promoting autonomy and protection for the elderly [6].
Ageing is responsible for numerous limitations and difficulties. Most elders have chronic illnesses which contribute to a decrease in autonomy and self-care ability, which results in the prescription of various pharmacological therapies and, consequently, polymedication [7].
According to the World Health Organization, there is no universal definition of polymedication. However, it is commonly understood to involve the concurrent use of five or more medications [8]. Even if there is no consensus on what is considered polymedication, taking five or more medications increases the risk of adverse reactions and drug interactions and can lead to negative and unexpected clinical results [9]. In elderly patients, polymedication is often categorized into two large groups: i) polymedication, when five to nine drugs are taken simultaneously; and ii) excessive polymedication, when 10 or more drugs are taken [10,11,12]. Polypharmacy, a term encompassing both categories, is a growing problem, whether due to an ageing population, multimorbidity, lack of communication between different prescribing doctors or the discovery of new drugs [8,12,13]. In the elderly population, the number of polymedicated and excessively polymedicated patients is 31.5% and 20.1% respectively [11]. In addition to drug interactions and the consequences they entail, polymedication leads to significant economic and clinical problems, including increased risk of falls, hospitalizations, and healthcare costs [13,14].
Promoting the appropriate use of medications trough multidisciplinary teams, reviewing pharmacotherapy, and tailoring medication to individual needs could help decrease mortality and the risks associated with polypharmacy [8,15]. In environments where elderly individuals receive care from specialized institutions or qualified health professionals, the risks of medication-related problems are notably decreased [16,17]. The elderly population is diverse, with varying medical conditions and degrees of physical, cognitive, and metabolic decline, making it challenging to identify and prevent adverse drug reactions [18]. Thus, individual needs, pharmacokinetic and pharmacodynamic changes, polymedication, and multimorbidity are risk factors that should be considered in pharmacotherapeutic analyses in this population [19].
The use of Potentially Inappropriate Medications (PIM) represents an increase in the complexity of pharmacotherapy in the elderly. In addition to anatomophysiological and metabolic changes, interactions, and risk for adverse reactions associated with any medication, research shows that there are medications that are considered inappropriate for elders [20]. PIM are drugs where the associated risks outweigh the clinical benefits, putting the patient at risk and prone to serious health risks [21,22]. Analyses of routine prescriptions and medication use in hospitals and nursing homes have shown that the prevalence of PIM use by elderly patients is high [23,24].
The use of PIM is associated with polymedication and the with the incidence of adverse effects [23,25,26,27]. Although PIM should be avoided in the elderly, sometimes their use is necessary, due to the lack of effective alternatives or when their discontinuation could cause more harm. When used inappropriately, without following medical recommendations and without proper monitoring, PIM can lead to increased hospitalizations, falls, adverse reactions and mortality among the elderly [28,29].
The pharmacotherapeutic regime for the elderly is complex, influenced by multimorbidity and age-related factors that contribute to polymedication and associated medication problems [17]. In addition to the extensive medical care that is already necessary at this stage of life, pharmaceutical care and medication review can favor quality of life and patient safety [30]. According to the Pharmaceutical Care Network Europe (PCNE), medication review “…is a structured assessment of a patient’s medicines with the aim of optimizing the use of medicines and improving health outcomes. This involves detecting medication-related problems and recommending interventions” [31]. Medication review leads to better clinical results from therapeutic practice and is therefore an extremely important procedure, especially for elderly, polymedicated patients, with multiple health issues [32].
This pilot study aimed to characterize the sociodemographic, clinical and pharmacotherapeutic profile and the use of PIM of institutionalized elders residing in two ERPI in the Faro municipality, in the Portuguese region of the Algarve.

2. Materials and Methods

We conducted a cross-sectional descriptive study in two ERPI located in the municipality of Faro, Portugal. ERPI selection and invitation were decided by convenience, without additional criteria apart from distance. The study included a total of 96 elderly people aged 65 or over, taking at least 2 medications and who consented the collection of their clinical and medication data, and summary clinical and demographic characteristics.
Analysis of the existing pharmacotherapeutic profile for each participant allowed to retrieve the names of the medicines (prescription and nonprescription) and food supplements used, pharmaceutical form, dosage and dosage regimen. A Type 2B medication review was carried out, according to the Pharmaceutical Care Network Europe criteria [31].
All medications were organized according to the Anatomical Therapeutic Chemical Code (ATC), level 3 [33]. The use of ≥5 medications was considered “polymedication” and the use of ≥10 medications was considered “excessive polymedication”. Individuals with less than five medications were considered “not polymedicated” [11].
Potential medication interactions were classified using the Lexidrug® Drug Interaction Module tool from the UpToDate platform. This tool classifies interactions into five different categories, according to the associated risk: type A (no potential pharmacokinetic or pharmacodynamic interactions; no known interaction), type B (little to no evidence of clinical concern; no action needed), type C (clinically significant interactions; monitor therapy), type D (clinically significant interactions and risk-benefit must be assessed; consider therapy modification), and type X (clinically significant interactions where the risks outweigh the benefits; avoid combination) [34].
Potentially inappropriate medicines for the elderly were considered according to the European EU(7)- PIM List [35], and the complexity of the pharmacotherapeutic regime was assessed using the criteria established by the Medication Regimen Complexity Index tool (MRCI) [36]. The MRCI score is calculated from three main subtotals, each contributing to the overall complexity. Subtotal A refers to the pharmaceutical form of the medication (e.g., tablet, injection, inhaler), as different forms may have different complexities. Subtotal B refers to the dosage frequency; more frequent dosing schedules increase the complexity. Subtotal C refers to the instructions and additional precautions for each medication, such as dietary restrictions or to avoid certain activities. Points are added with increased complexity added by the form, with increased frequency of dosing, and with additional specific instructions. The MRCI score is the sum of all subgroup scores and a total score >16.5 can be interpreted as high pharmacotherapeutic complexity [37].
Statistical analysis was carried out using IBM SPSS Statistics software for Macintosh, version 29.0. Armonk, NY: IBM Corp.
Data were described using absolute and relative frequencies, mean (M), median (Mdn), standard deviation (SD) and interquartile range (IQR). We used the Kolmogorov-Smirnov test to assess adherence to the Normal distribution. All variables in our study were either categorical or with a non-Normal distribution. Thus, group comparisons were made using Kruskal-Wallis, chi-square, and Mann-Whitney’s tests. When the results of the chi-square test were considered non-valid due to low expected frequency count, Fisher’s or Fisher-Freeman-Halton’s exact tests were computed. Paired comparisons were analyzed with Friedman’s test. Correlations were computed using Spearman’s correlation coefficient. Statistical significance for all procedures was set at 0.05.

3. Results

3.1. Sociodemographic and Pharmacotherapeutic Characterization

There were 96 patients included in this study, all aged 65 or over and residing in care institutions for the elderly. Mean age was 86.6±7.86 years, ranging from 68-109 years, with only 9.4% aged between 65-74 and 66.7% aged 85 or above. Most participants were women (68.8%). We found significant gender differences in age (p=0.044), with women (87.9±6.9) being older than men (83.7±9.04).
Mean number of medications used was 9.1±4.15, ranging from two to 24, and 90.6% of participants (n=87) were considered polymedicated (≥5 medications). Of the polymedicated, 47.1% (n=41) were excessively polymedicated (≥10 drugs). Only 9.4% of patients (n=9) had a pharmacotherapeutic profile with fewer than five drugs. Of the patients identified as polymedicated, 60.4% were aged 85 or over and 62.5% were female. The mean number of medications in the participants without polypharmacy was 3±0.87, while those with polypharmacy showed a significantly higher (p<0.001) mean of 9.8±3.83 medications.
According to the MRCI score, pharmacotherapeutic complexity, showed a mean score of 19.2±9.90, ranging between 5-55 points. Subtotals A, B and C had means of 3.2±2.39, 10.3±5.26 and 5.7±3.95 points, respectively. Table 1 presents age and selected data on medication use. No statistically significant differences in medication use were found between male and female participants (p>0.05).
MRCI score showed a strong positive correlation with the total number of medications used (R=0.873; p<0.001) and a negative correlation with age (R= -0.219, p=0.032), suggesting that younger patients and those that use more medications have a higher pharmacotherapeutic complexity. The statistical significant correlation of MRCI with age does not hold up when considering patients aged 65-74 years (R= 0.156, p=0.688; n=9) or ≥85 years (R= -0.005, p=0.967; n=64). This correlation is still significant in patients aged 75-84 years (n=23), but suggests a positive association, i.e., higher complexity in older patients (R=0.550, p=0.007). After adjusting for the number of medications, the correlation between MRCI and age was not significant (R=0.038, p=0.867) in this demographic. This suggests that the number of medications may have confounded the initial association, and that factors other than age, such as clinical condition, could be contributing to pharmacological complexity. Table 2 presents the correlation matrix between MRCI and other variables.
Of the participants, 91.7% (n=88) had at least one potential drug interaction, with a mean of 10.7±10.55 interactions per participant, ranging between 0-57. At least one potential interaction of each of the five types considered by the Lexidrug® tool was detected. Type C interactions were the most prevalent (86.5%; n=83) and had the highest mean occurrence per patient (7.93±7.68). Type A interactions, those with no potential pharmacokinetic or pharmacodynamic interactions, were seen in only two patients (2.0%), with a mean of 0.1±0.92 interactions. The most serious and clinically significant interactions (type X), where the risks outweigh the benefits and that should be avoided, were identified in 13 patients (13.5%), with a mean of 0.19±0.53. One of the patients presented those three interactions of this type simultaneously. Our data also shows that 59.4% (n=57) of the sample had at least one type B interaction, with an average of 1.34±1.89 of these type of interactions per participant. Type D interactions were identified in 40.6% (n=39) of patients, with an average of 1.10±2.02 interactions. The number of interactions is positively correlated with pharmacologic complexity (R=0.692, p<0.001). All interaction types apart from type A were also correlated with pharmacologic complexity (p<0.001).

3.2. Potentially Inappropriate Medication Characterization

Our data show that 86.5% (n=83) of the patients used at least one PIM (with a mean of 2.2±1.56 PIM per participant, ranging between 0-6), 67.5% (n=56) were women, 63.9% (n=53) were aged 85 or over, and 92.8% (n=77) had some kind of potential drug interaction and were polymedicated (≥5 medications). More than half of the patients who used any PIM (54.2%, n=45) had high pharmacotherapeutic complexity scores (MRCI>16.5 points). PIM was positively correlated with MRCI score (R=0.412, p<0.001), but no statistically significant difference in total MRCI score (p=0.368) was found when comparing patients who used PIM and those who do not. Nevertheless, subtotal B from the MCRI score was different in these patients (p=0.047).
No statistically significant differences in age, gender, polymedication, and interactions, were observed when comparing patients who used PIM and those who do not (p>0.05). Table 3 presents the comparisons between patients using PIM and those who do not use PIM.
PIM from the EU(7)-PIM list were classified according to their ATC. 209 PIM were identified and distributed among seven ATC groups (A, B, C, G, M, N and R). Of the total number of PIM, 49.8% (n=104) belong to central nervous system medications (ATC N) and 29.2% (n=61) to alimentary tract and metabolism medications (ATC A). Within these two groups, the use of anxiolytics (ATC N05B) and drugs to treat peptic ulcers and gastroesophageal reflux (ATC A02B) stood out, accounting for 23.4% (n=49) and 23.9% (n=50), respectively, of the total number of PIM.
Mean PIM in ATC G is significantly lower (p=0.024) in patients ≥85 years old (M=0.19±0.5) than in younger patients (M=0.44±0.67). Similarly, patients ≥85 years old also have lower (p<0.001) PIM in ATC N (M=3±1.79) than younger patients (M=4.8±2.55). Polymedicated patients have a higher (p=0.009) mean number of PIM in ATC A (M=1.6±1.25) than non-polymedicated patients (M=0.6±0.53), and patients with a high pharmacotherapeutic complexity have a higher (p<0.001) PIM in ATC C (M=2.5±1.7) than all other patients (M=1.3±1.1).
Of the patients who use PIM, 53.1% (n=51) use at least one from ATC A and 62.5% (n=60) use at least one from ATC N.

4. Discussion

In this cross-sectional study, we reviewed the medication of elders institutionalized in two ERPI. Our sample primarily consisted of individuals over 80, predominantly women, aligning with demographics reported in similar studies from the United States, Spain, Portugal, France, and Colombia [38,39,40,41]. This demographic trend underscores the critical need for targeted pharmacotherapy management, particularly given the elderly’s propensity for chronic diseases and the consequent polymedication [19,42].
Our data show the use of 9.13±4.15 medicines, ranging from two to 24, in accordance with previous research in Portugal and France suggesting high medication usage among the institutionalized elderly. The Portuguese study reports a mean use of 10.1±3.9 medications, ranging from 5 to 28 [43], and the French study reports a mean of 8.1±4.0, ranging from 1 to 20 medications [44]. However, the tools used to analyze the PIM were different, which may reflect differences in the results. Other studies reflect slight variances in medication usage, emphasizing the complexity of pharmacotherapy in this demographic [23,43].
Pharmacotherapeutic complexity can be assessed considering numerous factors, but the complexity index is one of the few methodologies capable of numerically quantifying this criterion [36,45,46] and is validated for Portuguese [36]. Studies from Brazil and Portugal reported similar MRCI means to the one in our data, while Australian studies found higher complexity [47,48,49,50]. The MRCI is instrumental in gauging the challenge each pharmacotherapeutic profile presents, and our findings corroborate a direct correlation between MRCI values, the number of medications, and patient age [49,51].
One of the decisive points for a good therapeutic review is the identification of potential drug interactions that could jeopardize clinical conditions and the treatment of pathological conditions [30,52]. Studies carried out in this area show different results in terms of the percentage of institutionalized elderly people with potential drug interactions. Research carried out in Brazil, Greenland and Spain revealed 25.4%, 61.0% and 81.1% of patients, respectively, with potential interactions [53,54,55], although our data showed more than 90% of the sample with potential interactions underscoring the critical need for vigilant drug management in this population. The differences found in potential drug interactions may be due to the assessment tool used. The literature shows that, depending on the tool used to assess potential drug interactions, the results can be different [56,57]. However, Lexidrug® is considered a tool with excellent performance and comprehensiveness in identifying potential drug interactions, according to the scientific literature [58].
Like the potential drug interactions, the various existing tools for assessing PIM make it difficult to compare our data with results from the literature. For instance, a study comparing three PIM identification tools in the same sample found variability between 35.3% and 96.3% in the detection rates of participants with at least one inappropriate medication. PRISCUS list had the lowest identification rate (35.5%), followed by the Beers criteria (90.8%) and finally, the tool with the highest identification rate (96.3%) was the STOPP Criteria [59]. This variability points to a generally high tendency toward prescribing PIM in institutionalized settings, confirmed by our findings (86.5%) and literature suggesting prevalence rates from 79.1% to 96.8% [23,60,61].
Population-based studies involving both institutionalized and non-institutionalized elders reported lower PIM usage (24.1% and 40%) likely due to reduced PIM consumption among the non-institutionalized [62,63,64,65]. The organization and care provided in institutions, the pathologies diagnosed, the greater number of drugs and the classes of drugs prescribed in institutions are pointed to as possible reasons for the differences found in the number of potentially inappropriate drugs between institutionalized and non-institutionalized elderly people [64,65]. A study comparing institutionalized elders and elderly outpatients showed that 82.4% of institutionalized participants where prescribed PIM, while this prevalence was 34.4% in outpatients [66]. This trend was also reported by a Swedish study, which suggested institutionalization as a potential risk factor for the use of PIM and proposing greater attention and care when prescribing drugs for institutionalized elderly people [67]. Contrary results were described in a study carried out in Ontario, Canada, where the number of potentially inappropriate medications in institutionalized elderly people was lower than that found in elderly people in the community. However, clinical pharmaceutical services, such as medication review, are mandatory in institutions for the elderly, which may justify the results found [68].
Moreover, our study aligns with other research indicating that female and polymedicated elderly patients are more likely to receive at least one PIM [60,63,65].
In Portugal, a national study suggested a significant consumption of PIM, with 1232 billion defined daily doses prescribed, resulting in an overall prevalence of 9.20%. This study showed a high consumption of PIMs, particularly anxiolytics and antidepressants, despite the implementation of national measures to prescribe these medicines. In the Algarve region, there seems to be an upward trend in the number of potentially inappropriate medicines [69]. This reality shows that it will be important to implement different measures to improve the safe use of medicines in institutionalized elderly people. Medication reviews could be an important service to implement [64].
Regarding ATC classification of PIM, our data are in accordance with the literature. A study on institutionalized elderly with dementia across eight countries identified major PIM within psycholeptics and drugs treating acid-related disorders (ATC N05 and ATC A02, respectively) [70]. A Portuguese study with institutionalized patients, which also used the EU(7)-PIM List, revealed a similar trend: proton pump inhibitors (A02BC) were the most prescribed PIM (25.8%), followed by anxiolytics (N05BA, 20.5%) [23]. Another study carried out using three different tools to identify PIM reported significant prescription of proton pump inhibitors and drugs associated with the nervous system among the PIM detected [59]. As mentioned above, it is to be expected that drugs from the ATC A and N groups are the most prescribed PIM, since they also correspond to the therapeutic groups more often used by institutionalized elderly people.
Regarding the number of medications used and the prescription of PIM, our results are also in accordance with the literature, such as a population-based study suggesting a significant association between these two variables (p<0.001) and higher mean medications in use by patients with PIM (7.7 vs. 5.6) [61]. Furthermore, regarding pharmacotherapeutic complexity, the literature suggests that the presence of PIM is also associated with a likelihood of higher MCI in institutionalized elderly (p<0.001) [48].
Our findings suggest that elderly patients below 85 years old use more PIM, as a study reporting a similar trend for patients under 70 [71]. This may reflect a tendency to prescribe fewer medications to older individuals [72,73].
We identify some limitations in our study. Even if this was not an objective in our study, our data does not allow us to conduct an in-depth analysis of the clinical variables and of the assumptions and reasons for the prescription of some medications. The non-random nature of the sample implies limited external validity for our results and our findings should be considered according to context. We cannot extrapolate for the institutionalized elderly population in the Algarve region, but this pilot study allowed us to assess the applicability of the data collection tools on this population and to carry out a type 2B medication review.

5. Conclusions

This study highlighted several key challenges associated with pharmacotherapeutics in the elderly, such as the excessive number of medicines prescribed, high therapeutic complexity, the frequent use of PIM, and a high prevalence of potential drug interactions.
Medication review is a critical intervention for preventing and correcting issues associated with medication use, particularly among the elderly, who are often subjected to polymedication. This clinical practice is essential to prevent the exacerbation of chronic illnesses and the overall decline in health status among older adults.
Medication review is an accessible and advantageous tool aimed at therapeutic success, and its benefits extend beyond the identification and correction of drug-related problems; they also contribute significantly to improving the physical condition and overall well-being of patients. Despite its clear benefits, our results suggest that medication review may remain underutilized within care institutions. This underscores a critical gap in practice that needs addressing. Enhancing awareness and understanding of medication review’s benefits among healthcare providers and institutional managers is essential. A broader dissemination of this practice should be considered, in order to contributing to integrate it as a standard component of elderly care, ensuring that elderly patients receive the most appropriate, effective, and safe pharmacotherapy possible. It is therefore important to sensitize health students at undergraduate level to the im-portance of medication review and interdisciplinarity in this process.

Author Contributions

Conceptualization, T.N. and H.L.; methodology, T.N., H.L. and E.P; formal analysis, A.A. and E.P; investigation, A.A. and C.C.; writing—original draft preparation, A.A, C.C, T.N. and E.P.; writing—review and editing, T.N., H.L and E.P; All authors have read and agreed to the published version of the manuscript.”

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of ABC Health Ethics Commission (CES-ABC) (Date of approval: 14/03/2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Due to privacy restrictions, the data presented in this study are only available on request from the corresponding author.

Acknowledgments

We thank the institutions for the support provided in the data collection process and for permitting us to conduct this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. H: Nations; Department of Economic and Social Affairs World Population Ageing 2019, 2019.
  2. INE; PORDATA Dados Sobre o Índice de Envelhecimento Em Portugal | Pordata Available online:. Available online: https://www.pordata.pt/portugal/indice+de+envelhecimento+e+outros+indicadores+de+envelhecimento-526 (accessed on 6 May 2024).
  3. Organization World Health Percentage of Total Population Aged 60 Years or Over Available online:. Available online: https://platform.who.int/data/maternal-newborn-child-adolescent-ageing/indicator-explorer-new/mca/percentage-of-total-population-aged-60-years-or-over (accessed on 25 June 2023).
  4. Padula, C.A. Self-Care and the Elderly: Review and Implications. Public Health Nurs 1992, 9, 22–28. [Google Scholar] [CrossRef] [PubMed]
  5. LeBlanc, R.G.; Jacelon, C.S. Self-Care among Older People Living with Chronic Conditions. Int J Older People Nurs 2018, 13. [Google Scholar] [CrossRef] [PubMed]
  6. Ministério da Solidariedade e da Segurança Social Portaria n. 2012.
  7. Davies, L.E.; Spiers, G.; Kingston, A.; Todd, A.; Adamson, J.; Hanratty, B. Adverse Outcomes of Polypharmacy in Older People: Systematic Review of Reviews. J Am Med Dir Assoc 2020, 21, 181–187. [Google Scholar] [CrossRef] [PubMed]
  8. 2019.
  9. Lee, E.A.; Brettler, J.W.; Kanter, M.H.; Steinberg, S.G.; Khang, P.; Distasio, C.C.; Martin, J.; Dreskin, M.; Thompson, N.H.; Cotter, T.M.; et al. Refining the Definition of Polypharmacy and Its Link to Disability in Older Adults: Conceptualizing Necessary Polypharmacy, Unnecessary Polypharmacy, and Polypharmacy of Unclear Benefit. Perm J 2020, 24. [Google Scholar] [CrossRef]
  10. Varghese, D.; Ishida, C.; Haseer Koya, H. 2023.
  11. O’Dwyer, M.; Peklar, J.; Mccallion, P.; Mccarron, M.; Henman, M.C. Factors Associated with Polypharmacy and Excessive Polypharmacy in Older People with Intellectual Disability Differ from the General Population: A Cross-Sectional Observational Nationwide Study. BMJ Open 2016, 6. [Google Scholar] [CrossRef] [PubMed]
  12. Hellemans, L.; Nuyts, S.; Hias, J.; van den Akker, M.; Van Pottelbergh, G.; Rygaert, X.; Spriet, I.; Vaes, B.; Tournoy, J.; Van der Linden, L. Polypharmacy and Excessive Polypharmacy in Community-Dwelling Middle Aged and Aged Adults between 2011 and 2015. Int J Clin Pract 2021, 75. [Google Scholar] [CrossRef]
  13. Wastesson, J.W.; Morin, L.; Tan, E.C.K.; Johnell, K. An Update on the Clinical Consequences of Polypharmacy in Older Adults: A Narrative Review. Expert Opin Drug Saf 2018, 17, 1185–1196. [Google Scholar] [CrossRef] [PubMed]
  14. Chang, T.I.; Park, H.; Kim, D.W.; Jeon, E.K.; Rhee, C.M.; Kalantar-Zadeh, K.; Kang, E.W.; Kang, S.W.; Han, S.H. Polypharmacy, Hospitalization, and Mortality Risk: A Nationwide Cohort Study. Sci Rep 2020, 10. [Google Scholar] [CrossRef] [PubMed]
  15. Laberge, M.; Sirois, C.; Lunghi, C.; Gaudreault, M.; Nakamura, Y.; Bolduc, C.; Laroche, M.L. Economic Evaluations of Interventions to Optimize Medication Use in Older Adults with Polypharmacy and Multimorbidity: A Systematic Review. Clin Interv Aging 2021, 16, 767–779. [Google Scholar] [CrossRef] [PubMed]
  16. Hatah, E.; Braund, R.; Tordoff, J.; Duffull, S.B. A Systematic Review and Meta-Analysis of Pharmacist-Led Fee-for-Services Medication Review. Br J Clin Pharmacol 2014, 77, 102–115. [Google Scholar] [CrossRef]
  17. Rodrigues, A.R.; Teixeira-Lemos, E.; Mascarenhas-Melo, F.; Lemos, L.P.; Bell, V. Pharmacist Intervention in Portuguese Older Adult Care. Healthcare (Switzerland) 2022, 10. [Google Scholar] [CrossRef] [PubMed]
  18. Cerreta, F.; Vučić, K.; Laslop, A. Assessing Medicines for Use in the Geriatric Population. Clin Pharmacol Ther 2023, 113, 536–540. [Google Scholar] [CrossRef] [PubMed]
  19. Kim, J.; Parish, A.L. Polypharmacy and Medication Management in Older Adults. Nursing Clinics of North America 2017, 52, 457–468. [Google Scholar] [CrossRef] [PubMed]
  20. Thorell, K.; Midlöv, P.; Fastbom, J.; Halling, A. Use of Potentially Inappropriate Medication and Polypharmacy in Older Adults: A Repeated Cross-Sectional Study. BMC Geriatr 2020, 20. [Google Scholar] [CrossRef] [PubMed]
  21. Laroche, M.L.; Charmes, J.P.; Merle, L. Potentially Inappropriate Medications in the Elderly: A French Consensus Panel List. Eur J Clin Pharmacol 2007, 63, 725–731. [Google Scholar] [CrossRef] [PubMed]
  22. Renom-Guiteras, A.; Meyer, G.; Thürmann, P.A. The EU(7)-PIM List: A List of Potentially Inappropriate Medications for Older People Consented by Experts from Seven European Countries. Eur J Clin Pharmacol 2015, 71, 861–875. [Google Scholar] [CrossRef]
  23. Plácido, A.I.; Aguiar, A.; Piñeiro-Lamas, M.; Varallo, F.; Figueiras, A.; Herdeiro, M.T.; Roque, F. Assessment of Potentially Inappropriate Medications Using the EU (7)-PIM List, in a Sample of Portuguese Older Adults’ Residents in Nursing Homes. Risk Manag Healthc Policy 2022, 15, 1343–1352. [Google Scholar] [CrossRef] [PubMed]
  24. Xing, X.X.; Zhu, C.; Liang, H.Y.; Wang, K.; Chu, Y.Q.; Zhao, L.B.; Jiang, D.C.; Wang, Y.Q.; Yan, S.Y. Associations Between Potentially Inappropriate Medications and Adverse Health Outcomes in the Elderly: A Systematic Review and Meta-Analysis. Annals of Pharmacotherapy 2019, 53, 1005–1019. [Google Scholar] [CrossRef] [PubMed]
  25. Galán Retamal, C.; Garrido Fernández, R.; Fernández Espínola, S.; Ruiz Serrato, A.; García Ordóñez, M.A.; Padilla Marín, V. Prevalencia de Medicación Potencialmente Inapropiada En Pacientes Ancianos Hospitalizados Utilizando Criterios Explícitos. Farmacia Hospitalaria 2014, 38, 305–316. [Google Scholar] [CrossRef]
  26. Morin, L.; Laroche, M.L.; Texier, G.; Johnell, K. Prevalence of Potentially Inappropriate Medication Use in Older Adults Living in Nursing Homes: A Systematic Review. J Am Med Dir Assoc 2016, 17, e1–e862. [Google Scholar] [CrossRef]
  27. Redston, M.R.; Hilmer, S.N.; McLachlan, A.J.; Clough, A.J.; Gnjidic, D. Prevalence of Potentially Inappropriate Medication Use in Older Inpatients with and without Cognitive Impairment: A Systematic Review. J Alzheimers Dis 2018, 61, 1639–1652. [Google Scholar] [CrossRef] [PubMed]
  28. Fernández Regueiro, R.; Estrada Menéndez, C.; Morís de la Tassa, J. Impact of an Intervention Program to Improve Potentially Inappropriate Prescription in Hospitalized Elderly Patients. Rev Clin Esp 2019, 219, 375–385. [Google Scholar] [CrossRef] [PubMed]
  29. Reinhild Haerig, T.; Krause, D.; Klaassen-Mielke, R.; Rudolf, H.; Trampisch, H.J.; Thuermann, P. Potentially Inappropriate Medication Including Drug-Drug Interaction and the Risk of Frequent Falling, Hospital Admission, and Death in Older Adults - Results of a Large Cohort Study (GetABI). Front Pharmacol 2023, 14. [Google Scholar] [CrossRef] [PubMed]
  30. Bulajeva, A.; Labberton, L.; Leikola, S.; Pohjanoksa-Mäntylä, M.; Geurts, M.M.E.; de Gier, J.J.; Airaksinen, M. Medication Review Practices in European Countries. Res Social Adm Pharm 2014, 10, 731–740. [Google Scholar] [CrossRef] [PubMed]
  31. Griese-Mammen, N.; Hersberger, K.E.; Messerli, M.; Leikola, S.; Horvat, N.; van Mil, J.W.F.; Kos, M. PCNE Definition of Medication Review: Reaching Agreement. Int J Clin Pharm 2018, 40, 1199–1208. [Google Scholar] [CrossRef] [PubMed]
  32. Beuscart, J.-B.; Pelayo, S.; Robert, L.; Thevelin, S.; Marien, S.; Dalleur, O. Medication Review and Reconciliation in Older Adults. Eur Geriatr Med 2021, 12, 499–507. [Google Scholar] [CrossRef] [PubMed]
  33. WHO Collaborating Centre for Drug Statistics Methodology ATC Classification Index with DDDs Available online:. Available online: https://www.whocc.no/atc_ddd_index/ (accessed on 5 September 2023).
  34. Wolters Kluwer Lexicomp Drug Interactions Module Available online:. Available online: https://www.wolterskluwer.com/en/solutions/lexicomp/resources/facts-comparisons-user-academy/drug-interactions (accessed on 9 September 2023).
  35. Rodrigues, D.A.; Herdeiro, M.T.; Thurmann, P.A.; Figueiras, A.; Coutinho, P.; Roque, F. Operationalisation for Portugal of the EU(7)-PIM List for Identification of Potentially Inappropriate Medicines in Older Adults. Acta Med Port 2020, 33. [Google Scholar] [CrossRef] [PubMed]
  36. Melchiors, A.C.; Correr, C.J.; Fernández-Llimos, F. Translation and Validation into Portuguese Language of the Medication Regimen Complexity Index. Arq Bras Cardiol 2007, 89. [Google Scholar] [CrossRef] [PubMed]
  37. Pantuzza, L.L.N.; Ceccato, M. das G.B.; Silveira, M.R.; Pinto, I.V.L.; Reis, A.M.M. Validation and Standardization of the Brazilian Version of the Medication Regimen Complexity Index for Older Adults in Primary Care. Geriatr Gerontol Int 2018, 18, 853–859. [Google Scholar] [CrossRef]
  38. Riquelme-Marín, A.; Martín-Carbonell, M.; Ortigosa-Quiles, J.M.; Fernández-Daza, M.; Méndez, I. Family Care Prior to the Admission of the Elderly in a Nursing Home and Continuity in Family Care: A Comparative Study of Colombia and Spain. Heliyon 2022, 8, e09677. [Google Scholar] [CrossRef]
  39. National Center for Health Statistics (U.S.) Long-Term Care Providers and Services Users in the United States, 2015-2016; 2019; ISBN 084060694X.
  40. Boucaud-Maitre, D.; Meillon, C.; Letenneur, L.; Villeneuve, R.; Dartigues, J.F.; Amieva, H.; Tabue-Teguo, M. Health Trajectories of Elderly Living in French Senior Housing: A Longitudinal Perspective. Sci Rep 2023, 13. [Google Scholar] [CrossRef]
  41. Silva, C.; Ramalho, C.; Luz, I.; Monteiro, J.; Fresco, P. Drug-Related Problems in Institutionalized, Polymedicated Elderly Patients: Opportunities for Pharmacist Intervention. Int J Clin Pharm 2015, 37, 327–334. [Google Scholar] [CrossRef] [PubMed]
  42. ELDesoky, E.S. Pharmacokinetic-Pharmacodynamic Crisis in the Elderly. Am J Ther 2007, 14, 488–498. [Google Scholar] [CrossRef]
  43. da Costa, F.A.; Periquito, C.; Carneiro, M.C.; Oliveira, P.; Fernandes, A.I.; Cavaco-Silva, P. Potentially Inappropriate Medications in a Sample of Portuguese Nursing Home Residents: Does the Choice of Screening Tools Matter? Int J Clin Pharm 2016, 38, 1103–1111. [Google Scholar] [CrossRef]
  44. Rousseau, A.; Rybarczyk-Vigouret, M.C.; Vogel, T.; Lang, P.O.; Michel, B. Prescriptions et Administrations Inappropriées de Médicaments Dans Dix Établissements Alsaciens d’hébergement Pour Personnes Âgées Dépendantes - France. Rev Epidemiol Sante Publique 2016, 64, 95–101. [Google Scholar] [CrossRef] [PubMed]
  45. Brysch, E.G.; Cauthon, K.A.B.; Kalich, B.A.; Sarbacker, G.B. Medication Regimen Complexity Index in the Elderly in an Outpatient Setting: A Literature Review. The Consultant Pharmacist 2018, 33, 484–496. [Google Scholar] [CrossRef] [PubMed]
  46. Wurmbach, V.S.; Schmidt, S.J.; Lampert, A.; Bernard, S.; Meid, A.D.; Frick, E.; Metzner, M.; Wilm, S.; Mortsiefer, A.; Bücker, B.; et al. Prevalence and Patient-Rated Relevance of Complexity Factors in Medication Regimens of Community-Dwelling Patients with Polypharmacy. Eur J Clin Pharmacol 2022, 78, 1127–1136. [Google Scholar] [CrossRef]
  47. Chen, E.Y.H.; Simon Bell, J.; Ilomaki, J.; Keen, C.; Corlis, M.; Hogan, M.; Emden, J. Van; Hilmer, S.N.; Sluggett, J.K. Medication Regimen Complexity in 8 Australian Residential Aged Care Facilities: Impact of Age, Length of Stay, Comorbidity, Frailty, and Dependence in Activities of Daily Living. Clin Interv Aging 2019, 14, 1783–1795. [Google Scholar] [CrossRef]
  48. Alves-Conceição, V.; da Silva, D.T.; de Santana, V.L.; dos Santos, E.G.; Santos, L.M.C.; de Lyra, D.P. Evaluation of Pharmacotherapy Complexity in Residents of Long-Term Care Facilities: A Cross-Sectional Descriptive Study. BMC Pharmacol Toxicol 2017, 18. [Google Scholar] [CrossRef] [PubMed]
  49. Advinha, A.M.; De Oliveira-Martins, S.; Mateus, V.; Pajote, S.G.; Lopes, M.J. Medication Regimen Complexity in Institutionalized Elderly People in an Aging Society. Int J Clin Pharm 2014, 36, 750–756. [Google Scholar] [CrossRef]
  50. Herson, M.; Bell, J.S.; Tan, E.C.K.; Emery, T.; Robson, L.; Wimmer, B.C. Factors Associated with Medication Regimen Complexity in Residents of Long-Term Care Facilities. Eur Geriatr Med 2015, 6, 561–564. [Google Scholar] [CrossRef]
  51. Pantuzza, L.L.; Ceccato, M. das G.B.; Silveira, M.R.; Junqueira, L.M.R.; Reis, A.M.M. Association between Medication Regimen Complexity and Pharmacotherapy Adherence: A Systematic Review. Eur J Clin Pharmacol 2017, 73, 1475–1489. [Google Scholar] [CrossRef]
  52. Mallet, L.; Spinewine, A.; Huang, A. The Challenge of Managing Drug Interactions in Elderly People. Lancet 2007, 370, 185–191. [Google Scholar] [CrossRef] [PubMed]
  53. Cavalcante, M.L.S.N.; Alcântara, R.K.L. de; Oliveira, I.C.L. de; Aires, S.F.; Girão, A.L.A.; Carvalho, R.E.F.L. de Drug Safety among Institutionalized Elderly People: Potential Interactions. Escola Anna Nery 2020, 24. [Google Scholar] [CrossRef]
  54. Albertsen, N.; Sommer, T.G.; Olsen, T.M.; Prischl, A.; Kallerup, H.; Andersen, S. Polypharmacy and Potential Drug–Drug Interactions among Greenland’s Care Home Residents. Ther Adv Drug Saf 2022, 13. [Google Scholar] [CrossRef] [PubMed]
  55. Díez, R.; Cadenas, R.; Susperregui, J.; Sahagún, A.M.; Fernández, N.; García, J.J.; Sierra, M.; López, C. Drug-Related Problems and Polypharmacy in Nursing Home Residents: A Cross-Sectional Study. Int J Environ Res Public Health 2022, 19. [Google Scholar] [CrossRef]
  56. Marcath, L.A.; Xi, J.; Hoylman, E.K.; Kidwell, K.M.; Kraft, S.L.; Hertz, D.L. Comparison of Nine Tools for Screening Drug-Drug Interactions of Oral Oncolytics. J Oncol Pract 2018, 14, e368–e374. [Google Scholar] [CrossRef]
  57. Günay, A.; Demirpolat, E.; Ünal, A.; Aycan, M.B. A Comparison of Four Drug-Drug Interaction Databases for Patients Undergoing Haematopoietic Stem Cell Transplantation. J Clin Pharm Ther 2022, 47, 1711–1719. [Google Scholar] [CrossRef]
  58. Gabay, M.; Spencer, S.H. S: Interactions, 2021.
  59. Díez, R.; Cadenas, R.; Susperregui, J.; Sahagún, A.M.; Fernández, N.; García, J.J.; Sierra, M.; López, C. Potentially Inappropriate Medication and Polypharmacy in Nursing Home Residents: A Cross-Sectional Study. J Clin Med 2022, 11. [Google Scholar] [CrossRef]
  60. Schneider, R.; Reinau, D.; Schur, N.; Blozik, E.; Früh, M.; Signorell, A.; Meier, C.R.; Schwenkglenks, M. Drug Prescription Patterns, Polypharmacy and Potentially Inappropriate Medication in Swiss Nursing Homes: A Descriptive Analysis Based on Claims Data. Swiss Med Wkly 2019, 149, w20126. [Google Scholar] [CrossRef]
  61. Jang, S.; Ah, Y.M.; Jang, S.; Kim, Y.; Lee, J.Y.; Kim, J.H. Potentially Inappropriate Medication Use and Associated Factors in Residents of Long-Term Care Facilities: A Nationwide Cohort Study. Front Pharmacol 2023, 13. [Google Scholar] [CrossRef] [PubMed]
  62. Grina, D.; Briedis, V. The Use of Potentially Inappropriate Medications among the Lithuanian Elderly According to Beers and EU(7)-PIM List – a Nationwide Cross-Sectional Study on Reimbursement Claims Data. J Clin Pharm Ther 2017, 42, 195–200. [Google Scholar] [CrossRef] [PubMed]
  63. Drusch, S.; Zureik, M.; Herr, M. Potentially Inappropriate Medications and Polypharmacy in the Older Population: A Nationwide Cross-Sectional Study in France in 2019. Therapies 2023. [Google Scholar] [CrossRef] [PubMed]
  64. Bony, H.; Lloyd, R.A.; Hotham, E.D.; Corre, L.J.; Corlis, M.E.; Loffler, H.A.; Scarlett, G.K.; Tsimbinos, J.M.; Todd, I.P.; Suppiah, V. Differences in the Prescribing of Potentially Inappropriate Medicines in Older Australians: Comparison of Community Dwelling and Residential Aged Care Residents. Sci Rep 2020, 10, 10170. [Google Scholar] [CrossRef]
  65. Drusch, S.; Le Tri, T.; Ankri, J.; Michelon, H.; Zureik, M.; Herr, M. Potentially Inappropriate Medications in Nursing Homes and the Community Older Adults Using the French Health Insurance Databases. Pharmacoepidemiol Drug Saf 2023, 32, 475–485. [Google Scholar] [CrossRef] [PubMed]
  66. Primejdie, D.P.; Bojita, M.T.; Popa, A. Potentially Inappropriate Medications in Elderly Ambulatory and Institutionalized Patients: An Observational Study. BMC Pharmacol Toxicol 2016, 17. [Google Scholar] [CrossRef] [PubMed]
  67. Haasum, Y.; Fastbom, J.; Johnell, K. Institutionalization as a Risk Factor for Inappropriate Drug Use in the Elderly: A Swedish Nationwide Register-Based Study. Annals of Pharmacotherapy 2012, 46, 339–346. [Google Scholar] [CrossRef]
  68. Lane, C.J.; Bronskill, S.E.; Sykora, K.; Dhalla, I.A.; Anderson, G.M.; Mamdani, M.M.; Gill, S.S.; Gurwitz, J.H.; Rochon, P.A. Potentially Inappropriate Prescribing in Ontario Community-Dwelling Older Adults and Nursing Home Residents. J Am Geriatr Soc 2004, 52, 861–866. [Google Scholar] [CrossRef] [PubMed]
  69. Rodrigues, D.A.; Plácido, A.I.; Tavares, A.B.; Azevedo, D.; Mateos-Campos, R.; Figueiras, A.; Herdeiro, M.T.; Roque, F. Potentially Inappropriate Medication Prescribing in Older Adults According to EU(7)-Potentially Inappropriate Medication List: A Nationwide Study in Portugal. Curr Ther Res Clin Exp 2022, 97. [Google Scholar] [CrossRef]
  70. Renom-Guiteras, A.; Thürmann, P.A.; Miralles, R.; Klaaßen-Mielke, R.; Thiem, U.; Stephan, A.; Bleijlevens, M.H.C.; Jolley, D.; Leino-Kilpi, H.; Rahm Hallberg, I.; et al. Potentially Inappropriate Medication among People with Dementia in Eight European Countries. Age Ageing 2018, 47, 68–74. [Google Scholar] [CrossRef]
  71. Almeida, T.A.; Reis, E.A.; Pinto, I.V.L.; Ceccato, M. das G.B.; Silveira, M.R.; Lima, M.G.; Reis, A.M.M. Factors Associated with the Use of Potentially Inappropriate Medications by Older Adults in Primary Health Care: An Analysis Comparing AGS Beers, EU(7)-PIM List, and Brazilian Consensus PIM Criteria. Research in Social and Administrative Pharmacy 2019, 15, 370–377. [Google Scholar] [CrossRef] [PubMed]
  72. Cadogan, C.A.; Murphy, M.; Boland, M.; Bennett, K.; McLean, S.; Hughes, C. Prescribing Practices, Patterns, and Potential Harms in Patients Receiving Palliative Care: A Systematic Scoping Review. Exploratory Research in Clinical and Social Pharmacy 2021, 3. [Google Scholar] [CrossRef] [PubMed]
  73. Peralta, T.; Castel-Branco, M.M.; Reis-Pina, P.; Figueiredo, I.V.; Dourado, M. Prescription Trends at the End of Life in a Palliative Care Unit: Observational Study. BMC Palliat Care 2022, 21. [Google Scholar] [CrossRef] [PubMed]
Table 1. Age and medication use for all participants and by gender.
Table 1. Age and medication use for all participants and by gender.
Characteristics
(M±SD)
Total sample Females Males p-value
(n=96) (n=66) (n=30)
Age (years) 86.6 ±7.86 87.9 ±6.94 83.7 ±9.04 0.044
No. of medications (total) 9.1 ±4.15 9 ±4.25 9.3 ±4 0.565
5-9 medications n (%) 46 (47.9) 33 (50) 13 (43.3) 0.831c
≥10 medications n (%) 41 (42.7) 27 (40.9) 14 (46.7)
Interactions (total) 10.7 ±10.54 10.7 ±10.92 10.5 ±9.85 0.997
Type A 0.1 ±0.92 0.1 ±1.11 0 ±0.18 0.576
Type B 1.3 ±1.89 1.6 ±2.1 0.9 ±1.22 0.077
Type C 7.9 ±7.68 7.8 ±7.75 8.2 ±7.64 0.809
Type D 1.1 ±2.02 1.1 ±2.05 1.1 ±1.97 0.775
Type X 0.2 ±0.53 0.1 ±0.45 0.3 ±0.66 0.054
MRCI score (total) 19.2 ±9.9 18.6 ±10.02 20.4 ±9.68 0.213
Subtotal A 3.2 ±2.39 2.9 ±2.14 3.9 ±2.76 0.084
Subtotal B 10.3 ±5.26 10.2 ±5.53 10.7 ±4.68 0.342
Subtotal C 5.7 ±3.95 5.6 ±4 5.9 ±3.91 0.625
PIM-EU List 2.2 ±1.56 2.1 ±1.6 2.3 ±1.47 0.395
Characteristics are presented as mean (M) and standard deviation (SD), with noted exceptions; MRCI - Medication Regimen Complexity Index ; PIM - Potentially inappropriate medications; Interactions classified according to Lexidrug® Drug Interaction Module; Gender differences computed with Mann-Whitney’s test except in: c - chi-square test;.
Table 2. Correlations with Medication Regimen Complexity Index (MRCI).
Table 2. Correlations with Medication Regimen Complexity Index (MRCI).
Variable Correlation with total MRCI score
All (n=96) 65-74 (n=9) 75-84 (n=23) 85+ (n=64)
Age -0.219* 0.156 0.550** -0.005
MRCI A 0.598** 0.322 0.526** 0.592**
MRCI B 0.910** 0.987** 0.924** 0.898**
MRCI C 0.859** 0.657 0.896** 0.835**
No. of medications 0.873** 0.928** 0.887** 0.866
Interactions (total) 0.692** 0.450 0.854** 0.608**
Type A 0.079 0.138 0.031
Type B 0.506** 0.479 0.480* 0.579**
Type C 0.639** 0.392 0.885** 0.542**
Type D 0.482** 0.538 0.591** 0.386**
Type X 0.387** 0.143 0.396 0.361**
PIM 0.412** 0.658 0.707** 0.115
PIM - Potentially inappropriate medications; Interactions classified according to Lexidrug® Drug Interaction Module; * - significant correlation at p<0.05; ** - significant correlation at p<0.001.
Table 3. Comparisons between patients with and without potentially inappropriate medications (PIM).
Table 3. Comparisons between patients with and without potentially inappropriate medications (PIM).
Characteristics
(M±SD)
Without PIM Using PIM p-value
(n=13) (n=83)
Age (years) 88.8 ±7.8 86.2 ±7.85 0.245
Gender    Female; n (%) 10 (76.9) 56 (67.5) 0.494c
Male n (%) 3 (23.1) 27 (32.5)
No. of medications 6.8 ±3.26 9.5 ±4.18 0.063
5-9 medications n (%) 6 (46.2) 40 (48.2) 0.172c
≥10 medications n (%) 4 (30.8) 37 (44.6)
Interactions (total) 6.6 ±5.33 11.3 ±11.03 0.187
Type A 0.1 ±0.99 0.574
Type B 0.6 ±96 1.5 ±1.98 0.085
Type C 5.6 ±4.37 8.3 ±8.03 0.462
Type D 0.4 ±0.51 1.2 ±2.14 0.374
Type X 0.2 ±0.56 -
MRCI score (total) 16.2 ±7.47 19.6 ±10.19 0.368
Subtotal A M±SD 3.8 ±2.71 3.1 ±2.34 0.266
Subtotal B M±SD 7.4 ±3.49 10.8 ±5.36 0.047
Subtotal C M±SD 5.1 ±3.38 5.8 ±4.04 0.867
Characteristics are presented as mean (M) and standard deviation (SD), with noted exceptions; MRCI - Medication Regimen Complexity Index ; Interactions classified according to Lexidrug® Drug Interaction Module; Group differences computed with Mann-Whitney’s test except in: c - chi-square test;.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.

Downloads

107

Views

50

Comments

0

Subscription

Notify me about updates to this article or when a peer-reviewed version is published.

Email

Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2025 MDPI (Basel, Switzerland) unless otherwise stated