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Observational Study
. 2022 Nov 29;19(23):15902.
doi: 10.3390/ijerph192315902.

Comprehensive Multimorbidity Patterns in Older Patients Are Associated with Quality Indicators of Medication-MoPIM Cohort Study

Marina Lleal  1   2 , Marisa Baré  1   3   4 , Sara Ortonobes  5 , Daniel Sevilla-Sánchez  6 , Rosa Jordana  7 , Susana Herranz  8 , Maria Queralt Gorgas  5 , Mariona Espaulella-Ferrer  9 , Marta Arellano  10 , Marta de Antonio  11 , Gloria Julia Nazco  12 , Rubén Hernández-Luis  13 , On Behalf Of The MoPIM Study Group
Affiliations
Observational Study

Comprehensive Multimorbidity Patterns in Older Patients Are Associated with Quality Indicators of Medication-MoPIM Cohort Study

Marina Lleal et al. Int J Environ Res Public Health. .

Abstract

Multimorbidity is increasing and poses a challenge to the clinical management of patients with multiple conditions and drug prescriptions. The objectives of this work are to evaluate if multimorbidity patterns are associated with quality indicators of medication: potentially inappropriate prescribing (PIP) or adverse drug reactions (ADRs). A multicentre prospective cohort study was conducted including 740 older (≥65 years) patients hospitalised due to chronic pathology exacerbation. Sociodemographic, clinical and medication related variables (polypharmacy, PIP according to STOPP/START criteria, ADRs) were collected. Bivariate analyses were performed comparing previously identified multimorbidity clusters (osteoarticular, psychogeriatric, minor chronic disease, cardiorespiratory) to presence, number or specific types of PIP or ADRs. Significant associations were found in all clusters. The osteoarticular cluster presented the highest prevalence of PIP (94.9%) and ADRs (48.2%), mostly related to anxiolytics and antihypertensives, followed by the minor chronic disease cluster, associated with ADRs caused by antihypertensives and insulin. The psychogeriatric cluster presented PIP and ADRs of neuroleptics and the cardiorespiratory cluster indicators were better overall. In conclusion, the associations that were found reinforce the existence of multimorbidity patterns and support specific medication review actions according to each patient profile. Thus, determining the relationship between multimorbidity profiles and quality indicators of medication could help optimise healthcare processes. Trial registration number: NCT02830425.

Keywords: adverse drug reaction; cluster analysis; healthcare quality indicator; multimorbidity; older patient; polypharmacy; potential prescribing omission; potentially inappropriate medication.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(A): Percentage of patients per cluster having the most frequent STOPP PIM criteria. (B): Percentage of patients per cluster having the most frequent START PPO criteria. Fisher’s exact test p-value: p-values are shown in the figure when p < 0.05. Error bars show 95% confidence interval for the estimated proportion. ACE: angiotensin converting enzyme; ARB: angiotensin II receptor blocker; AFib: atrial fibrillation; TCA: tricyclic antidepressant; AChE: acetylcholinesterase.
Figure 2
Figure 2
Percentage of patients per cluster having at least one ADR registered in the most frequent drug families. Fisher’s exact test p-value is shown when p < 0.05. ADR: adverse drug reaction; ACE: angiotensin-converting enzyme; ARB: angiotensin II receptor blocker. Error bars show 95% confidence interval for the estimated proportion.
Figure 3
Figure 3
Proportions of patients per cluster according to the worst consequence suffered in those patients with an ADR during hospitalisation. ADR: adverse drug reaction. Fisher’s Exact Test: p-value = 0.02.
See this image and copyright information in PMC

References

    1. Fortin M., Stewart M., Poitras M.-E., Almirall J., Maddocks H. A Systematic Review of Prevalence Studies on Multimorbidity: Toward a More Uniform Methodology. Ann. Fam. Med. 2012;10:142–151. doi: 10.1370/afm.1337. - DOI - PMC - PubMed
    1. Barnett K., Mercer S.W., Norbury M., Watt G., Wyke S., Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: A cross-sectional study. Lancet. 2012;380:37–43. doi: 10.1016/S0140-6736(12)60240-2. - DOI - PubMed
    1. The Academy of Medical Sciences . Multimorbidity: A Priority For Global Health Research. The Academy of Medical Sciences; London, UK: 2018. [(accessed on 8 August 2022)]. Available online: https://acmedsci.ac.uk/file-download/82222577.
    1. Rijken M., Struckmann V., Van Der Heide I., Hujala A., Barbabella F., Van Ginneken E., Schellevis F. How to Improve Care For People with Multimorbidity in Europe? European Observatory on Health Systems and Policies; Brussels, Belgium: 2016. [(accessed on 8 August 2022)]. Available online: https://www.euro.who.int/en/about-us/partners/observatory/publications/p.... - PubMed
    1. Johnston M.C., Crilly M., Black C., Prescott G.J., Mercer S.W. Defining and measuring multimorbidity: A systematic review of systematic reviews. Eur. J. Public Health. 2019;29:182–189. doi: 10.1093/eurpub/cky098. - DOI - PubMed

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