Dataset Information

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study.

ABSTRACT:

Background

Drug interactions increase the risk of treatment failure, intoxication, hospital admissions, consultations and mortality. Computer-assisted prescription systems can help to detect interactions.

Objectives

To describe the drug-drug interaction (DDI) and drug-disease interaction (DdI) prevalence identified by a computer-assisted prescription system in patients with multimorbidity and polypharmacy. Factors associated with clinically relevant interactions were analysed.

Methods

Observational, descriptive, cross-sectional study in primary health care centres was undertaken in Spain. The sample included 593 patients aged 65-74 years with multimorbidity and polypharmacy participating in the MULTIPAP Study, recruited from November 2016 to January 2017. Drug interactions were identified by a computer-assisted prescription system. Descriptive, bivariate, and multivariate analyses with logistic regression models and robust estimators were performed.

Results

Half (50.1% (95% CI 46.1-54.1)) of the patients had at least one relevant DDI and 23.9% (95% CI 18.9-25.6) presented with a DdI. Non-opioid-central nervous system depressant drug combinations and benzodiazepine-opioid drug combinations were the two most common clinically relevant interactions (10.8% and 5.9%, respectively). Factors associated with DDI were the use of more than 10 drugs (OR 11.86; 95% CI 6.92-20.33) and having anxiety/depressive disorder (OR 1.98; 95% CI 1.31-2.98). Protective factors against DDI were hypertension (OR 0.62; 95% CI 0.41-0.94), diabetes (OR 0.57; 95% CI 0.40-0.82), and ischaemic heart disease (OR 0.43; 95% CI 0.25-0.74).

Conclusion

Drug interactions are prevalent in patients aged 65-74 years with multimorbidity and polypharmacy. The clinically relevant DDI frequency is low. The number of prescriptions taken is the most relevant factor associated with presenting a clinically relevant DDI.

SUBMITTER: Rogero-Blanco E

PROVIDER: S-EPMC8128212 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study.

Rogero-Blanco Eloísa E Del-Cura-González Isabel I Aza-Pascual-Salcedo Mercedes M García de Blas González Francisca F Terrón-Rodas Carmen C Chimeno-Sánchez Sergio S García-Domingo Eva E López-Rodríguez Juan A JA

The European journal of general practice 20211201 1

<h4>Background</h4>Drug interactions increase the risk of treatment failure, intoxication, hospital admissions, consultations and mortality. Computer-assisted prescription systems can help to detect interactions.<h4>Objectives</h4>To describe the drug-drug interaction (DDI) and drug-disease interaction (DdI) prevalence identified by a computer-assisted prescription system in patients with multimorbidity and polypharmacy. Factors associated with clinically relevant interactions were analysed.<h4> ...[more]

PMID: 33982632

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Project description:Pharmaceutical prescribing and drug-drug interaction data underlie recommendations on drug combinations that should be avoided or closely monitored by prescribers. Because the number of patients taking multiple medications is increasing, a comprehensive view of prescribing patterns in patients is important to better assess real world pharmaceutical response and evaluate the potential for multi-drug interactions. We obtained self-reported prescription data from NHANES surveys between 1999 and 2010, and confirm the previously reported finding of increasing drug use in the elderly. We studied co-prescription drug trends by focusing on the 2009-2010 survey, which contains prescription data on 690 drugs used by 10,537 subjects. We found that medication profiles were unique for individuals aged 65 years or more, with ≥98 unique drug regimens encountered per 100 subjects taking 3 or more medications. When drugs were viewed by therapeutic class, it was found that the most commonly prescribed drugs were not the most commonly co-prescribed drugs for any of the 16 drug classes investigated. We cross-referenced these medication lists with drug interaction data from Drugs.com to evaluate the potential for drug interactions. The number of drug alerts rose proportionally with the number of co-prescribed medications, rising from 3.3 alerts for individuals prescribed 5 medications to 11.7 alerts for individuals prescribed 10 medications. We found 22% of elderly subjects taking both a substrate and inhibitor of a given cytochrome P450 enzyme, and 4% taking multiple inhibitors of the same enzyme simultaneously. By examining drug pairs prescribed in 0.1% of the population or more, we found low agreement between co-prescription rate and co-discussion in the literature. These data show that prescribing trends in treatment could drive a large extent of individual variability in drug response, and that current pairwise approaches to assessing drug-drug interactions may be inadequate for predicting real world outcomes.

Dataset Information

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study.

Background

Objectives

Methods

Results

Conclusion

Publications

Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study.

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