ArticleInternational journal of clinical pharmacy2018
Identification of variables influencing pharmaceutical interventions to improve medication review efficiency.
Article in International journal of clinical pharmacy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Assessment of a hybrid decision support system using machine learning with artificial intelligence to safely rule out prescriptions from medication review in daily practice.International journal of clinical pharmacy · 2022Trial
- "Doctor, would it surprise you if there were prescribing errors in this patient's medication?" Identifying eligible patients for in-hospital pharmacotherapeutic stewardship: A matched case-control study.British journal of clinical pharmacology · 2025Article
- A machine learning-based clinical predictive tool to identify patients at high risk of medication errors.Scientific reports · 2024Article
- Prioritizing patients for medication review by emergency department pharmacists: a multi-method study.International journal of clinical pharmacy · 2023Article
- A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.Journal of the American Medical Informatics Association : JAMIA · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Clinical pharmacists' involvement has improved patients' care, by suggesting therapeutic optimizations. However, budget restrictions require a prioritization of these activities to focus resources on patients more at risk of medication errors. Objective The aim of our study was to identify variables influencing the formulation of pharmaceutical to improve medication review efficiency. Setting This study was conducted in medical wards of a 643-acute beds hospital in Paris, France. Methods All hospital medical prescriptions of all patients admitted within four medical wards (cardiology, rheumatology, neurology, vascular medicine) were analyzed. The study was conducted in each ward for 2 weeks, during 4 weeks. For each patient, variables prospectively collected were: age, gender, weight, emergency admission, number of high-alert medications and of total drugs prescribed, care unit, serum creatinine. Number of pharmaceutical interventions (PIs) and their type were reported. Main outcome measures Variables influencing the number of pharmaceutical interventions during medication review were identified using simple and multiple linear regressions. Results A total of 2328 drug prescriptions (303 patients, mean age 70.6 years-old) were analyzed. Mean number of hospital drug prescriptions was 7.9. A total of 318 PIs were formulated. Most frequent PIs were drug omission (n = 88, 27.7%), overdosing (n = 69, 21.7%), and underdosing (n = 51, 16.0%). Among variables studied, age, serum creatinine level, number of high-alert medications prescribed and total number of drugs prescribed were significantly associated with the formulation of pharmaceutical interventions (adjusted R
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