Literature DB >> 29860706

Identification of variables influencing pharmaceutical interventions to improve medication review efficiency.

Lauriane Cornuault1, Victorine Mouchel1, Thuy-Tan Phan Thi1, Hélène Beaussier1, Yvonnick Bézie1, Jennifer Corny2.   

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 R2 = 0.34). Conclusions This study identified variables (age, serum creatinine level, number of high-alert medication, number of prescribed drugs) that may help institutions/pharmacists target their reviews towards patients most likely to require pharmacist interventions.

Entities:  

Keywords:  Clinical pharmacy; France; Hospital pharmacy; Medication review; Prioritization

Mesh:

Year:  2018        PMID: 29860706     DOI: 10.1007/s11096-018-0668-y

Source DB:  PubMed          Journal:  Int J Clin Pharm


  9 in total

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5.  Drug errors and related interventions reported by United States clinical pharmacists: the American College of Clinical Pharmacy practice-based research network medication error detection, amelioration and prevention study.

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9.  Pharmacists' Perceptions of the Barriers and Facilitators to the Implementation of Clinical Pharmacy Key Performance Indicators.

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  9 in total
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1.  Assessment of a hybrid decision support system using machine learning with artificial intelligence to safely rule out prescriptions from medication review in daily practice.

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2.  A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.

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  2 in total

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