Prescribing optimization method for improving prescribing in elderly patients receiving polypharmacy: results of application to case histories by general practitioners.

摘要

BACKGROUND: Optimizing polypharmacy is often difficult, and critical appraisal of medication use often leads to one or more changes. We developed the Prescribing Optimization Method (POM) to assist physicians, especially general practitioners (GPs), in their attempts to optimize polypharmacy in elderly patients. The POM is based on six questions: (i) is undertreatment present and addition of medication indicated; (ii) does the patient adhere to his/her medication schedule; (iii) which drug(s) can be withdrawn or which drugs(s) is/are inappropriate for the patient; (iv) which adverse effects are present; (v) which clinically relevant interactions are to be expected; and (vi) should the dose, dose frequency and/or form of the drug be adjusted? OBJECTIVE: The aim of this study was to evaluate the usefulness of the POM as a tool for improving appropriate prescribing of complex polypharmacy in the elderly. METHODS: Forty-five GPs were asked to optimize the medication of two case histories, randomly chosen from ten histories of geriatric patients admitted to a hospital geriatric outpatient clinic with a mean +/- SD of 7.9 +/- 1.2 problems treated with 8.7 +/- 3.1 drugs. The first case was optimized without knowledge of the POM. After a 2-hour lecture on the POM, the GPs used the POM to optimize the medication of the second case history. The GPs were allowed 20 minutes for case optimization. Medication recommendations were compared with those made by an expert panel of four geriatricians specialized in clinical pharmacology. Data were analysed using a linear mixed effects model. RESULTS: Optimization was significantly better when GPs used the POM. The proportion of correct decisions increased from 34.7% without the POM to 48.1% with the POM (p = 0.0037), and the number of potentially harmful decisions decreased from a mean +/- SD of 3.3 +/- 1.8 without the POM to 2.4 +/- 1.4 with the POM (p = 0.0046). CONCLUSION: The POM improves appropriate prescribing of complex polypharmacy in case histories.