Prescribing Optimization Method for Improving Prescribing in Elderly Patients Receiving Polypharmacy
- 633 Downloads
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of medication indicated; (ii) does the patient adhere to his/her medication schedule; (iii) which drug(s) can be withdrawn or which drugs(s) is/are inappropriate for the patient; (iv) which adverse effects are present; (v) which clinically relevant interactions are to be expected;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?
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.
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.
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).
The POM improves appropriate prescribing of complex polypharmacy in case histories.
KeywordsExpert Panel Linear Mixed Effect Model Inappropriate Medication Medication List Acute Hospital Admission
No sources of funding were used to assist in the conduct or preparation of this study. The authors have no conflicts of interest that are directly relevant to the content of this study. The authors would like to thank E.P. Martens, PhD, for his help with regard to the statistical analysis.
- 1.Stich ting Farmaceutische Kengetallen. Polyfarmacie. Pharm Weekblad 2005; 32: 968Google Scholar
- 26.Nederlands Huisartsen Genootschap. NHG-standaarden [online]. Available from URL: http://nhg.artsennet.nl [Accessed 2009 Jun 24]
- 27.Farmacotherapeutisch Kompas. College voor Zorgverzekeringen [online]. Available from URL: http://www.fk.cvz.nl [Accessed 2009 Jun 24]
- 28.Wetenschappelijk Instituut Nederlandse Apothekers. Koninklijke Maatschappij ter bevordering van de Pharmacie Webrapportages farmacotherapie [online]. Available from URL: http://www.winap.nl [Accessed 2009 Jun 24]
- 29.Centraal BegeleidingsOrgaan voor de intercollegiale toetsing. Kwaliteitsinstituut voor de gezondheidszorg. Richtlijnen [online]. Available from URL: http://www.cbo.nl [Accessed 2009 Jun 24]
- 35.Indiana University Department of Medicine. Division of Clinical Pharmacology. Cytochrome P450 drug interaction table [online]. Available from URL: http://medicine.iupui.edu/flockhart/ [Accessed 2009 Jun 24]
- 37.Fadem SZ. Cockroft Gault calculator [online]. Available from URL: http://nephron.com/cgi-bin/CGSI.cgi [Accessed 2009 Jun 24]
- 40.Koninklijke Nederlandse Maatschappij ter bevordering van de Pharmacie. Kennisbank. G-standaard verminderde nierfunctie. Tabel bij ‘Verminderde nierfunctie. Doseringsadviezen voor geneesmiddelen’ [online]. Available from URL: http://kennisbank.knmp.nl [Accessed 2009 Jun 24]