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J Health Serv Res Policy. 2008 Apr;13(2):85-91. doi: 10.1258/jhsrp.2007.007011.

Modelling the expected net benefits of interventions to reduce the burden of medication errors.

Author information

1
Department of Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, UK. j.karnon@sheffield.ac.uk

Abstract

OBJECTIVES:

The aim of this study is to estimate the potential costs and benefits of three key interventions (computerized physician order entry [CPOE], additional ward pharmacists and bar coding) to help prioritize research to reduce medication errors.

METHODS:

A generic model structure was developed to describe the incidence and impacts of medication errors in hospitals. The model follows pathways from medication error points at alternative stages of the medication pathway through to the outcomes of undetected errors. The model was populated from a systematic review of the medication errors literature combined with novel probabilistic calibration methods. Cost ranges were applied to the interventions, the treatment of preventable adverse drug events (pADEs), and the value of the health lost as a result of an ADE.

RESULTS:

The model predicts annual health service costs of between pound 0.3 million and pound 1 million for the treatment of pADEs in a 400-bed acute hospital in the UK. Including only health service costs, it is uncertain whether any of the three interventions will produce positive net benefits, particularly if high intervention costs are assumed. When the monetary value of lost health is included, all three interventions have a high probability of producing positive net benefits with a mean estimate of around pound 31.5 million for CPOE over a five-year time horizon.

CONCLUSIONS:

The results identify the potential cost-effectiveness of interventions aimed at medication errors, as well as identifying key drivers of cost-effectiveness that should be specifically addressed in the design of primary evaluations of medication error interventions.

PMID:
18416913
DOI:
10.1258/jhsrp.2007.007011
[Indexed for MEDLINE]

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