Potential costs and consequences associated with medication error at hospital discharge: an expert judgement study

Assessing the cost-effectiveness of complex pharmaceutical care interventions and medication error outcomes is hindered by lack of available data on actual outcomes consequent to errors that were intercepted for patient safety reasons. Expert judgement is an approach to acquire data regarding unknown parameters in an economic model which are otherwise insufficient or not possible to obtain. The aim of this paper is to describe a method to approach this problem using findings from a single intervention study and to calculate the potential costs and consequences associated with discharge medication error.

Using data from a previous intervention study, the hypothetical consequences of medication error(s) at hospital discharge, in terms of diagnosis, healthcare resource utilisation and impact on health-related quality of life, were identified by expert judgement of anonymised cases. Primary healthcare utilisation costs were derived from published tariffs, inpatient costs were derived by simulation in the hospital discharge activity database test environment and the difference between adjudicated baseline and posterror health state was expressed as quality-adjusted life year (QALY) decrement.

Four experts provided judgement on 81 cases. Of these, 75 were judged to have potential clinical consequences. Between 56 and 69 of the 81 cases were variably judged to require remedial healthcare utilisation. The mean calculated cost per case (representing an individual patient), based on all 81 cases, was €1009.58, 95% CI 726.64 to 1585.67. The mean QALY loss was 0.03 (95% CI 0.01 to 0.05).

An expert judgement process proved feasible and useful to estimate financial cost and QALY loss associated with hospital discharge medication error. These estimates will be employed in model-based economic evaluation. This method could be transferred to other prospective observational patient safety research which seeks to assess value for money of complex interventions.