Validity of performance indicators for assessing prescribing quality: the case of XXXX .

@entity1 @entity565 @entity2286 @entity102 @entity288
OBJECTIVES: The aim of this study was to assess the concurrent validity between the identification of sub-optimal treatment based on clinical information and computer generated indicators. Indicators that are associated with sub-optimal treatment in one of the four steps of @entity565 management were assessed. DESIGN: The ability of each indicator to identify @entity1 with sub-optimal @entity565 treatment from computerised general practitioner (GP) prescription records was assessed by comparing them with the results of an individual @entity1 assessment using clinical data. SETTING: @entity102 @entity1 ( n=146) registered with 16 Dutch GPs. MAIN MEASURES: The sensitivity and positive predictive value ( @entity2286 ) of each performance indicator was determined. RESULTS: The step-1 indicator, focusing on @entity1 not prescribed a short-acting beta-agonist, had an acceptable sensitivity (0.86), but a low @entity2286 (0.52). The two step-2 indicators, targeting under-prescription of inhaled @entity288 , had sensitivities of 0.74 and 0.37 and PPVs of 0.46 and 0.71, respectively. The step-3 indicator, which targeted under-dosing of inhaled @entity288 , had a sensitivity of 0.07 and a @entity2286 of 0.2. The fourth indicator, focusing on under-prescription of long-acting beta-agonists, could not be validated due to inadequate numbers of @entity1 with severe @entity565 in our study sample. DISCUSSION: None of the indicators investigated was considered valid for assessing prescriber performance, despite having good face and content validity. Performance indicators that have not been validated can only provide a broad-brush approach for assessing prescribing quality and should be used with extreme caution.
