OBJECTIVE: To define and validate a battery of prescription indicators on the use of anti-hypertensives, lipid-lowerers, diabetes drugs, and insulin, as measurements of family doctors' quality of prescription in primary health care. DESIGN: Transversal, descriptive study. SETTING: Two primary care health districts, Camas and Sierra Norte, Spain. PARTICIPANTS: Eighty three family doctors, 94.32% of the doctors in the study area. DEFINITION AND VALIDATION OF INDICATORS: To construct the prescription indicators, we used evidence found in the scientific bibliography available. To validate it, we analysed its statistical relationship with a series of selected clinical tests, collected from the clinical records. RESULTS: For each doctor, there was a statistically significant relationship between the index of quality of prescription and the clinical quality seen in the records (P=.004). The variables of age, sex, and training fine-tuned the model. CONCLUSIONS: There is a statistically significant relationship between a good prescription indicator and proper control of intermediate health variables.
OBJECTIVE: To define and validate a battery of prescription indicators on the use of anti-hypertensives, lipid-lowerers, diabetes drugs, and insulin, as measurements of family doctors' quality of prescription in primary health care. DESIGN: Transversal, descriptive study. SETTING: Two primary care health districts, Camas and Sierra Norte, Spain. PARTICIPANTS: Eighty three family doctors, 94.32% of the doctors in the study area. DEFINITION AND VALIDATION OF INDICATORS: To construct the prescription indicators, we used evidence found in the scientific bibliography available. To validate it, we analysed its statistical relationship with a series of selected clinical tests, collected from the clinical records. RESULTS: For each doctor, there was a statistically significant relationship between the index of quality of prescription and the clinical quality seen in the records (P=.004). The variables of age, sex, and training fine-tuned the model. CONCLUSIONS: There is a statistically significant relationship between a good prescription indicator and proper control of intermediate health variables.