RATIONALE, AIMS AND OBJECTIVES: Achieving control over elevated lipid parameters, particularly low-density lipoprotein (LDL)-cholesterol, is an acknowledged quality indicator in primary care. The Centers for Disease Control and Prevention (CDC)'s model for investigation of outbreaks (person-place-time) can be applied to the analysis of quality indicators. METHODS: A sample of 322 family medicine patients for whom lipid levels were ordered was extracted. LDL > 100 mg/dL was cross-tabulated by personal characteristics [age group, gender, body mass index (BMI), diagnoses], month (time) and ordering department (place). RESULTS: Age (except one age category), gender, time and location were not related to LDL > 100 mg/dL after adjustment for covariates. All levels of BMI above normal elevated the risk of LDL > 100 mg/dL [BMI 25-29.9: odds ratio (OR) = 3.41, confidence interval (CI) = 1.61-7.23, P = 0.0014; BMI 30-34.9: OR = 2.93, CI = 1.28-6.70, P = 0.0109; BMI ≥ 35: OR = 2.75, CI = 1.19-6.37, P = 0.0181]. Patients with coronary artery disease (CAD) and diabetes mellitus (DM) were at reduced risk for LDL > 100 mg/dL (CAD: OR = 0.47, CI = 0.24-0.91, P = 0.0254; DM: OR = 0.28, CI = 0.14-0.55, P = 0.0002). CONCLUSION: An outbreak investigation model is useful for analysing variations in this quality indicator. Patients with higher BMI and those not diagnosed with CAD or DM type I/II may be considered for intensified lipid lowering using quality improvement efforts. These might include counselling for lifestyle changes or medication therapy depending upon their calculated cardiac risk.
RATIONALE, AIMS AND OBJECTIVES: Achieving control over elevated lipid parameters, particularly low-density lipoprotein (LDL)-cholesterol, is an acknowledged quality indicator in primary care. The Centers for Disease Control and Prevention (CDC)'s model for investigation of outbreaks (person-place-time) can be applied to the analysis of quality indicators. METHODS: A sample of 322 family medicine patients for whom lipid levels were ordered was extracted. LDL > 100 mg/dL was cross-tabulated by personal characteristics [age group, gender, body mass index (BMI), diagnoses], month (time) and ordering department (place). RESULTS: Age (except one age category), gender, time and location were not related to LDL > 100 mg/dL after adjustment for covariates. All levels of BMI above normal elevated the risk of LDL > 100 mg/dL [BMI 25-29.9: odds ratio (OR) = 3.41, confidence interval (CI) = 1.61-7.23, P = 0.0014; BMI 30-34.9: OR = 2.93, CI = 1.28-6.70, P = 0.0109; BMI ≥ 35: OR = 2.75, CI = 1.19-6.37, P = 0.0181]. Patients with coronary artery disease (CAD) and diabetes mellitus (DM) were at reduced risk for LDL > 100 mg/dL (CAD: OR = 0.47, CI = 0.24-0.91, P = 0.0254; DM: OR = 0.28, CI = 0.14-0.55, P = 0.0002). CONCLUSION: An outbreak investigation model is useful for analysing variations in this quality indicator. Patients with higher BMI and those not diagnosed with CAD or DM type I/II may be considered for intensified lipid lowering using quality improvement efforts. These might include counselling for lifestyle changes or medication therapy depending upon their calculated cardiac risk.