BACKGROUND: Although guidelines indicate when patients are eligible for antihypertensives and statins, little is known about whether general practitioners (GPs) follow this guidance. OBJECTIVE: To determine the factors influencing GPs decisions to prescribe cardiovascular prevention drugs. DESIGN OF STUDY: Secondary analysis of data collected on patients whose cardiovascular risk factors were measured as part of a controlled study comparing nurse-led risk assessment (four practices) with GP-led risk assessment (two practices). SETTING: Six general practices in the West Midlands, England. PATIENTS: Five hundred patients: 297 assessed by the project nurse, 203 assessed by their GP. MEASUREMENTS: Cardiovascular risk factor data and whether statins or antihypertensives were prescribed. Multivariable logistic regression models investigated the relationship between prescription of preventive treatments and cardiovascular risk factors. RESULTS: Among patients assessed by their GP, statin prescribing was significantly associated only with a total cholesterol concentration ≥ 7 mmol/L and antihypertensive prescribing only with blood pressure ≥ 160/100 mm Hg. Patients prescribed an antihypertensive by their GP were five times more likely to be prescribed a statin. Among patients assessed by the project nurse, statin prescribing was significantly associated with age, sex, and all major cardiovascular risk factors. Antihypertensive prescribing was associated with blood pressures ≥ 140/90 mm Hg and with 10-year cardiovascular risk. LIMITATIONS: Generalizability is limited, as this is a small analysis in the context of a specific cardiovascular prevention program. CONCLUSIONS: GP prescribing of preventive treatments appears to be largely determined by elevation of a single risk factor. When patients were assessed by the project nurse, prescribing was much more consistent with established guidelines.
BACKGROUND: Although guidelines indicate when patients are eligible for antihypertensives and statins, little is known about whether general practitioners (GPs) follow this guidance. OBJECTIVE: To determine the factors influencing GPs decisions to prescribe cardiovascular prevention drugs. DESIGN OF STUDY: Secondary analysis of data collected on patients whose cardiovascular risk factors were measured as part of a controlled study comparing nurse-led risk assessment (four practices) with GP-led risk assessment (two practices). SETTING: Six general practices in the West Midlands, England. PATIENTS: Five hundred patients: 297 assessed by the project nurse, 203 assessed by their GP. MEASUREMENTS: Cardiovascular risk factor data and whether statins or antihypertensives were prescribed. Multivariable logistic regression models investigated the relationship between prescription of preventive treatments and cardiovascular risk factors. RESULTS: Among patients assessed by their GP, statin prescribing was significantly associated only with a total cholesterol concentration ≥ 7 mmol/L and antihypertensive prescribing only with blood pressure ≥ 160/100 mm Hg. Patients prescribed an antihypertensive by their GP were five times more likely to be prescribed a statin. Among patients assessed by the project nurse, statin prescribing was significantly associated with age, sex, and all major cardiovascular risk factors. Antihypertensive prescribing was associated with blood pressures ≥ 140/90 mm Hg and with 10-year cardiovascular risk. LIMITATIONS: Generalizability is limited, as this is a small analysis in the context of a specific cardiovascular prevention program. CONCLUSIONS: GP prescribing of preventive treatments appears to be largely determined by elevation of a single risk factor. When patients were assessed by the project nurse, prescribing was much more consistent with established guidelines.
Authors: Chris Schilling; Duncan Mortimer; Kim Dalziel; Emma Heeley; John Chalmers; Philip Clarke Journal: Pharmacoeconomics Date: 2016-02 Impact factor: 4.981
Authors: Marlise E A van Eersel; Sipke T Visser; Hanneke Joosten; Ron T Gansevoort; Joris P J Slaets; Gerbrand J Izaks Journal: BMC Neurol Date: 2020-06-12 Impact factor: 2.474