A novel approach to population-based risk stratification, comprising individualized lifestyle intervention in Danish general practice to prevent chronic diseases:Results from a feasibility study

Early detection of patients at risk seems to be effective for reducing the prevalence of lifestyle-related chronic diseases. We aim to test the feasibility of a novel intervention for early detection of lifestyle-related chronic diseases based on a population-based stratification using a combination of questionnaire and electronic patient record data. The intervention comprises four elements: (1) collection of information on lifestyle risk factors using a short 15-item questionnaire, (2) electronic transfer of questionnaire data to the general practitioners’ electronic patient records, (3) identification of patients already diagnosed with a lifestyle-related chronic disease, and (4) risk estimation and stratification of apparently healthy patients using questionnaire and electronic patient record data on validated risk estimation models. We show that it is feasible to implement a novel intervention that identifies and stratifies patients for further examinations in general practice or behaviour change interventions at the municipal level without any additional workload for the general practitioner. Early detection of patients at risk seems to be effective for reducing the prevalence of lifestyle-related chronic diseases. We aim to test the feasibility of a novel intervention for early detection of lifestyle-related chronic diseases based on a population-based stratification using a combination of questionnaire and electronic patient record data. The intervention comprises four elements: (1) collection of information on lifestyle risk factors using a short 15-item questionnaire, (2) electronic transfer of questionnaire data to the general practitioners' electronic patient records, (3) identification of patients already diagnosed with a lifestyle-related chronic disease, and (4) risk estimation and stratification of apparently healthy patients using questionnaire and electronic patient record data on validated risk estimation models. We show that it is feasible to implement a novel intervention that identifies and stratifies patients for further examinations in general practice or behaviour change interventions at the municipal level without any additional workload for the general practitioner.