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Cardiometabolic prevention consultation in the Netherlands: screening uptake and detection of cardiometabolic risk factors and diseases - a pilot study.
Meer, V. van der, Nielen, M.M.J., Drenthen, A.J.M., Vliet, M. van, Assendelft, W.J.J., Schellevis, F.G. Cardiometabolic prevention consultation in the Netherlands: screening uptake and detection of cardiometabolic risk factors and diseases - a pilot study. BMC Family Practice: 2013, 14(29)
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Background: Until now, cardiometabolic risk assessment in Dutch primary health care was directed at case-finding, and structured, programmatic prevention is lacking. Therefore, the Prevention Consultation cardiometabolic risk (PC CMR), a stepwise approach to identify and manage patients with cardiometabolic risk factors, was developed. The aim of this study was 1) to evaluate uptake rates of the two steps of the PC CMR, 2) to assess the rates of newly diagnosed hypertension, hypercholesterolemia, diabetes mellitus and chronic kidney disease and 3) to explore reasons for non-participation. Methods: Sixteen general practices throughout the Netherlands were recruited to implement the PC CMR during 6 months. In eight practices eligible patients aged between 45 and 70 years without a cardiometabolic disease were actively invited by a personal letter ('active approach') and in eight other practices eligible patients were informed about the PC CMR only by posters and leaflets in the practice ('passive approach'). Participating patients completed an online risk estimation (first step). Patients estimated as having a high risk according to the online risk estimation were advised to visit their general practice to complete the risk profile with blood pressure measurements and blood tests for cholesterol and glucose and to receive recommendations about risk lowering interventions (second step). Results: The online risk estimation was completed by 521 (33%) and 96 (1%) of patients in the practices with an active and passive approach, respectively. Of these patients 392 (64%) were estimated to have a high risk and were referred to the practice; 142 of 392 (36%) consulted the GP. A total of 31 (22%) newly diagnosed patients were identified. Hypertension, hypercholesterolemia, diabetes and chronic kidney disease were diagnosed in 13%, 11%, 1% and 0%, respectively. Privacy risks were the most frequently mentioned reason not to participate. Conclusions: One third of the patients responded to an active invitation to complete an online risk estimation. A passive invitation resulted in only a small number of participating patients. Two third of the participants of the online risk estimation had a high risk, but only one third of them attended the GP office. One in five visiting patients had a diagnosed cardiometabolic risk factor or disease. (aut. ref.)
Background: Until now, cardiometabolic risk assessment in Dutch primary health care was directed at case-finding, and structured, programmatic prevention is lacking. Therefore, the Prevention Consultation cardiometabolic risk (PC CMR), a stepwise approach to identify and manage patients with cardiometabolic risk factors, was developed. The aim of this study was 1) to evaluate uptake rates of the two steps of the PC CMR, 2) to assess the rates of newly diagnosed hypertension, hypercholesterolemia, diabetes mellitus and chronic kidney disease and 3) to explore reasons for non-participation. Methods: Sixteen general practices throughout the Netherlands were recruited to implement the PC CMR during 6 months. In eight practices eligible patients aged between 45 and 70 years without a cardiometabolic disease were actively invited by a personal letter ('active approach') and in eight other practices eligible patients were informed about the PC CMR only by posters and leaflets in the practice ('passive approach'). Participating patients completed an online risk estimation (first step). Patients estimated as having a high risk according to the online risk estimation were advised to visit their general practice to complete the risk profile with blood pressure measurements and blood tests for cholesterol and glucose and to receive recommendations about risk lowering interventions (second step). Results: The online risk estimation was completed by 521 (33%) and 96 (1%) of patients in the practices with an active and passive approach, respectively. Of these patients 392 (64%) were estimated to have a high risk and were referred to the practice; 142 of 392 (36%) consulted the GP. A total of 31 (22%) newly diagnosed patients were identified. Hypertension, hypercholesterolemia, diabetes and chronic kidney disease were diagnosed in 13%, 11%, 1% and 0%, respectively. Privacy risks were the most frequently mentioned reason not to participate. Conclusions: One third of the patients responded to an active invitation to complete an online risk estimation. A passive invitation resulted in only a small number of participating patients. Two third of the participants of the online risk estimation had a high risk, but only one third of them attended the GP office. One in five visiting patients had a diagnosed cardiometabolic risk factor or disease. (aut. ref.)