OBJECTIVE: To evaluate the feasibility of a web-based coaching programme for vascular risk factor treatment, to describe the patterns of use and to measure changes in risk factors. METHODS: Patients with a clinical manifestation of arterial disease and Internet access were asked to participate in the nurse-led Internet-based risk factor management programme. At the first clinic visit, a personalized action plan was made for the treatment of risk factors. Patients were instructed on communication with a specialized nurse through Internet and encouraged to enter self-measured risk factor levels at their personalized website. The nurse practitioner replied on working days and gave feedback, support, and recommendations on lifestyle and medical treatment. After 6 months, risk factors were re-measured. RESULTS: Fifty patients participated, 70% were overweight, 64% had hypertension, 42% hyperlipidemia, and 24% smoked at baseline. During 6 months, the log-in average at the individual website was 35 times per patient (1.3 log-ins/week); while the nurse practitioner logged-in at the overall website 23 times/week. The website was hardly used by five patients. Most e-mail messages were sent by patients for hypertension (211 times) and obesity (203 times), whereas the nurse practitioner sent nearly twice as many e-mail messages for hypertension (400 times) and obesity (455 times). The level of most risk factors decreased and the fraction of achieved treatment goals increased (blood pressure from 36 to 58%, LDL-cholesterol from 58 to 64%, glucose from 64 to 82%). CONCLUSIONS: A web-based vascular risk factor intervention programme is feasible; it is frequently used by patients and suitable to decrease the level of several risk factors. It has the promise of being an efficacious intervention for risk factor sanitation in patients with symptomatic vascular disease. PRACTICE IMPLICATIONS: An Internet-based individualised risk management programme could make patients aware of their self-management capability and may contribute to risk factor reduction.
OBJECTIVE: To evaluate the feasibility of a web-based coaching programme for vascular risk factor treatment, to describe the patterns of use and to measure changes in risk factors. METHODS:Patients with a clinical manifestation of arterial disease and Internet access were asked to participate in the nurse-led Internet-based risk factor management programme. At the first clinic visit, a personalized action plan was made for the treatment of risk factors. Patients were instructed on communication with a specialized nurse through Internet and encouraged to enter self-measured risk factor levels at their personalized website. The nurse practitioner replied on working days and gave feedback, support, and recommendations on lifestyle and medical treatment. After 6 months, risk factors were re-measured. RESULTS: Fifty patients participated, 70% were overweight, 64% had hypertension, 42% hyperlipidemia, and 24% smoked at baseline. During 6 months, the log-in average at the individual website was 35 times per patient (1.3 log-ins/week); while the nurse practitioner logged-in at the overall website 23 times/week. The website was hardly used by five patients. Most e-mail messages were sent by patients for hypertension (211 times) and obesity (203 times), whereas the nurse practitioner sent nearly twice as many e-mail messages for hypertension (400 times) and obesity (455 times). The level of most risk factors decreased and the fraction of achieved treatment goals increased (blood pressure from 36 to 58%, LDL-cholesterol from 58 to 64%, glucose from 64 to 82%). CONCLUSIONS: A web-based vascular risk factor intervention programme is feasible; it is frequently used by patients and suitable to decrease the level of several risk factors. It has the promise of being an efficacious intervention for risk factor sanitation in patients with symptomatic vascular disease. PRACTICE IMPLICATIONS: An Internet-based individualised risk management programme could make patients aware of their self-management capability and may contribute to risk factor reduction.
Authors: Lora E Burke; Jun Ma; Kristen M J Azar; Gary G Bennett; Eric D Peterson; Yaguang Zheng; William Riley; Janna Stephens; Svati H Shah; Brian Suffoletto; Tanya N Turan; Bonnie Spring; Julia Steinberger; Charlene C Quinn Journal: Circulation Date: 2015-08-13 Impact factor: 29.690
Authors: R Jay Widmer; Nerissa M Collins; C Scott Collins; Colin P West; Lilach O Lerman; Amir Lerman Journal: Mayo Clin Proc Date: 2015-04 Impact factor: 7.616
Authors: J W P Vernooij; H A H Kaasjager; Y van der Graaf; J Wierdsma; H M H Grandjean; M M C Hovens; G A de Wit; F L J Visseren Journal: BMJ Date: 2012-06-12
Authors: Liesje Donkin; Helen Christensen; Sharon L Naismith; Bruce Neal; Ian B Hickie; Nick Glozier Journal: J Med Internet Res Date: 2011-08-05 Impact factor: 5.428
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