Feasibility of a Preventive Program Against Lifestyle Related Diseases
NCT ID: NCT02797392
Last Updated: 2019-04-29
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
9400 participants
INTERVENTIONAL
2016-09-30
2017-12-31
Brief Summary
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Two recent systematic reviews of general practice based health checks suggest that people at increased risk of a chronic disease may benefit from a targeted approach to health checks. Targeted or selective preventive actions are a generally accepted and well integrated part of the health care system (e.g. treatment of hypertension and hyperlipidemia). However, selective prevention is challenged in terms of how to identify citizens at increased risk of disease in the general population in order to start the indicated preventive actions.
The aim of the present pilot study is to test the acceptability, feasibility and short-term effect of a selective preventive program that systematically helps citizens evaluate individual risk of lifestyle related disease and offers targeted and coordinated preventive services in the primary health care sector.
The intervention comprises four elements: 1) Systematic collection of information on lifestyle risk factors using questionnaire 2) Risk estimation and stratification into risk groups based on questionnaire data and information from the electronic patient record (EPR) using validated risk estimation models, 3) An individual electronic health profile with personalized advise on lifestyle change and 4) targeted preventive services at the general practitioner (GP) or the municipality for citizens at risk of lifestyle disease and citizens with risk behavior, respectively.
The intervention is supported by a patient-centered health information system that facilitates informed patient action and integrates general practice and municipality health care providers.
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Detailed Description
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The study is carried out in two municipalities in the Region of Southern Denmark (Haderslev and Varde municipality. Total number of inhabitants: 98.925). All general practitioners in the two municipalities (n=68) have been invited, and a total of 47 have agreed to participate in the study. A total of 200 citizens born 1957-1986 are selected from the patient list of each participating GP. Before selection, the citizens are stratified into households, and subsequently households are randomly selected until the total number of citizens per enrolled GP reaches 200. In selection of households the proportion of citizens living alone and the proportion of citizens living with one or more potential participants is taken into account. No disease-related criteria for excluding a citizen are defined prior to the study. The selected citizens are invited to participate and asked to sign a declaration of consent.
Risk stratification and preventive services offered:
Enrolled participants receive a 15-item questionnaire on lifestyle, familiar disposition of lifestyle disease and selected symptoms. From the individual electronic patient records (EPR) at the GP information on diagnoses and treatment of COPD, type-2 diabetes, hyperlipidemia, hypertension and ischemic heart disease are drawn. Based on questionnaire and EPR data the participants are stratified into four groups: 1) Citizens with an already diagnosed lifestyle related disease, 2) Citizens with an increased risk of lifestyle related disease, 3) Citizens with risk behavior and 4) Citizens with a healthy lifestyle.
Citizens in group 1 are already being treated and/or receive behavioral interventions and are therefore not the primary target of this study. Citizens in group 2 has a calculated increased risk of lifestyle related disease(s) based on validated predictive models for risk of COPD, type-2 diabetes and cardiovascular disease. The risk of COPD is calculated using the COPD-PS screener algorithm taking into account information on age, total cigarette consumption and respiratory symptoms. The risk of type-2 diabetes is calculated based on the algorithm used in the Addition study including information on age, gender, BMI, history of hypertension, physical activity and family history of diabetes. The cut-off value for being at risk of type-2 diabetes, and COPD follows the recommendations of the two models. The risk of cardiovascular disease is calculated using the Heart Score BMI score based on information about age, gender, smoking status and BMI. An increased risk of cardiovascular disease is defined in citizens with a ≥5% risk of dying of cardiovascular disease within the next 10 years. Citizens in group 2 are offered a preventive program at the GP including an initial health examination and subsequent behavior counselling. Citizens in group 3 are defined by having a BMI\>35, being daily smoker, having a high risk alcohol consumption, having unhealthy eating habits and/or low physical activity. Evaluation of eating habits is based on the recommendations in the Swedish National Guidelines on Disease Prevention, and evaluation of alcohol consumption and physical activity is based on recommendations from the Danish Health Authority. Citizens in group 3 are offered behavior counselling in the municipality and community health services, if necessary. Citizens in group 4 are not offered any further services.
Electronic health information system:
The intervention is supported by a patient-centered health information system that facilitates informed patient action based on the predictive model for identification and stratification of citizens to the appropriate care providers and that supports the initiation and follow up of preventive care through the provision of health information resources, decision aids, risk calculators, personalized motivational messages and integrates primary care and municipality health care providers.
Common training course:
Before the study commences enrolled GPs, practice staff and health professionals from the municipalities are offered a common training course. The aim of the course is to train the specific intervention elements and to improve the inter-sectoral knowledge and collaboration on prevention of lifestyle diseases.
Evaluation:
Evaluation of the study will be carried out using quantitative as well as qualitative research methods. Details on evaluation methods are included in section 9.
Results of the present pilot study will be used for the adjustment of the intervention prior to a large scale study comprising 10 municipalities, up to 360 GPs and 200.000 citizens.
Conditions
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Study Design
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NA
SINGLE_GROUP
PREVENTION
NONE
Study Groups
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Lifestyle intervention
All included citizens receive a questionnaire to estimate risk of disease and risk behavior. Information about lifestyle is collated with existing Electronic Patient Record (EPR) data and the citizen's risk of lifestyle-related disease is estimated based on validated algorithms for risk of type-2 diabetes, cardiovascular disease and COPD (Stratification). All citizens receive an electronic health profile and targeted advice. Citizens at increased risk of disease are offered a preventive program at the GP including an initial health examination and subsequent lifestyle counselling. Citizens with risk behavior are offered lifestyle counselling in the municipality and community health services, if necessary. Citizens diagnosed with a lifestyle related disease are already being treated by the GP, and therefore, like citizens with a healthy lifestyle, they are not offered any further services.
Lifestyle intervention
1\) Systematic collection of information on lifestyle risk factors using questionnaire 2) Risk estimation and stratification into risk groups based on questionnaire data and information from the electronic patient record (EPR) using validated risk estimation models, 3) An individual electronic health profile with personalized advise on lifestyle change and 4) targeted preventive services incl. lifestyle counseling at the GP or the municipality for citizens at increased risk of lifestyle disease and citizens with risk behavior, respectively.
Interventions
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Lifestyle intervention
1\) Systematic collection of information on lifestyle risk factors using questionnaire 2) Risk estimation and stratification into risk groups based on questionnaire data and information from the electronic patient record (EPR) using validated risk estimation models, 3) An individual electronic health profile with personalized advise on lifestyle change and 4) targeted preventive services incl. lifestyle counseling at the GP or the municipality for citizens at increased risk of lifestyle disease and citizens with risk behavior, respectively.
Eligibility Criteria
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Inclusion Criteria
* Place of residence: One of the two participating municipalities in the Region of Southern Denmark.
* Year of birth: 1957-1986
Exclusion Criteria
30 Years
59 Years
ALL
No
Sponsors
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University of Oslo
OTHER
Lund University
OTHER
University of Southern Denmark
OTHER
Responsible Party
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Trine Thilsing
Postdoc, research coordinator
Principal Investigators
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Jens Søndergaard
Role: PRINCIPAL_INVESTIGATOR
Research Unit of General Practice, Dept. of Public Health, University of Southern Denmark, DK-5000 Odense C, Denmark
Locations
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Research Programme on Health Promotion and Prevention, National Institute of Public Health, University of Southern Denmark,
Copenhagen, , Denmark
Center of Health Economics Research, Department of Business and Economics, University of Southern Denmark
Odense, , Denmark
Department of Sports Science and Clinical Biomechanics, Musculoskeletal Function and Physiotherapy, University of Southern Denmark
Odense, , Denmark
Research Unit of General Practice, Dept. of Public Health, University of Southern Denmark,
Odense C, , Denmark
Research Group for Information Systems, Department of Informatics, University of Oslo
Oslo, , Norway
Center for Primary Health Care Research, Department of Clinical Sciences
Malmo, , Sweden
Countries
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References
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James WP. The epidemiology of obesity: the size of the problem. J Intern Med. 2008 Apr;263(4):336-52. doi: 10.1111/j.1365-2796.2008.01922.x. Epub 2008 Feb 27.
King H, Aubert RE, Herman WH. Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections. Diabetes Care. 1998 Sep;21(9):1414-31. doi: 10.2337/diacare.21.9.1414.
Yusuf S, Reddy S, Ounpuu S, Anand S. Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation. 2001 Nov 27;104(22):2746-53. doi: 10.1161/hc4601.099487.
Si S, Moss JR, Sullivan TR, Newton SS, Stocks NP. Effectiveness of general practice-based health checks: a systematic review and meta-analysis. Br J Gen Pract. 2014 Jan;64(618):e47-53. doi: 10.3399/bjgp14X676456.
Engelsen Cd, Koekkoek PS, Godefrooij MB, Spigt MG, Rutten GE. Screening for increased cardiometabolic risk in primary care: a systematic review. Br J Gen Pract. 2014 Oct;64(627):e616-26. doi: 10.3399/bjgp14X681781.
Martinez FJ, Raczek AE, Seifer FD, Conoscenti CS, Curtice TG, D'Eletto T, Cote C, Hawkins C, Phillips AL; COPD-PS Clinician Working Group. Development and initial validation of a self-scored COPD Population Screener Questionnaire (COPD-PS). COPD. 2008 Apr;5(2):85-95. doi: 10.1080/15412550801940721.
Christensen JO, Sandbaek A, Lauritzen T, Borch-Johnsen K. Population-based stepwise screening for unrecognised Type 2 diabetes is ineffective in general practice despite reliable algorithms. Diabetologia. 2004 Sep;47(9):1566-73. doi: 10.1007/s00125-004-1496-2. Epub 2004 Sep 8.
Cardiology. ESo. Heartscore BMI score [Internet]. Available from: https://escol.escardio.org/heartscore/calc.aspx?model=europelow. 2014.
Socialstyrelsen. S. Sjukdomsförebyggande metoder. Vetenskabeligt underlag för nationella riktlinjer. 2011
Leick C, Larsen LB, Larrabee Sonderlund A, Svensson NH, Sondergaard J, Thilsing T. Non-participation in a targeted prevention program aimed at lifestyle-related diseases: a questionnaire-based assessment of patient-reported reasons. BMC Public Health. 2022 May 13;22(1):970. doi: 10.1186/s12889-022-13382-8.
Hansen CB, Pavlovic KMH, Sondergaard J, Thilsing T. Does GP empathy influence patient enablement and success in lifestyle change among high risk patients? BMC Fam Pract. 2020 Aug 8;21(1):159. doi: 10.1186/s12875-020-01232-8.
Thilsing T, Sonderlund AL, Sondergaard J, Svensson NH, Christensen JR, Thomsen JL, Hvidt NC, Larsen LB. Changes in Health-Risk Behavior, Body Mass Index, Mental Well-Being, and Risk Status Following Participation in a Stepwise Web-Based and Face-to-Face Intervention for Prevention of Lifestyle-Related Diseases: Nonrandomized Follow-Up Cohort Study. JMIR Public Health Surveill. 2020 Jul 9;6(3):e16083. doi: 10.2196/16083.
Larsen LB, Thilsing T, Pedersen LB. Patient preferences for preventive health checks in Danish general practice: a discrete choice experiment among patients at high risk of noncommunicable diseases. Fam Pract. 2020 Oct 19;37(5):689-694. doi: 10.1093/fampra/cmaa038.
van Tunen JAC, Peat G, Bricca A, Larsen LB, Sondergaard J, Thilsing T, Roos EM, Thorlund JB. Association of osteoarthritis risk factors with knee and hip pain in a population-based sample of 29-59 year olds in Denmark: a cross-sectional analysis. BMC Musculoskelet Disord. 2018 Aug 21;19(1):300. doi: 10.1186/s12891-018-2183-7.
Other Identifiers
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11/13244
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
15/10562
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
14/43732.
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
2015-57-0008
Identifier Type: REGISTRY
Identifier Source: secondary_id
TOFpilot2016
Identifier Type: -
Identifier Source: org_study_id
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