Individual preferences on the balancing of good and harm of cardiovascular disease screening (original) (raw)

Cardiac risk factors and prevention

Original research article

Individual preferences on the balancing of good and harm of cardiovascular disease screening

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  1. Tina Birgitte Hansen1,2,
  2. Jes Sanddal Lindholt3,4,
  3. http://orcid.org/0000-0002-1285-4826Axel Cosmus Pyndt Diederichsen4,5,
  4. Michiel C J Bliemer6,
  5. Jess Lambrechtsen7,
  6. Flemming Hald Steffensen8,
  7. Rikke Søgaard9,10
  8. 1 Department of Cardiology, Zealand University Hospital, Roskilde, Denmark
  9. 2 Department of Regional Health Research, University of Southern Denmark, Odense, Denmark
  10. 3 Department of Cardiothoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark
  11. 4 Elitary Research Unit of Personalized Medicine in Arterial Disease (CIMA), Odense University Hospital, Odense, Denmark
  12. 5 Department of Cardiology, Odense University Hospital, Odense, Denmark
  13. 6 Institute of Transport and Logistics Studies, University of Sydney Business School, Sydney, New South Wales, Australia
  14. 7 Department of Cardiology, University Hospital Odense, Odense, Denmark
  15. 8 Department of Cardiology, Lillebaelt Hospital, Vejle, Denmark
  16. 9 Department of Public Health, Aarhus University, Aarhus, Denmark
  17. 10 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
  18. Correspondence to Dr Tina Birgitte Hansen, Department of Cardiology, Zealand University Hospital, Roskilde, Denmark; tbh{at}regionsjaelland.dk

Abstract

Objective Transition towards value-based healthcare requires insight into what makes value to the individual. The aim was to elicit individual preferences for cardiovascular disease screening with respect to the difficult balancing of good and harm as well as mode of delivery.

Methods A discrete choice experiment was conducted as a cross-sectional survey among 1231 male screening participants at three Danish hospitals between June and December 2017. Participants chose between hypothetical screening programmes characterised by varying levels of mortality risk reduction, avoidance of overtreatment, avoidance of regretting participation, screening duration and location. A multinomial mixed logit model was used to model the preferences and the willingness to trade mortality risk reduction for improvements on other characteristics.

Results Respondents expressed preferences for improvements on all programme characteristics. They were willing to give up 0.09 (95% CI 0.08 to 0.09) lives saved per 1000 screened to avoid one individual being over treated. Similarly, respondents were willing to give up 1.22 (95% CI 0.90 to 1.55) or 5.21 (95% CI 4.78 to 5.67) lives saved per 1000 screened to upgrade the location from general practice to a hospital or to a high-tech hospital, respectively. Subgroup analysis revealed important preference heterogeneity with respect to smoking status, level of health literacy and self-perceived risk of cardiovascular disease.

Conclusions Individuals are able to express clear preferences about what makes value to them. Not only health benefit but also time with health professionals and access to specialised facilities were important. This information could guide the optimal programme design in search of value-based healthcare.

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