Purpose: Patients have an increasing list of preventive health options to reduce mortality and morbidity. Ranking these based on demographic, health characteristics and preferences should allow patients to prioritise and tailor preventive health care. ‘My Health Check’ (MHC) is a web-based multi-criteria decision analysis tool populated by age and gender-specific burden of disease data for YLL and YLD. Individual demographic and health data entered by the patient provides a personalised list of relevant options whilst preferences can be interactively adjusted using a slide bar. Prior qualitative work derived the four key attributes/utilities for preventive health decisions as ‘avoiding premature death’, ‘avoiding chronic illness/disability’, ‘avoid difficulty/loss of enjoyment’ and ‘minimising financial costs’. This trial tests the effect of MHC on preventive healthcare decisions.
Method: 941 Australian participants aged 30-69 years recruited nationally via random-digit dialling and randomised by computer to the self-administered ‘My Health Check’ (MHC) which provides personalised ranking of relevant preventive health options and links to information; or the control site which comprises a portal with the same information links but does not include the personalised ranking of relevant options. The design is double-blind. The primary outcome is the proportion of MHC participants who have undertaken at least one of their top 3 self-identified preventive behaviours after 3 months compared with the control.
Result: Mean time for completing either version was 6 minutes. The most common priorities at baseline related to weight loss, diet and exercise. The median weightings (i.e importance) were near maximal for reducing premature mortality or chronic illness/disability and avoiding loss of enjoyment associated with healthy lifestyle choices. There was greater variability around the importance of financial costs. MCDA participants rated smoking cessation and weight loss as the most difficult to achieve. MCDA users were more likely to change their healthy lifestyle priorities 56.9% vs 47.8% (P=0.01). MCDA users were twice as likely to change priorities to maximise life expectancy (P=0.006). So far MCDA users rate their adherence slightly higher than information only (mean 2.8 vs 2.5 on 0-5 scale). Final results will be presented at the meeting.
Conclusion: Multi-criteria decision analysis appears to be a promising method for personalising and prioritising a range of healthcare options. It allows patients to tailor population-level evidence to individual clinical factors and combine with personal preferences.
See more of: The 34th Annual Meeting of the Society for Medical Decision Making