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Integrating Evidence and Individual Preferences Using a Web-Based Multi-Criteria Decision Analytic Tool

An Application to Prostate Cancer Screening

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Abstract

Background: Annalisa© (AL) is a web-based decision-support template grounded in multi-criteria decision analysis (MCDA). It uses a simple expected value algorithm to calculate a score for each option by taking into account the individual’s preferences for different criteria (as importance weights) and the evidence of the performance of each option on each criterion. Given the uncertainty surrounding the trade offs between benefits and harms for prostate cancer screening, this topic was chosen as the vehicle to introduce this new decision-support template.

Objective: The aim of the study was to introduce a new decision-support template, AL, and to develop and pilot a decision-support tool for prostate cancer screening using it.

Methods: A decision-support tool for prostate cancer screening (ALProst) was implemented in the AL template. ALProst incorporated evidence on both the benefits and the potential harms of prostate cancer screening (the ‘attributes’) from published randomized controlled trials (RCTs). Individual weights for each attribute were elicited during interviews. By combining the individual’s preferences and the evidence, the best option for the user was identified on the basis of quantified scores.

A convenience sample of computer-proficient primary-care physicians (general practitioners [GPs] in Australia) from the Sydney Metropolitan area (Australia) were invited to complete a face-to-face interview involving the decision-support tool. Preference for undergoing prostate-specific antigen testing for prostate cancer, both personally and for their patients, was sought prior to seeing the tool. After gaining hands-on experience with using the tool, GPs were asked to comment on the merits of the template and the tool. Preference for presenting the benefits of prostate cancer screening as the relative or absolute risk reduction in prostate cancer-specific mortality was also sought.

Results: Of 60 GPs approached, ten (six men and four women) completed an interview (16.7% response rate). Most GPs agreed/strongly agreed with positive statements about the ease with which they could use AL (seven GPs), and understand the information in, and format of, AL (nine and eight, respectively). Eight agreed/strongly agreed that ALProst would be a useful tool for discussing prostate cancer screening with their patients. GPs were also asked to nominate difficult clinical decisions that they, and their patients, have had to make; responses included cancer screening (including prostate cancer); treating patients with multiple illnesses/diseases; managing multiple cardiovascular disease risk factors; and managing patients who are receiving multiple medications. The common element was the need to consider multiple factors in making these complex decisions.

Conclusions: AL is distinguishable from most other decision-support templates available today by its underlying conceptual framework, MCDA, and its power to combine individual preferences with evidence to derive the best option for the user quantitatively. It therefore becomes potentially useful for all decisions at all levels in the healthcare system. Moreover, it will provide a universal graphic ‘language’ that can overcome the burden to patients of encountering a plethora of widely varying decision aids for different conditions during their lifetime.

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References

  1. Affordable Health Care for America Act of 2010, HR 3590, 111th Cong., Section 1236. Enrolled Bill signed into Law. 23 March 2010 [online]. Available from URL: http://docs.house.gov/rules/health/111_ahcaa.pdf [Accessed 2010 Sep 16]

  2. Bates DW, Kuperman G J, Wang S, et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc 2003; 10: 523–30

    Article  PubMed  Google Scholar 

  3. Annalisa: balancing intuition and analysis [online]. Available from URL: http://www.annalisa.org.uk [Accessed 2010 Sep 21]

  4. Café Annalisa [online]. Available from URL: http://www.cafeannalisa.org.uk [Accessed 2010 Sep 21]

  5. Dolan J. Multi-criteria clinical decision support: a primer on the use of multiple-criteria decision-making methods to promote evidence-based, patient-centered healthcare. Patient 2010; 3(4): 229–48

    Article  PubMed  Google Scholar 

  6. Richman MB, Forman EH, Bayazit Y, et al. A novel computer based expert decision making model for prostate cancer disease management. J Urol 2005; 174: 2310–8

    Article  PubMed  Google Scholar 

  7. Schröder FH, Hugosson J, Roobol MJ, et al., ERSPC Investigators. Screening and prostate-cancer mortalit in a randomized European study. N Engl J Med 2009; 360(13): 1320–8

    Article  PubMed  Google Scholar 

  8. Hugosson J, Carlsson S, Aus G, et al. Mortalit results from the Göteborg randomised population-based prostate-cancer screening trial. Lancet Oncol 2010; 11: 725–32

    Article  PubMed  Google Scholar 

  9. Andriole GL, Crawford ED, Grubb III RL, et al., PLCO Project Team. Mortalit results from a randomized prostate-cancer screening trial. N Engl J Med 2009; 360(13): 1310–9

    Article  PubMed  CAS  Google Scholar 

  10. Evans R, Joseph-Williams N, Edwards A, et al. supporting Informed decision making for prostate specific antigen (PSA) testing on the web: an online randomized controlled trial. J Med Internet Res 2010; 12(3): e27

    Article  PubMed  Google Scholar 

  11. Schröder FH, Hugosson J, Roobol MJ, et al. Screening and prostate-cancer mortalit in a randomized European study. N Engl J Med 2009 Mar 26; 360(13): 1320–8

    Article  PubMed  Google Scholar 

  12. Evans R, Edwards A, Brett J, et al. Reduction in uptake of PSA tests following decision aids: systematic review of current aids and their evaluations. Patient Educ Counsel 2005; 58: 13–26

    Article  Google Scholar 

  13. van Til JA, Renzenbrink GJ, Dolan JG, et al. The use of the analytic hierarch process to aid decision making in acquired equinovarus deformity. Arch Phys Med Rehab 2008; 89: 457–62

    Article  Google Scholar 

  14. vanTil JA, Drossaert CHC, Renzenbrink GJ, et al. Feasibilit of web-based decision aids in neurological patients. J Telemed Telecare 2010; 16: 48–52

    Article  PubMed  Google Scholar 

  15. International Patient Decision Aids Standards (IPDAS) Collaboration. IPDAS 2005: criteria for judging the qualit of patient decision aids [online]. Available from URL: http://www.ipdas.ohri.ca/resources.html [Accessed 2009 Sep 13]

  16. Gigerenzer G, Wolfgang G, Kurz-Milcke E, et al. Helping doctors and patients make sense of health statistics. Psychol Sci Public Interest 2008; 8(2): 53–96

    Google Scholar 

  17. Howard K, Barrett A, Mann GJ, et al. A model of prostate-specific antigen screening outcomes for low-to high-risk men. Arch Intern Med 2009; 169(17): 1603–10

    Article  PubMed  Google Scholar 

  18. Draisma G, Boer R, Otto S, et al. Lead times and overdetection due to prostate-specific antigen screening: estimates from the European randomized stud of screening for prostate cancer. J Natl Cancer Inst 2003; 95(12): 868–78

    Article  PubMed  Google Scholar 

  19. Sanda MG, Dunn RL, Michalski J, et al. Qualit of life and satisfaction with outcome among prostate-cancer survivors. N Engl J Med 2008; 358(12): 1250–61

    Article  PubMed  CAS  Google Scholar 

  20. The Royal Australian College of General Practitioners (RACGP). Guidelines for preventive activities in general practice. 7th ed. Melbourne (VIC): RACGP, 2009

    Google Scholar 

  21. Gigerenzer G, Edwards A. Simple tools for understanding risks: from innumerac to insight. BMJ 2003; 327: 741–4

    Article  PubMed  Google Scholar 

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Acknowledgements

This study was undertaken as part of the Screening and Diagnostic Test Evaluation Program funded by the National Health and Medical Research Council of Australia under program grant number 402764. The authors wish to thank the ten general practitioners who participated in this pilot study. Jack Dowie has a financial interest in the AL software.

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Correspondence to Michelle Cunich.

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Cunich, M., Salkeld, G., Dowie, J. et al. Integrating Evidence and Individual Preferences Using a Web-Based Multi-Criteria Decision Analytic Tool. Patient-Patient-Centered-Outcome-Res 4, 153–162 (2011). https://doi.org/10.2165/11587070-000000000-00000

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