Multi-criteria clinical decision support: A primer on the use of multiple-criteria decision-making methods to promote evidence-based, patient-centered healthcare

Patient

Volumn 3, Issue 4, 2010, Pages 229-248

  Dolan, James G ^a  

^a UNIVERSITY OF ROCHESTER   (United States)

Author keywords

Decision making; Evidence based medicine; Patient preference

Indexed keywords

CLINICAL DECISION MAKING; CLINICAL EFFECTIVENESS; CONJOINT ANALYSIS; COST UTILITY ANALYSIS; DECISION SUPPORT SYSTEM; EVIDENCE BASED PRACTICE; HEALTH SURVEY; HUMAN; PRIORITY JOURNAL; REVIEW; SCORING SYSTEM; STRUCTURED QUESTIONNAIRE;

EID: 77956512548     PISSN: 11781653     EISSN: 11781661     Source Type: Journal    
DOI: 10.2165/11539470-000000000-00000     Document Type: Review

References (47)

1. Institute of Medicine. Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press, 2001
2. Agency for Healthcare Research and Quality. National healthcare quality report, 2008: key themes from the national healthcare quality report [online]. Available from URL: http:// www.ahrq.gov/qual/nhqr08/Key.htm [Accessed 2010 Aug 11]
3. Elwyn G, Edwards A, Gwyn R, et al. Towards a feasible model for shared decision making: focus group study with general practice registrars. BMJ 1999; 319: 753-6
4. Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness: the Chronic Care model, part 2. JAMA 2002; 288 (15): 1909-14
5. OConnor AM, Wennberg JE, Legare F, et al. Toward the tipping point: decision aids and informed patient choice. Health Aff 2007; 26 (3): 716-25
6. Belton V, Stewart TJ. Multiple criteria decision analysis. Boston (MA): Kluwer Academic Publishers, 2002
7. Figueira J, Greco S, Ehrgott M. Multiple criteria decision analysis: state of the art surveys. New York: Springer, 2005
8. Wallenius J, Dyer JS, Fishburn PC, et al. Multiple criteria decision making, multiattribute utility theory: recent accomplishments and what lies ahead. Manage Sci 2008; 54 (7): 1336-49
9. Baltussen R, Niessen L. Priority setting of health interventions: the need for multi-criteria decision analysis. Cost Eff Resour Alloc 2006; 4 (1): 14-14
10. Goetghebeur MM, Wagner M, Khoury H, et al. Evidence and Value: Impact on DEcisionMaking. The EVIDEM framework and potential applications. BMC Health Serv Res 2008; 8: 270
11. Liberatore MJ, Nydick RL. The analytic hierarchy process in medical and health care decision making: a literature review. Eur J Oper Res 2008; 189 (1): 194-207
12. Sloane EB, Liberatore MJ, Nydick RL. Medical decision support using the analytic hierarchy process. J Healthc Inf Manag 2002; 16 (4): 38-43
13. Sloane EB, Liberatore MJ, Nydick RL, et al. Using the analytic hierarchy process as a clinical engineering tool to facilitate an iterative, multidisciplinary, microeconomic health technology assessment. Computers Operations Res 2003; 30 (10): 1447-65
14. Pieterse AH, Berkers F, Baas-Thijssen MC, et al. Adaptive conjoint analysis as individual preference assessment tool: feasibility through the internet and reliability of preferences. Patient Educ Counsel 2010; 78 (2): 224-33
15. Mele NL. Conjoint analysis. Nurs Res 2008; 57 (3): 220-4
16. Ahmed SF, Smith WA, Blamires C. Facilitating and understanding the familys choice of injection device for growth hormone therapy by using conjoint analysis. Arch Dis Child 2008; 93 (2): 110-4
17. Fisher K, Orkin F, Frazer C. Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study. Appl Nurs Res 2010; 23 (1): 30-5
18. Ryan M, Farrar S. Using conjoint analysis to elicit preferences for health care. BMJ 2000; 320 (7248): 1530-3
19. Breslin M, Mullan RJ, Montori VM. The design of a decision aid about diabetes medications for use during the consultation with patients with type 2 diabetes. Patient Educ Counsel 2008; 73 (3): 465-72
20. Few S. Information dashboard design: the effective visual communication of data. Sebastopol (CA): OReilly Media, Inc., 2006
21. Mullan RJ, Montori VM, Shah ND, et al. The diabetes mellitus medication choice decision aid: a randomized trial. Arch Int Med 2009; 169 (17): 1560-8
22. Marewski JN, Gaissmaier W, Gigerenzer G. Good judgments do not require complex cognition. Cogn Process 2010 May; 11 (2): 103-21
23. Eddy DM. Comparing benefits and harms: the balance sheet. JAMA 1990; 263 (18): 2493-505
24. Dougherty MR, Franco-Watkins AM, Thomas R. Psychological plausibility of the theory of probabilistic mental models and the fast and frugal heuristics. Psychol Rev 2008; 115 (1): 199-213
25. Hastie R, Dawes RM. Rational choice in an uncertain world. Thousand Oaks (CA): Sage Publications, Inc., 2001
26. Hammond JS, Keeney RL, Raiffa H. Even swaps: a rational method for making trade-offs. Harv Bus Rev 1998; 76 (2): 137-8, 143-8, 150
27. Hammond JS, Keeney RL, Raiffa H. Smart choices: a practical guide to making better decisions. Boston (MA): Harvard Business School Press, 1999
28. Mustajoki J, Hamalainen RP. Smart-Swaps: a decision support system for multicriteria decision analysis with the even swaps method. Decis Support Syst 2007; 44: 313-25
29. SMART-SWAPS: smart choices with the even swaps method [online]. Available from URL: http://www.smartswaps. hut.fi/ [Accessed 2010 Jul 29]
30. McCaffrey JD. Using the Multi-Attribute Global Inference of Quality (MAGIQ) technique for software testing. Sixth International Conference on Information Technology: New Generations; 2009 Apr 27-29; Las Vegas (NV)
31. Edwards W, Barron FH. SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organizational Behavior Hum Decis Processes 1994; 60 (3): 306-25
32. OConnor AM, Tugwell P, Wells GA, et al. A decision aid for women considering hormone therapy after menopause: decision support framework and evaluation. Patient Educ Couns 1998; 33 (3): 267-79 (Pubitemid 28168092)
33. Man-Son-Hing M, Laupacis A, OConnor AM, et al. Development of a decision aid for patients with atrial fibrillation who are considering antithrombotic therapy. J Gen Int Med 2000; 15 (10): 723-30
34. Masya LM, Young JM, Solomon MJ, et al. Preferences for outcomes of treatment for rectal cancer: patient and clinician utilities and their application in an interactive computer- based decision aid. Dis Colon Rectum 2009; 52 (12): 1994-2002
35. WEB-HIPRE: global decision support [online]. Available from URL: http://www.hipre.hut.fi/ [Accessed 2010 Jul 29]
36. café Annalisa [online]. Available from URL: http://www. cafeannalisa.org.uk/index.php [Accessed 2010 Jul 29]
37. Von Winterfeldt D, Edwards W. Decision analysis and behavioral research. Cambridge: Cambridge University Press, 1986
38. de Bock GH, Reijneveld SA, van Houwelingen JC, et al. Multiattribute utility scores for predicting family physicians decisions regarding sinusitis. Med Decis Making 1999; 19 (Jan-Mar): 58-65
39. Forman EH, Gass SI. The analytic hierarchy process: an exposition. Oper Res 2001; 49: 469-86
40. Sato J. Comparison between multiple-choice and analytic hierarchy process: measuring human perception. Int Trans Oper Res 2004; 11 (1): 77-86
41. Katsumura Y, Yasunaga H, Imamura T, et al. Relationship between risk information on total colonoscopy and patient preferences for colorectal cancer screening options: analysis using the Analytic Hierarchy Process. BMC Health Serv Res 2008; 8: 106
42. Dolan JG, Isselhardt Jr BJ, Cappuccio JD. The analytic hierarchy process in medical decision making: a tutorial. Med Decis Making 1989; 9 (1): 40-50
43. Saaty TL. How to make a decision: the analytic hierarchy process. Eur J Oper Res 1990; 48 (1): 9-26
44. Saaty TL. How to make a decision: the analytic hierarchy process. Interfaces 1994; 24: 19-43
45. Saaty TL. Decision making for leaders. Pittsburgh (PA): RWS Publications, 2001
46. Gass SI. Model world: when is a number a number? Interfaces 2001; 31 (5): 93-103
47. Super Decisions Software for Decision-Making [online]. Available from URL: http://www.superdecisions.com [Accessed 2010 Jul 29]