Literature DB >> 29083251

The Feasibility of Sophisticated Multicriteria Support for Clinical Decisions.

James G Dolan1, Peter J Veazie1.   

Abstract

BACKGROUND: Multicriteria decision-making (MCDM) methods are well-suited to serve as the foundation for clinical decision support systems. To do so, however, they need to be appropriate for use in busy clinical settings. We compared decision-making processes and outcomes of patient-level analyses done with a range of multicriteria methods that vary in ease of use and intensity of decision support, 2 factors that could affect their ease of implementation into practice.
METHODS: We conducted a series of Internet surveys to compare the effects of 5 multicriteria methods that differ in user interface and required user input format on decisions regarding selection of a preferred method for lowering the risk of cardiovascular disease. The study sample consisted of members of an online Internet panel maintained by Fluidsurveys, an Internet survey company. Study outcomes were changes in preferred option, decision confidence, preparation for decision making, the Values Clarification and Decisional Uncertainty subscales of the Decisional Conflict Scale, and method ease of use.
RESULTS: The frequency of changes in the preferred option ranged from 9% to 38%, P < 0.001, and rose progressively as the level of decision support provided by the MCDM method increased. The proportion of respondents who rated the method as easy ranged from 57% to 79% and differed significantly among MCDM methods, P = 0.003, but was not consistently related to intensity of decision support or ease of use.
CONCLUSION: Decision support based on MCDM methods is not necessarily limited by decreases in ease of use. This result suggests that it is possible to develop decision support tools using sophisticated multicriteria techniques suitable for use in routine clinical care settings.

Entities:  

Keywords:  cardiovascular disease prevention; decision making; decision making techniques; decision support; multicriteria decision making; patient-centered care; shared decision making

Mesh:

Year:  2017        PMID: 29083251      PMCID: PMC5878967          DOI: 10.1177/0272989X17736769

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  23 in total

1.  The effect of judgment type and confidence scale on confidence-accuracy calibration in face recognition.

Authors:  Nathan Weber; Neil Brewer
Journal:  J Appl Psychol       Date:  2003-06

2.  Validation of a preparation for decision making scale.

Authors:  Carol Bennett; Ian D Graham; Elizabeth Kristjansson; Stephen A Kearing; Kate F Clay; Annette M O'Connor
Journal:  Patient Educ Couns       Date:  2009-06-26

3.  Development and validation of the numeracy understanding in Medicine Instrument short form.

Authors:  Marilyn M Schapira; Cindy M Walker; Tamara Miller; Kathlyn E Fletcher; Pamela S Ganschow; Elizabeth A Jacobs; Diana Imbert; Maria O'Connell; Joan M Neuner
Journal:  J Health Commun       Date:  2014

4.  Validity of a low literacy version of the Decisional Conflict Scale.

Authors:  Suzanne K Linder; Paul R Swank; Sally W Vernon; Patricia D Mullen; Robert O Morgan; Robert J Volk
Journal:  Patient Educ Couns       Date:  2011-02-05

5.  Toward the 'tipping point': decision aids and informed patient choice.

Authors:  Annette M O'Connor; John E Wennberg; France Legare; Hilary A Llewellyn-Thomas; Benjamin W Moulton; Karen R Sepucha; Andrea G Sodano; Jaime S King
Journal:  Health Aff (Millwood)       Date:  2007 May-Jun       Impact factor: 6.301

6.  Validation of screening questions for limited health literacy in a large VA outpatient population.

Authors:  Lisa D Chew; Joan M Griffin; Melissa R Partin; Siamak Noorbaloochi; Joseph P Grill; Annamay Snyder; Katharine A Bradley; Sean M Nugent; Alisha D Baines; Michelle Vanryn
Journal:  J Gen Intern Med       Date:  2008-03-12       Impact factor: 5.128

Review 7.  Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP).

Authors:  Gillian A Hawker; Samra Mian; Tetyana Kendzerska; Melissa French
Journal:  Arthritis Care Res (Hoboken)       Date:  2011-11       Impact factor: 4.794

8.  Measuring the quality of physician practice by using clinical vignettes: a prospective validation study.

Authors:  John W Peabody; Jeff Luck; Peter Glassman; Sharad Jain; Joyce Hansen; Maureen Spell; Martin Lee
Journal:  Ann Intern Med       Date:  2004-11-16       Impact factor: 25.391

9.  Use of the analytic hierarchy process for medication decision-making in type 2 diabetes.

Authors:  Nisa M Maruthur; Susan M Joy; James G Dolan; Hasan M Shihab; Sonal Singh
Journal:  PLoS One       Date:  2015-05-22       Impact factor: 3.240

Review 10.  Vignette studies of medical choice and judgement to study caregivers' medical decision behaviour: systematic review.

Authors:  Lucas M Bachmann; Andrea Mühleisen; Annekatrin Bock; Gerben ter Riet; Ulrike Held; Alfons G H Kessels
Journal:  BMC Med Res Methodol       Date:  2008-07-30       Impact factor: 4.615

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