Literature DB >> 21394218

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

James G Dolan1.   

Abstract

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Entities:  

Year:  2010        PMID: 21394218      PMCID: PMC3049911          DOI: 10.2165/11539470-000000000-00000

Source DB:  PubMed          Journal:  Patient        ISSN: 1178-1653            Impact factor:   3.883


  23 in total

1.  The analytic hierarchy process in medical decision making: a tutorial.

Authors:  J G Dolan; B J Isselhardt; J D Cappuccio
Journal:  Med Decis Making       Date:  1989 Jan-Mar       Impact factor: 2.583

2.  Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study.

Authors:  Kathleen Fisher; Fredrick Orkin; Christine Frazer
Journal:  Appl Nurs Res       Date:  2009-01-15       Impact factor: 2.257

3.  A decision aid for women considering hormone therapy after menopause: decision support framework and evaluation.

Authors:  A M O'Connor; P Tugwell; G A Wells; T Elmslie; E Jolly; G Hollingworth; R McPherson; H Bunn; I Graham; E Drake
Journal:  Patient Educ Couns       Date:  1998-03

4.  Towards a feasible model for shared decision making: focus group study with general practice registrars.

Authors:  G Elwyn; A Edwards; R Gwyn; R Grol
Journal:  BMJ       Date:  1999-09-18

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.  Adaptive Conjoint Analysis as individual preference assessment tool: feasibility through the internet and reliability of preferences.

Authors:  Arwen H Pieterse; Frank Berkers; Monique C M Baas-Thijssen; Corrie A M Marijnen; Anne M Stiggelbout
Journal:  Patient Educ Couns       Date:  2009-07-05

7.  The design of a decision aid about diabetes medications for use during the consultation with patients with type 2 diabetes.

Authors:  Maggie Breslin; Rebecca J Mullan; Victor M Montori
Journal:  Patient Educ Couns       Date:  2008-09-03

8.  Multiattribute utility scores for predicting family physicians' decisions regarding sinusitis.

Authors:  G H de Bock; S A Reijneveld; J C van Houwelingen; J A Knottnerus; J Kievit
Journal:  Med Decis Making       Date:  1999 Jan-Mar       Impact factor: 2.583

Review 9.  Good judgments do not require complex cognition.

Authors:  Julian N Marewski; Wolfgang Gaissmaier; Gerd Gigerenzer
Journal:  Cogn Process       Date:  2009-09-27

10.  Relationship between risk information on total colonoscopy and patient preferences for colorectal cancer screening options: analysis using the analytic hierarchy process.

Authors:  Yuichi Katsumura; Hideo Yasunaga; Tomoaki Imamura; Kazuhiko Ohe; Hiroshi Oyama
Journal:  BMC Health Serv Res       Date:  2008-05-21       Impact factor: 2.655

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  66 in total

1.  Giving Patients a Meaningful Voice in European Health Technology Assessments: The Role of Health Preference Research.

Authors:  Axel C Mühlbacher; F Reed Johnson
Journal:  Patient       Date:  2017-08       Impact factor: 3.883

2.  VIKOR method with enhanced accuracy for multiple criteria decision making in healthcare management.

Authors:  Qiang-Lin Zeng; Dan-Dan Li; Yi-Bin Yang
Journal:  J Med Syst       Date:  2013-02-03       Impact factor: 4.460

3.  Surgical approaches for cam femoroacetabular impingement: the use of multicriteria decision analysis.

Authors:  Claudio Diaz-Ledezma; Javad Parvizi
Journal:  Clin Orthop Relat Res       Date:  2013-08       Impact factor: 4.176

4.  Field testing of a multicriteria decision analysis (MCDA) framework for coverage of a screening test for cervical cancer in South Africa.

Authors:  Jacqui Miot; Monika Wagner; Hanane Khoury; Donna Rindress; Mireille M Goetghebeur
Journal:  Cost Eff Resour Alloc       Date:  2012-02-29

Review 5.  Multicriteria decision analysis in oncology.

Authors:  Georges Adunlin; Vakaramoko Diaby; Alberto J Montero; Hong Xiao
Journal:  Health Expect       Date:  2014-03-17       Impact factor: 3.377

6.  Coping strategies and immune neglect in affective forecasting: Direct evidence and key moderators.

Authors:  Michael Hoerger
Journal:  Judgm Decis Mak       Date:  2012-01-01

7.  Patient-Important Outcomes in the Long-Term Treatment of Bipolar Disorder: A Mixed-Methods Approach Investigating Relative Preferences and a Proposed Taxonomy.

Authors:  Øystein Eiring; Magne Nylenna; Kari Nytrøen
Journal:  Patient       Date:  2016-04       Impact factor: 3.883

8.  Clinical Reasoning Terms Included in Clinical Problem Solving Exercises?

Authors:  John L Musgrove; Jason Morris; Carlos A Estrada; Ryan R Kraemer
Journal:  J Grad Med Educ       Date:  2016-05

9.  Diagnosis of periprosthetic joint infection in Medicare patients: multicriteria decision analysis.

Authors:  Claudio Diaz-Ledezma; Paul M Lichstein; James G Dolan; Javad Parvizi
Journal:  Clin Orthop Relat Res       Date:  2014-11       Impact factor: 4.176

10.  Using the analytic hierarchy process to elicit patient preferences: prioritizing multiple outcome measures of antidepressant drug treatment.

Authors:  Marjan J M Hummel; Fabian Volz; Jeannette G van Manen; Marion Danner; Charalabos-Markos Dintsios; Maarten J Ijzerman; Andreas Gerber
Journal:  Patient       Date:  2012       Impact factor: 3.883

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