Literature DB >> 22273359

Measuring Preferences for Colorectal Cancer Screening: What are the Implications for Moving Forward?

Deborah Marshall1, S Elizabeth McGregor, Gillian Currie.   

Abstract

There is a growing interest in the application of preferences to inform healthcare planning and delivery. Clinical practice guidelines are encouraging incorporation of preferences in patient management choices in recognition that often no single approach is best.The objective of this focused review is to provide an overview of the current state of preference measurement for colorectal cancer screening (CRCS) and highlight the implications for health policy, CRCS program implementation, and further research.MEDLINE and EMBASE electronic databases were searched (1990-May 2009) for English-language literature examining patient preferences for CRCS, using conjoint analysis methods. We systematically extracted information on the study population, whether the choice sets were framed around specific CRCS tests or the overall program, the attributes and levels included, and, where available, the ordering of importance of the attributes and key study findings.Qualitative data synthesis of key differences and commonalities in the approaches and findings are presented. Six conjoint analysis studies of CRCS were identified. While 66-88% of respondents in the general population indicated they would choose CRCS, this is greater than observed rates of uptake (40-50%). All studies were administered in a sample of the general population at average risk of CRC, except one that included a sample of physicians. The studies varied in the attributes and levels they included. However, accuracy, whether expressed in the context of a CRCS test or program, was consistently identified as a statistically significant and important attribute. Other attributes included in the conjoint analysis studies included level of discomfort during the test, preparation for the test, the testing process, frequency of testing, frequency of complications, the process of follow up, and cost.Our results suggested that (i) a majority of people would choose to be screened for CRC, although actual CRCS participation rates suggest otherwise; (ii) patients have distinct preferences for CRCS tests that can be linked to CRC test attributes; and consequently, (iii) there is no single CRCS test that is preferred by everyone. In addition, although the specific approach, attributes, and levels in the studies varied, they consistently found that multiple factors are important from the patient's perspective and that preferences vary amongst subgroups. Consequently, careful consideration should be given to the design and implementation of a CRCS program based on a broader range of factors than the traditional outcomes such as mortality and incidence reduction. Attention should now be focused on how to use this information to inform health policy and develop CRCS programs that will increase screening uptake and adherence in the context of the health system in which the program will be provided. We propose a two-step process to designing and implementing a CRCS program based on evidence and preferences that informs patient choice.

Entities:  

Year:  2010        PMID: 22273359     DOI: 10.2165/11532250-000000000-00000

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


  49 in total

1.  Analysing public preferences for cancer screening programmes.

Authors:  D Gyrd-Hansen; J Søgaard
Journal:  Health Econ       Date:  2001-10       Impact factor: 3.046

2.  Screening guidelines for colorectal cancer: a twice-told tale.

Authors:  Michael Pignone; Harold C Sox
Journal:  Ann Intern Med       Date:  2008-10-07       Impact factor: 25.391

3.  Attitudes toward colorectal cancer screening tests.

Authors:  B S Ling; M A Moskowitz; D Wachs; B Pearson; P C Schroy
Journal:  J Gen Intern Med       Date:  2001-12       Impact factor: 5.128

4.  Patient preferences and adherence to colorectal cancer screening in an urban population.

Authors:  Randi L Wolf; Charles E Basch; Corey H Brouse; Celia Shmukler; Steven Shea
Journal:  Am J Public Health       Date:  2006-03-29       Impact factor: 9.308

5.  Primary care patients' understanding of colorectal cancer screening.

Authors:  Anthony Greisinger; Sarah T Hawley; Judy L Bettencourt; Catherine A Perz; Sally W Vernon
Journal:  Cancer Detect Prev       Date:  2006-02-02

6.  Patient preferences for colon cancer screening.

Authors:  M Pignone; D Bucholtz; R Harris
Journal:  J Gen Intern Med       Date:  1999-07       Impact factor: 5.128

7.  Community-based preferences for stool cards versus colonoscopy in colorectal cancer screening.

Authors:  Ann C DeBourcy; Scott Lichtenberger; Susanne Felton; Kiel T Butterfield; Dennis J Ahnen; Thomas D Denberg
Journal:  J Gen Intern Med       Date:  2007-12-21       Impact factor: 5.128

8.  Colorectal cancer testing in Canada--2008.

Authors:  Kathryn Wilkins; Margot Shields
Journal:  Health Rep       Date:  2009-09       Impact factor: 4.796

9.  Rates and predictors of colorectal cancer screening.

Authors:  Su-Ying Liang; Kathryn A Phillips; Mika Nagamine; Uri Ladabaum; Jennifer S Haas
Journal:  Prev Chronic Dis       Date:  2006-09-15       Impact factor: 2.830

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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  17 in total

Review 1.  Assessing stated preferences for colorectal cancer screening: a critical systematic review of discrete choice experiments.

Authors:  S Wortley; G Wong; A Kieu; K Howard
Journal:  Patient       Date:  2014       Impact factor: 3.883

2.  Measuring Acceptability and Preferences for Implementation of Pre-Exposure Prophylaxis (PrEP) Using Conjoint Analysis: An Application to Primary HIV Prevention Among High Risk Drug Users.

Authors:  Roman Shrestha; Pramila Karki; Frederick L Altice; Oleksandr Dubov; Liana Fraenkel; Tania Huedo-Medina; Michael Copenhaver
Journal:  AIDS Behav       Date:  2018-04

3.  Preferences for CT colonography and colonoscopy as diagnostic tests for colorectal cancer: a discrete choice experiment.

Authors:  Kirsten Howard; Glenn Salkeld; Michael Pignone; Peter Hewett; Peter Cheung; Julie Olsen; Wayne Clapton; Ian C Roberts-Thomson
Journal:  Value Health       Date:  2011-12       Impact factor: 5.725

4.  Patients' preferences and priorities regarding colorectal cancer screening.

Authors:  James G Dolan; Emily Boohaker; Jeroan Allison; Thomas F Imperiale
Journal:  Med Decis Making       Date:  2012-08-15       Impact factor: 2.583

5.  Attributes Used for Cancer Screening Discrete Choice Experiments: A Systematic Review.

Authors:  Rebekah Hall; Antonieta Medina-Lara; Willie Hamilton; Anne E Spencer
Journal:  Patient       Date:  2021-10-21       Impact factor: 3.883

Review 6.  Patient preferences for the treatment of type 2 diabetes: a scoping review.

Authors:  Susan M Joy; Emily Little; Nisa M Maruthur; Tanjala S Purnell; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2013-10       Impact factor: 4.981

7.  Colorectal Cancer Screening: Preferences, Past Behavior, and Future Intentions.

Authors:  Carol Mansfield; Donatus U Ekwueme; Florence K L Tangka; Derek S Brown; Judith Lee Smith; Gery P Guy; Chunyu Li; Brett Hauber
Journal:  Patient       Date:  2018-12       Impact factor: 3.883

8.  The COMPASs Study: Community Preferences for Prostate cAncer Screening. Protocol for a quantitative preference study.

Authors:  Kirsten Howard; Glenn P Salkeld; Graham J Mann; Manish I Patel; Michelle Cunich; Michael P Pignone
Journal:  BMJ Open       Date:  2012-01-07       Impact factor: 2.692

9.  And When I Die: Theory of Planned Behavior as Applied to Sperm Cryopreservation.

Authors:  Limor Dina Gonen
Journal:  Healthcare (Basel)       Date:  2021-05-09

10.  Evaluating preferences for colorectal cancer screening in individuals under age 50 using the Analytic Hierarchy Process.

Authors:  Travis Hyams; Bruce Golden; John Sammarco; Shahnaz Sultan; Evelyn King-Marshall; Min Qi Wang; Barbara Curbow
Journal:  BMC Health Serv Res       Date:  2021-07-29       Impact factor: 2.655

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