Literature DB >> 11028136

Cost-benefit analysis of mammography screening in Denmark based on discrete ranking data.

D Gyrd-Hansen1.   

Abstract

OBJECTIVE: Economic evaluations such as cost-effectiveness and cost-utility analyses generally fail to incorporate elements of intangible costs and benefits, such as anxiety and discomfort associated with the screening test and diagnostic test, as well as the magnitude of utility associated with a reduction in the risk of dying from cancer. This paper seeks to include all costs and effects incurred by introducing mammography screening through the application of discrete ranking modeling.
METHODS: In the present analysis, 207 women were interviewed and asked to rank, according to priority, a number of alternative breast cancer screening setups. The alternative programs varied with respect to number of tests performed, risk reduction obtained, probability of a false-positive outcome, and extent of copayment. Using discrete ranking modeling, the stated preferences were analyzed and the relative weighting of the program attributes identified. For a range of hypothetical breast cancer programs, relative utilities and corresponding willingness-to-pay estimates were derived.
RESULTS: A comparison of cost and willingness to pay for each of the programs suggested that net benefits are maximized when screening person aged 50-74 years biennially. More intensive screening produces lower or similar levels of utility at a higher cost.
CONCLUSION: Discrete ranking modeling can aid decision making by identifying inferior healthcare programs, i.e., programs that are more costly but less beneficial.

Entities:  

Mesh:

Year:  2000        PMID: 11028136     DOI: 10.1017/s0266462300102089

Source DB:  PubMed          Journal:  Int J Technol Assess Health Care        ISSN: 0266-4623            Impact factor:   2.188


  6 in total

1.  Recommendations on screening for breast cancer in average-risk women aged 40-74 years.

Authors:  Marcello Tonelli; Sarah Connor Gorber; Michel Joffres; James Dickinson; Harminder Singh; Gabriela Lewin; Richard Birtwhistle; Donna Fitzpatrick-Lewis; Nicole Hodgson; Donna Ciliska; Mary Gauld; Yan Yun Liu
Journal:  CMAJ       Date:  2011-11-22       Impact factor: 8.262

2.  Recommendations on screening for breast cancer in women aged 40-74 years who are not at increased risk for breast cancer.

Authors:  Scott Klarenbach; Nicki Sims-Jones; Gabriela Lewin; Harminder Singh; Guylène Thériault; Marcello Tonelli; Marion Doull; Susan Courage; Alejandra Jaramillo Garcia; Brett D Thombs
Journal:  CMAJ       Date:  2018-12-10       Impact factor: 8.262

3.  A review of studies examining stated preferences for cancer screening.

Authors:  Kathryn A Phillips; Stephanie Van Bebber; Deborah Marshall; Judith Walsh; Lehana Thabane
Journal:  Prev Chronic Dis       Date:  2006-06-15       Impact factor: 2.830

Review 4.  Stated Preference for Cancer Screening: A Systematic Review of the Literature, 1990-2013.

Authors:  Carol Mansfield; Florence K L Tangka; Donatus U Ekwueme; Judith Lee Smith; Gery P Guy; Chunyu Li; A Brett Hauber
Journal:  Prev Chronic Dis       Date:  2016-02-25       Impact factor: 2.830

5.  Women's preferences, willingness-to-pay, and predicted uptake for single-nucleotide polymorphism gene testing to guide personalized breast cancer screening strategies: a discrete choice experiment.

Authors:  Xin Yi Wong; Catharina Gm Groothuis-Oudshoorn; Chuen Seng Tan; Janine A van Til; Mikael Hartman; Kok Joon Chong; Maarten J IJzerman; Hwee-Lin Wee
Journal:  Patient Prefer Adherence       Date:  2018-09-18       Impact factor: 2.711

6.  Developing a discrete choice experiment in Malawi: eliciting preferences for breast cancer early detection services.

Authors:  Racquel E Kohler; Clara N Lee; Satish Gopal; Bryce B Reeve; Bryan J Weiner; Stephanie B Wheeler
Journal:  Patient Prefer Adherence       Date:  2015-10-14       Impact factor: 2.711

  6 in total

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