Literature DB >> 27379742

Use of Decision Models in the Development of Evidence-Based Clinical Preventive Services Recommendations: Methods of the U.S. Preventive Services Task Force.

Douglas K Owens1, Evelyn P Whitlock1, Jillian Henderson1, Michael P Pignone1, Alex H Krist1, Kirsten Bibbins-Domingo1, Susan J Curry1, Karina W Davidson1, Mark Ebell1, Matthew W Gillman1, David C Grossman1, Alex R Kemper1, Ann E Kurth1, Michael Maciosek1, Albert L Siu1, Michael L LeFevre1.   

Abstract

The U.S. Preventive Services Task Force (USPSTF) develops evidence-based recommendations about preventive care based on comprehensive systematic reviews of the best available evidence. Decision models provide a complementary, quantitative approach to support the USPSTF as it deliberates about the evidence and develops recommendations for clinical and policy use. This article describes the rationale for using modeling, an approach to selecting topics for modeling, and how modeling may inform recommendations about clinical preventive services. Decision modeling is useful when clinical questions remain about how to target an empirically established clinical preventive service at the individual or program level or when complex determinations of magnitude of net benefit, overall or among important subpopulations, are required. Before deciding whether to use decision modeling, the USPSTF assesses whether the benefits and harms of the preventive service have been established empirically, assesses whether there are key issues about applicability or implementation that modeling could address, and then defines the decision problem and key questions to address through modeling. Decision analyses conducted for the USPSTF are expected to follow best practices for modeling. For chosen topics, the USPSTF assesses the strengths and limitations of the systematically reviewed evidence and the modeling analyses and integrates the results of each to make preventive service recommendations.

Mesh:

Year:  2016        PMID: 27379742     DOI: 10.7326/M15-2531

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  10 in total

1.  Clinical Benefits, Harms, and Cost-Effectiveness of Breast Cancer Screening for Survivors of Childhood Cancer Treated With Chest Radiation : A Comparative Modeling Study.

Authors:  Jennifer M Yeh; Kathryn P Lowry; Clyde B Schechter; Lisa R Diller; Oguzhan Alagoz; Gregory T Armstrong; John M Hampton; Wendy Leisenring; Qi Liu; Jeanne S Mandelblatt; Diana L Miglioretti; Chaya S Moskowitz; Kevin C Oeffinger; Amy Trentham-Dietz; Natasha K Stout
Journal:  Ann Intern Med       Date:  2020-07-07       Impact factor: 25.391

2.  Management of Active Surveillance-Eligible Prostate Cancer during Pretransplantation Workup of Patients with Kidney Failure: A Simulation Study.

Authors:  Uwe Bieri; Kerstin Hübel; Harald Seeger; Girish S Kulkarni; Tullio Sulser; Thomas Hermanns; Marian S Wettstein
Journal:  Clin J Am Soc Nephrol       Date:  2020-05-07       Impact factor: 8.237

Review 3.  New Agents, Emerging Late Effects, and the Development of Precision Survivorship.

Authors:  Eric J Chow; Zoltan Antal; Louis S Constine; Rebecca Gardner; W Hamish Wallace; Brent R Weil; Jennifer M Yeh; Elizabeth Fox
Journal:  J Clin Oncol       Date:  2018-06-06       Impact factor: 44.544

4.  Family Spillover Effects: Are Economic Evaluations Misrepresenting the Value of Healthcare Interventions to Society?

Authors:  Ashley A Leech; Pei-Jung Lin; Brittany D'Cruz; Susan K Parsons; Tara A Lavelle
Journal:  Appl Health Econ Health Policy       Date:  2022-08-23       Impact factor: 3.686

Review 5.  Current and coming challenges in the management of the survivorship population.

Authors:  Eric J Chow; Kirsten K Ness; Gregory T Armstrong; Nickhill Bhakta; Jennifer M Yeh; Smita Bhatia; Wendy Landier; Louis S Constine; Melissa M Hudson; Paul C Nathan
Journal:  Semin Oncol       Date:  2020-03-04       Impact factor: 4.929

6.  Cost-effectiveness of antithrombotic agents for atrial fibrillation in older adults at risk for falls: a mathematical modelling study.

Authors:  Eric K C Wong; Christina Belza; David M J Naimark; Sharon E Straus; Harindra C Wijeysundera
Journal:  CMAJ Open       Date:  2020-11-06

Review 7.  Cancer screening recommendations: an international comparison of high income countries.

Authors:  Mark H Ebell; Thuy Nhu Thai; Kyle J Royalty
Journal:  Public Health Rev       Date:  2018-03-02

8.  The Effectiveness and Cost-Effectiveness of Hepatitis C Screening for Migrants in the EU/EEA: A Systematic Review.

Authors:  Christina Greenaway; Iuliia Makarenko; Claire Nour Abou Chakra; Balqis Alabdulkarim; Robin Christensen; Adam Palayew; Anh Tran; Lukas Staub; Manish Pareek; Joerg J Meerpohl; Teymur Noori; Irene Veldhuijzen; Kevin Pottie; Francesco Castelli; Rachael L Morton
Journal:  Int J Environ Res Public Health       Date:  2018-09-14       Impact factor: 3.390

9.  Adjuvant Versus Salvage Radiotherapy for Patients With Adverse Pathological Findings Following Radical Prostatectomy: A Decision Analysis.

Authors:  Christopher J D Wallis; Gerard Morton; Angela Jerath; Raj Satkunasviam; Ewa Szumacher; Sender Herschorn; Ronald T Kodama; Girish S Kulkarni; David Naimark; Robert K Nam
Journal:  MDM Policy Pract       Date:  2017-05-19

10.  Effect and cost-effectiveness of national gastric cancer screening in Japan: a microsimulation modeling study.

Authors:  Hsi-Lan Huang; Chi Yan Leung; Eiko Saito; Kota Katanoda; Chin Hur; Chung Yin Kong; Shuhei Nomura; Kenji Shibuya
Journal:  BMC Med       Date:  2020-09-14       Impact factor: 8.775

  10 in total

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