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Applied Health Economics and Health Policy

, Volume 17, Issue 4, pp 493–511 | Cite as

Budget Impact Analysis of Cancer Screening: A Methodological Review

  • Beate Jahn
  • Jovan Todorovic
  • Marvin Bundo
  • Gaby Sroczynski
  • Annette Conrads-Frank
  • Ursula Rochau
  • Gottfried Endel
  • Ingrid Wilbacher
  • Nikoletta Malbaski
  • Niki Popper
  • Jagpreet Chhatwal
  • Dan Greenberg
  • Josephine Mauskopf
  • Uwe SiebertEmail author
Systematic Review

Abstract

Background

Budget impact analyses (BIAs) describe changes in intervention- and disease-related costs of new technologies. Evidence on the quality of BIAs for cancer screening is lacking.

Objectives

We systematically reviewed the literature and methods to assess how closely BIA guidelines are followed when BIAs are performed for cancer-screening programs.

Data sources

Systematic searches were conducted in MEDLINE, EMBASE, EconLit, CRD (Centre for Reviews and Dissemination, University of York), and CEA registry of the Tufts Medical Center.

Study eligibility criteria

Eligible studies were BIAs evaluating cancer-screening programs published in English, 2010–2018.

Synthesis methods

Standardized evidence tables were generated to extract and compare study characteristics outlined by the ISPOR BIA Task Force.

Results

Nineteen studies were identified evaluating screening for breast (5), colorectal (6), cervical (3), lung (1), prostate (3), and skin (1) cancers. Model designs included decision-analytic models (13) and simple cost calculators (6). From all studies, only 53% reported costs for a minimum of 3 years, 58% compared to a mix of screening options, 42% reported model validation, and 37% reported uncertainty analysis for participation rates. The quality of studies appeared to be independent of cancer site.

Limitations

“Gray” literature was not searched, misinterpretation is possible due to limited information in publications, and focus was on international methodological guidelines rather than regional guidelines.

Conclusions

Our review highlights considerable variability in the extent to which BIAs evaluating cancer-screening programs followed recommended guidelines. The annual budget impact at least over the next 3–5 years should be estimated. Validation and uncertainty analysis should always be conducted. Continued dissemination efforts of existing best-practice guidelines are necessary to ensure high-quality analyses.

Notes

Acknowledgements

This project has been part of the DEXHELPP (Decision Support for Health Policy and Planning: Methods, Models and Technologies based on Existing Health Care Data) project in the frame of COMET-Competence Centers for Excellent Technologies supported by BMVIT, BMWFW and the state Vienna, by UMIT (University for Health Sciences, Medical Informatics and Technology), and by Erasmus Mundus Western Balkans (ERAWEB), a project funded by the European Commission. We thank Kelley J. P. Lindberg for proofreading and language editing.

Author Contributions

BJ, JT, MB, and US made substantial contributions to conception and design, acquisition of information, analysis and interpretation of results. BJ, JT, MB, GS, ACF, UR, GE, IW, NM, NP, JC, DG, JM, and US were involved in drafting the manuscript and revising it critically for important intellectual content. BJ, JT, MB, GS, ACF, UR, GE, IW, NM, NP, JC, DG, JM, and US agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final manuscript.

Compliance with Ethical Standards

The study was registered at the ethics committee of UMIT (University for Health Sciences, Medical Computer Science and Technology), Hall i.T. Austria (Registration 2162). Ethical standards were followed.

Availability of data and material

All data and material are available in published, mentioned, and referenced studies.

Conflict of interest

The authors (Jahn B, Todorovic J, Bundo M, Sroczynski G, Conrads-Frank A, Rochau U, Endel G, Wilbacher I, Malbaski N, Popper N, Chhatwal J, Greenberg D, Mauskopf J, Siebert U) declare that they have no competing interests.

Funding

This project was supported in part by DEXHELPP (Decision Support for Health Policy and Planning: Methods, Models and Technologies based on Existing Health Care Data, Grant no. 843550). DEXHELPP is in the frame of COMET-Competence Centers for Excellent Technologies. DEXHELPP is supported by BMVIT, BMWFW and the state Vienna. The COMET program is transacted by the FFG. In parts, this work has also been financially supported through Erasmus Mundus Western Balkans (ERAWEB), a project funded by the European Commission. The funding body did not have any influence on the design of the study and collection, analysis, and interpretation of data and in manuscript writing.

Supplementary material

40258_2019_475_MOESM1_ESM.docx (208 kb)
Supplementary material 1 (DOCX 207 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Beate Jahn
    • 1
  • Jovan Todorovic
    • 1
  • Marvin Bundo
    • 1
  • Gaby Sroczynski
    • 1
  • Annette Conrads-Frank
    • 1
  • Ursula Rochau
    • 1
  • Gottfried Endel
    • 2
  • Ingrid Wilbacher
    • 2
  • Nikoletta Malbaski
    • 2
  • Niki Popper
    • 3
    • 4
  • Jagpreet Chhatwal
    • 5
  • Dan Greenberg
    • 6
  • Josephine Mauskopf
    • 7
  • Uwe Siebert
    • 1
    • 5
    • 8
    • 9
    Email author
  1. 1.Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology AssessmentUMIT-University for Health Sciences, Medical Informatics and TechnologyHall in TyrolAustria
  2. 2.Evidence-based Health CareMain Association of Austrian Social Insurance InstitutionsViennaAustria
  3. 3.DWH Simulation ServicesDEXHELPPViennaAustria
  4. 4.TU Wien, Information and Software Engineering Group (ifs - E194-01)ViennaAustria
  5. 5.Institute for Technology Assessment and Department of Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonUSA
  6. 6.Department of Health Systems Management, School of Public Health, Faculty of Health SciencesBen-Gurion University of the NegevBe’er-ShevaIsrael
  7. 7.RTI Health Solutions, RTI InternationalDurhamUSA
  8. 8.Division of Health Technology AssessmentONCOTYROL-Center for Personalized Cancer MedicineInnsbruckAustria
  9. 9.Department of Health Policy and Management, Center for Health Decision ScienceHarvard T.H. Chan School of Public HealthBostonUSA

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