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.
We systematically reviewed the literature and methods to assess how closely BIA guidelines are followed when BIAs are performed for cancer-screening programs.
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.
Eligible studies were BIAs evaluating cancer-screening programs published in English, 2010-2018.
Standardized evidence tables were generated to extract and compare study characteristics outlined by the ISPOR BIA Task Force.
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.
"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.
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.
Applied health economics and health policy. 2019 Apr 24 [Epub ahead of print]
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 Siebert
Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, 6060, Hall in Tyrol, Austria., Evidence-based Health Care, Main Association of Austrian Social Insurance Institutions, Haidingergasse 1, 1030, Vienna, Austria., DWH Simulation Services, DEXHELPP, Neustiftgasse 57-59, 1070, Vienna, Austria., Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac St, Boston, MA, 02114, USA., Department of Health Systems Management, School of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er-Sheva, Israel., RTI Health Solutions, RTI International, 3040 Cornwallis Rd, Durham, NC, 27709, USA., Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, 6060, Hall in Tyrol, Austria. .