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Economic evaluation in implementation science: Making the business case for implementation strategies
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Implementation researchers have made notable progress in developing and testing implementation strategies (i.e., highly-specified methods used to help providers improve uptake of mental health evidence-based practices: EBPs). Yet, implementation strategies are not widely applied in healthcare organizations to improve delivery of EBPs. Economic considerations are a key factor influencing the use of implementation strategies to deliver and sustain mental health evidence-based practices, in part because many health care leaders are reluctant to invest in ongoing implementation strategy support without knowing the return-on-investment. Comparative economic evaluation of implementation strategies provides critical information for payers, policymakers, and providers to make informed decisions if specific strategies are an efficient use of scarce organizational resources. Currently, few implementation studies include implementation cost data and even fewer conduct comparative economic analyses of implementation strategies. This summary will introduce clinicians, researchers and other health professionals to the economic evaluation in implementation science. We provide an overview of different economic evaluation methods, discuss differences between economic evaluation in health services and implementation science. We also highlight approaches and frameworks to guide economic evaluation of implementation, provide an example for a cognitive-behavioral therapy program and discuss recommendations.
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“Ongoing work is making economic evaluations more relevant to implementation (see [9])—e.g., through increased use of budget impact analyses to characterize budget gaps—but additional information is needed by key healthcare delivery and financing decision-makers.”
From Translating economic evaluations into financing strategies for implementing evidence-based practices (2021) · cites this paper as [9]
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Self-citationIncluding Economic Evaluations in Implementation Science
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The forgotten contexts of evaluation
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Metadata
- Authors
- Eisman, A. B., Kilbourne, A. M., Dopp, A. R., Saldana, L., & Eisenberg, D.
- Affiliations
- University of Michigan (US)
- United States Department of Veterans Affairs (US)
- University of Arkansas at Fayetteville (US)
- Oregon Social Learning Center (US)
- Corresponding author
- Eisman, Andria B.
- Venue
- Psychiatry Research
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 283
- Pages
- 112433
- ISSN
- 0165-1781 (ISSN-L)
- PMC
- PMC6898762
- OpenAlex
- W2952330955
- Cited by
- 210
- References
- 50
- Citations by year
- 2026: 21 · 2025: 30 · 2024: 47 · 2023: 37 · 2022: 35 · 2021: 24 · 2020: 12
- FWCI
- 3.40
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Psychiatry Research (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health
- National Institute on Drug Abuse
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Social Sciences › Public Administration › Evaluation and Performance Assessment
- Keywords
- economic evaluation, implementation science, implementation strategies, return on investment, implementation costs, comparative economic analysis, cognitive behavioral therapy
- MeSH terms
- Implementation Science, Mental Disorders, Cost-Benefit Analysis, Delivery of Health Care, Humans, Mental Health, Cognitive Behavioral Therapy, Evidence-Based Practice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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