HERC: Economics of Implementation & QUERI
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Economics of Implementation & QUERI

Implementation research is designed to improve the delivery of effective care. There are different implementation strategies, and they often involve different levels of effort. We work to understand the economics of these different implementation strategies. Our analyses are usually conducted in conjunction with the primary trial to ensure coordinated measurement of clinical and economic outcomes.

What is QUERI?

The Quality Enhancement Research Initiative (QUERI) is a quality improvement program that is a central component of VA's commitment to improving the quality of Veterans' healthcare by implementing effective clinical practices into routine care. QUERI supports economic analyses of implementation research to support future decisions.

How does HERC support QUERI?

HERC supports QUERI by (a) facilitating scientifically rigorous economic analyses of QUERI implementation research, (b) assisting QUERI strategic goals that are working to reduce the time from research to practice and (c) developing resources and tools to guide QUERI researchers interested in economics.

What are the steps to conduct economic analyses for implementation research?

There are three phases for conducting economic analyses for implementation research: (i) Study Design, (ii) Data Collection, and (iii) Data Analysis.

(i) Study Design

HERC developed these Guidelines for Economic Analysis to consider which form of economic analysis is most appropriate for the implementation/QUERI study.

The most common forms of economic analysis for implementation/QUERI studies include:

(ii) Data Collection

Examples of micro-costing tools from other studies:

(Note: This form was used in an implementation trial. See https://www.cdc.gov/pcd/issues/2007/jan/06_0058.htm).

(Note: Please direct questions regarding this form to John.Fortney@va.gov and Suparna.Rajan@va.gov).

(Note: Please direct questions regarding this form to Michael.Palmer8@va.gov.

(iii) Data Analysis

Analyze the data and estimate costs for patients.

This Statistical Program, designed for a past project, provides guidance on how to estimate annualized costs for patients. Users can modify this program, as needed, to identify the appropriate time interval and cost subtotals. In this program, the time interval was set at 1 year. For many projects, shorter time intervals, such as monthly or quarterly intervals, may be appropriate.

Where can I learn more about Economics of Implementation?

Cyber Seminars

QUERI Implementation Seminars on the HSR&D Cyber Seminar Web Site

Journal Articles and Book Chapters

Costing and the Stages of Implementation

  • Grimshaw JM, Thomas RE, MacLennan G, et al. Effectiveness and efficiency of guideline dissemination and implementation strategies. Health Technol Assess. Feb 2004;8(6):iii-iv, 1-72.
  • Liu CF, Rubenstein LV, Kirchner JE, et al. Organizational cost of quality improvement for depression care. Health Serv Res. Feb 2009;44(1):225-244.
  • McInnes DK, Solomon JL, Shimada SL, et al. Development and evaluation of an internet and personal health record training program for low-income patients with HIV or hepatitis C. Med Care. Mar 2013;51(3 Suppl 1):S62-66.
  • McIntosh E. Economic evaluation of guidelines implementation strategies. In: Changing professional practice: theory and practice of clinical guidelines implementation. Thorson T, Mäkelä M, eds. Copenhagen: Danish Institute for Health Services Research and Development, 1999. DSI Report no. 99.05. URL: http://www.dsi.dk/projects/cpp/monograph/DSI9905.pdf.
  • Severens JL. Value for money of changing healthcare services? Economic evaluation of quality improvement. Qual Saf Health Care 2003;12(5):366-371.
  • Smith MW, Barnett PG. The role of economics in the QUERI program: QUERI Series. Implement Sci. 2008;3:20.
  • Vale L, Thomas R, MacLennan G, Grimshaw J. Systematic review of economic evaluations and cost analyses of guideline implementation strategies. Eur J Health Econ 2007;8(2):111-121.

Cost-Effectiveness Analysis Methods (without referece to implementation)

  • Drummond MF, Jefferson TO. Guidelines for authors and peer reviewers of economic submissions to the British Medical Journal. BMJ 1996;313:275-283.
  • Neumann PJ, Sanders GD, Russell LB, Siegel JE, Ganiats TG. Cost-effectiveness in Health and Medicine: Second Edition. New York: Oxford University Press, 2016.
  • Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D, Krahn M, Kuntz KM, Meltzer DO, Owens DK, Prosser LA, Salomon JA, Sculpher MJ, Trikalinos TA, Russell LB, Siegel JE, Ganiats TG. Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness AnalysesSecond Panel on Cost-Effectiveness in Health and Medicine. JAMA. 2016;316(10):1093–1103. doi:10.1001/jama.2016.12195

Budget Impact Analysis

  • Luck J, Parkerton P, Hagigi F. What is the business case for improving care for patients with complex conditions? J Gen Int Med 2007;22(Suppl 3):396-402.
  • Mauskopf JA, Sullivan SD, Annemans L, et al. Principle of good practice for budget impact analysis: report of the ISPOR Task Force on Good Research Practices – Budget Impact Analysis. Value in Health 2007;10(5):336-347.
  • Nicholson S, Pauly MV, Polsky D, et al. How to present the business case for healthcare quality to employers. Appl Health Econ Health Policy 2005;4(4):209-218.
  • Sullivan SD, Mauskopf JA, Augustovski F, et al. Budget impact analysis-principles of goodpractice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value Health. Jan-Feb 2014;17(1):5-14.

Sensitivity Analysis

  • Briggs A, Goeree R, Blackhouse G, O’ Brien B. Probabilistic analysis of cost-effectiveness models: choosing between treatment strategies for gastroesophageal reflux disease. Medical Decision Making 2002;4:290–308.
  • Briggs A, Schulpher M, Claxton K. Decision modelling for health economic evaluation. Oxford: Oxford University Press, 2006.
  • Doubilet P, Begg CB, Weinstein MC, Braun P, McNeil BJ. Probabilistic sensitivity analysis using Monte Carlo simulation. A practical approach. Medical Decision Making 1985;5(2):157-177.