Prevention Science

, Volume 15, Issue 6, pp 789–798 | Cite as

Research Priorities for Economic Analyses of Prevention: Current Issues and Future Directions

  • D. Max Crowley
  • Laura Griner Hill
  • Margaret R. Kuklinski
  • Damon E. Jones
Article

Abstract

In response to growing interest in economic analyses of prevention efforts, a diverse group of prevention researchers, economists, and policy analysts convened a scientific panel, on “Research Priorities in Economic Analysis of Prevention” at the 19th annual conference of the Society for Prevention Research. The panel articulated four priorities that, if followed in future research, would make economic analyses of prevention efforts easier to compare and more relevant to policymakers and community stakeholders. These priorities are: (1) increased standardization of evaluation methods, (2) improved economic valuation of common prevention outcomes, (3) expanded efforts to maximize evaluation generalizability and impact as well as (4) enhanced transparency and communicability of economic evaluations. In this paper, we define three types of economic analyses in prevention, provide context and rationale for these four priorities as well as related sub-priorities, and discuss the challenges inherent in meeting them.

Keywords

Economic analysis Benefit–cost Economics of prevention Prevention efficiency 

References

  1. Adler, M. D., & Posner, E. A. (1999). Rethinking cost–benefit analysis. The Yale Law Journal, 109, 165. doi:10.2307/797489.CrossRefGoogle Scholar
  2. Akerlund, K. M. (2000). Prevention program sustainability: The state’s perspective. Journal of Community Psychology, 28, 353–362. doi:10.1002/(SICI)1520-6629(200005)28:3<353::AID-JCOP9>3.0.CO;2-6.CrossRefGoogle Scholar
  3. Anderson, D., Bowland, B., Cartwright, W., & Bassin, G. (1998). Service-level costing of drug abuse treatment. Journal of Substance Abuse Treatment, 15, 201–211. doi:10.1016/S0740-5472(97)00189-X.CrossRefPubMedGoogle Scholar
  4. Aos, S., Lee, S., Drake, E. K., Pennucci, A., Klima, T., Millier, M., … Burley, M. (2011). Return on Investment: Evidence-Based Options to Improve Statewide Outcomes. Retrieved from http://www.wsipp.wa.gov/pub.asp?docid=11-07-1201
  5. Aos, S., Lieb, R., Mayfield, J., Miller, M., & Pennucci, A. (2004). Benefits and Costs of Prevention and Early Intervention Programs for Youth. Retrieved from http://www.wsipp.wa.gov/pub.asp?docid=04-07-3901
  6. Armstrong, R., Waters, E., Moore, L., Riggs, E., Cuervo, L. G., Lumbiganon, P., & Hawe, P. (2008). Improving the reporting of public health intervention research: Advancing TREND and CONSORT. Journal of Public Health, 30, 103–109. doi:10.1093/pubmed/fdm082.CrossRefPubMedGoogle Scholar
  7. August, G. J., Bloomquist, M. L., Lee, S. S., Realmuto, G. M., & Hektner, J. M. (2006). Can evidence-based prevention programs be sustained in community practice settings? The early risers’ advanced-stage effectiveness trial. Prevention Science, 7, 151–165. doi:10.1007/s11121-005-0024-z.CrossRefPubMedGoogle Scholar
  8. Beatty, A. S. (2009). Strengthening benefit-cost analysis for early childhood interventions workshop summary. Washington, D.C.: National Academies Press.Google Scholar
  9. Belfield, C., Nores, M., Barnett, S., & Scheweinhart, L. (2006). The high/scope Perry preschool program: Cost–benefit analysis using data from the age-40 follow up. Journal of Human Resources, 41, 162–190.CrossRefGoogle Scholar
  10. Bierman, K. L., Coie, J. D., Dodge, K. A., Foster, E. M., Greenberg, M. T., Lochman, J. E., & Pinderhughes, E. E. (2004). The effects of the fast track program on serious problem outcomes at the end of Elementary School. Journal of Clinical Child and Adolescent Psychology, 33, 650–661. doi:10.1207/s15374424jccp3304_1.CrossRefPubMedGoogle Scholar
  11. Briggs, A., Sculpher, M., & Buxton, M. (1994). Uncertainty in the economic evaluation of health care technologies: The role of sensitivity analysis. Health Economics, 3, 95–104. doi:10.1002/hec.4730030206.CrossRefPubMedGoogle Scholar
  12. Brouwer, W. B. F., Koopmanschap, M. A., & Rutten, F. F. H. (1997). Productivity costs in cost-effectiveness analysis: Numerator or denominator: A further discussion. Health Economics, 6, 511–514. doi:10.1002/(SICI)1099-1050(199709)6:5<511::AID-HEC297>3.0.CO;2-K.CrossRefPubMedGoogle Scholar
  13. Bureau of Labor Statistics and the Census Bureau. (2012). Current Population Survey (CPS). Retrieved from http://www.census.gov/cps/
  14. Claxton, K., Sculpher, M., Culyer, A., McCabe, C., Briggs, A., Akehurst, R., & Brazier, J. (2006). Discounting and cost-effectiveness in NICE—Stepping back to sort out a confusion. Health Economics, 15, 1–4. doi:10.1002/hec.1081.CrossRefPubMedGoogle Scholar
  15. Cochrane Collaboration. (2012). Health Economic Evaluations Database (HEED) extended to all Cochrane contributors. Campbell & Cochrane Economics Methods Group. Retrieved from http://www.cochrane.org/news/blog/health-economic-evaluations-database-heed-extended-all-cochrane-contributors
  16. Cole, S., & Hernan, M. (2008). Constructing inverse probability weights for marginal structural models. American Journal of Epidemiology, 168, 656–664.PubMedCentralCrossRefPubMedGoogle Scholar
  17. Cookson, R., Drummond, M., & Weatherly, H. (2009). Explicit incorporation of equity considerations into economic evaluation of public health interventions. Health Economics, Policy and Law, 4(02), 231. doi:10.1017/S1744133109004903
  18. Corso, P., Mercy, J., Simon, T., Finkelstein, E., & Miller, T. (2007). Medical Costs and Productivity Losses Due to Interpersonal and Self-Directed Violence in the United States. American Journal of Preventive Medicine, 32(6), 474–482.e2. doi:10.1016/j.amepre.2007.02.010 Google Scholar
  19. Corso, P. S., Fang, X., & Mercy, J. A. (2011). Benefits of preventing a death associated with child maltreatment: Evidence from willingness-to-pay survey data. American Journal of Public Health, 101, 487–490. doi:10.2105/AJPH.2010.196584.PubMedCentralCrossRefPubMedGoogle Scholar
  20. Crowley, D. M., Jones, D. E., Greenberg, M. T., Feinberg, M. E., & Spoth, R. (2012). Resource consumption of a diffusion model for prevention programs: The prosper delivery system. Journal of Adolescent Health, 50, 256–263. doi:10.1016/j.jadohealth.2011.07.001.PubMedCentralCrossRefPubMedGoogle Scholar
  21. Crowley, D. M., Coffman, D. L., Feinberg, M. E., Greenberg, M. T., & Spoth, R. L. (2013). Evaluating the impact of implementation factors on family-based prevention programming: Methods for strengthening causal inference. Prevention Science. doi:10.1007/s11121-012-0352-8.
  22. Diehr, P., Yanez, D., Ash, A., Hornbrook, M., & Lin, D. Y. (1999). Methods for analyzing health care utilization and costs. Annual Review of Public Health, 20, 125–144. doi:10.1146/annurev.publhealth.20.1.125.CrossRefPubMedGoogle Scholar
  23. Dino, G., Horn, K., Abdulkadri, A., Kalsekar, I., & Branstetter, S. (2008). Cost-effectiveness analysis of the not on tobacco program for adolescent smoking cessation. Prevention Science, 9, 38–46. doi:10.1007/s11121-008-0082-0.CrossRefPubMedGoogle Scholar
  24. Doubilet, P., Begg, C. B., Weinstein, M. C., Braun, P., & McNeil, B. J. (1985). Probabilistic sensitivity analysis using Monte Carlo simulation. A practical approach. Medical Decision Making: An International Journal of the Society for Medical Decision Making, 5, 157–177.CrossRefGoogle Scholar
  25. Drummond, M. F. (2005). Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press.Google Scholar
  26. Drummond, M. F., & Jefferson, T. (1996). Guidelines for authors and peer reviewers of economic submissions to BMJ. BMJ, 313, 275–283.PubMedCentralCrossRefPubMedGoogle Scholar
  27. Durlak, J. A. (1998). Common risk and protective factors in successful prevention programs. American Journal of Orthopsychiatry, 68, 512–520. doi:10.1037/h0080360.CrossRefPubMedGoogle Scholar
  28. Elliott, D. S., & Mihalic, S. (2004). Issues in disseminating and replicating effective prevention programs. Prevention Science, 5, 47–53. doi:10.1023/B:PREV.0000013981.28071.52.CrossRefPubMedGoogle Scholar
  29. Flay, B. R., Biglan, A., Boruch, R. F., Castro, F. G., Gottfredson, D., Kellam, S., & Ji, P. (2005). Standards of evidence: Criteria for efficacy, effectiveness and dissemination. Prevention Science, 6, 151–175. doi:10.1007/s11121-005-5553-y.CrossRefPubMedGoogle Scholar
  30. Foster, E. M. (2003). Propensity score matching. Medical Care, 41, 1183–1192. doi:10.1097/01.MLR.0000089629.62884.22.CrossRefPubMedGoogle Scholar
  31. Foster, E. M., Dodge, K. A., & Jones, D. (2003). Issues in the economic evaluation of prevention programs. Applied Developmental Science, 7, 76–86. doi:10.1207/S1532480XADS0702_4.PubMedCentralCrossRefPubMedGoogle Scholar
  32. Foster, E. M., Jones, D., & And the Conduct Problems Prevention Research Group. (2006). Can a costly intervention be cost-effective?: An analysis of violence prevention. Archives of General Psychiatry, 63, 1284–1291. doi:10.1001/archpsyc.63.11.1284.PubMedCentralCrossRefPubMedGoogle Scholar
  33. Foster, E. M., Porter, M. M., Ayers, T. S., Kaplan, D. L., & Sandler, I. (2007). Estimating the costs of preventive interventions. Evaluation Review, 31, 261–286. doi:10.1177/0193841X07299247.CrossRefPubMedGoogle Scholar
  34. Foster, E. M., Prinz, R. J., Sanders, M. R., & Shapiro, C. J. (2008). The costs of a public health infrastructure for delivering parenting and family support. Children and Youth Services Review, 30, 493–501. doi:10.1016/j.childyouth.2007.11.002.CrossRefGoogle Scholar
  35. Frangakis, C., & Rubin, D. (2002). Principal stratification in causal inference. Biometrics, 58, 21–29. doi:10.1111/j.0006-341X.2002.00021.x.PubMedCentralCrossRefPubMedGoogle Scholar
  36. French, M. T., Salomé, H. J., Sindelar, J. L., & Thomas McLellan, A. (2002). Benefit–cost analysis of addiction treatment: Methodological guidelines and empirical application using the DATCAP and ASI. Health Services Research, 37, 433–455. doi:10.1111/1475-6773.031.PubMedCentralCrossRefPubMedGoogle Scholar
  37. Gold, M. R., Stevenson, D., & Fryback, D. G. (2002). HALYS and QALYS and DALYS, oh my: Similarities and differences in summary measures of population health. Annual Review of Public Health, 23, 115–134. doi:10.1146/annurev.publhealth.23.100901.140513.CrossRefPubMedGoogle Scholar
  38. Gravelle, H., Brouwer, W., Niessen, L., Postma, M., & Rutten, F. (2007). Discounting in economic evaluations: Stepping forward towards optimal decision rules. Health Economics, 16, 307–317. doi:10.1002/hec.1168.CrossRefPubMedGoogle Scholar
  39. Greenberg, M. T., Domitrovich, C., & Bumbarger, B. (2001). The prevention of mental disorders in school-aged children: Current state of the field. Prevention & Treatment, 4. doi:10.1037/1522-3736.4.1.41a
  40. Gruen, R., Elliott, J., Nolan, M., Lawton, P., Parkhill, A., Mclaren, C., & Lavis, J. (2008). Sustainability science: An integrated approach for health-programme planning. The Lancet, 372, 1579–1589. doi:10.1016/S0140-6736(08)61659-1.CrossRefGoogle Scholar
  41. Haddix, A. C., Teutsch, S. M., & Corso, P. S. (2003). Prevention effectiveness: A guide to decision analysis and economic evaluation. Oxford: Oxford University Press.Google Scholar
  42. Hansen, R. N., Oster, G., Edelsberg, J., Woody, G. E., & Sullivan, S. D. (2011). Economic costs of nonmedical use of prescription opioids. The Clinical Journal of Pain, 27, 194–202. doi:10.1097/AJP.0b013e3181ff04ca.CrossRefPubMedGoogle Scholar
  43. Hawkins, J. D., Catalano, R. F., Arthur, M. W., Egan, E., Brown, E. C., Abbott, R. D., & Murray, D. M. (2008). Testing communities that care: The rationale, design anduran behavioral baseline equivalence of the community youth development study. Prevention Science, 9, 178–190. doi:10.1007/s11121-008-0092-y.PubMedCentralCrossRefPubMedGoogle Scholar
  44. Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin, 112, 64–105. doi:10.1037/0033-2909.112.1.64.CrossRefPubMedGoogle Scholar
  45. Heckman, J. (2006). Skill formation and the economics of investing in disadvantaged children. Science, 312, 1900–1902. doi:10.1126/science.1128898.CrossRefPubMedGoogle Scholar
  46. Heckman, J., Moon, S. H., Pinto, R., Savelyev, P. A., & Yavitz, A. (2010). The rate of return to the highscope Perry Preschool program. Journal of Public Economics, 94, 114–128. doi:10.1016/j.jpubeco.2009.11.001.PubMedCentralCrossRefPubMedGoogle Scholar
  47. Hill, L. G., Goates, S. G., & Rosenman, R. (2010). Detecting selection effects in community implementations of family-based substance abuse prevention programs. American Journal of Public Health, 100, 623–630. doi:10.2105/AJPH.2008.154112.PubMedCentralCrossRefPubMedGoogle Scholar
  48. Hoffmann, C., Stoykova, B. A., Nixon, J., Glanville, J. M., Misso, K., & Drummond, M. F. (2002). Do health-care decision makers find economic evaluations useful? The findings of focus group research in UK health authorities. Value in Health, 5, 71–78. doi:10.1046/j.1524-4733.2002.52109.x.CrossRefPubMedGoogle Scholar
  49. Karoly, L. A. (1998). Investing in our children: What we know and don’t know about the costs and benefits of early childhood interventions. Santa Monica: Rand.Google Scholar
  50. Karoly, L. A. (2010). Principles and standards for benefit–cost analysis of early childhood interventions. RAND.Google Scholar
  51. Kautt, P., & Spohn, C. (2002). Crack-ing down on black drug offenders? Testing for interactions among offenders’ race, drug type, and sentencing strategy in federal drug sentences*. Justice Quarterly, 19, 1–35. doi:10.1080/07418820200095151.CrossRefGoogle Scholar
  52. Kilburn, K., & Karoly, L. A. (2008). The Economics of Early Childhood Policy What the Dismal Science Has to Say About Investing in Children. Retrieved from http://www.rand.org/pubs/occasional_papers/OP227.html
  53. Kuklinski, M. R., Briney, J. S., Hawkins, J. D., & Catalano, R. F. (2012). Cost–benefit analysis of communities that care outcomes at eighth grade. Prevention Science. doi:10.1007/s11121-011-0259-9.PubMedCentralPubMedGoogle Scholar
  54. Lave, L. B., & Joshi, S. V. (1996). Benefit–cost analysis in public health. Annual Review of Public Health, 17, 203–219. doi:10.1146/annurev.pu.17.050196.001223.CrossRefPubMedGoogle Scholar
  55. Lazaro, A. (2002). Theoretical arguments for the discounting of health consequences: Where do we go from here? PharmacoEconomics, 20, 943–961.CrossRefPubMedGoogle Scholar
  56. Lee, S., Aos, S., Drake, E. K., Pennucci, A., Miller, G. E., & Anderson, L. (2012). Return on Investment: Evidence-Based Options to Improve Statewide Outcomes April 2012 Update. Olympia, WA: Washington State Institute for Public Policy. Retrieved from http://www.wsipp.wa.gov/pub.asp?docid=12-04-1201
  57. Lunceford, J. K., & Davidian, M. (2004). Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study. Statistics in Medicine, 23, 2937–2960. doi:10.1002/sim.1903.CrossRefPubMedGoogle Scholar
  58. McCaffrey, D. F., Ridgeway, G., & Morral, A. R. (2004). Propensity score estimation with boosted regression for evaluating causal effects in observational studies. Psychological Methods, 9, 403–425. doi:10.1037/1082-989X.9.4.403.CrossRefPubMedGoogle Scholar
  59. Miller, & Hendrie, D. (2008). Substance Abuse Prevention Dollars and Cents: A Cost-Benefit Analysis (No. DHHS Pub. No. (SMA) 07-4298). Rockville, MD: Center for Substance Abuse Prevention, Substance Abuse and Mental Health Services Administration.Google Scholar
  60. Miller, T., Levy, D., Spicer, R., & Taylor, D. (2006). Societal costs of underage drinking. Journal of Studies on Alcohol, 67.Google Scholar
  61. Mishan, E. J., & Quah, E. (2007). Cost–benefit analysis. London: Routledge.Google Scholar
  62. Nicosia, N., Pacula, R., Kilmer, B., Lundberg, R., & Chiesa, J. (2009). The costs of methamphetamine use. Santa Monica: RAND.Google Scholar
  63. Noble, P. V. (2002). Safe and drug free schools. New York: Novinka Books.Google Scholar
  64. O’Connell, M. E., Boat, T. F., & Warner, K. E. (2009). Preventing mental, emotional, and behavioral disorders among young people: Progress and possibilities. Washington, D.C.: National Academies Press.Google Scholar
  65. Olds, D., Hill, P., Obrien, R., Racine, D., & Moritz, P. (2003). Taking preventive intervention to scale: The nurse-family partnership*. Cognitive and Behavioral Practice, 10, 278–290. doi:10.1016/S1077-7229(03)80046-9.CrossRefGoogle Scholar
  66. Ramsey, S., Willke, R., Briggs, A., Brown, R., Buxton, M., Chawla, A., & Reed, S. (2005). Good research practices for cost-effectiveness analysis alongside clinical trials: The ISPOR RCT-CEA task force report. Value in Health, 8, 521–533. doi:10.1111/j.1524-4733.2005.00045.x.CrossRefPubMedGoogle Scholar
  67. Reynolds, A. J., Temple, J. A., White, B. A. B., Ou, S.-R., & Robertson, D. L. (2011). Age 26 cost-benefit analysis of the child–parent center early education program. Child Development, 82, 379–404. doi:10.1111/j.1467-8624.2010.01563.x.CrossRefPubMedGoogle Scholar
  68. Ringwalt, C. L., Hanley, S., Vincus, A. A., Ennett, S. T., Rohrbach, L. A., & Bowling, J. M. (2008). The prevalence of effective substance use prevention curricula in the nation’s high schools. The Journal of Primary Prevention, 29, 479–488. doi:10.1007/s10935-008-0158-4.PubMedCentralCrossRefPubMedGoogle Scholar
  69. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55. doi:10.1093/biomet/70.1.41.CrossRefGoogle Scholar
  70. Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79, 516. doi:10.2307/2288398.CrossRefGoogle Scholar
  71. Russell, L. B., Gold, M. R., Siegel, J. E., Daniels, N., & Weinstein, M. C. (1996). The role of cost-effectiveness analysis in health and medicine. JAMA: The Journal of the American Medical Association, 276, 1172–1177. doi:10.1001/jama.1996.03540140060028.CrossRefPubMedGoogle Scholar
  72. Savaya, R., & Spiro, S. E. (2011). Predictors of sustainability of social programs. American Journal of Evaluation. doi:10.1177/1098214011408066.Google Scholar
  73. Spoth, R., & Greenberg, M. T. (2005). Toward a comprehensive strategy for effective practitioner–scientist partnerships and larger-scale community health and well-being. American Journal of Community Psychology, 35, 107–126. doi:10.1007/s10464-005-3388-0.PubMedCentralCrossRefPubMedGoogle Scholar
  74. The Pew Charitable Trusts. (2012). Results First. Retrieved from http://www.pewstates.org/projects/results-first-328069.
  75. U.S. Department of Health and Human Services. (2012). Preventing Tobacco Use Among Youth and Young Adults: A Report of the Surgeon General. Atlanta, GA: Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. Retrieved from http://www.surgeongeneral.gov/library/reports/preventing-youth-tobacco-use/full-report.pdf
  76. Weinstein, M. C., Siegel, J. E., Gold, M. R., Kamlet, M. S., & Russell, L. B. (1996). Recommendations of the panel on cost-effectiveness in health and medicine. JAMA: The Journal of the American Medical Association, 276, 1253–1258. doi:10.1001/jama.1996.03540150055031.CrossRefPubMedGoogle Scholar
  77. Welsh, B. C., Sullivan, C. J., & Olds, D. L. (2009). When early crime prevention goes to scale: A new look at the evidence. Prevention Science, 11, 115–125. doi:10.1007/s11121-009-0159-4.CrossRefGoogle Scholar
  78. Williams, A. (1972). Cost–benefit analysis: Bastard science? and/or insidious poison in the body politick? Journal of Public Economics, 1, 199–225. doi:10.1016/0047-2727(72)90002-3.CrossRefGoogle Scholar
  79. Wolfenstetter, S. B. (2011). Conceptual framework for standard economic evaluation of physical activity programs in primary prevention. Prevention Science. doi:10.1007/s11121-011-0235-4.PubMedGoogle Scholar
  80. Yates, B. T. (1994). Toward the incorporation of costs, cost-effectiveness analysis, and cost–benefit analysis into clinical research. Journal of Consulting and Clinical Psychology, 62, 729–736. doi:10.1037/0022-006X.62.4.729.CrossRefPubMedGoogle Scholar
  81. Yates, B. T. (1996). Analyzing costs, procedures, processes, and outcomes in human services. Thousand Oaks: Sage Publications.CrossRefGoogle Scholar
  82. Zerbe, R. O., Davis, T., Garland, N., & Scott, T. (2010). Toward principles and standards in the use of benefit-cost analysis. Seattle, WA: Benefit-Cost Analysis Center, Evans School of Public Affairs, University of Washington. Retrieved from http://evans.washington.edu/files/Final-Principles-and%20Standards-Report--6_23_2011.pdf.

Copyright information

© Society for Prevention Research 2013

Authors and Affiliations

  • D. Max Crowley
    • 1
  • Laura Griner Hill
    • 2
  • Margaret R. Kuklinski
    • 3
  • Damon E. Jones
    • 4
  1. 1.Center for Child and Family PolicyDuke UniversityDurhamUSA
  2. 2.Washington State UniversityPullmanUSA
  3. 3.University of WashingtonSeattleUSA
  4. 4.The Pennsylvania State UniversityPennsylvaniaUSA

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