IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v41y2021i1p9-20.html
   My bibliography  Save this article

Using Clinical Trial Data to Estimate the Costs of Behavioral Interventions for Potential Adopters: A Guide for Trialists

Author

Listed:
  • Louise B. Russell

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA
    The Leonard Davis Institute of Health Economics (LDI), University of Pennsylvania, Philadelphia, PA, USA)

  • Laurie A. Norton

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • David Pagnotti

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • Christianne Sevinc

    (Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA)

  • Sophia Anderson

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • Darra Finnerty Bigelow

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • Lauren G. Iannotte

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • Michael Josephs

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • Ryan McGilloway

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA)

  • Iwan Barankay

    (Department of Management and Department of Business Economics and Public Policy, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA)

  • Mary E. Putt

    (Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA)

  • Peter P. Reese

    (The Leonard Davis Institute of Health Economics (LDI), University of Pennsylvania, Philadelphia, PA, USA
    Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
    Renal Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA)

  • David A. Asch

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA
    The Leonard Davis Institute of Health Economics (LDI), University of Pennsylvania, Philadelphia, PA, USA
    Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
    The Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA)

  • Lee R. Goldberg

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA
    Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA)

  • Shivan J. Mehta

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA
    The Leonard Davis Institute of Health Economics (LDI), University of Pennsylvania, Philadelphia, PA, USA
    Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
    Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA)

  • Monique S. Tanna

    (Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA)

  • Andrea B. Troxel

    (Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY, USA)

  • Kevin G. Volpp

    (Department of Medical Ethics and Health Policy, Perelman School of Medicine, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, USA
    The Leonard Davis Institute of Health Economics (LDI), University of Pennsylvania, Philadelphia, PA, USA
    Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA
    Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA)

Abstract

Behavioral interventions involving electronic devices, financial incentives, gamification, and specially trained staff to encourage healthy behaviors are becoming increasingly prevalent and important in health innovation and improvement efforts. Although considerations of cost are key to their wider adoption, cost information is lacking because the resources required cannot be costed using standard administrative billing data. Pragmatic clinical trials that test behavioral interventions are potentially the best and often only source of cost information but rarely incorporate costing studies. This article provides a guide for researchers to help them collect and analyze, during the trial and with little additional effort, the information needed to inform potential adopters of the costs of adopting a behavioral intervention. A key challenge in using trial data is the separation of implementation costs, the costs an adopter would incur, from research costs. Based on experience with 3 randomized clinical trials of behavioral interventions, this article explains how to frame the costing problem, including how to think about costs associated with the control group, and describes methods for collecting data on individual costs: specifications for costing a technology platform that supports the specialized functions required, how to set up a time log to collect data on the time staff spend on implementation, and issues in getting data on device, overhead, and financial incentive costs.

Suggested Citation

  • Louise B. Russell & Laurie A. Norton & David Pagnotti & Christianne Sevinc & Sophia Anderson & Darra Finnerty Bigelow & Lauren G. Iannotte & Michael Josephs & Ryan McGilloway & Iwan Barankay & Mary E., 2021. "Using Clinical Trial Data to Estimate the Costs of Behavioral Interventions for Potential Adopters: A Guide for Trialists," Medical Decision Making, , vol. 41(1), pages 9-20, January.
  • Handle: RePEc:sae:medema:v:41:y:2021:i:1:p:9-20
    DOI: 10.1177/0272989X20973160
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X20973160
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X20973160?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Juster, F Thomas & Stafford, Frank P, 1991. "The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement," Journal of Economic Literature, American Economic Association, vol. 29(2), pages 471-522, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fali Huang & Myoung-Jae Lee, 2010. "Dynamic treatment effect analysis of TV effects on child cognitive development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 392-419.
    2. Kan, Kamhon & Fu, Tsu-Tan, 1997. "Analysis of Housewives' Grocery Shopping Behavior in Taiwan: An Application of the Poisson Switching Regression," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 29(2), pages 397-407, December.
    3. Maliar, Lilia & Maliar, Serguei, 2004. "Endogenous Growth And Endogenous Business Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 8(5), pages 559-581, November.
    4. Daniel S. Hamermesh & Jungmin Lee, 2007. "Stressed Out on Four Continents: Time Crunch or Yuppie Kvetch?," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 374-383, May.
    5. Heim, Bradley T. & Meyer, Bruce D., 2004. "Work costs and nonconvex preferences in the estimation of labor supply models," Journal of Public Economics, Elsevier, vol. 88(11), pages 2323-2338, September.
    6. Artemov Viktor & Novokhatskaya Olga, 2014. "Everyday activity of rural employees in Siberia," Eastern European Countryside, Sciendo, vol. 20(1), pages 189-210, December.
    7. Naomi Friedman-Sokuler & Claudia Senik, 2022. "Time-Use and Subjective Well-Being: Is there a Preference for Activity Diversity?," PSE Working Papers halshs-03828272, HAL.
    8. Jara-Díaz, Sergio & Rosales-Salas, Jorge, 2017. "Beyond transport time: A review of time use modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 209-230.
    9. Urwin, Sean & Lau, Yiu-Shing & Grande, Gunn & Sutton, Matt, 2021. "The extent and predictors of discrepancy between provider and recipient reports of informal caregiving," Social Science & Medicine, Elsevier, vol. 277(C).
    10. Georg-Levi Gayle & Limor Golan & Mehmet A. Soytas, "undated". "Estimating the Returns to Parental Time Investment in Children Using a Life Cycle Dynastic Model," GSIA Working Papers 2011-E18, Carnegie Mellon University, Tepper School of Business.
    11. Magnus Henrekson & Jesper Roine, 2007. "Promoting Entrepreneurship in the Welfare State," Chapters, in: David B. Audretsch & Isabel Grilo & A. Roy Thurik (ed.), Handbook of Research on Entrepreneurship Policy, chapter 5, Edward Elgar Publishing.
    12. Marcus Dittrich & Bianka Mey, 2015. "Are people satisfied with their time use? Empirical evidence from German survey data," Economics Bulletin, AccessEcon, vol. 35(4), pages 2903-2914.
    13. Rupert, Peter & Rogerson, Richard & Wright, Randall, 2000. "Homework in labor economics: Household production and intertemporal substitution," Journal of Monetary Economics, Elsevier, vol. 46(3), pages 557-579, December.
    14. Santos, Marcelo Rodrigues dos & Pereira, Thiago Neves, 2010. "Moving to a Consumption-Based Tax System: A Quantitative Assessment for Brazil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(2), June.
    15. Daniel S. Hamermesh, 1999. "The Art of Labormetrics," NBER Working Papers 6927, National Bureau of Economic Research, Inc.
    16. Kollmann, Robert, 1996. "Incomplete asset markets and the cross-country consumption correlation puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 20(5), pages 945-961, May.
    17. Gómez, Manuel A. & Monteiro, Goncalo, 2015. "Internal habits in an endogenous growth model with elastic labor supply," Economic Modelling, Elsevier, vol. 51(C), pages 583-595.
    18. Elisabetta Lazzaro & Carlofilippo Frateschi, 2017. "Couples’ arts participation: assessing individual and joint time use," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(1), pages 47-69, February.
    19. Tobias Wolf & Maria Metzing & Richard E. Lucas, 2022. "Experienced Well-Being and Labor Market Status: The Role of Pleasure and Meaning," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(2), pages 691-721, September.
    20. Richard K. Lyons, 2002. "Foreign exchange: macro puzzles, micro tools," Economic Review, Federal Reserve Bank of San Francisco, pages 51-69.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:41:y:2021:i:1:p:9-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.