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How does the quality of care for type 2 diabetic patients benefit from GPs-nurses’ teamwork? A staggered difference-in-differences design based on a French pilot program

Author

Listed:
  • Julie Gilles de la Londe

    (Université de Paris)

  • Anissa Afrite

    (Institute for Research and Information in Health Economics (IRDES))

  • Julien Mousquès

    (Ecole Des Hautes Etudes en Santé Publique (EHESP)
    Institute for Research and Information in Health Economics (IRDES))

Abstract

In many countries, policies have explicitly encouraged primary care teams and inter-professional cooperation and skill mix, as a way to improve both productive efficiency gains and quality improvement. France faces barriers to developing team working as well as new and more advanced roles for health care professionals including nurses. We aim to estimate the impact of a national pilot experiment of teamwork between general practitioners (GPs) and advance practitioners nurses (APN)–who substitute and complement GPs–on yearly quality of care process indicators for type two diabetes patients (T2DP). Implemented by a not-for-profit meso-tier organisation and supported by the Ministry of Health, the pilot relied on the voluntary enrolment of newly GPs from 2012 to 2015; the staffing and training of APNs; skill mixing and new remuneration schemes. We use latent-response formulation models, control for endogeneity and selection bias by using controlled before-after and quasi-experimental design combining coarsened exact matching–prior to the treatment, at both GPs (435 treated vs 973 control) and T2DP levels –, with intention to treat (ITT; 18,310 in each group) and per protocol (PP, 2943 in each group) perspectives, as well as difference-in-differences estimates on balanced panel claims data from the National Health Insurance Fund linked to clinical data over the period 2010–2017. We show evidence of a positive and significant positive impact for T2DP followed-up by newly enrolled GPs in the pilot compared to the pretreatment period and the control group. The effect magnitudes were larger for PP than for ITT subsamples.

Suggested Citation

  • Julie Gilles de la Londe & Anissa Afrite & Julien Mousquès, 2023. "How does the quality of care for type 2 diabetic patients benefit from GPs-nurses’ teamwork? A staggered difference-in-differences design based on a French pilot program," International Journal of Health Economics and Management, Springer, vol. 23(3), pages 433-466, September.
  • Handle: RePEc:kap:ijhcfe:v:23:y:2023:i:3:d:10.1007_s10754-023-09354-z
    DOI: 10.1007/s10754-023-09354-z
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    1. repec:dau:papers:123456789/14979 is not listed on IDEAS
    2. Sophie Massin & Alain Paraponaris & Marion Bernhard & Pierre Verger & Marie Cavillon & Fanny Mikol & Bruno Ventelou, 2014. "Les médecins généralistes face au paiement à la performance et à la coopération avec les infirmiers," Post-Print hal-01241473, HAL.
    3. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2011. "Multivariate Matching Methods That Are Monotonic Imbalance Bounding," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 345-361.
    4. Tsiachristas, A. & Wallenburg, I. & Bond, C.M. & Elliot, R.F. & Busse, R. & van Exel, J. & Rutten-van Mölken, M.P. & de Bont, A., 2015. "Costs and effects of new professional roles: Evidence from a literature review," Health Policy, Elsevier, vol. 119(9), pages 1176-1187.
    5. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    6. Mousquès, Julien & Bourgueil, Yann & Le Fur, Philippe & Yilmaz, Engin, 2010. "Effect of a French experiment of team work between general practitioners and nurses on efficacy and cost of type 2 diabetes patients care," Health Policy, Elsevier, vol. 98(2-3), pages 131-143, December.
    7. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    8. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    9. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    10. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    11. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
    12. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    13. Sebastiaan T Houweling & Nanne Kleefstra & Kornelis JJ van Hateren & Klaas H Groenier & Betty Meyboom‐de Jong & Henk JG Bilo, 2011. "Can diabetes management be safely transferred to practice nurses in a primary care setting? A randomised controlled trial," Journal of Clinical Nursing, John Wiley & Sons, vol. 20(9‐10), pages 1264-1272, May.
    14. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    15. King, Gary & Nielsen, Richard, 2019. "Why Propensity Scores Should Not Be Used for Matching," Political Analysis, Cambridge University Press, vol. 27(4), pages 435-454, October.
    16. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    17. Chevillard, Guillaume & Mousquès, Julien & Lucas-Gabrielli, Véronique & Rican, Stéphane, 2019. "Has the diffusion of primary care teams in France improved attraction and retention of general practitioners in rural areas?," Health Policy, Elsevier, vol. 123(5), pages 508-515.
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    More about this item

    Keywords

    General practitioners; Nurse’s role; Teamwork; Diabetes mellitus; Controlled before-after Studies; Difference-in-differences;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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