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Teamwork in health care and medical malpractice liability: an experimental investigation

Abstract

The treatment of a patient often implies consultations with different health care professionals. This complex health care pathway raises the issue of the regulation of health care quality. In this study, we explore how teamwork among health care professionals affects the precaution behavior of each one depending on the liability regime. To this end, we develop a theoretical model that is tested in a controlled laboratory experiment. Each health care professional chooses the precaution level invested to treat the patient. His decisions have real consequences outside the lab for charities dealing with real patients. Experimental conditions vary the number of involved health care professionals and the liability regime. Contrary to theory, we show that the negligence rule and strict liability do not provide optimal incentives to take care. The negligence rule is more efficient than strict liability to reduce the absolute deviations from optimal precaution level. Moreover, under both liability rules, teamwork decreases the health care professionals’ precaution levels.

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Fig. 1

Notes

  1. 1.

    For the Institute of Healthcare Improvement, an adverse event is an “unintended physical injury resulting from or contributed to by medical care that requires additional monitoring, treatment or hospitalization, or that results in death”. Available online: http://www.ihi.org Accessed July 12, 2021.

  2. 2.

    This assumption is made for the needs of comparison between our experimental conditions. In practice, precautions could also be complements or substitutes. See Leshem (2017) for a general analysis.

  3. 3.

    French Court of Cassation, Civ., 20 May 1936, Mercier.

  4. 4.

    Art. L. 1142-1 of the French Public Health Code.

  5. 5.

    We call “condition” an experimental treatment. In our article, the word “treatment” is only related to the health care treatment.

  6. 6.

    In our experiment, patients are represented by charities. Although the participants could take precautions for voluntarily giving to charities, we interpret their preferences as patient-regarding preferences. We discuss later this assumption.

  7. 7.

    Other theoretical contributions consider the effect of imperfections on the incentives provided by the negligence rule. See Olbrich (2008a), Wright (2011) and Antoci et al. (2018) for the effect of claim costs borne by the patient, and see Olbrich (2008b) for the effect of judgment court errors.

  8. 8.

    See Sullivan and Holt (2017) for a literature review of the experimental studies in law and economics.

  9. 9.

    For a discussion on the optimal allocation rule for non-independent precautions, see the complete analysis of Leshem (2017). For similar analyses, see also van Velthoven and Van Wijck (2009), and Young et al. (2004, 2007).

  10. 10.

    See Galizzi et al. (2015) for a review on the physician’s preferences.

  11. 11.

    See Galizzi and Wiesen (2018) for a literature review on the behavioral experiments in the health field.

  12. 12.

    Precaution cost is identical for each consultation, even if the same HCP achieves both consultations. Indeed, each consultation is related to a specific task, which requires a specific informational search.

  13. 13.

    Our modeling of the treatment benefit is based on the theoretical analysis of Arlen and MacLeod (2005).

  14. 14.

    We assume that both HCPs take their precaution decisions simultaneously. Even if both consultations are made in a sequential way, the second HCP does not observe the precaution level of his colleague before taking his decision. Indeed, teamwork among HCPs is based on a trust relationship in general. For example, the second HCP does not call into question the diagnosis or the treatment prescribed by his colleague. Thus, he does not look for the time spent by his colleague to be informed.

  15. 15.

    This demonstration is based on the contribution of Kornhauser and Revesz (1989). See also Landes and Posner (1980) and Schweizer (2017).

  16. 16.

    It is easily verifiable that this equilibrium is unique. Another Nash equilibrium breaches the optimality of \(x^{*}\).

  17. 17.

    Our experiment is consistent with the five features characterizing the behavioral experiments in the health field according to Galizzi and Wiesen (2017): the issues and behaviors are health-related, the outcomes of decisions are behavioral, we test the insights from behavioral economics and conventional economics, we make a laboratory experiment, and we do not use deception.

  18. 18.

    The instructions can be found in the Appendix B.

  19. 19.

    The experiment was programmed by Kene Boun My on the web platform EconPlay (http://www.econplay.fr).

  20. 20.

    The other experiments on accident law do not use the terminology of accident (Kornhauser & Schotter, 1990; Angelova et al., 2014; Deffains et al., 2019).

  21. 21.

    See Carpenter and Huet-Vaughn (2019) for a literature review on real-effort tasks.

  22. 22.

    The SVO Slide Measure is divided into six primary items and nine secondary items. Each item consists in a distribution of gains for the participant and for another one in the lab. The six primary items determine the participant’s behavior: altruist, prosocial, or individualist. The problem is that we find negative coefficients associated with the SVO. This would mean that a selfless HCP chooses a smaller precaution level than a selfish HCP, which is unlikely. See the Appendix A for the econometric analysis with the SVO variable.

  23. 23.

    Differences are compared by t-test.

  24. 24.

    See the post-experimental questionnaire in the Appendix C.

  25. 25.

    Table 6 reports tests for the differences between mean precaution levels provided in each treatment. Between liability regimes, we proceed to Tukey’s studentized range tests to control for the type I experiment-wise error rate. Between health care pathways, we perform paired t-tests because the experimental conditions are composed of the same samples. Non-parametric tests are used as robustness checks.

  26. 26.

    The difference is only significant at the \(10\%\) level whether HCPs work together according to two-sided Dunn test with Bonferroni adjustement.

  27. 27.

    In model (4), we add the dummy Damage in the period t-1 equal to 1 if damage occurred in the previous period; Selfish which expresses the average degree of egoism reported in the post-experimental questionnaire; Risk lover which expresses the average degree of risk loving and corresponds to the average choice of lottery made in Task 5; the dummy HealthMedicine equal to 1 if the participant is registered in health sciences, medicine or pharmacy; the interaction term HealthMedicine\(\times\)Teamwork to test whether health students behave differently from other participants when they work in a team; the dummy MasterPhD equal to 1 if the student is registered in a Master or PhD programme; Age which expresses the participant’s age in years; and the dummy Gender equal to 1 if the participant is female.

  28. 28.

    The absolute deviation is not censored at the same upper limit depending on the precaution behavior: to 3 for excess of caution, and to 13 for negligence. That is why we do not use a panel model for censored data but simply a linear panel model.

  29. 29.

    Comparison of variances is made by F-test (\(p<0.01\)), and Levene test as robustness check (\(p<0.05\) for one HCP, \(p<0.01\) for two HCPs).

  30. 30.

    The precaution level explained by the panel model is censored to be non-negative and below 16 units.

  31. 31.

    Differences are compared by t-test.

  32. 32.

    In our experimental design, we assume that there is no medical hazard.

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Acknowledgements

I thank the participants at the 5th Annual Conference of the French Association of Law and Economics, the 37th Annual Conference of the European Association of Law and Economics, the 16th Conference of the Italian Society of Law and Economics, the 42th French Health Economists Days, and the 37th French Applied Microeconomics Days for the discussion on this paper. I also acknowledge Camille Aït-Youcef, Kene Boun My, Cécile Bourreau-Dubois, Gaye Del Lo, Sophie Harnay, Eve-Angéline Lambert, Sébastien Massoni, Sarah Van Driessche, and the two anonymous referees for their helpful comments and suggestions. Financial support by the University of Lorraine is gratefully acknowledged.

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Martin-Lapoirie, D. Teamwork in health care and medical malpractice liability: an experimental investigation. Eur J Law Econ (2021). https://doi.org/10.1007/s10657-021-09708-3

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Keywords

  • Laboratory experiment
  • Liability
  • Medical malpractice
  • Multiple injurers
  • Teamwork

JEL Classification

  • K13
  • C72
  • C91
  • I10