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Hospital staffing and local pay: an investigation into the impact of local variations in the competitiveness of nurses’ pay on the staffing of hospitals in France

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Abstract

Spatial wage theory suggests that employers in different regions may offer different pay rates to reflect local amenities and cost of living. Higher wages may be required to compensate for a less pleasant environment or a higher cost of living. If wages in a competing sector within an area are less flexible and therefore less competitive this may lead to an inability to employ staff. This paper considers the market for nursing staff in France where there is general regulation of wages and public hospitals compete for staff with the private hospital and non-hospital sectors. We consider two types of nursing staff, registered and assistant nurses and first establish the degree of spatial variation in the competitiveness of pay of nurses in public hospitals. We then consider whether these spatial variations are associated with variation in the employment of nursing staff. We find that despite regulation of pay in the public and private sector, there are substantial local variations in the competitiveness of nurses’ pay. We find evidence that the spatial variations in the competitiveness of pay are associated with relative numbers of assistant nurses but not registered nurses. While we find the influence of the competitiveness of pay is small, it suggests that nonpay conditions may be an important factor in adjusting the labour market as might be expected in such a regulated market.

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Notes

  1. In France, training places for nurses are funded by the ministry of education.

  2. Public hospitals include military hospitals, which report to the ministry of defence. They constitute 9 out of a total of 942 public hospitals and employ 0.68 % and 0.56 % of the total number of registered and assistant nurses, respectively.

  3. Only 20 out of 910 private for-profit hospitals participate in the public service while 482 out of 668 private not-for-profit hospitals participate in the public service.

  4. Procedures performed by private hospitals not participating in the public service are, nevertheless, subject to authorisation by the regulatory body (which reports to the Ministry of Health).

  5. Registered nurses receive 38 months training in specialised institutions recognised by the Ministry of Health. Entrance to training is open to anyone who has the baccalauréat and is at least 17 years of age before the end of the year in which the exams are held.

  6. Regional authorities (préfet) will grant authorisation to practice following the decision of a regional committee. These regional committees were set up by the Direction Départementale des Affaires Sanitaires et Sociales (DDASS) which, up to 2010, were the public bodies in charge of organisation of health care at the département level.

  7. Assistant nurses receive 12 months’ training in institutes that are recognised by the Ministry of Health. Entrance to training is open to anyone who has completed a secondary education and achieved the brevet des collèges (BEPC) and is at least 17 years of age before the end of the year in which the exams are held.

  8. We use départements as our labour market areas, we discuss this in Subsection 5.3.

  9. We add the superscript suffix AN or RN to each gap measure to signify whether it refers to assistant nurses (AN) or registered nurses (RN) resulting in 6 gap measures in total, Gap GLMAN and Gap GLMRN, GAP PNPAN and GAP PNPRN and finally GAP PPAN and GAP PPRN.

  10. However, some simple tasks usually performed by registered nurses could be performed by assistant nurses as the skills they have overlap. For example, in the skills that registered nurses and assistant nurses should have according to the statuses is being able to help dress a patient (For registered nurses see [42] and for assistant nurses see [43].

  11. http://www.sae-diffusion.sante.gouv.fr/ accessed the 5th of May 2014.

  12. http://www.sante.gouv.fr/statistique-annuelle-des-etablissements-sae.html accessed the 5th of May 2014.

  13. Hospital data also include number of beds, number of days realised and other technology indicators such as the number of scanners. Full details are available in the Appendix with the full results.

  14. Pensions are deducted on gross pay, net pay is therefore net of pension deductions even for complementary pensions.

  15. As defined in France, gross pay minus social contributions but without deducting income tax.

  16. Federation of not-for-profit hospital and private assistance premises (Fédération des établissements hospitaliers et d'assistance privés à but non lucratif).

  17. Private federation of hospitals (Fédération hospitalière privée).

  18. All hospitals are covered by a collective agreement.

  19. There are 341 “zones d'emploi” in France.

  20. The fact that TTWA do not identify occupations is highlighted in the review of the TTWA for the UK as a drawback of this measure [45].

  21. Complete care is major treatments that involve a long admission period.

  22. Weekly care are patients who remain in hospital for less than 5 days.

  23. In addition to the mentioned episodes we also investigated adding the number of patients who came for night care, ambulatory surgery, day care and at-home care. This did not change the results qualitatively.

  24. Covariates include the ones described in 5.1 and number of beds, number of days realised and different indicators of equipment; the full list is available in the Appendix.

  25. As reported in Table 3.

  26. Hospitals not covered by the named categories. This represents the largest category. This is how the SAE data describes hospitals with no further detail available.

  27. The remaining miscellaneous sub-category of hospitals gathers very different types of hospitals including military hospitals (30 observations), paediatric hospitals (3 observations), long-stay hospitals (9 observations), joint ventures of hospitals participating in the public service, public hospitals and private not-for-profit hospitals which participate in the hospitals public service (27 observations), alcoholics post-care centres (3 observations) and health-care for prisons (3 observations).

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Acknowledgments

We are very grateful for the comments of two anonymous referees who greatly improved this article. Our thanks go to the following for their support for this project: to Rennes Métropole for the grant “Allocation Installation Jeunes Chercheurs” and to the University of Aberdeen for financial support; to the Ecole Nationale de la Statistique et de l’Analyse de l’Information, for providing facilities for one of the authors to conduct part of this research; to the Institute National de la Statistique et des Études Économiques for permitting access to and assisting in interpretation of the Déclaration Annuelle des Données Sociales (DADS); to Mehni Benyaala, Martine Delangre, Elodie Kranklader, Alain Esnault for their assistance in accessing and interpreting the DADS and Statistique Annuelle des Etablissements de Santé (SAE); and to Cécile Martin for her comments on this paper at the CES-HESG joint conference in Aix-en-Provence in January 2012. An earlier version of part of this research was presented at Paris, Dauphine and we are grateful to participants for their comments. Although this paper has received very useful comments, we retain responsibility for any remaining errors.

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Authors and Affiliations

  1. Institute for Research and Information in Health Economics, 10, rue Vauvenargues, 75018, Paris, France

    Jean-Baptiste Combes

  2. Université de Cergy-Pontoise and THEMA (UMR CNRS 8184), 33 Boulevard Du Port, 95011, Cergy-Pontoise, France

    Eric Delattre

  3. Health Economics Research Unit, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen, AB25 2ZD, Scotland

    Bob Elliott & Diane Skåtun

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  1. Jean-Baptiste Combes
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Combes, JB., Delattre, E., Elliott, B. et al. Hospital staffing and local pay: an investigation into the impact of local variations in the competitiveness of nurses’ pay on the staffing of hospitals in France. Eur J Health Econ 16, 763–780 (2015). https://doi.org/10.1007/s10198-014-0628-y

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