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Exploring differences in healthcare utilization of prisoners in the Canton of Vaud, Switzerland

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Listed:
  • Karine Moschetti
  • Véra Zabrodina
  • Pierre Stadelmann
  • Tenzin Wangmo
  • Alberto Holly
  • Jean-Blaise Wasserfallen
  • Bernice S Elger
  • Bruno Gravier

Abstract

Prison healthcare is an important public health concern given the increasing healthcare needs of a growing and aging prison population, which accumulates vulnerability factors and suffers from higher disease prevalence than the general population. This study identifies the key factors associated with outpatient general practitioner (GP), nursing or psychiatric healthcare utilization (HCU) within prisons. Cross-sectional data systematically collected by the prison medical staff were obtained for a sample of 1664 adult prisoners of the Canton of Vaud, Switzerland, for the year 2011. They contain detailed information on demographics (predisposing factors), diagnosed chronic somatic and psychiatric disorders (needs factors), as well as prison stay characteristics (contextual factors). For GP, nurse and psychiatric care, two-part regressions are used to model separately the probability and the volume of HCU. Predisposing factors are generally not associated with the probability to use healthcare services after controlling for needs factors. However, female inmates use higher volumes of care, and the volume of GP consultations increases with age. Chronic somatic and psychiatric conditions are the most important predictors of the probability of HCU, but associations with volumes differ in their magnitude and significance across disease groups. Infectious, musculoskeletal, nervous and circulatory diseases actively mobilize GP and nursing staff. Schizophrenia, illicit drug and pharmaceuticals abuse are strongly positively associated with psychiatric and nurse HCU. The occupancy rate displays positive associations among contextual factors. Prison healthcare systems face increasingly complex organizational, budgetary and ethical challenges. This study provides relevant insights into the HCU patterns of a marginalized and understudied population.

Suggested Citation

  • Karine Moschetti & Véra Zabrodina & Pierre Stadelmann & Tenzin Wangmo & Alberto Holly & Jean-Blaise Wasserfallen & Bernice S Elger & Bruno Gravier, 2017. "Exploring differences in healthcare utilization of prisoners in the Canton of Vaud, Switzerland," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0187255
    DOI: 10.1371/journal.pone.0187255
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    References listed on IDEAS

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    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, January.
    2. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    3. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    4. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    5. Wilper, A.P. & Woolhandler, S. & Boyd, J.W. & Lasser, K.E. & McCormick, D. & Bor, D.H. & Himmelstein, D.U., 2009. "The health and health care of US prisoners: Results of a nationwide survey," American Journal of Public Health, American Public Health Association, vol. 99(4), pages 666-672.
    6. A. J. Culyer & J. P. Newhouse (ed.), 2000. "Handbook of Health Economics," Handbook of Health Economics, Elsevier, edition 1, volume 1, number 1.
    7. Bernice Elger & Catherine Geohring & Sylvie Revaz & Alfredo Morabia, 2002. "Prescription of hypnotics and tranquilisers at the Geneva prison's outpatient service in comparison to an urban outpatient medical service," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 47(1), pages 39-43, March.
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    1. Pinheiro, Marina & Gonçalves, Rui Abrunhosa & Cunha, Olga, 2021. "Criminal lifestyle, psychopathy, and prison adjustment among female inmates," Journal of Criminal Justice, Elsevier, vol. 76(C).

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