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Analysis of HIV/AIDS DRG in Portugal: a hierarchical finite mixture model

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Abstract

Inpatient length of stay (LOS) is an important measure of hospital activity, but its empirical distribution is often positively skewed, representing a challenge for statistical analysis. Taking this feature into account, we seek to identify factors that are associated with HIV/AIDS through a hierarchical finite mixture model. A mixture of normal components is applied to adult HIV/AIDS diagnosis-related group data (DRG) from 2008. The model accounts for the demographic and clinical characteristics of the patients, as well the inherent correlation of patients clustered within hospitals. In the present research, a normal mixture distribution was fitted to the logarithm of LOS and it was found that a model with two-components had the best fit, resulting in two subgroups of LOS: a short-stay subgroup and a long-stay subgroup. Associated risk factors for both groups were identified as well as some statistical differences in the hospitals. Our findings provide important information for policy makers in terms of discharge planning and the efficient management of LOS. The presence of “atypical” hospitals also suggests that hospitals should not be viewed or treated as homogenous bodies.

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References

  1. Augusto, G.F.: Cuts in Portugal’s NHS could compromise care. Lancet 379(9814), 400 (2012)

    Article  PubMed  Google Scholar 

  2. Martin, S., Smith, P.: Explaining variations in inpatient length of stay in the National Health Service. J. Health Econ. 15(3), 279–304 (1996). doi:10.1016/0167-6296(96)00003-3

    Article  PubMed  CAS  Google Scholar 

  3. Xiao, J., Douglas, D., Lee, A.H.: A Delphi evaluation of the factors influencing length of stay in Australian hospitals. Int. J. Health Plan. Manag. 12, 207–218 (1997)

    Article  CAS  Google Scholar 

  4. Fetter, R.B., Youngsoo, S., Freeman, J.L., Averill, R.F., Thomson, J.D.: Case-mix: definition by diagnosis related groups. Med. Care 18, 1–53 (1980)

    Google Scholar 

  5. Averill, R.F., Goldfield, N., Hughes, J.S., Bonazelli, J., McCullough, E.C., Steinbeck, B.A., Mullin, R., Tang, A.M., Muldoon, J., Turner, L., Gay, J.: All patient refined diagnosis related groups (APR-DRGs) Version 20.0. Clinical Research and Documentation Departments of 3M Health Information Systems, Wallingford (2003)

  6. ACSS: Sistema de Classificação de Doentes em Grupos de Diagnósticos Homogéneos (GDH). http://www.acss.min-saude.pt (2006)

  7. Ministério, da, Saúde: Anexo I – Regulamento das Tabelas de Preços das Instituições e dos Serviços Integrados no Serviço Nacional de Saúde, Secção I, Artigo 3º - Definições. In, vol. Portaria nº 567/2006. pp. 4173-4267. Diário da República I—`série B, (2006)

  8. Krentz, H.B., Dean, S., Gill, M.J.: Longitudinal assessment (1995–2003) of hospitalizations of HIV-infected patients within a geographical population in Canada. HIV Med. 7(7), 457–466 (2006)

    Article  PubMed  CAS  Google Scholar 

  9. Barbour, K.E., Fabio, A., Pearlman, D.N.: Inpatient charges among HIV/AIDS patients in Rhode Island from 2000–2004. BMC Health Serv. Res. 9(1), 1–7 (2009)

    Google Scholar 

  10. Monitoring, F.H.: Diagnostic data of the hospitals starting from 2000 (cases/deaths, cases per 100,000 inhabitants, days of care, average length of stay). Classification: years, place of residence, age, sex, length of stay, ICD10. http://www.gbe-bund.de/gbe10/pkg_isgbe5.prc_isgbe?p_uid=gast&p_aid=&p_sprache=E (2007)

  11. Lee, A.H., Gracey, M., Wang, K., Kelvin, K.W.: A robustified modeling approach to analyze pediatric length of stay. Ann. Epidemiol. 15(9), 637–677 (2005)

    Article  Google Scholar 

  12. Atienza, N., Garcia-Heras, J., Munoz-Pichardo, J.M., Villa, R.: An application of mixture distributions in modelization of length of hospital stay. Stat. Med. 27(9):, 1403–1420 (2008)

    Article  PubMed  CAS  Google Scholar 

  13. Dias, S.S., Andreozzi, V., Martins, M.O., Torgal, J.: Predictors of mortality in HIV-associated hospitalizations in Portugal: a hierarchical survival model. BMC Health Serv. Res. 9, 1–10 (2009)

    Google Scholar 

  14. Pérez-Hoyos, S., Ballester, F., Tenías, J.M., Marelles, A., Rivera, M.L.: Length of stay in a hospital emergency room due to asthma and chronic obstructive pulmonary disease: implications for air pollution studies. Eur. J. Epidemiol. 16, 455–463 (2000)

    Article  PubMed  Google Scholar 

  15. Koton, S., Bornstein, N.M., Tsabari, R., Tanne, D., Investigators, N.: Derivation and validation of the prolonged length of stay score in acute stroke patients. Neurology 74(19), 1511–1516 (2010). doi:10.1212/WNL.0b013e3181dd4dc5

    Article  PubMed  CAS  Google Scholar 

  16. Saez-Castillo, A.J., Olmo-Jimenez, M.J., Sanchez, J.M.P., Hernandez, M.A.N., Arcos-Navarro, A., Diaz-Oller, J.: Bayesian analysis of nosocomial infection risk and length of stay in a Department of General and Digestive Surgery. Value Health 13(4), 431–439 (2010). doi:10.1111/j.1524-4733.2009.00680.x

    Article  PubMed  Google Scholar 

  17. Singh, C.H., Ladusingh, L.: Inpatient length of stay: a finite mixture modeling analysis. Eur. J. Health Econ. 11(2), 119–126 (2010). doi:10.1007/s10198-009-0153-6

    Article  PubMed  Google Scholar 

  18. Xiao, J., Lee, A.H., Vemurri, S.R.: Mixture distribution analysis of length of stay for efficient funding. Socio-Econ. Plan. Sci. 33, 39–59 (1999)

    Article  Google Scholar 

  19. Leyland, A.H., Boddy, F.A.: Measuring performance in hospital care—length of stay in gynaecology. Eur. J. Pub. Health 7(2), 136–143 (1997)

    Article  Google Scholar 

  20. Leung, K.M., Elashoff, R.M., Rees, K.S., Hasan, M.M., Legorreta, A.P.: Hospital- and patient-related characteristics determining maternity length of stay: a hierarchical linear model approach. Am. J. Public Health 88(3), 377–381 (1998)

    Article  PubMed  CAS  Google Scholar 

  21. Downing, A., Lansdown, M., West, R.M., Thomas, J.D., Lawrence, G., Forman, D.: Changes in and predictors of length of stay in hospital after surgery for breast cancer between 1997/98 and 2004/05 in two regions of England: a population-based study. BMC Health Serv. Res. 9 (2009). doi:10.1186/1472-6963-9-202

  22. Lee, A.H., Ng, S.K., Yau, K.K.W.: Determinants of maternity length of stay: a gamma mixture risk-adjusted model. Health Care Manag. Sci. 4, 249–255 (2001)

    Article  PubMed  CAS  Google Scholar 

  23. INE: Principais indicadores. http://www.ine.pt (2008). Accessed June 2010

  24. Ng, S.K., Yau, K.K.W., Lee, A.H.: Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm. Math. Comput. Model. 37(3–4), 365–375 (2003)

    Article  Google Scholar 

  25. Everitt, B.S., Hand, D.J.: Finite mixture distribution. Monographs on applied probability and statistics. Chapman and Hall, London (1981)

    Book  Google Scholar 

  26. McLachlan, G.J., Basford, K.E.: Mixture models. Inference and applications to clustering. Dekker, New York (1988)

    Google Scholar 

  27. Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via EM algorithm. J. R. Stat. Soc. Ser. B Methodol. 39(1), 1–38 (1977)

    Google Scholar 

  28. Team, R.D.C.: R: A Language and Environment for Statistical Computing. In: The R Foundation for Statistical Computer, Vienna, Austria, (2008)

  29. Leisch, F.: FlexMix: a general framework for finite mixture models and latent class regression. R. J. Stat. Softw. 11(8), 1–18

  30. Grun, B., Leisch, F.: Fitting finite mixtures of generalized linear regressions in R. Comput. Stat. Data Anal. 51(11), 5247–5252 (2007). doi:10.1016/j.csda.2006.08.014

    Article  Google Scholar 

  31. Tribunal, de, Contas, Portugal: Auditoria ao sistema de pagamentos e de formação dos preços pagos às unidades hospitalares do Serviço Nacional de Saúde In. Lisboa, (2011)

  32. Crystal, S., Lo Sasso, A.T., Sambamoorthi, U.: Incidence and duration of hospitalizations among persons with AIDS: an event history approach. Health Serv. Res. 33(6), 1611–1638 (1999)

    PubMed  CAS  Google Scholar 

  33. Nunes, A.A., de Melo, I.M., da Silva, A.L.A., Rezende, L.D.D., Guimaraes, P.B., Silva-Vergara, M.L.: Hospitalizations for HIV/AIDS: differences between sexes. Gend. Med. 7(1), 28–38 (2010). doi:10.1016/j.genm.2010.01.004

    Article  PubMed  Google Scholar 

  34. Mocroft, A., Monforte, A.D., Kirk, O., Johnson, M.A., Friis-Moller, N., Banhegyi, D., Blaxhult, A., Mulcahy, F., Gatell, J.M., Lundgren, J.D., Euro, S.S.G.: Changes in hospital admissions across Europe: 1995–2003. Results from the EuroSIDA study. HIV Med. 5(6), 437–447 (2004)

    Article  PubMed  CAS  Google Scholar 

  35. Penniman, T.V., Taylor, S.L., Bird, C.E., Beckman, R., Collins, R.L., Cunningham, W.: The associations of gender, sexual identity and competing needs with healthcare utilization among people with HIV/AIDS. J. Natl Med. Assoc. 99(4), 419–427 (2007)

    PubMed  Google Scholar 

  36. Wang, K., Yau, K.K.W., Lee, A.H.: A hierarchical Poisson mixture regression model to analyse maternity length of stay. Stat. Med. 21, 3639–3654 (2002)

    Article  PubMed  CAS  Google Scholar 

  37. Eastaugh, S.R.: Organizational determinants of surgical lengths of stay. Inquiry 17(1), 85–96 (1980)

    PubMed  CAS  Google Scholar 

  38. Aiken, L.H., Sloane, D.M., Lake, E.T., Sochalski, J., Weber, A.L.: Organization and outcomes of inpatient AIDS care. Med. Care 37(8), 760–772 (1999)

    Article  PubMed  CAS  Google Scholar 

  39. Greenland, S.: Principles of multilevel modelling. Int. J. Epidemiol. 29, 158–167 (2000)

    Article  PubMed  CAS  Google Scholar 

  40. Diez-Roux, A.V.: Multilevel analysis in public health research. Annu. Rev. Public Health 21, 171–192 (2000)

    Article  PubMed  CAS  Google Scholar 

  41. Leyland, A., Goldstein, H.: Multilevel modelling of health statistics. Wiley series in probability and statistics—applied probability and statistics section. Wiley, New York (2001)

    Google Scholar 

  42. Bingenheimer, J.B., Raudenbush, S.W.: Statistical and substantive inferences in public health: issues in the application of multilevel models. Annu. Rev. Public Health 25, 53–77 (2004)

    Article  PubMed  Google Scholar 

  43. Čačala, S., Mafana, E., Thomson, S., Smith, A.: Prevalence of HIV status and CD4 counts in a surgical cohort: their relationship to clinical outcome. Ann. R. Coll. Surg. Engl. 88(1), 46–51 (2006)

    Article  PubMed  Google Scholar 

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Acknowledgments

This research is supported partially by the Portuguese agency Fundação para a Ciência e Tecnologia (FCT/OE PEst-OE/MAT/UI0006/2011), and partially by FCT providing a PhD scholarship to S.S.D. The authors would also like to thank Bettina Gruen for her endless support with the Flexmix library.

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Authors and Affiliations

  1. Departamento Universitário de Saúde Pública, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Campo dos Mártires da Pátria 130, 1169-056, Lisbon, Portugal

    Sara Simões Dias

  2. Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal

    Sara Simões Dias & Rosário O. Martins

  3. Centro de Estatística e Aplicações da Universidade de Lisboa, Faculdade de Ciências da Universidade de Lisboa, Bloco C6, Piso 4 Campo Grande, 1749-016, Lisbon, Portugal

    Valeska Andreozzi

  4. Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Rua da Junqueira 100, 1349-008, Lisbon, Portugal

    Rosário O. Martins

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  1. Sara Simões Dias
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  2. Valeska Andreozzi
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  3. Rosário O. Martins
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Correspondence to Sara Simões Dias.

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Dias, S.S., Andreozzi, V. & Martins, R.O. Analysis of HIV/AIDS DRG in Portugal: a hierarchical finite mixture model. Eur J Health Econ 14, 715–723 (2013). https://doi.org/10.1007/s10198-012-0416-5

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  • DOI: https://doi.org/10.1007/s10198-012-0416-5

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