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2013, Number 1

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Revista Cubana de Salud Pública 2013; 39 (1)

Usefulness of

Tamargo BTO, Jiménez PRE, Álvarez RJM, Terry VO

Language: Spanish
References: 31
Page: 4-18
PDF size: 193.54 Kb.


ABSTRACT

Introduction: the severity of cases has become an important confounding factor in the comparative analyses of the hospital performance based on outcome indicators.
Objective: to assess the usefulness, in terms of validity and reliability of "the severity of illness index of the clinical services of Hermanos Ameijeiras hospital" in a medical care service.
Methods: a retrospective descriptive research was conducted in the rheumatology service of "Hermanos Ameijeiras" hospital. The source of information was the medical histories of 339 discharged patients. After applying the exclusion criteria, the sample was composed by 306 histories from which the necessary data were taken. The analyzed period was January to November, 2008.
Results: regarding the conceptual validity, it was observed that there might be a relationship between the condition of patient at discharge and the quantitative severity of illness index. The validity of the criterion showed a Kappa statistic of 0.47 (95 % CI, 0.3908-0.5431) and a correlation coefficient between the Horm's severity of illness index and the severity of illness index of the clinical services of Hermanos Ameijeiras hospital, the quantitative index of 0.66 (p‹0,001). The inter-observer agreement yielded a reliability coefficient of 0.81 and a global weighted Kappa coefficient of 0.64. Cronbach's alpha coefficient was 0.62.
Conclusions: the severity index of the clinical services of "Hermanos Ameijeiras" hospital has acceptable validity and reliability, so it is useful to make an objective classification of the patient's severity.


REFERENCES

  1. Levy MM, Rapoport J, Lemeshow S, Chalfin DB, Phillips G, Danis M. Association between Critical Care Physician Management and Patient Mortality in the Intensive Care Unit. Ann Intern Med. 2008;148:801-9.

  2. Peiró S, Librero J. Evaluación de calidad a partir del conjunto mínimo de datos básicos al alta hospitalaria. Rev Neurol. 1999;29:651-61.

  3. Iezzoni LI. Risk adjustment for measuring healthcare outcomes. 2nd ed. Chicago, Illinois: Health Administration Press; 1997.

  4. Iezzoni LI. Risk and Outcomes. En: Iezzoni LI, editor. Risk adjustment for measuring healthcare outcomes. 2nd ed. Chicago: Illinois, Health Administration Press; 1997. p. 1-41.

  5. Iezzoni LI. The risk of risks adjustment . Special Communications. JAMA. 1997;278(19):325-43.

  6. Tamargo Barbeito TO, Jiménez Paneque RE. El ajuste por riesgo en la evaluación del desempeño hospitalario. Revista Cubana Salud Pública. 2009 [citado 13 Ago 2009];35(3). Disponible en: http://bvs.sld.cu/revistas/spu/vol35_3_09/spu10309.htm

  7. Iezzoni LI. Developing Risk-Adjustment Methods. En: Iezzoni LI, editor. Risk adjustment for measuring healthcare outcomes. 2nd ed. Chicago, Illinois: Health Administration Press; 1997. p.279-329.

  8. Martins M, Blais R, da Costa Leite I. Mortalidade hospitalar e tempo de permanência: comparação entre hospitais públicos e privados na região de Ribeirão Preto, São Paulo, Brasil. Cad Saúde Pública. 2004;20(Sup 2):268-82.

  9. Jiménez R, Domínguez E, López L, Fariñas H. Difference between observed and predicted length of stay as indicator of patient care inefficiency. Internat J Quality Health Care. 1999;11(5):375-84.

  10. Horn SD, Horn RA. Reliability and validity of the severity of illness index. Med Care. 1986;24(2):159-78.

  11. Moya del Madrigal L. Aplicación del grupos del los grupos de diagnósticos relacionados a la gestión del sistema nacional del servicios de la hospitalización del la CCSS. Rev Cienc Adm Financ Segur Soc. 1998;6(2):13-33.

  12. Librero J, Marín M, Peiró S, Verdaguer Manujos A. Exploring the impact of complications on length of stay in major surgery diagnosis-related groups. Internat J Quality Health Care. 2004;16:51-7.

  13. Gonnella JS, Hornbrook ML, Louis DZ. Staging of disease. A case-mix measurement. JAMA. 1984;251:637-46.

  14. Myers RP, Quan H, Hubbard JN, Shaheen AA, Kaplan GG. Predicting in-hospital mortality in patients with cirrhosis: results differ across risk adjustment methods. Hepatology. 2009;49(2):568-77.

  15. Smith KD, Yuen EJ, Louis DZ, Rabinowitz C, Maio V, Jimbo M. Risk adjustment in a non-market based system. The case of Emilia-Romagna, Italy. Internat J Technol Management. 2006;7(1/2):100-115.

  16. Li B, Evans D, Faris P, Stafford D, Quan H. Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases. BMC Health Ser Res. 2008 [cited 2009 Mar 20];8:12. Available from: http://www.biomedcentral.com/content/pdf/1472-6963-8-12.pdf2.pdf

  17. Zhu H, Hill MD. The Elixhauser Index for comorbidity adjustment of in-hospital case Fatality. Neurology. 2008;71:2837.

  18. Jiménez RE, Vázquez J, Fariñas H. Construcción y validación de un índice de gravedad para pacientes hospitalizados en áreas clínicas. Gac Sanit, Xunta de Galicia. 1997;11:122-30.

  19. Jiménez RE, Lam RM, Marot M, Delgado A. Observed-predicted length of stay for an acute psychiatric department, as an indicator of inpatient care inefficiencies. Retrospective case-series study. BMC Health Serv Res. 2004 [cited 2007 Mar 20];4(4). Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=387834

  20. Ferreira A, Rígoli F, Bazzani R. Procesos asociados con el tiempo de estadía en el Hospital de Clínicas: estudio en cuatro enfermedades trazadoras. Rev Med Uruguay. 1997;13:23-36.

  21. Liu Y, Phillips M, Codde J. Factors influencing patients' length of stay. Aust Health Rev. 2001;24(2)63-70.

  22. Sánchez R, Echeverri J. Validación de escalas de medición en salud. Rev Salud Pública. 2004;6(3):302-18.

  23. Fleiss JL. The measurement of interrater agreement. En: Fleiss JL, editor. Statistical methods for rates and proportions. 2nd ed. New York: John Wiley and Sons;1981. p. 212-36.

  24. López de Ullibari Galparsoro I, Pita Fernández. Medidas de concordancia: el índice de Kappa. Cad Aten Primaria. 1999;6:169-71.

  25. Cerda J, Villarroel L. Evaluación de la concordancia inter-observador en investigación pediátrica: Coeficiente de Kappa. Rev Chil Pediatr. 2008;79(1):54-8.

  26. Boonen A, van der Heijde D, Landewé R, van Tubergen A, Mielants H, Dougados M, et al. How do the EQ-5D, SF-6D and the well-being rating scale compare in patients with ankylosing spondylitis? Ann Rheum Dis. 2007;66(6):771-7.

  27. Wells G, Becker JC, Tenq J, Dougados M, Schiff M, Smolen J, et al. Validation of the 28-joint Disease Activity Score (DAS-28) and European League Against Rheumatism response criteria based on C-reactive protein against disease progression in patients with rheumatoid arthritis, and comparison with the DAS28 based on erythrocyte sedimentation rate. Ann Rheum Dis. 2009;68(6):954-60.

  28. Streiner DL, Norman GR. Health measurement scales. A practical guide to their development and use. Oxford: Oxford University Press; 1989.

  29. Pita Fernández S, Pértega Díaz S, Rodríguez Maseda E. La fiabilidad de las mediciones clínicas: el análisis de concordancia para variables numéricas. Cad Aten Primaria. 2003;10(4):290-6.

  30. Bland JM, Altman DG.Statistics Notes: Cronbach's Alpha. BMJ. 1997; 314:572.

  31. Feinstein AR. Clinimetrics. New Haven: Yale University Press; 1987.




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