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Estimation of direct cost and resource allocation in intensive care: correlation with Omega system

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Abstract

Objective: An instrument able to estimate the direct costs of stays in Intensive Care Units (ICUs) simply would be very useful for resource allocation inside a hospital, through a global budget system. The aim of this study was to propose such a tool.

Design: Since 1991, a region-wide common data base has collected standard data of intensive care such as the Omega Score, Simplified Acute Physiologic Score, length of stay, length of ventilation, main diagnosis and procedures. The Omega Score, developed in France in 1986 and proved to be related to the workload, was recorded on each patient of the study.

Setting: Eighteen ICUs of Assistance Publique-Hopitaux de Paris (AP-HP) and suburbs.

Patients: 1) Hundred twenty-one randomly selected ICU patients; 2) 12,000 consecutive ICU stays collected in the common data base in 1993.

Measurements: 1) On the sample of 121 patients, medical expenditure and nursing time associated with interventions were measured through a prospective study. The correlation between Omega points and direct costs was calculated, and regression equations were applied to the 12,000 stays of the data base, leading to estimated costs. 2) From the analytic accounting of AP-HP, the mean direct cost per stay and per unit was calculated, and compared with the mean associated Omega score from the data base. In both methods a comparison of actual and estimated costs was made.

Results: The Omega Score is strongly correlated to total direct costs, medical direct costs and nursing requirements. This correlation is observed both in the random sample of 121 stays and on the data base’ stays. The discrepancy of estimated costs through Omega Score and actual costs may result from drugs, blood product underestimation and therapeutic procedures not involved in the Omega Score.

Conclusions: The Omega system appears to be a simple and relevant indicator with which to estimate the direct costs of each stay, and then to organise nursing requirements and resource allocation.

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References

  1. Knaus WA, Wagner DP, Zimmerman JE, Draper EA (1993) Variations in mortality and length of stay in Intensive Care Units. Ann of Int Med 118: 753–761

    CAS  Google Scholar 

  2. Singer M, Meyers S, Hall G, Cohen SL, Armstrong RF (1994) The cost of intensive care: a comparison on one unit between 1988 and 1991. Intensive Care Med 20: 542–549

    Article  PubMed  CAS  Google Scholar 

  3. Jacobs CJ (1994) Mortality and quality of life after intensive care for critical illness. Intensive Care Med 14: 217–220

    Article  Google Scholar 

  4. Mundt DJ (1989) Intensive Care Unit patient follow-up mortality, functional status, and return to work. Arch Intern Med 149: 68–72

    Article  PubMed  CAS  Google Scholar 

  5. Loirat Ph (1990) Results of intensive care: assessment of the quality of life. Intensive Care Med 16: S 25 (91)

  6. Ridley S (1991) Cost of intensive therapy: Anaesthesia 46: 523–530

    Article  PubMed  CAS  Google Scholar 

  7. Birnbaum M, Walleck CA (1993) Rationing health care; impact on critical care. Crit Care Clin 9: 585–602

    PubMed  CAS  Google Scholar 

  8. Noseworthy TW, Konopad E, Shustack A, Johnston R, Grace M (1996) Cost accounting of adult intensive care: methods and human and capital inputs. Crit Care Med 24:1168–1172

    Article  PubMed  CAS  Google Scholar 

  9. Oye RK (1991) Patterns of resource consumption in medical intensive care. Chest 99: 685–689

    Article  PubMed  CAS  Google Scholar 

  10. Rodrigues JM (1986) La nouvelle comptabilité hospitalière: l’analyse des couts par groupes homogénes de malades. Gestions hospitalieres 258: 500–507

    Google Scholar 

  11. Giraud A (1985) Le “systéme Fetter” ou la définition du produit hospitalier par DRG. Journal d’Economie Médicale 3:183–190

    Google Scholar 

  12. Description de la nouvelle procédure d’allocation budgétaire (1995) Direction des Hôpitaux. Ministère des Affaires Sociales, de la Santé et de la Ville

  13. Pourriat JL (1990) Groupes homogènes de malades: analyse critique. In: Le Gall JR, Loirat Ph (eds) Evaluation en Réanimation, Paris, pp 157–168

    Google Scholar 

  14. Saulnier F, Naiditch M, Comar L, Nicolas F (1995) Système GHM et réanimation: résultats de l’étude SRLF-Image. Réan Urg 75–89

  15. Saulnier F (1992) Management of ICUs. A simplified index to assess the nurse workload: ICU PRN. Intensive Care Med 18, S 71 (129)

    Google Scholar 

  16. Rappoport J (1990) Explaining variability of cost using a severity of illness measure for ICU patients. Med Care 28: 338–348

    Article  Google Scholar 

  17. Mälstam J (1992) TISS: a method for measuring workload and calculating costs in the ICU. Acta Anaesthesiol Scand 36: 758–763

    Article  PubMed  Google Scholar 

  18. Le Gall JR, Loirat P, Mathieu D, Williams A (1990) The patients in management of intensive Care. In: Miranda DR, Williams A, Loirat Ph (eds) Guidelines for better use of resources. Kluwer, Dordrecht, pp 11–53

    Google Scholar 

  19. Lazard T, Metel O, Guidet B, Maury E, Valleron AJ, Offenstadt G (1996) AIDS in a Medical Intensive Care Unit. Immediate prognosis and long-term survival. JAMA 276:1240–1245

    Article  PubMed  CAS  Google Scholar 

  20. Le Gall JR, Loirat Ph, Alpérovitch A et al. (1984) Simplified acute physiology score (SAPS) for ICU patients. Crit Care Med 12: 975–977

    Article  PubMed  Google Scholar 

  21. Durand-Zaleski I (1994) Estimating the cost of intensive care. Intensive Care Med 20: 538–539

    Article  PubMed  CAS  Google Scholar 

  22. Merlière Y, Dutheil M (1992) Détermination d’une typologie des services de reanimation mèdicale dans les hôpitaux de l’AP-HP. Rean Urg 1,1005 (094)

  23. Groeger JS et al. (1992) Descriptive analysis of critical care units in the United States. Crit Care Med 20: 846–863

    Article  PubMed  CAS  Google Scholar 

  24. Dragsted L, Qvist J (1992) Epidemiology of intensive care. Int J Technol Assess Health Care 8: 395–407

    Article  PubMed  CAS  Google Scholar 

  25. Jars-Guincestre MC, Leleu G, Comar L, Naiditch M, Le Gall JR (1992) Choix du diagnostic principal d’un séjour de réanimation polyvalente adulte. Réan Urg 1,1066 (098)

    Google Scholar 

  26. Nicolas F (1995) L’audit médical interne répétitif comme instrument de maît-rise médicalisée des dépenses. RéaUrg 123–131

  27. Le Gall JR, Lemeshow S, Saulnier F (1993) New simplified acute physiology score (SAPS II) based on a European North American Multicenter Study: JAMA 270: 2957–2963

    Article  PubMed  Google Scholar 

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Sznajder, M., Leleu, G., Buonamico, G. et al. Estimation of direct cost and resource allocation in intensive care: correlation with Omega system. Intensive Care Med 24, 582–589 (1998). https://doi.org/10.1007/s001340050619

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