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Orthopedics ; 32(7): 495, 2009 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-19634848

RESUMO

The introduction of the hospitalist co-management model represents an opportunity to improve care by changing the system as it applies to a small group of patients. Eighty-six consecutive patients with multiple comorbidities were selectively enrolled in an academic medical center hospitalist-orthopedic surgery co-management patient care program. Patients were stratified by all patient refined diagnosis-related groups, severity of illness, and risk of mortality. Hospital length of stay, cost of care, in-hospital mortality, complications, and intensive care unit admissions were compared with a retrospectively constructed control group of 54 patients undergoing similar surgery during the period immediately preceding initiation of the program. The University Health System Consortium observed-to-expected ratio for hospital length of stay was 0.693 compared to 0.862 for the control group. The severity of illness and risk of mortality scores represented a relatively higher risk stratification in the study group. While the overall observed-to-expected cost of care remained virtually unchanged, the positive impact of the study model revealed an increased positive effect on the more severely affected severity of illness and risk of mortality patients. The results of this study suggest that a proactive, cooperative, co-management model for the perioperative management of high-risk patients undergoing complex surgery can improve the quality and efficiency metrics associated with the delivery of service to patients.


Assuntos
Custos de Cuidados de Saúde/estatística & dados numéricos , Médicos Hospitalares/economia , Médicos Hospitalares/estatística & dados numéricos , Ortopedia/economia , Ortopedia/estatística & dados numéricos , Procedimentos de Cirurgia Plástica/economia , Procedimentos de Cirurgia Plástica/estatística & dados numéricos , Humanos , Illinois/epidemiologia , Tempo de Internação/economia , Tempo de Internação/estatística & dados numéricos , Medição de Risco
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