Francesc Cots1, Lluc Mercadé, Xavier Castells, Xavier Salvador. 1. Health Services Research Unit, Municipal Institute of Health, IMAS, Hospital del Mar, Passeig Marítim 25-29 E-08003, Barcelona, Spain. fcots@imas.imim.es
Abstract
BACKGROUND: Hospital structural level has been suggested as a factor that could explain part of the resource use variation left unexplained by diagnosis related groups (DRGs). However, the relationship between hospital structural level and the presence of cases of extreme resource use (outliers) is not known. Some prospective payment systems pay these cases separately. OBJECTIVES: To analyze the relationship between different hospital structural levels, defined according to hospital size, teaching activity and location, and the presence of length of stay (LOS) outliers. RESEARCH DESIGN: A logit model was used to analyze the patient discharge records of the acute care public hospitals' Minimum Data Set in Catalonia (Spain) in 1998. The final population contained 631,096 discharges grouped in 329 adjacent DRGs. MEASURES: LOS outliers were defined as cases with a LOS exceeding the geometric mean plus two standard deviations of all the stays in the same DRG. The 64 public hospitals of the Catalan health system were classified into large urban teaching hospitals, medium-sized teaching and community hospitals, and small community hospitals according to their structural complexity. The model also controlled for patient and health care process characteristics. RESULTS: Outliers accounted for 4.5% of total discharges distributed as follows: large urban teaching hospitals (5.6%), medium-sized teaching and community hospitals (4.6%), small community hospitals (3.6%). The probability of a patient being an outlier was higher in hospitals with greater structural complexity: large urban teaching hospitals (OR = 1.59), medium teaching and community hospitals (OR = 1.30) and small community hospitals (OR = 1). Adjustment through the control variables reduced differences among hospitals: large urban teaching hospitals (OR = 1.32), medium-sized teaching and community hospitals (OR = 1.22), and small community hospitals (OR = 1), but the differences remained significant (P < 0.01). CONCLUSIONS: Hospital structural level influences the presence of outliers even when controlling for patient and process characteristics. Thus, some outliers are due to hospital structural level and are not justified by patient characteristics.
BACKGROUND: Hospital structural level has been suggested as a factor that could explain part of the resource use variation left unexplained by diagnosis related groups (DRGs). However, the relationship between hospital structural level and the presence of cases of extreme resource use (outliers) is not known. Some prospective payment systems pay these cases separately. OBJECTIVES: To analyze the relationship between different hospital structural levels, defined according to hospital size, teaching activity and location, and the presence of length of stay (LOS) outliers. RESEARCH DESIGN: A logit model was used to analyze the patient discharge records of the acute care public hospitals' Minimum Data Set in Catalonia (Spain) in 1998. The final population contained 631,096 discharges grouped in 329 adjacent DRGs. MEASURES: LOS outliers were defined as cases with a LOS exceeding the geometric mean plus two standard deviations of all the stays in the same DRG. The 64 public hospitals of the Catalan health system were classified into large urban teaching hospitals, medium-sized teaching and community hospitals, and small community hospitals according to their structural complexity. The model also controlled for patient and health care process characteristics. RESULTS: Outliers accounted for 4.5% of total discharges distributed as follows: large urban teaching hospitals (5.6%), medium-sized teaching and community hospitals (4.6%), small community hospitals (3.6%). The probability of a patient being an outlier was higher in hospitals with greater structural complexity: large urban teaching hospitals (OR = 1.59), medium teaching and community hospitals (OR = 1.30) and small community hospitals (OR = 1). Adjustment through the control variables reduced differences among hospitals: large urban teaching hospitals (OR = 1.32), medium-sized teaching and community hospitals (OR = 1.22), and small community hospitals (OR = 1), but the differences remained significant (P < 0.01). CONCLUSIONS: Hospital structural level influences the presence of outliers even when controlling for patient and process characteristics. Thus, some outliers are due to hospital structural level and are not justified by patient characteristics.
Authors: Aaron C Miller; Linnea A Polgreen; Joseph E Cavanaugh; Philip M Polgreen Journal: Infect Control Hosp Epidemiol Date: 2016-02-09 Impact factor: 3.254
Authors: Alberto Freitas; Tiago Silva-Costa; Fernando Lopes; Isabel Garcia-Lema; Armando Teixeira-Pinto; Pavel Brazdil; Altamiro Costa-Pereira Journal: BMC Health Serv Res Date: 2012-08-20 Impact factor: 2.655