Predictors of mortality in HIV-associated hospitalizations in Portugal: a hierarchical survival model.
BACKGROUND
The beneficial effects of highly active antiretroviral therapy, increasing survival and the prevention of AIDS defining illness development are well established. However, the annual Portuguese hospital mortality is still higher than expected. It is crucial to understand the hospitalization behaviour to better allocate resources. This study investigates the predictors of mortality in HIV associated hospitalizations in Portugal through a hierarchical survival model.


METHODS
The study population consists of 12,078 adult discharges from patients with HIV infection diagnosis attended at Portuguese hospitals from 2005-2007 that were registered on the diagnosis-related groups' database.We used discharge and hospital level variables to develop a hierarchical model. The discharge level variables were: age, gender, type of admission, type of diagnoses-related group, related HIV complication, the region of the patient's residence, the number of diagnoses and procedures, the Euclidean distance from hospital to the centroid of the patient's ward, and if patient lived in the hospital's catchment area. The hospital characteristics include size and hospital classification according to the National Health System. Kaplan-Meier plots were used to examine differences in survival curves. Cox proportional hazard models with frailty were applied to identify independent predictors of hospital mortality and to calculate hazard ratios (HR).


RESULTS
The Cox proportional model with frailty showed that male gender, older patient, great number of diagnoses and pneumonia increased the hazard of HIV related hospital mortality. On the other hand tuberculosis was associated with a reduced risk of death. Central hospital discharge also presents less risk of mortality.The frailty variance was small but statistically significant, indicating hazard ratio heterogeneity among hospitals that varied between 0.67 and 1.34, and resulted in two hospitals with HR different from the average risk.


CONCLUSIONS
The frailty model suggests that there are unmeasured factors affecting mortality in HIV associated hospitalizations. Consequently, for healthcare policy purposes, hospitals should not all be treated in an equal manner.
Dias
Sara S
SS
Higher Institute of Statistics and Information Management, New University of Lisbon, Lisbon, Portugal. sdias@isegi.unl.pt
Andreozzi
Valeska
V
Martins
Maria O
MO
Torgal
Jorge
J
D000328:Adult; D019992:Databases as Topic; D003953:Diagnosis-Related Groups; D005260:Female; D005544:Forecasting; D015658:HIV Infections / Q000188:drug therapy / Q000401:mortality*; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011174:Portugal; D016019:Survival Analysis