Online Program

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Thursday, January 11
Thu, Jan 11, 7:30 AM - 9:00 AM
Crystal Ballroom Prefunction
Continental Breakfast & Poster Session II

NYS SPARCS public DATASET: Let's look at Septicemia, what can we learn? (304129)

Simon Sheather, Texas A & M University 
*Lisa Szydziak, Northwell Health 

Keywords: septicemia, SPARCS, statistical analysis

New York State Department of Health provides publicly available de-identified data for the general public and researchers at referred to as SPARCS data. SEPTICEMIA & DISSEMINATED INFECTIONS cases representing a high volume APR-DRG in the 2014 SPARCS dataset were investigated. A statistical analysis enables a comparison of facilities in terms of cost/charges adjusting for race, gender, age, length of stay (LOS), Admit type, Disposition, Severity of Illness, Risk of Mortality, Payor, Procedure, High Cost, Admit day of week and Discharge day of week. In modeling cost/charges, a single model was found not to fit and models differed across 2 groups: Patients that die in 1 day and Patients that do not die in 1 day. A Logistic Model was produced for examining the probability of death in patients that do not die in 1 day adjusting for gender, age, LOS, Admit type, Disposition, Severity of Illness, Risk of Mortality, Facility, Payor, Procedure and Discharge Day of week. Modeling of publicly reported data is very powerful, it could support policy makers, administrators and patients in understanding the complexity of healthcare costs and quality.