AI Article Synopsis
- - The study aimed to create a risk-adjustment model for hospitals to evaluate their performance in treating sepsis patients by analyzing 30-day mortality rates using administrative data from Pennsylvania hospitals in 2012-2013.
- - Researchers found significant variation in hospital-specific mortality rates for sepsis, ranging from 12.2% to 24.5%, and the model achieved strong accuracy with a C-statistic of 0.78.
- - The model showed that performance assessments remained stable over the two years studied, with a high correlation that indicates consistent ranking of hospitals in their care for sepsis patients.
Article Abstract
Background: Given the increased attention to sepsis at the population level there is a need to assess hospital performance in the care of sepsis patients using widely-available administrative data. The goal of this study was to develop an administrative risk-adjustment model suitable for profiling hospitals on their 30-day mortality rates for patients with sepsis.
Methods: We conducted a retrospective cohort study using hospital discharge data from general acute care hospitals in Pennsylvania in 2012 and 2013. We identified adult patients with sepsis as determined by validated diagnosis and procedure codes. We developed an administrative risk-adjustment model in 2012 data. We then validated this model in two ways: by examining the stability of performance assessments over time between 2012 and 2013, and by examining the stability of performance assessments in 2012 after the addition of laboratory variables measured on day one of hospital admission.
Results: In 2012 there were 115,213 sepsis encounters in 152 hospitals. The overall unadjusted mortality rate was 18.5%. The final risk-adjustment model had good discrimination (C-statistic = 0.78) and calibration (slope and intercept of the calibration curve = 0.960 and 0.007, respectively). Based on this model, hospital-specific risk-standardized mortality rates ranged from 12.2 to 24.5%. Comparing performance assessments between years, correlation in risk-adjusted mortality rates was good (Pearson's correlation = 0.53) and only 19.7% of hospitals changed by more than one quintile in performance rankings. Comparing performance assessments after the addition of laboratory variables, correlation in risk-adjusted mortality rates was excellent (Pearson's correlation = 0.93) and only 2.6% of hospitals changed by more than one quintile in performance rankings.
Conclusions: A novel claims-based risk-adjustment model demonstrated wide variation in risk-standardized 30-day sepsis mortality rates across hospitals. Individual hospitals' performance rankings were stable across years and after the addition of laboratory data. This model provides a robust way to rank hospitals on sepsis mortality while adjusting for patient risk.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458755 | PMC |
| http://dx.doi.org/10.1186/s12913-019-4037-x | DOI Listing |
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