ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021
The Limited Utility of Ranking Hospitals Based on Their Colon Surgery Infection Rates.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Development and Application of New Risk-Adjustment Models to Improve the Current Model for Hospital Standardized Mortality Ratio in South Korea.Yonsei medical journal · 2025Article
- Variable selection in modelling clustered data via within-cluster resampling.The Canadian journal of statistics = Revue canadienne de statistique · 2025Article
- Do risk adjustment calculations used by governmental agencies adequately assess risk for infection after colon surgery?American journal of infection control · 2024Article
- Reportable infections following colon surgery in a large public healthcare system in New York City: The consequences of being a level 1 trauma center.Infection control and hospital epidemiology · 2024Article
- Antimicrobial approach of abdominal post-surgical infections.World journal of gastrointestinal surgery · 2023Review
- The impact of surgical volume on hospital ranking using the standardized infection ratio.Scientific reports · 2023Article
- Combined laparoscopic and open colon surgery rankings fail to accurately rank hospitals by surgical-site infection rate.Infection control and hospital epidemiology · 2023Article
- Evaluating Risk-Adjusted Hospital Performance Using Large-Scale Data on Mortality Rates of Patients in Intensive Care Units: A Flexible Semi-Nonparametric Modeling Approach.IEEE journal of translational engineering in health and medicine · 2023Article
- Impact of Risk Adjustment Using Clinical vs Administrative Data on Hospital Sepsis Mortality Comparisons.Open forum infectious diseases · 2020Article
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Centers for Medicare and Medicaid Services (CMS) use colon surgical site infection (SSI) rates to rank hospitals and apply financial penalties. The CMS' risk-adjustment model omits potentially impactful variables that might disadvantage hospitals with complex surgical populations.
methodsWe analyzed adult patients who underwent colon surgery within facilities associated with HCA Healthcare from 2014 to 2016. SSIs were identified from National Health Safety Network (NHSN) reporting. We trained and validated 3 SSI prediction models, using (1) current CMS model variables, including hospital-specific random effects (HCA-adapted CMS model); (2) demographics and claims-based comorbidities (expanded-claims model); and (3) demographics, claims-based comorbidities, and NHSN variables (claims-plus-electronic health record [EHR] model). Discrimination, calibration, and resulting rankings were compared among all models and the current CMS model with published coefficient values.
resultsWe identified 39 468 colon surgeries in 149 hospitals, resulting in 1216 (3.1%) SSIs. Compared to the HCA-adapted CMS model, the expanded-claims model had similar performance (c-statistic, 0.65 vs 0.67, respectively), while the claims-plus-EHR model was more accurate (c-statistic, 0.70; 95% confidence interval, .67-.73; P = .004). The sampling variation, due to the low surgical volume and small number of infections, contributed 74% of the total variation in observed SSI rates between hospitals. When CMS model rankings were compared to those from the expanded-claims and claims-plus-EHR models, 18 (15%) and 26 (22%) hospitals changed quartiles, respectively, and 10 (8.3%) and 12 (10%) hospitals changed into or out of the lowest-performing quartile, respectively.
conclusionsAn expanded set of variables improved colon SSI risk predictions and quartile assignments, but low procedure volumes and SSI events remain a barrier to effectively comparing hospitals.
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