National Healthcare Quality and Disparities Report
Latest available findings on quality of and access to health care
Data
- Data Infographics
- Data Visualizations
- Data Tools
- Data Innovations
- All-Payer Claims Database
- Healthcare Cost and Utilization Project (HCUP)
- Medical Expenditure Panel Survey (MEPS)
- AHRQ Quality Indicator Tools for Data Analytics
- State Snapshots
- United States Health Information Knowledgebase (USHIK)
- Data Sources Available from AHRQ
Search All Research Studies
AHRQ Research Studies
Sign up: AHRQ Research Studies Email updates
Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 1 of 1 Research Studies DisplayedKamineni M, Ötleş Meng E, Oh J
Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers.
The purpose of this prospective study was to assess a data-driven approach for Clostridioides difficile infection (CDI) risk prediction that had previously demonstrated a high performance in retrospective evaluations at 2 large academic health centers. The final retrospective cohort included 18,030 admissions (138 CDI cases) at Massachusetts General Hospital (MGH) and 25,341admissions (158 CDI cases) at Michigan Medicine. The prospective cohort included 13,712 admissions (119 CDI cases) at MGH and 26,864 admissions (190 CDI cases) at MM. At MGH, the model achieved area under the receiver operator characteristic curve (AUROC). AUROCs of 0.744 in the retrospective cohort and 0.748 in the prospective cohort. At MM, the model achieved AUROCs of 0.778 in the retrospective cohort and 0.767 in the prospective cohort. The AUROCs for predicting CDI risk on both retrospective and prospective cohorts were similar each month and did not exhibit significant monthly variation throughout either assessment period.
AHRQ-funded; HS027431.
Citation: Kamineni M, Ötleş Meng E, Oh J .
Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers.
Infect Control Hosp Epidemiol 2023 Jul; 44(7):1163-66. doi: 10.1017/ice.2022.218..
Keywords: Clostridium difficile Infections, Healthcare-Associated Infections (HAIs), Risk