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 Date
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 2 of 2 Research Studies DisplayedOlsen MA, Young-Xu Y, Stwalley D
The burden of Clostridium difficile infection: estimates of the incidence of CDI from U.S. administrative databases.
The researchers used comparable methods with multiple administrative databases to compare the incidence of clostridium difficile infection (CDI) in older and younger persons in the United States. They found that the incidence of CDI was 10-fold lower and the proportion of community-onset CDI was much higher in the privately insured younger LabRx population compared to the elderly Medicare population.
AHRQ-funded; HS019455.
Citation: Olsen MA, Young-Xu Y, Stwalley D .
The burden of Clostridium difficile infection: estimates of the incidence of CDI from U.S. administrative databases.
BMC Infect Dis 2016 Apr 22;16:177. doi: 10.1186/s12879-016-1501-7.
.
.
Keywords: Healthcare Cost and Utilization Project (HCUP), Clostridium difficile Infections, Healthcare-Associated Infections (HAIs), Data, Prevention
Warren DK, Nickel KB, Wallace AE
Can additional information be obtained from claims data to support surgical site infection diagnosis codes?
The authors sought to confirm a claims algorithm to identify surgical site infections (SSIs) by examining the presence of clinically expected SSI treatment. They found that over 94% of patients identified by their claims algorithm as having an SSI received clinically expected treatment for infection, including antibiotics, surgical treatment, and culture, suggesting that this algorithm has very good positive predictive value. They concluded that their method may facilitate retrospective SSI surveillance and comparison of SSI rates across facilities and providers.
AHRQ-funded; HS019713.
Citation: Warren DK, Nickel KB, Wallace AE .
Can additional information be obtained from claims data to support surgical site infection diagnosis codes?
Infect Control Hosp Epidemiol 2014 Oct;35 Suppl 3:S124-32. doi: 10.1086/677830.
.
.
Keywords: Data, Healthcare-Associated Infections (HAIs), Patient Safety, Surgery, Injuries and Wounds, Adverse Events