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Search All Research Studies
Topics
- Adverse Events (2)
- Clostridium difficile Infections (2)
- (-) Data (5)
- Electronic Health Records (EHRs) (1)
- (-) Healthcare-Associated Infections (HAIs) (5)
- Healthcare Cost and Utilization Project (HCUP) (1)
- Health Information Technology (HIT) (1)
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 5 of 5 Research Studies DisplayedHu Z, Melton GB, Arsoniadis EG
Strategies for handling missing clinical data for automated surgical site infection detection from the electronic health record.
Proper handling of missing data is important for many secondary uses of electronic health record (EHR) data. Data imputation methods can be used to handle missing data, but their use for postoperative complication detection is unclear. Overall, models with missing data imputation almost always outperformed reference models without imputation that included only cases with complete data for detection of SSI overall achieving very good average area under the curve values.
AHRQ-funded; HS024532.
Citation: Hu Z, Melton GB, Arsoniadis EG .
Strategies for handling missing clinical data for automated surgical site infection detection from the electronic health record.
J Biomed Inform 2017 Apr;68:112-20. doi: 10.1016/j.jbi.2017.03.009.
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Keywords: Data, Electronic Health Records (EHRs), Healthcare-Associated Infections (HAIs), Registries, Surgery, Injuries and Wounds, Health Information Technology (HIT), Quality Improvement, Quality of Care, Adverse Events
Olsen 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.
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Keywords: Healthcare Cost and Utilization Project (HCUP), Clostridium difficile Infections, Healthcare-Associated Infections (HAIs), Data, Prevention
van Mourik MS, van Duijn PJ, Moons KG
Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review.
The researchers conducted a systematic review evaluating the diagnostic accuracy of administrative data for the detection of HAI. They concluded that administrative data had limited and highly variable accuracy for the detection of HAI, and their judicious use for internal surveillance efforts and external quality assessment is recommended.
AHRQ-funded; HS018414.
Citation: van Mourik MS, van Duijn PJ, Moons KG .
Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review.
BMJ Open 2015 Aug 27;5(8):e008424. doi: 10.1136/bmjopen-2015-008424..
Keywords: Healthcare-Associated Infections (HAIs), Data, Patient Safety, Quality of Care
Pakyz AL, Patterson JA, Motzkus-Feagans C
Performance of the present-on-admission indicator for Clostridium difficile infection.
The researchers compared performance of a hospital- and community-onset Clostridium difficile infection definition using administrative data to a present on- admission indicator with definitions using clinical surveillance. For hospital-onset C. difficile infection, there was moderate sensitivity (68 percent) and high specificity (93 percent); for community-onset, sensitivity and specificity were high (both 85 percent).
AHRQ-funded; HS018578.
Citation: Pakyz AL, Patterson JA, Motzkus-Feagans C .
Performance of the present-on-admission indicator for Clostridium difficile infection.
Infect Control Hosp Epidemiol 2015 Jul;36(7):838-40. doi: 10.1017/ice.2015.63..
Keywords: Clostridium difficile Infections, Patient Safety, Healthcare-Associated Infections (HAIs), Data
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.
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Keywords: Data, Healthcare-Associated Infections (HAIs), Patient Safety, Surgery, Injuries and Wounds, Adverse Events