National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Events (1)
- Children/Adolescents (1)
- Clinical Decision Support (CDS) (1)
- Decision Making (1)
- (-) Diagnostic Safety and Quality (3)
- Electronic Health Records (EHRs) (1)
- (-) Healthcare-Associated Infections (HAIs) (3)
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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 3 of 3 Research Studies DisplayedBucher BT, Yang M, Arndorfer J
Changes in the accuracy of administrative data for the detection of surgical site infections.
The authors performed a retrospective analysis of the changes in accuracy of International Classification of Diseases, Clinical Modification (ICD-CM) diagnosis codes for colectomy and hysterectomy surgical site infection surveillance. They found no significant change in the accuracy of these codes following the transition from ICD-CM ninth edition to tenth edition codes.
AHRQ-funded; HS025776.
Citation: Bucher BT, Yang M, Arndorfer J .
Changes in the accuracy of administrative data for the detection of surgical site infections.
Infect Control Hosp Epidemiol 2021 Sep;42(9):1128-30. doi: 10.1017/ice.2020.1346..
Keywords: Surgery, Healthcare-Associated Infections (HAIs), Diagnostic Safety and Quality
Zhu Y, Simon GJ, Wick EC
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. The purpose of the study was to understand the generalizability of a machine learning algorithm between sites; automated surgical site infection (SSI) detection algorithms developed at one center were tested at another distinct center.
AHRQ-funded; HS024532.
Citation: Zhu Y, Simon GJ, Wick EC .
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
J Am Coll Surg 2021 Jun;232(6):963-71.e1. doi: 10.1016/j.jamcollsurg.2021.03.026..
Keywords: Healthcare-Associated Infections (HAIs), Surgery, Adverse Events, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Sick-Samuels AC, Linz M, Bergmann J
Diagnostic stewardship of endotracheal aspirate cultures in a PICU.
This study describes the development and impact of a clinical decision support algorithm to standardize the use of endotracheal aspirate cultures (EACs) from ventilated PICU patients in the evaluation of suspected ventilator-associated infections. Bacterial growth in EACs does not distinguish bacterial colonization from infection and may lead to overtreatment with antibiotics. The rate of EACs was compared pre- and postintervention. In the preintervention year there were 557 EACs over 5092 ventilator days. After introduction of the algorithm the rate went down to 234 EACs over 3654 ventilator days. There was a 41% decrease in the monthly rate of EACs. This intervention did not affect mortality, readmissions, or length of stay in ventilated PICU patients.
AHRQ-funded; HS025642.
Citation: Sick-Samuels AC, Linz M, Bergmann J .
Diagnostic stewardship of endotracheal aspirate cultures in a PICU.
Pediatrics 2021 May;147(5). doi: 10.1542/peds.2020-1634..
Keywords: Children/Adolescents, Intensive Care Unit (ICU), Clinical Decision Support (CDS), Decision Making, Healthcare-Associated Infections (HAIs), Diagnostic Safety and Quality