National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- (-) Adverse Events (4)
- Data (2)
- Elderly (1)
- Electronic Health Records (EHRs) (1)
- Healthcare-Associated Infections (HAIs) (3)
- Health Information Technology (HIT) (1)
- Hospitals (1)
- Injuries and Wounds (3)
- Medical Errors (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 4 of 4 Research Studies DisplayedSkube SJ, Hu Z, Arsoniadis EG
Characterizing surgical site infection signals in clinical notes.
Building off of previous work for automated and semi-automated surgical site infections (SSIs) detection using expert-derived "strong features" from clinical notes, researchers hypothesized that additional SSI phrases may be contained in clinical notes. They systematically characterized phrases and expressions associated with SSIs. While 83 percent of expert-derived original terms overlapped with new terms and modifiers, an additional 362 modifiers associated with both positive and negative SSI signals were identified.
AHRQ-funded; HS024532.
Citation: Skube SJ, Hu Z, Arsoniadis EG .
Characterizing surgical site infection signals in clinical notes.
Stud Health Technol Inform 2017;245:955-59.
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Keywords: Healthcare-Associated Infections (HAIs), Surgery, Injuries and Wounds, Patient Safety, Adverse Events, Quality Improvement, Quality of Care
Hu 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
Kang H, Gong Y
A novel schema to enhance data quality of patient safety event reports.
In this study, the researchers designed a patient safety event (PSE) similarity searching model based on semantic similarity measures, and proposed a novel schema of PSE reporting system which can effectively learn from previous experiences and timely inform the subsequent actions. Their system will not only help promote the report qualities but also serve as a knowledge base and education tool to guide healthcare providers in terms of preventing the recurrence of PSEs.
AHRQ-funded; HS022895.
Citation: Kang H, Gong Y .
A novel schema to enhance data quality of patient safety event reports.
AMIA Annu Symp Proc 2017 Feb 10;2016:1840-49.
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Keywords: Quality of Care, Patient Safety, Data, Adverse Events, Medical Errors
Calderwood MS, Kleinman K, Huang SS
Surgical site infections: volume-outcome relationship and year-to-year stability of performance rankings.
The researchers evaluated the volume-outcome relationship as well as the year-to-year stability of performance rankings following coronary artery bypass graft (CABG) surgery and hip arthroplasty. They concluded that aggregate surgical site infection risk is highest in hospitals with low annual procedure volumes. Even for higher volume hospitals, year-to-year random variation makes past experience an unreliable estimator of current performance.
AHRQ-funded; HS021424.
Citation: Calderwood MS, Kleinman K, Huang SS .
Surgical site infections: volume-outcome relationship and year-to-year stability of performance rankings.
Med Care 2017 Jan;55(1):79-85. doi: 10.1097/mlr.0000000000000620.
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Keywords: Surgery, Healthcare-Associated Infections (HAIs), Adverse Events, Injuries and Wounds, Hospitals, Provider Performance, Quality Indicators (QIs), Quality of Care, Patient Safety, Elderly