National Healthcare Quality and Disparities Report
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Search All Research Studies
Topics
- Adverse Events (1)
- Cardiovascular Conditions (1)
- Comparative Effectiveness (2)
- (-) Data (6)
- Electronic Health Records (EHRs) (1)
- Healthcare-Associated Infections (HAIs) (1)
- Health Information Technology (HIT) (1)
- Health Services Research (HSR) (1)
- Hospital Discharge (3)
- Hospitals (3)
- Injuries and Wounds (1)
- Maternal Care (1)
- Patient-Centered Outcomes Research (1)
- Patient Safety (2)
- (-) Quality Improvement (6)
- Quality Indicators (QIs) (1)
- Quality of Care (4)
- Racial and Ethnic Minorities (2)
- Registries (3)
- Research Methodologies (1)
- Surgery (2)
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 6 of 6 Research Studies DisplayedHsu YJ, Kosinski AS, Wallace AS
Using a society database to evaluate a patient safety collaborative: the Cardiovascular Surgical Translational Study.
The authors assessed the utility of using external databases for quality improvement (QI) evaluations in the context of an innovative QI collaborative aimed to reduce three infections and improve patient safety across the cardiac surgery service line. They compared changes in each outcome between 15 intervention hospitals and 52 propensity score-matched hospitals, and found that improvement trends in several outcomes among the studied intervention hospitals were not statistically different from those in comparison hospitals. They conclude that using external databases may permit comparative effectiveness assessment by providing concurrent comparison groups, additional outcome measures, and longer follow-up.
AHRQ-funded; HS019934.
Citation: Hsu YJ, Kosinski AS, Wallace AS .
Using a society database to evaluate a patient safety collaborative: the Cardiovascular Surgical Translational Study.
J Comp Eff Res 2019 Jan;8(1):21-32. doi: 10.2217/cer-2018-0051..
Keywords: Patient Safety, Quality Improvement, Quality Indicators (QIs), Quality of Care, Surgery, Cardiovascular Conditions, Comparative Effectiveness, Data, Hospitals, Research Methodologies, Patient-Centered Outcomes Research
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
Sundararajan V, Romano PS, Quan H
Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety.
The purpose of this project was to develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data. The WHO Quality and Safety Topic Advisory Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting. This paper discusses their concerns and recommendations.
AHRQ-funded; HS020543.
Citation: Sundararajan V, Romano PS, Quan H .
Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety.
Int J Qual Health Care 2015 Aug;27(4):328-33. doi: 10.1093/intqhc/mzv037..
Keywords: Patient Safety, Quality of Care, Quality Improvement, Hospitals, Data
Zingmond DS, Parikh P, Louie R
Improving hospital reporting of patient race and ethnicity--approaches to data auditing.
This study investigated new metrics to improve the reporting of patient race and ethnicity (R/E) by hospitals. It examined agreement between hospital reported R/E versus self-report among mothers delivering babies and a cancer cohort in California. It concluded that comparison between reported R/E and R/E estimates using zip code level data may be a reasonable first approach to evaluate and track hospital R/E reporting.
AHRQ-funded; HS019963.
Citation: Zingmond DS, Parikh P, Louie R .
Improving hospital reporting of patient race and ethnicity--approaches to data auditing.
Health Serv Res 2015 Aug;50 Suppl 1:1372-89. doi: 10.1111/1475-6773.12324..
Keywords: Racial and Ethnic Minorities, Hospitals, Hospital Discharge, Health Services Research (HSR), Registries, Quality Improvement, Quality of Care, Data
Salemi JL, Salinas-Miranda AA, Wilson RE
Transformative use of an improved all-payer hospital discharge data infrastructure for community-based participatory research: a sustainability pathway.
The researchers describe the use of a clinically enhanced maternal and child health (MCH) database to strengthen community-engaged research activities, and to support the sustainability of data infrastructure initiatives. The population-based, longitudinal database was used to supplement data collected from focus groups and community surveys with epidemiological and health care cost data on important MCH disparity issues in the target community.
AHRQ-funded; HS019997.
Citation: Salemi JL, Salinas-Miranda AA, Wilson RE .
Transformative use of an improved all-payer hospital discharge data infrastructure for community-based participatory research: a sustainability pathway.
Health Serv Res 2015 Aug;50 Suppl 1:1322-38. doi: 10.1111/1475-6773.12309..
Keywords: Maternal Care, Comparative Effectiveness, Hospital Discharge, Data, Quality Improvement
Bigback KM, Hoopes M, Dankovchik J
Using record linkage to improve race data quality for American Indians and Alaska Natives in two Pacific Northwest State Hospital Discharge Databases.
This study aimed to evaluate and adjust for American Indian and Alaska Native (AI/AN) racial misclassification in two hospital discharge datasets in the Pacific Northwest. It found that in Oregon, 55.4 percent of matching records were misclassified (66.5 percent miscoded white, and 22.1 percent were missing race information). Linkage increased ascertainment of AI/AN hospitalizations by 31.8 percent in Oregon and 33.9 percent in Washington.
AHRQ-funded; HS019972.
Citation: Bigback KM, Hoopes M, Dankovchik J .
Using record linkage to improve race data quality for American Indians and Alaska Natives in two Pacific Northwest State Hospital Discharge Databases.
Health Serv Res 2015 Aug;50 Suppl 1:1390-402. doi: 10.1111/1475-6773.12331..
Keywords: Racial and Ethnic Minorities, Quality Improvement, Registries, Hospital Discharge, Data