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 DisplayedFlynn A, Taksler G, Caverly T
CBK model composition using paired web services and executable functions: A demonstration for individualizing preventive services.
The integration of Computable Biomedical Knowledge (CBK) models presents a difficult task for evolving health systems. The purpose of the study was to show that by utilizing the technical abilities of the World Wide Web (WWW), along with digital entities named Knowledge Objects, and introducing a fresh method of CBK model activation, the assembly of CBK models can be achieved in a more standardized, manageable, and beneficial manner. Using previously indicated compound digital objects known as Knowledge Objects, CBK models are packaged with metadata, API descriptions, and runtime requirements. Using open-source runtimes and a tool the researchers developed (the KGrid Activator) CBK models can be instantiated inside runtimes and made accessible via RESTful APIs by the KGrid Activator. The KGrid Activator then serves as a gateway and provides a method for interconnecting CBK model outputs and inputs, thus establishing a CBK model composition method. As a means of validating their method, the researchers created an intricate composite CBK model made up of 42 CBK submodels. The resulting model (CM-IPP), calculates life-gain estimates for individuals based on their unique characteristics. The outcome is a highly modularized CM-IPP execution that can be distributed and made operational in any usual server environment. The study found that construction of CBK models using compound digital entities and distributed computing technologies is achievable.
AHRQ-funded; HS026257.
Citation: Flynn A, Taksler G, Caverly T .
CBK model composition using paired web services and executable functions: A demonstration for individualizing preventive services.
Learn Health Syst 2023 Apr; 7(2):e10325. doi: 10.1002/lrh2.10325..
Keywords: Learning Health Systems, Health Information Technology (HIT)
Bradford A, Shofer M, Singh H
AHRQ Author: Shofer M, Singh H
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
This paper discusses Measure Dx, a new AHRQ resource that translates knowledge from diagnostic measurement research into actionable recommendations. This resource guides healthcare organizations to detect, analyze, and learn from diagnostic safety events as part of a continuous learning and feedback cycle. The goal of Measure Dx is to advance new frontiers in reducing preventable diagnostic harm to patients.
AHRQ-authored; AHRQ-funded; 233201500022I; HS027363.
Citation: Bradford A, Shofer M, Singh H .
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
Int J Qual Health Care 2022 Sep 10;34(3). doi: 10.1093/intqhc/mzac068..
Keywords: Diagnostic Safety and Quality, Patient Safety, Quality Improvement, Quality of Care, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Systems, Learning Health Systems