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Search All Research Studies
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- Arthritis (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 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
Austin EJ, LeRouge C, Lee JR
A learning health systems approach to integrating electronic patient-reported outcomes across the health care organization.
The authors reported on their effort to develop generalizable learnings that can support the integration of electronic patient-reported outcome measures into clinical practice within a learning health system (LHS) framework. They concluded that the guidelines produced from this work highlighted the complex, multidisciplinary nature of implementing change within LHS contexts, as well as the value of action research approaches to enable rapid, iterative learning that leverages the knowledge and experience of communities of practice.
AHRQ-funded; HS023785.
Citation: Austin EJ, LeRouge C, Lee JR .
A learning health systems approach to integrating electronic patient-reported outcomes across the health care organization.
Learn Health Syst 2021 Oct;5(4):e10263. doi: 10.1002/lrh2.10263..
Keywords: Learning Health Systems, Health Information Technology (HIT), Patient-Centered Outcomes Research, Outcomes, Evidence-Based Practice
Subash M, Liu LH, DeQuattro K
The Development of the Rheumatology Informatics System for Effectiveness Learning Collaborative for improving patient-reported outcome collection and patient-centered communication in adult rheumatology.
Patient-reported outcomes (PROs) are an integral part of treat-to-target approaches in managing rheumatoid arthritis (RA). In clinical practice, however, routine collection, documentation, and discussion of PROs with patients are highly variable. In this paper, the investigators discussed the Development of the Rheumatology Informatics System for Effectiveness Learning Collaborative for improving patient-reported outcome collection and patient-centered communication in adult rheumatology.
AHRQ-funded; HS025638.
Citation: Subash M, Liu LH, DeQuattro K .
The Development of the Rheumatology Informatics System for Effectiveness Learning Collaborative for improving patient-reported outcome collection and patient-centered communication in adult rheumatology.
ACR Open Rheumatol 2021 Oct;3(10):690-98. doi: 10.1002/acr2.11310..
Keywords: Arthritis, Patient-Centered Outcomes Research, Learning Health Systems, Health Information Technology (HIT)
Franklin P, Chenok K, Lavalee D
Framework to guide the collection and use of patient-reported outcome measures in the learning healthcare system.
Web-based collection of patient-reported outcome measures (PROMs) in clinical practice is expanding rapidly as electronic health records include web portals for patients to report standardized assessments of their symptoms. As the value of PROMs in patient care expands, a framework to guide the implementation planning, collection, and use of PROs to serve multiple goals and stakeholders is needed. In this study, researchers identified diverse clinical, quality, and research settings where PROMs have been successfully integrated into care and routinely collected and analyzed drivers of successful implementation.
AHRQ-funded; HS022789.
Citation: Franklin P, Chenok K, Lavalee D .
Framework to guide the collection and use of patient-reported outcome measures in the learning healthcare system.
eGEMS 2017 Sep 4;5(1):17. doi: 10.5334/egems.227..
Keywords: Learning Health Systems, Health Systems, Electronic Health Records (EHRs), Health Information Technology (HIT), Web-Based, Patient-Centered Healthcare