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Search All Research Studies
Topics
- Clinical Decision Support (CDS) (1)
- Communication (2)
- (-) Data (6)
- Electronic Health Records (EHRs) (3)
- Genetics (1)
- Healthcare Delivery (1)
- Health Information Exchange (HIE) (1)
- Health Information Technology (HIT) (2)
- Heart Disease and Health (1)
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- (-) Patient-Centered Healthcare (6)
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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 6 of 6 Research Studies DisplayedArcia A, Woollen J, Bakken S
A systematic method for exploring data attributes in preparation for designing tailored infographics of patient reported outcomes.
Tailored visualizations of patient reported outcomes (PROs) are valuable health communication tools to support shared decision making, health self-management, and engagement with research participants, such as cohorts in the NIH Precision Medicine Initiative. The authors of the study present a systematic method to exploring data attributes, with a specific focus on application to self-reported health data. They present two case studies to illustrate how this method affected design decisions particularly with respect to outlier and non-missing zero values.
AHRQ-funded; HS019853; HS022961.
Citation: Arcia A, Woollen J, Bakken S .
A systematic method for exploring data attributes in preparation for designing tailored infographics of patient reported outcomes.
eGEMS 2018 Jan 24;6(1):2. doi: 10.5334/egems.190..
Keywords: Communication, Shared Decision Making, Patient-Centered Healthcare, Patient-Centered Outcomes Research, Outcomes, Data
LeRouge C, Hasselquist MB, Kellogg L
Using heuristic evaluation to enhance the visual display of a provider dashboard for patient-reported outcomes.
A human-centered design (HCD) approach to understanding the data visualization needs for patient-reported outcomes (PRO) in clinical practice can optimize the visual design of an interactive PRO system. Beyond iterative methods, the authors explored the additive value of other HCD methods such as heuristic evaluation. Their evaluation led to several recommendations to improve the display, accessibility, and interpretability of the dashboard’s data.
AHRQ-funded; HS023785.
Citation: LeRouge C, Hasselquist MB, Kellogg L .
Using heuristic evaluation to enhance the visual display of a provider dashboard for patient-reported outcomes.
eGEMS 2017 Apr 20;5(2):Article 6. doi: 10.13063/2327-9214.1283.
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Keywords: Patient-Centered Healthcare, Patient-Centered Outcomes Research, Health Information Technology (HIT), Data, Shared Decision Making
Richesson RL, Sun J, Pathak J
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
The authors sought to use electronic health records data to advance understanding of disease risk and drug response, and to support the practice of precision medicine on a national scale. They found that machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, as it comes from data rather than experts. They suggested that research networks and phenotype developers cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and modernize biomedical research.
AHRQ-funded; HS023921; HS023077.
Citation: Richesson RL, Sun J, Pathak J .
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
Artif Intell Med 2016 Jul;71:57-61. doi: 10.1016/j.artmed.2016.05.005.
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Keywords: Data, Electronic Health Records (EHRs), Genetics, Patient-Centered Healthcare
Marshall DA, Burgos-Liz L, Pasupathy KS
Transforming healthcare delivery: integrating dynamic simulation modelling and big data in health economics and outcomes research.
The authors discussed the synergies between big data and dynamic simulation modelling (DSM), practical considerations and challenges, and how integrating big data and DSM can be useful to decision makers to address complex, systemic health economics and outcomes questions and to transform healthcare delivery.
AHRQ-funded; HS023710.
Citation: Marshall DA, Burgos-Liz L, Pasupathy KS .
Transforming healthcare delivery: integrating dynamic simulation modelling and big data in health economics and outcomes research.
Pharmacoeconomics 2016 Feb;34(2):115-26. doi: 10.1007/s40273-015-0330-7.
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Keywords: Data, Shared Decision Making, Healthcare Delivery, Patient-Centered Healthcare, Patient-Centered Outcomes Research
Panahiazar M, Taslimitehrani V, Pereira NL
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
The authors developed a multidimensional patient similarity assessment technique that leverages multiple types of information from the electronic health records and predicts a medication plan for each new patient based on prior knowledge and data from similar patients.Their findings suggest that it is feasible to harness population-based information for an individual patient-specific assessment.
AHRQ-funded; HS023077.
Citation: Panahiazar M, Taslimitehrani V, Pereira NL .
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
Stud Health Technol Inform 2015;210:369-73.
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Keywords: Clinical Decision Support (CDS), Data, Electronic Health Records (EHRs), Heart Disease and Health, Patient-Centered Healthcare
Kim KK, Joseph JG, Ohno-Machado L
Comparison of consumers' views on electronic data sharing for healthcare and research.
The researchers surveyed California consumers to learn their views of privacy, security, and consent in electronic data sharing for healthcare and research together. They found considerable concern that health information exchanges will worsen privacy (40.3 percent) and security (42.5 percent). Consumers are in favor of electronic data sharing but elements of transparency are important: individual control, who has access, and the purpose for use of data.
AHRQ-funded; HS019913.
Citation: Kim KK, Joseph JG, Ohno-Machado L .
Comparison of consumers' views on electronic data sharing for healthcare and research.
J Am Med Inform Assoc 2015 Jul;22(4):821-30. doi: 10.1093/jamia/ocv014..
Keywords: Communication, Data, Electronic Health Records (EHRs), Health Information Exchange (HIE), Health Information Technology (HIT), Patient-Centered Healthcare