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Search All Research Studies
Topics
- (-) Data (4)
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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 DisplayedCohen GR, Jones DJ, Heeringa J
AHRQ Author: Furukawa MF, Miller D
Leveraging diverse data sources to identify and describe U.S. health care delivery systems.
Health care delivery systems are a growing presence in the U.S., yet research is hindered by the lack of universally agreed-upon criteria to denote formal systems. This study assesses available data sources to identify and describe systems, including system members and relationships among the members.
AHRQ-authored.
Citation: Cohen GR, Jones DJ, Heeringa J .
Leveraging diverse data sources to identify and describe U.S. health care delivery systems.
eGEMS 2017 Dec 15;5(3):9. doi: 10.5334/egems.200..
Keywords: Healthcare Delivery, Data, Health Services Research (HSR), System Design
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, Decision Making, Healthcare Delivery, Patient-Centered Healthcare, Patient-Centered Outcomes Research
Fleming C, Rich E, DesRoches C
Measuring changes in the economics of medical practice.
This paper explores current issues relevant to defining and measuring the inputs and outputs of physician practice. It reviews practice inputs and outputs as typically described in the literature on the economics of medical practice, and identifies the conceptual challenges for defining these inputs and outputs in a complex and evolving health care system.
AHRQ-funded; 23320095642WC; 23337033T.
Citation: Fleming C, Rich E, DesRoches C .
Measuring changes in the economics of medical practice.
J Gen Intern Med 2015 Aug;30 Suppl 3:S562-7. doi: 10.1007/s11606-015-3368-5..
Keywords: Healthcare Delivery, Health Systems, Practice Patterns, Data
Shenvi EC, Meeker D, Boxwala AA
Understanding data requirements of retrospective studies.
This study seeks to characterize the types and patterns of data usage from EHRs for clinical research. It found that studies used an average of 4.46 (range 1–12) data element types in the selection criteria and 6.44 (range 1–15) in the study variables. The most frequently used items (e.g., procedure, condition, medication) are often available in coded form in EHRs.
AHRQ-funded; HS019913.
Citation: Shenvi EC, Meeker D, Boxwala AA .
Understanding data requirements of retrospective studies.
Int J Med Inform 2015 Jan;84(1):76-84. doi: 10.1016/j.ijmedinf.2014.10.004..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Data, Healthcare Delivery