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
Topics
- Clinician-Patient Communication (1)
- Communication (1)
- (-) Data (7)
- Decision Making (2)
- Disparities (2)
- Electronic Health Records (EHRs) (1)
- Healthcare Delivery (1)
- Health Information Technology (HIT) (1)
- Medicare (1)
- Nursing (1)
- Outcomes (1)
- Patient-Centered Healthcare (2)
- (-) Patient-Centered Outcomes Research (7)
- Registries (2)
- Research Methodologies (3)
- Surgery (1)
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 7 of 7 Research Studies DisplayedGhaferi AA, Dimick JB
Practical guide to surgical data sets: Medicare claims data.
In this article, the authors discuss pros and cons of Medicare data and explore commonly studied categories using this data (health policy evaluation, comparative effectiveness research, and outcome variations). They conclude that it is important to frame questions carefully and to use appropriate methods to ensure scientific rigor.
AHRQ-funded; HS023621; HS024403.
Citation: Ghaferi AA, Dimick JB .
Practical guide to surgical data sets: Medicare claims data.
JAMA Surg 2018 Jul;153(7):677-78. doi: 10.1001/jamasurg.2018.0489..
Keywords: Medicare, Data, Surgery, Patient-Centered Outcomes Research, Research Methodologies
Arcia 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, Decision Making, Patient-Centered Healthcare, Patient-Centered Outcomes Research, Outcomes, Data
Woloshin S, Schwartz LM, Bagley PJ
Characteristics of interim publications of randomized clinical trials and comparison with final publications.
The authors describe the characteristics of interim publications from ongoing randomized trials and compare their consistency and prominence with those of final publications. They conclude that interim publication should be limited to protocol prespecified analyses performed when enough outcomes occurred for statistical stability and to scenarios least likely to undermine trial integrity.
AHRQ-funded; HS024075.
Citation: Woloshin S, Schwartz LM, Bagley PJ .
Characteristics of interim publications of randomized clinical trials and comparison with final publications.
JAMA 2018 Jan 23;319(4):404-06. doi: 10.1001/jama.2017.20653.
.
.
Keywords: Data, Patient-Centered Outcomes Research, Research Methodologies
Bakken S, Reame N
http://www.ingentaconnect.com/content/springer/arnr/2016/00000034/00000001/art00013
The promise and potential perils of big data for advancing symptom management research in populations at risk for health disparities.
The purposes of this chapter are to (a) briefly summarize the current drivers for the use of big data in research; (b) describe the promise of big data and associated data science methods for advancing symptom management research; and (c) explicate the potential perils of big data and data science from the perspective of the ethical principles of autonomy, beneficence, and justice.
AHRQ-funded; HS022961
Citation: Bakken S, Reame N .
The promise and potential perils of big data for advancing symptom management research in populations at risk for health disparities.
Annu Rev Nurs Res 2016;34:247-60. doi: 10.1891/0739-6686.34.247..
Keywords: Data, Disparities, Nursing, Patient-Centered Outcomes Research
Cato KD, Bockting W, Larson E
Did I tell you that? Ethical issues related to using computational methods to discover non-disclosed patient characteristics.
Using the Belmont Report's principles of respect for persons, beneficence, and justice as a framework, the authors examined the ethical issues posed by electronic phenotyping. Ethical issues identified include the ability of the patient to consent for the use of their information, the ability to suppress pediatric information, and ensuring that the potential benefits justify the risks of harm to patients.
AHRQ-funded; HS022961.
Citation: Cato KD, Bockting W, Larson E .
Did I tell you that? Ethical issues related to using computational methods to discover non-disclosed patient characteristics.
J Empir Res Hum Res Ethics 2016 Jul;11(3):214-9. doi: 10.1177/1556264616661611.
.
.
Keywords: Clinician-Patient Communication, Data, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient-Centered Outcomes Research, Registries, Research Methodologies
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.
.
.
Keywords: Data, Decision Making, Healthcare Delivery, Patient-Centered Healthcare, Patient-Centered Outcomes Research
Bakken S, Reame N
The promise and potential perils of big data for advancing symptom management research in populations at risk for health disparities.
The purposes of this chapter are to (a) briefly summarize the current drivers for the use of big data in research; (b) describe the promise of big data and associated data science methods for advancing symptom management research; and (c) explicate the potential perils of big data and data science from the perspective of the ethical principles of autonomy, beneficence, and justice.
AHRQ-funded; HS022961.
Citation: Bakken S, Reame N .
The promise and potential perils of big data for advancing symptom management research in populations at risk for health disparities.
Annu Rev Nurs Res 2016;34:247-60. doi: 10.1891/0739-6686.34.247..
Keywords: Disparities, Data, Patient-Centered Outcomes Research, Registries