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Topics
- Cardiovascular Conditions (1)
- Clinician-Patient Communication (1)
- Communication (1)
- Comparative Effectiveness (4)
- (-) Data (14)
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- (-) Patient-Centered Outcomes Research (14)
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- Quality Indicators (QIs) (1)
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- Research Methodologies (5)
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- Shared Decision Making (3)
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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 14 of 14 Research Studies DisplayedHsu YJ, Kosinski AS, Wallace AS
Using a society database to evaluate a patient safety collaborative: the Cardiovascular Surgical Translational Study.
The authors assessed the utility of using external databases for quality improvement (QI) evaluations in the context of an innovative QI collaborative aimed to reduce three infections and improve patient safety across the cardiac surgery service line. They compared changes in each outcome between 15 intervention hospitals and 52 propensity score-matched hospitals, and found that improvement trends in several outcomes among the studied intervention hospitals were not statistically different from those in comparison hospitals. They conclude that using external databases may permit comparative effectiveness assessment by providing concurrent comparison groups, additional outcome measures, and longer follow-up.
AHRQ-funded; HS019934.
Citation: Hsu YJ, Kosinski AS, Wallace AS .
Using a society database to evaluate a patient safety collaborative: the Cardiovascular Surgical Translational Study.
J Comp Eff Res 2019 Jan;8(1):21-32. doi: 10.2217/cer-2018-0051..
Keywords: Patient Safety, Quality Improvement, Quality Indicators (QIs), Quality of Care, Surgery, Cardiovascular Conditions, Comparative Effectiveness, Data, Hospitals, Research Methodologies, Patient-Centered Outcomes Research
Ghaferi 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, Shared 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.
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Keywords: Data, Patient-Centered Outcomes Research, Research Methodologies
Angraal S, Ross JS, Dhruva SS
Merits of data sharing: The Digitalis Investigation Group Trial.
This letter discusses the merits of data sharing, such as its importance in maximizing what can be learned from clinical trials. The letter describes The DIG (Digitalis Investigation Group) trial as an ideal o assess the effects of data sharing.
AHRQ-funded; HS023000.
Citation: Angraal S, Ross JS, Dhruva SS .
Merits of data sharing: The Digitalis Investigation Group Trial.
J Am Coll Cardiol 2017 Oct 3;70(14):1825-27. doi: 10.1016/j.jacc.2017.07.786..
Keywords: Data, Patient-Centered Outcomes Research, Research Methodologies
Ong TC, Kahn MG, Kwan BM
Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.
The researchers designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code. Their results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets.
AHRQ-funded; HS019908; HS022956.
Citation: Ong TC, Kahn MG, Kwan BM .
Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.
BMC Med Inform Decis Mak 2017 Sep 13;17(1):134. doi: 10.1186/s12911-017-0532-3.
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Keywords: Comparative Effectiveness, Data, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient-Centered Outcomes Research
Ong T, Pradhananga R, Holve E
A framework for classification of electronic health data extraction-transformation-loading challenges in data network participation.
The researchers conducted key-informant interviews with data partner representatives to survey the Extract, Transform, Load (ETL) process challenges faced in clinical data research networks (CDRNs) and registries. The paper concluded that overcoming ETL technical challenges requires significant investments in a broad array of information technologies and human resources. Identifying these technical obstacles can inform optimal resource allocation to minimize the barriers and cost of entry for new data partners into extant networks, which in turn can expand data networks' inclusiveness and diversity.
AHRQ-funded; HS019564.
Citation: Ong T, Pradhananga R, Holve E .
A framework for classification of electronic health data extraction-transformation-loading challenges in data network participation.
eGEMS 2017 Jun 13;5(1):10. doi: 10.5334/egems.222..
Keywords: Comparative Effectiveness, Data, Health Information Technology (HIT), Patient-Centered Outcomes Research, Registries
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
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.
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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.
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Keywords: Data, Shared 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
Pine M, Kowlessar NM, Salemi JL
Enhancing clinical content and race/ethnicity data in statewide hospital administrative databases: obstacles encountered, strategies adopted, and lessons learned.
Eight grant teams used Agency for Healthcare Research and Quality infrastructure development research grants to enhance the clinical content of and improve race/ethnicity identifiers in statewide all-payer hospital administrative databases. The authors concluded that creation of enhanced administrative databases to support comparative effectiveness research is difficult, particularly in the face of numerous challenges with recruiting data partners such as competing demands on information technology resources.
AHRQ-funded
Citation: Pine M, Kowlessar NM, Salemi JL .
Enhancing clinical content and race/ethnicity data in statewide hospital administrative databases: obstacles encountered, strategies adopted, and lessons learned.
Health Serv Res 2015 Aug;50 Suppl 1:1300-21. doi: 10.1111/1475-6773.12330..
Keywords: Healthcare Cost and Utilization Project (HCUP), Comparative Effectiveness, Patient-Centered Outcomes Research, Data
Wang HE, Donnelly JP, Shapiro NI
Hospital variations in severe sepsis mortality.
The authors characterized variations in severe sepsis mortality between hospitals in the United States. They used hospital discharge data from the University HealthSystem Consortium and found variations in institutional severe sepsis observed mortality rates and observed-to-expected mortality ratios.
AHRQ-funded; HS019465; HS013852.
Citation: Wang HE, Donnelly JP, Shapiro NI .
Hospital variations in severe sepsis mortality.
Am J Med Qual 2015 Jul-Aug;30(4):328-36. doi: 10.1177/1062860614534461.
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Keywords: Data, Hospitals, Mortality, Patient-Centered Outcomes Research, Sepsis