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Search All Research Studies
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- Cardiovascular Conditions (1)
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- (-) Comparative Effectiveness (9)
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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 9 of 9 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
Dagne GA, Brown CH, Howe G
Testing moderation in network meta-analysis with individual participant data.
The authors extended existing network methods for main effects to examining moderator effects. They further studied how the use of individual participant data may increase the sensitivity of network meta-analysis (NMA) for detecting moderator effects. They proposed a new NMA diagram and applied it to data from a classroom-based randomized study that involved two sub-trials, each comparing interventions that were contrasted with separate control groups.
AHRQ-funded; HS020263.
Citation: Dagne GA, Brown CH, Howe G .
Testing moderation in network meta-analysis with individual participant data.
Stat Med 2016 Jul 10;35(15):2485-502. doi: 10.1002/sim.6883.
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Keywords: Comparative Effectiveness, Data, Research Methodologies
Wang SV, Verpillat P, Rassen JA
Transparency and reproducibility of observational cohort studies using large healthcare databases.
The researchers explored the extent to which published pharmacoepidemiologic studies using commercially available databases could be reproduced by other investigators. Based on a nonsystematic sample of 38 descriptive or comparative safety/effectiveness cohort studies, they concludedc that an essential component of transparent and reproducible databases is more complete reporting of study implementation.
AHRQ-funded; HS022193.
Citation: Wang SV, Verpillat P, Rassen JA .
Transparency and reproducibility of observational cohort studies using large healthcare databases.
Clin Pharmacol Ther 2016 Mar;99(3):325-32. doi: 10.1002/cpt.329..
Keywords: Health Information Technology (HIT), Data, Research Methodologies, Comparative Effectiveness
Meeker D, Jiang X, Matheny ME
A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.
The authors’ objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features. They were able to implement massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared.
AHRQ-funded; HS019913.
Citation: Meeker D, Jiang X, Matheny ME .
A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.
J Am Med Inform Assoc 2015 Nov;22(6):1187-95. doi: 10.1093/jamia/ocv017..
Keywords: Communication, Comparative Effectiveness, Data, Health Information Technology (HIT), Policy, Research Methodologies
Ross ME, Kreider AR, Huang YS
Propensity score methods for analyzing observational data like randomized experiments: challenges and solutions for rare outcomes and exposures.
The researchers expanded upon an approach to the analysis of observational data sets that mimics a sequence of randomized studies by implementing propensity score models within each trial to achieve covariate balance, using weighting and matching. Challenges included a rare outcome, a rare exposure, substantial and important differences between exposure groups, and a very large sample size.
AHRQ-funded; HS018550.
Citation: Ross ME, Kreider AR, Huang YS .
Propensity score methods for analyzing observational data like randomized experiments: challenges and solutions for rare outcomes and exposures.
Am J Epidemiol 2015 Jun 15;181(12):989-95. doi: 10.1093/aje/kwu469..
Keywords: Comparative Effectiveness, Data, Research Methodologies
Brouwer ES, Moga DC, Eron JJ
Evaluating the incident user design in the HIV population: incident use versus naive?
Through linkage to a comprehensive HIV clinical cohort, the researchers aimed to quantify and describe the truly naïve patients in an incident use population identified in Medicaid administrative claims. In their sample, they found that 34 percent of the Medicaid incident users were naïve based on medical record abstraction of antiretroviral use.
AHRQ-funded; HS018731.
Citation: Brouwer ES, Moga DC, Eron JJ .
Evaluating the incident user design in the HIV population: incident use versus naive?
Pharmacoepidemiol Drug Saf 2015 Mar;24(3):297-300. doi: 10.1002/pds.3705..
Keywords: Human Immunodeficiency Virus (HIV), Research Methodologies, Comparative Effectiveness, Data, Medicaid
Neugebauer R, Schmittdiel JA, Zhu Z
High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions.
The authors described the application and performance of the hdPS algorithm to improve covariate selection in CER with time-varying interventions based on inverse probability weighting estimation and explored stabilization of the resulting estimates using Super Learning. Their evaluation was based on both the analysis of electronic health records data in a real-world CER study of adults with type 2 diabetes and a simulation study.
AHRQ-funded; 29020050016I.
Citation: Neugebauer R, Schmittdiel JA, Zhu Z .
High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions.
Stat Med 2015 Feb 28;34(5):753-81. doi: 10.1002/sim.6377..
Keywords: Comparative Effectiveness, Data, Research Methodologies
Li T, Vedula SS, Hadar N
Innovations in data collection, management, and archiving for systematic reviews.
The authors provide a step-by-step tutorial for collecting, managing, and archiving data for systematic reviews and suggest steps for developing rigorous data collection forms in the Systematic Review Data Repository to facilitate implementation of the methodological standards and expectations of the Institute of Medicine and other organizations.
AHRQ-funded; 290200710055I; 290201200012I.
Citation: Li T, Vedula SS, Hadar N .
Innovations in data collection, management, and archiving for systematic reviews.
Ann Intern Med. 2015 Feb 17;162(4):287-94. doi: 10.7326/M14-1603..
Keywords: Data, Comparative Effectiveness, Outcomes, Research Methodologies
Jalbert JJ, Ritchey ME, Mi X
Methodological considerations in observational comparative effectiveness research for implantable medical devices: an epidemiologic perspective.
This article discusses some of the most salient issues encountered in conducting comparative effectiveness research on implantable devices. Included in this discussion are special methodological considerations regarding the use of data sources, exposure and outcome definitions, timing of exposure, and sources of bias.
AHRQ-funded; 29020050016; HS017731
Citation: Jalbert JJ, Ritchey ME, Mi X .
Methodological considerations in observational comparative effectiveness research for implantable medical devices: an epidemiologic perspective.
Am J Epidemiol. 2014 Nov 1;180(9):949-58. doi: 10.1093/aje/kwu206..
Keywords: Comparative Effectiveness, Research Methodologies, Data