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AHRQ Research Studies Date
Topics
- Communication (1)
- Comparative Effectiveness (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 23 of 23 Research Studies DisplayedCohen KB, Goss FR, Zweigenbaum P
Translational morphosyntax: distribution of negation in clinical records and biomedical journal articles.
This paper describes the distribution of negation in two types of biomedical texts: scientific journal articles and progress notes. Two types of negation are examined: explicit negation at the syntactic level and affixal negation at the sub-word level. The data show that the distribution of negation is significantly different in the two document types.
AHRQ-funded; HS024541.
Citation: Cohen KB, Goss FR, Zweigenbaum P .
Translational morphosyntax: distribution of negation in clinical records and biomedical journal articles.
Stud Health Technol Inform 2017;245:346-50.
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Keywords: Data, Health Information Technology (HIT), Research Methodologies
Ji X, Machiraju R, Ritter A
Visualizing article similarities via sparsified article network and map projection for systematic reviews.
In this study, the authors visualized article similarities to extend its utilization in practical settings for SR researchers, aiming to promote human comprehension of article distributions and hidden patterns. To prompt an effective visualization in an interpretable, intuitive, and scalable way, they implemented a graph-based network visualization with three network sparsification approaches and a distance-based map projection via dimensionality reduction.
AHRQ-funded; HS025047.
Citation: Ji X, Machiraju R, Ritter A .
Visualizing article similarities via sparsified article network and map projection for systematic reviews.
Stud Health Technol Inform 2017;245:422-26.
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Keywords: Data, Evidence-Based Practice, Health Services Research (HSR), Research Methodologies
Wallace BC, Noel-Storr A, Marshall IJ
Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.
Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. In this study, the investigators aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML.
AHRQ-funded; HS025024.
Citation: Wallace BC, Noel-Storr A, Marshall IJ .
Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.
J Am Med Inform Assoc 2017 Nov 1;24(6):1165-68. doi: 10.1093/jamia/ocx053..
Keywords: Data, 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
Guise JM, Chang C, Butler M
AHRQ Author: Chang C
AHRQ series on complex intervention systematic reviews-paper 1: an introduction to a series of articles that provide guidance and tools for reviews of complex interventions.
The seven articles in this series reflect and distill the discussions from the in-person meeting and follow-up workgroups on tools and approaches to systematic reviews of complex interventions. The first three articles address how systematic reviews for complex interventions are conceptualized and operationalized for the protocol. The next two articles discuss how to choose appropriate analytic methods to implement analyses of complex interventions. The final two articles describe proposed reporting elements for systematic reviews of complex interventions.
AHRQ-authored; AHRQ-funded; 290201200004C; 290201200016I; 290201500011I.
Citation: Guise JM, Chang C, Butler M .
AHRQ series on complex intervention systematic reviews-paper 1: an introduction to a series of articles that provide guidance and tools for reviews of complex interventions.
J Clin Epidemiol 2017 Oct;90:6-10. doi: 10.1016/j.jclinepi.2017.06.011.
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Keywords: Data, Evidence-Based Practice, Guidelines, Research Methodologies
Kelly MP, Noyes J, Kane RL
AHRQ Author: Chang C
AHRQ series on complex intervention systematic reviews-paper 2: defining complexity, formulating scope, and questions.
This paper builds on concepts introduced in paper 1 of this series. It describes the methodological, practical, and philosophical challenges and potential approaches for formulating the questions and scope of systematic reviews of complex interventions. Furthermore, it discusses the use of theory to help organize reviews of complex interventions.
AHRQ-authored; AHRQ-funded; 290-2012-00004-C; 290-2015-00008I; 290-2015-00011I.
Citation: Kelly MP, Noyes J, Kane RL .
AHRQ series on complex intervention systematic reviews-paper 2: defining complexity, formulating scope, and questions.
J Clin Epidemiol 2017 Oct;90:11-18. doi: 10.1016/j.jclinepi.2017.06.012.
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Keywords: Data, Evidence-Based Practice, Guidelines, Research Methodologies
Viswanathan M, McPheeters ML, Murad MH
AHRQ series on complex intervention systematic reviews-paper 4: selecting analytic approaches.
This article addresses the uncertainty that systematic reviewers face in selecting methods for reviews of complex interventions. Specifically, it lays out parameters for systematic reviewers to consider when selecting analytic approaches that best answer the questions at hand and suggests analytic techniques that may be appropriate in different circumstances.
AHRQ-funded; 290201200004C.
Citation: Viswanathan M, McPheeters ML, Murad MH .
AHRQ series on complex intervention systematic reviews-paper 4: selecting analytic approaches.
J Clin Epidemiol 2017 Oct;90:28-36. doi: 10.1016/j.jclinepi.2017.06.014.
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Keywords: Data, Evidence-Based Practice, Guidelines, Research Methodologies
Guise JM, Butler M, Chang C
AHRQ Author: Chang C
AHRQ series on complex intervention systematic reviews-paper 7: PRISMA-CI elaboration and explanation.
The Complex Interventions Methods Workgroup developed an extension to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Complex Interventions (PRISMA-CI). Following the guidance for Preferred Reporting Items for Systematic Reviews and Meta-Analysis extensions, this Explanation and Elaboration (EE) document accompanies the PRISMA-CI checklist to promote consistency in reporting of systematic reviews of complex interventions.
AHRQ-authored; AHRQ-funded; 290201200004C; 290201200016I; 290201500011I.
Citation: Guise JM, Butler M, Chang C .
AHRQ series on complex intervention systematic reviews-paper 7: PRISMA-CI elaboration and explanation.
J Clin Epidemiol 2017 Oct;90:51-58. doi: 10.1016/j.jclinepi.2017.06.017.
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Keywords: Data, Evidence-Based Practice, Guidelines, Research Methodologies
Bashir R, Bourgeois FT, Dunn AG
A systematic review of the processes used to link clinical trial registrations to their published results.
Studies measuring the completeness and consistency of trial registration and reporting rely on linking registries with bibliographic databases. In this systematic review, the researchers quantified the processes used to identify these links. In 43 studies that examined cohorts of registry entries, 24 used automatic and manual processes to find articles; 3 only automatic; and 11 only manual (5 did not specify).
AHRQ-funded; HS024798.
Citation: Bashir R, Bourgeois FT, Dunn AG .
A systematic review of the processes used to link clinical trial registrations to their published results.
Syst Rev 2017 Jul 3;6(1):123. doi: 10.1186/s13643-017-0518-3.
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Keywords: Evidence-Based Practice, Research Methodologies, Data
Cefalu M, Dominici F, Arvold N
Model averaged double robust estimation.
Researchers estimating causal effects are increasingly challenged with decisions on how to best control for a potentially high-dimensional set of confounders. Typically, a single propensity score model is chosen and used to adjust for confounding. The researchers propose a practical and generalizable approach that overcomes limitations through the use of model averaging. They develop and evaluate this approach in the context of double robust estimation.
AHRQ-funded; HS021991.
Citation: Cefalu M, Dominici F, Arvold N .
Model averaged double robust estimation.
Biometrics 2017 Jun;73(2):410-21. doi: 10.1111/biom.12622.
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Keywords: Data, Research Methodologies
Mirel LB, Chowdhury SR
AHRQ Author: Chowdhury SR
Using linked survey paradata to improve sampling strategies in the Medical Expenditure Panel Survey.
The main objective of this article is to examine how paradata from a prior survey can be used in developing a sampling scheme in a subsequent survey. A framework for optimal allocation of the sample in substrata formed for this purpose is presented and evaluated for the relative effectiveness of alternative substratification schemes.
AHRQ-authored.
Citation: Mirel LB, Chowdhury SR .
Using linked survey paradata to improve sampling strategies in the Medical Expenditure Panel Survey.
J Off Stat 2017 Jun;33(2):367–83.
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Keywords: Data, Medical Expenditure Panel Survey (MEPS), Research Methodologies
Paynter R, Banez LL, Erinoff E
AHRQ Author: Banez LL
Commentary on EPC methods: an exploration of the use of text-mining software in systematic reviews.
This commentary summarizes a recent peer-reviewed Agency for Healthcare Research and Quality (AHRQ) white paper EPC Methods: An Exploration of the Use of Text-Mining Software in Systematic Reviews followed by a discussion of current and future issues.
AHRQ-authored.
Citation: Paynter R, Banez LL, Erinoff E .
Commentary on EPC methods: an exploration of the use of text-mining software in systematic reviews.
J Clin Epidemiol 2017 Apr;84:33-36. doi: 10.1016/j.jclinepi.2016.11.019..
Keywords: Data, Evidence-Based Practice, Research Methodologies
Hartling L, Guise JM, Kato E
AHRQ Author: Kato, E, Berliner E
A taxonomy of rapid reviews links report types and methods to specific decision-making contexts.
The researchers described characteristics of rapid reviews and examined the impact of methodological variations on their reliability and validity. They concluded that rapid products have tremendous methodological variation and that categorization based on timeframe or type of synthesis reveals patterns. The similarity across rapid products lies in the close relationship with the end user to meet time-sensitive decision-making needs.
AHRQ-authored; AHRQ-funded; 290201200013I; 290201200010I; 290201200011I; 290201200015I; 290201200007I; 290201200004C.
Citation: Hartling L, Guise JM, Kato E .
A taxonomy of rapid reviews links report types and methods to specific decision-making contexts.
J Clin Epidemiol 2015 Dec;68(12):1451-62.e3. doi: 10.1016/j.jclinepi.2015.05.036.
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Keywords: Decision Making, Evidence-Based Practice, Data, Research Methodologies
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
Haukoos JS, Lewis RJ
The propensity score.
The authors discuss studies by Rozé et al and Huybrechts et al that used propensity score matching and propensity score stratification, respectively. They argue that although both methods are more valid in terms of balancing study groups than simple matching or stratification based on baseline characteristics, they vary in their ability to minimize bias. In general, propensity score matching minimizes bias to a greater extent than propensity score stratification.
AHRQ-funded; HS021749.
Citation: Haukoos JS, Lewis RJ .
The propensity score.
JAMA 2015 Oct 20;314(15):1637-8. doi: 10.1001/jama.2015.13480..
Keywords: Research Methodologies, Data, Risk
Wang C, Dominici F, Parmigiani G
Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models.
The authors propose and evaluate a Bayesian method to estimate average causal effects in studies with a large number of potential confounders, relatively few observations, likely interactions between confounders and the exposure of interest, and uncertainty on which confounders and interaction terms should be included. Their method is applicable across all exposures and outcomes that can be handled through generalized linear models.
AHRQ-funded; HS021991.
Citation: Wang C, Dominici F, Parmigiani G .
Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models.
Biometrics 2015 Sep;71(3):654-65. doi: 10.1111/biom.12315.
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Keywords: Data, Research Methodologies
Thiel DB, Platt J, Platt T
Testing an online, dynamic consent portal for large population biobank research.
Michigan's BioTrust for Health contains over 4 million samples collected without written consent. Participant-centric initiatives are IT tools that hold great promise to address the consent challenges in biobank research. The authors created and pilot tested a dynamic informed consent simulation focusing on consent for research. Pilot testers raised concerns about the process of identity verification and appeared to have little experience with sharing health information online. The authors recommended applying online, dynamic approaches to address the consent challenges raised by biobanks with legacy sample collections.
AHRQ-funded; HS000053.
Citation: Thiel DB, Platt J, Platt T .
Testing an online, dynamic consent portal for large population biobank research.
Public Health Genomics 2015;18(1):26-39. doi: 10.1159/000366128.
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Keywords: Data, Newborns/Infants, Research Methodologies, Screening
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
Kozlowski SWJ, Chao GT, Chang C-H
https://www.routledge.com/Big-Data-at-Work-The-Data-Science-Revolution-and-Organizational-Psychology/Tonidandel-King-Cortina/p/book/9781848725829
Using big data to advance the science of team effectiveness.
The authors discuss the longstanding treatment of team processes as static constructs rather than as dynamic processes per se. They then highlight research design issues that need to be considered in any effort to directly observe, assess, and capture teamwork process dynamics. Finally, they explain how researchers can directly assess and capture team process dynamics using illustrations from three ongoing projects.
AHRQ-funded; HS020295; HS022458.
Citation: Kozlowski SWJ, Chao GT, Chang C-H .
Using big data to advance the science of team effectiveness.
In: Tonidandel S, King E, Cortina J, editors. Big Data at Work: The Data Science Revolution and Organizational Psychology. New York: Routledge; 2015. p. 272-309, chapter 10..
Keywords: Teams, Research Methodologies, Data
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