National Healthcare Quality and Disparities Report
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Topics
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- (-) Data (174)
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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
76 to 100 of 174 Research Studies DisplayedGovindan S, Chopra V, Iwashyna TJ
Do clinicians understand quality metric data? An evaluation in a Twitter-derived sample.
The researchers assessed clinician comprehension of central line-associated blood stream infection (CLABSI) quality metric data. It found that the mean percentage of correct answers was 61 percent. Overall, doctor performance was better than performance by nurses and other respondents. In basic numeracy, mean percent correct was 82 percent. For risk-adjustment numeracy, the mean percent correct was 70 percent.
AHRQ-funded; HS022835.
Citation: Govindan S, Chopra V, Iwashyna TJ .
Do clinicians understand quality metric data? An evaluation in a Twitter-derived sample.
J Hosp Med 2017 Jan;12(1):18-22.
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Keywords: Central Line-Associated Bloodstream Infections (CLABSI), Data, Quality of Care, Provider Performance, Social Media
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
Sauser Zachrison K, Iwashyna TJ, Gebremariam A
Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.
The authors' primary objective was to determine to what extent, and under what conditions, the generalized estimating equation (GEE) approach recreate the actual dynamics in an agent-based model. They found that the GEE models have sensitivity and specificity for determining the presence or absence of network influence, but have little ability to distinguish whether or not homophily is present.
AHRQ-funded; HS024561.
Citation: Sauser Zachrison K, Iwashyna TJ, Gebremariam A .
Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.
BMC Med Res Methodol 2016 Dec 28;16(1):174. doi: 10.1186/s12874-016-0274-4.
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Keywords: Data
Wilcox HC, Kharrazi H, Wilson RF
Data linkage strategies to advance youth suicide prevention: a systematic review for a National Institutes of Health Pathways to Prevention Workshop.
This review sought to identify and describe data systems that can be linked to data from prevention studies to advance youth suicide prevention research. It concluded that there is untapped potential to evaluate and enhance suicide prevention efforts by linking suicide prevention data with existing data systems. However, sparse availability of data dictionaries and lack of adherence to standard data elements limit this potential.
AHRQ-funded; 290201200007I.
Citation: Wilcox HC, Kharrazi H, Wilson RF .
Data linkage strategies to advance youth suicide prevention: a systematic review for a National Institutes of Health Pathways to Prevention Workshop.
Ann Intern Med 2016 Dec 6;165(11):779-85. doi: 10.7326/m16-1281.
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Keywords: Behavioral Health, Children/Adolescents, Data, Evidence-Based Practice, Prevention
Yoon S, Co MC, Jr., Suero-Tejeda N
A data mining approach for exploring correlates of self-reported comparative physical activity levels of urban Latinos.
The authors applied data mining techniques to a community-based behavioral dataset to build prediction models to gain insights about physical activity levels as the foundation for future interventions for urban Latinos. They identified environment factors and psychological factors. They concluded that the data mining methods were useful to build prediction models to gain insights about perceptions of physical activity behavior as compared to peers.
AHRQ-funded; HS019853; HS022961.
Citation: Yoon S, Co MC, Jr., Suero-Tejeda N .
A data mining approach for exploring correlates of self-reported comparative physical activity levels of urban Latinos.
Stud Health Technol Inform 2016;225:553-7.
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Keywords: Data, Lifestyle Changes, Racial and Ethnic Minorities, Racial and Ethnic Minorities, Urban Health
Khatibzadeh S, Saheb Kashaf M, Micha R
A global database of food and nutrient consumption.
The authors conducted an empirical assessment of dietary intakes in order for evidence-based policy-making to address global health challenges. They derived The Global Dietary Database, which combines broad global coverage with estimates of food and nutrient consumption by age, sex and time. They believe that these data provide an empirical basis for global dietary surveillance, policy-making and priority setting to address diet-related burdens of disease.
AHRQ-funded; HS000062.
Citation: Khatibzadeh S, Saheb Kashaf M, Micha R .
A global database of food and nutrient consumption.
Bull World Health Organ 2016 Dec;94(12):931-34. doi: 10.2471/blt.15.156323.
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Keywords: Data, Evidence-Based Practice, Nutrition, Policy, Public Health
Roosan D, Samore M, Jones M
Big-data based decision-support systems to improve clinicians' cognition.
This study focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. It found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records.
AHRQ-funded; HS023349.
Citation: Roosan D, Samore M, Jones M .
Big-data based decision-support systems to improve clinicians' cognition.
IEEE Int Conf Healthc Inform 2016;2016:285-88. doi: 10.1109/ichi.2016.39.
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Keywords: Clinical Decision Support (CDS), Shared Decision Making, Data, Electronic Health Records (EHRs)
Groeneveld PW, Rumsfeld JS
Can big data fulfill its promise?
This article discusses the pros and cons of using big data analytics in healthcare. The authors note that the rise of big data analytics in health care settings has promise. However, they assert that it is critical to recognize that the fundamental pitfalls of observational data analysis cannot be ignored, and in fact the risks of such pitfalls demand rigorous scientific testing and novel methods for peer review of big data analytic models.
AHRQ-funded; HS023615.
Citation: Groeneveld PW, Rumsfeld JS .
Can big data fulfill its promise?
Circ Cardiovasc Qual Outcomes 2016 Nov;9(6):679-82. doi: 10.1161/circoutcomes.116.003097..
Keywords: Data, Health Services Research (HSR)
Riehle-Colarusso TJ, Bergersen L, Broberg CS
AHRQ Author: Gray DT
Databases for congenital heart defect public health studies across the lifespan.
Key experts and stakeholders have identified public health knowledge gaps about congenital heart defects (CHDs). These gaps, and strategies to address them, formed the basis of a CHD public health science agenda. The strategies included leveraging information in existing databases to examine the epidemiology, health outcomes, and health service utilization of the CHD population. The authors discuss this complex constellation of databases, their relative characteristics and possible linkages.
AHRQ-authored.
Citation: Riehle-Colarusso TJ, Bergersen L, Broberg CS .
Databases for congenital heart defect public health studies across the lifespan.
J Am Heart Assoc 2016 Oct 26;5(11). doi: 10.1161/jaha.116.004148.
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Keywords: Cardiovascular Conditions, Public Health, Data
Folch DC, Arribas-Bel D, Koschinsky J
Spatial variation in the quality of American Community Survey estimates.
The authors use a series of multivariate spatial regression models to describe the patterns of association between uncertainty in estimates and economic, demographic, and geographic factors, controlling for the number of responses in the American Community Survey. They find that these demographic and geographic patterns in estimate quality persist even after accounting for the number of responses, and they present advice for data users and potential solutions to the challenges identified.
AHRQ-funded; HS021752.
Citation: Folch DC, Arribas-Bel D, Koschinsky J .
Spatial variation in the quality of American Community Survey estimates.
Demography 2016 Oct;53(5):1535-54. doi: 10.1007/s13524-016-0499-1.
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Keywords: Data, Research Methodologies, Social Determinants of Health
Murphy DR, Meyer AN, Bhise V
Computerized triggers of big data to detect delays in follow-up of chest imaging results.
A "trigger" algorithm was used to identify delays in follow-up of abnormal chest imaging results in a large national clinical data warehouse of electronic health record (EHR) data. In this study, the authors applied a trigger in a repository hosting EHR data from all Department of Veterans Affairs health-care facilities and analyzed data from seven facilities. The investigators concluded that application of triggers on "big" EHR data may aid in identifying patients experiencing delays in diagnostic evaluation of chest imaging results suspicious for malignancy.
Citation: Murphy DR, Meyer AN, Bhise V .
Computerized triggers of big data to detect delays in follow-up of chest imaging results.
Chest 2016 Sep;150(3):613-20. doi: 10.1016/j.chest.2016.05.001..
Keywords: Imaging, Electronic Health Records (EHRs), Health Information Technology (HIT), Data, Diagnostic Safety and Quality, Cancer
Fu R, Holmer HK
Change score or follow-up score? Choice of mean difference estimates could impact meta-analysis conclusions.
This study assessed the impact of using change score vs. follow-up score on the conclusions of meta-analyses. It concluded that using the change vs. the follow-up score could lead to important discrepancies in conclusions. Sensitivity analyses should be conducted to check the robustness of results to the choice of mean difference estimates.
AHRQ-funded; 290200710057I.
Citation: Fu R, Holmer HK .
Change score or follow-up score? Choice of mean difference estimates could impact meta-analysis conclusions.
J Clin Epidemiol 2016 Aug;76:108-17. doi: 10.1016/j.jclinepi.2016.01.034.
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Keywords: Research Methodologies, Data, Outcomes
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
Colantonio LD, Kent ST, Kilgore ML
Agreement between Medicare pharmacy claims, self-report, and medication inventory for assessing lipid-lowering medication use.
This paper analyzed the agreement between Medicare claims for lipid-lowering medication (LLM) and LLM use. Many Medicare beneficiaries reporting LLM use or having LLMs in a medication inventory have no claims for these medications.
AHRQ-funded; HS018517.
Citation: Colantonio LD, Kent ST, Kilgore ML .
Agreement between Medicare pharmacy claims, self-report, and medication inventory for assessing lipid-lowering medication use.
Pharmacoepidemiol Drug Saf 2016 Jul;25(7):827-35. doi: 10.1002/pds.3970.
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Keywords: Medicare, Medication, Elderly, Racial and Ethnic Minorities, Data
Richesson RL, Sun J, Pathak J
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
The authors sought to use electronic health records data to advance understanding of disease risk and drug response, and to support the practice of precision medicine on a national scale. They found that machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, as it comes from data rather than experts. They suggested that research networks and phenotype developers cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and modernize biomedical research.
AHRQ-funded; HS023921; HS023077.
Citation: Richesson RL, Sun J, Pathak J .
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
Artif Intell Med 2016 Jul;71:57-61. doi: 10.1016/j.artmed.2016.05.005.
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Keywords: Data, Electronic Health Records (EHRs), Genetics, Patient-Centered Healthcare
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
Raebel MA, Shetterly S, Lu CY
Methods for using clinical laboratory test results as baseline confounders in multi-site observational database studies when missing data are expected.
The purpose of this paper was to quantify missing baseline laboratory results, assess predictors of missingness, and examine performance of missing data methods. The researchers used the Mini-Sentinel Distributed Database to select three exposure-outcome scenarios with laboratory results as baseline confounders. They found that missing data methods performed similarly.
AHRQ-funded; HS023898.
Citation: Raebel MA, Shetterly S, Lu CY .
Methods for using clinical laboratory test results as baseline confounders in multi-site observational database studies when missing data are expected.
Pharmacoepidemiol Drug Saf 2016 Jul;25(7):798-814. doi: 10.1002/pds.4015.
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Keywords: Adverse Drug Events (ADE), Blood Thinners, Data, Diagnostic Safety and Quality, Medication
Roosan D, Del Fiol G, Butler J
Feasibility of population health analytics and data visualization for decision support in the infectious diseases domain: a pilot study.
The objectives of this study were: 1) to explore the feasibility of extracting and displaying population-based information from an actual clinical population's database records, 2) to explore specific design features for improving population display, 3) to explore perceptions of population information displays, and 4) to explore the impact of population information display on cognitive outcomes. It concluded that a population database has great potential for reducing complexity and uncertainty in medicine to improve clinical care.
AHRQ-funded; HS023349.
Citation: Roosan D, Del Fiol G, Butler J .
Feasibility of population health analytics and data visualization for decision support in the infectious diseases domain: a pilot study.
Appl Clin Inform 2016 Jun 29;7(2):604-23. doi: 10.4338/aci-2015-12-ra-0182.
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Keywords: Clinical Decision Support (CDS), Data, Shared Decision Making, Infectious Diseases, Public Health
Vock DM, Wolfson J, Bandyopadhyay S
Adapting machine learning techniques to censored time-to-event health record data: a general-purpose approach using inverse probability of censoring weighting.
In this paper, the authors present a general-purpose approach to account for right-censored outcomes using inverse probability of censoring weighting (IPCW). They illustrate how IPCW can easily be incorporated into a number of existing machine learning algorithms used to mine big health care data including Bayesian networks, k-nearest neighbors, decision trees, and generalized additive models.
AHRQ-funded; HS017622.
Citation: Vock DM, Wolfson J, Bandyopadhyay S .
Adapting machine learning techniques to censored time-to-event health record data: a general-purpose approach using inverse probability of censoring weighting.
J Biomed Inform 2016 Jun;61:119-31. doi: 10.1016/j.jbi.2016.03.009.
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Keywords: Data, Electronic Health Records (EHRs), Health Information Technology (HIT)
Terza JV
Inference using sample means of parametric nonlinear data transformations.
AHRQ-funded; HS017434.
Citation: Terza JV .
Inference using sample means of parametric nonlinear data transformations.
Health Serv Res 2016 Jun;51(3):1109-13. doi: 10.1111/1475-6773.12494.
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Keywords: Research Methodologies, Health Services Research (HSR), Data
Sandmeyer B, Fraser I
AHRQ Author: Sandmeyer B
New evidence on what works in effective public reporting.
The authors describe the current state of the public reporting field and provide guidance to public report producers based on the evidence. They concluded that public reports have advanced greatly in recent years, but there remains much room for improvement. They recommend that report producers should continually evaluate their reports and apply the latest evidence to maximize their usefulness and impact.
AHRQ-authored.
Citation: Sandmeyer B, Fraser I .
New evidence on what works in effective public reporting.
Health Serv Res 2016 Jun;51(Suppl 2):1159-66. doi: 10.1111/1475-6773.12502.
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Keywords: Data, Provider Performance, Public Reporting
Lee SJ, Grobe JE, Tiro JA
Assessing race and ethnicity data quality across cancer registries and EMRs in two hospitals.
The objective of this study was to characterize the quality of race/ethnicity data collection efforts. The authors assessed race and ethnicity data quality across cancer registries and electronic medical records in two hospitals. Their findings suggested that high-quality race/ethnicity data are attainable. Many of the "errors" in race/ethnicity data were caused by missing or "Unknown" data values.
AHRQ-funded; HS022418.
Citation: Lee SJ, Grobe JE, Tiro JA .
Assessing race and ethnicity data quality across cancer registries and EMRs in two hospitals.
J Am Med Inform Assoc 2016 May;23(3):627-34. doi: 10.1093/jamia/ocv156..
Keywords: Cancer, Data, Electronic Health Records (EHRs), Health Information Technology (HIT), Hospitals, Racial and Ethnic Minorities, Registries
Olsen MA, Young-Xu Y, Stwalley D
The burden of Clostridium difficile infection: estimates of the incidence of CDI from U.S. administrative databases.
The researchers used comparable methods with multiple administrative databases to compare the incidence of clostridium difficile infection (CDI) in older and younger persons in the United States. They found that the incidence of CDI was 10-fold lower and the proportion of community-onset CDI was much higher in the privately insured younger LabRx population compared to the elderly Medicare population.
AHRQ-funded; HS019455.
Citation: Olsen MA, Young-Xu Y, Stwalley D .
The burden of Clostridium difficile infection: estimates of the incidence of CDI from U.S. administrative databases.
BMC Infect Dis 2016 Apr 22;16:177. doi: 10.1186/s12879-016-1501-7.
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Keywords: Healthcare Cost and Utilization Project (HCUP), Clostridium difficile Infections, Healthcare-Associated Infections (HAIs), Data, Prevention
Burda BU, Holmer HK, Norris SL
Limitations of A Measurement Tool to Assess Systematic Reviews (AMSTAR) and suggestions for improvement.
A Measurement Tool to Assess Systematic Reviews (AMSTAR) is a commonly used tool to assess the quality of systematic reviews; however, modifications are needed to improve its usability, reliability, and validity. In this commentary, the authors summarize their experience and the experiences of others who have used AMSTAR and provide suggestions for its improvement.
AHRQ-funded; HS018500.
Citation: Burda BU, Holmer HK, Norris SL .
Limitations of A Measurement Tool to Assess Systematic Reviews (AMSTAR) and suggestions for improvement.
Syst Rev 2016 Apr 12;5:58. doi: 10.1186/s13643-016-0237-1.
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Keywords: Research Methodologies, Data, Evidence-Based Practice, Guidelines, Quality Measures
Zhu Y, Chen CY, Matsuyama Y
Comparative validity of methods to select appropriate cutoff weight for probabilistic linkage without unique personal identifiers.
The researchers aimed to assess the validity of probabilistic linkage in the absence of unique personal identifiers (UPI) and the methods of cutoff weight selection. They found that probabilistic linkage without UPI generated valid linkages when an optimal cutoff was chosen and concluded that histogram inspection, the duplicate method, and the odds formula method can be used in conjunction when a gold standard is not available.
AHRQ-funded; 29020050016I.
Citation: Zhu Y, Chen CY, Matsuyama Y .
Comparative validity of methods to select appropriate cutoff weight for probabilistic linkage without unique personal identifiers.
Pharmacoepidemiol Drug Saf 2016 Apr;25(4):444-52. doi: 10.1002/pds.3832.
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Keywords: Data, Medical Devices, Registries