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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 3 of 3 Research Studies DisplayedPolubriaginof FCG, Ryan P, Salmasian H
Challenges with quality of race and ethnicity data in observational databases.
This study assessed the quality of race and ethnicity information in observational health databases as well as electronic health records (EHRs) and to propose patient self-recording as a way to improve accuracy. Data from the Healthcare Cost and Utilization Project (HCUP) and Optum Labs, and from a single New York City healthcare system’s EHR was compared. Among 160 million patients in the HCUP database, no race or ethnicity data was recorded for 25% of the records. Among the 2.4 million patients in the New York City HER, race or ethnicity was unknown for 57%. However, when patients were allowed to directly record their race and ethnicity, percentages rose to 86%.
AHRQ-funded; HS021816; HS023704; HS024713.
Citation: Polubriaginof FCG, Ryan P, Salmasian H .
Challenges with quality of race and ethnicity data in observational databases.
J Am Med Inform Assoc 2019 Aug;26(8-9):730-36. doi: 10.1093/jamia/ocz113..
Keywords: Healthcare Cost and Utilization Project (HCUP), Data, Racial and Ethnic Minorities, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Services Research (HSR)
Althoff KN, Wong C, Hogan B
Mind the gap: observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data.
Under the hypothesis that use of electronic health records in health research may lead to false assumptions of complete event ascertainment, the authors of this article estimated "observation windows" (OWs) as a quality-control approach to reduce the likelihood of false assumption. The impact of OWs on estimating rates of type II diabetes mellitus from HIV clinical cohorts are demonstrated. Data from 16 HIV clinical cohorts to the NA-ACCORD were used to identify and evaluate OWs for an operationalized definition of diabetes occurrence. The authors conclude that OWs have utility as a quality-control approach to complete event ascertainment and help to improve the accuracy of estimates.
AHRQ-funded; 90047713.
Citation: Althoff KN, Wong C, Hogan B .
Mind the gap: observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data.
Ann Epidemiol 2019 May;33:54-63. doi: 10.1016/j.annepidem.2019.01.015..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Services Research (HSR), Quality of Care
Schroeder J, Karkar R, Fogarty J
A patient-centered proposal for bayesian analysis of self-experiments for health.
This article describes the types of questions people want to answer via self-experimentation in order to develop a complementary patient-centered perspective on the potential benefits of Bayesian analysis. Information was gathered via the authors’ experiences in engaging with irritable bowel syndrome patients and their healthcare providers and a survey that investigated what questions individuals want to answer about their health and wellness. The authors find that the majority of the questions people want to answer with self-tracking data are better answered with Bayesian methods than with frequentist methods. Examples of how those questions might be answered using frequentist null hypothesis significance testing, frequentist estimation, and Bayesian estimation and prediction, as well as design recommendations for analyses and visualizations to help people answer and interpret such questions are also provided.
AHRQ-funded; HS023654.
Citation: Schroeder J, Karkar R, Fogarty J .
A patient-centered proposal for bayesian analysis of self-experiments for health.
J Healthc Inform Res 2019 Mar;3(1):124-55. doi: 10.1007/s41666-018-0033-x..
Keywords: Health Information Technology (HIT), Health Services Research (HSR)