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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.
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1 to 3 of 3 Research Studies DisplayedPredmore Z, Hatef E, Weiner JP
Integrating social and behavioral determinants of health into population health analytics: a conceptual framework and suggested road map.
There is growing recognition that social and behavioral risk factors impact population health outcomes. Interventions that target these risk factors can improve health outcomes. This study presents a review of existing literature and proposes a conceptual framework for the integration of social and behavioral data into population health analytics platforms. The authors describe several use cases for these platforms at the patient, health system, and community levels, and align these use cases with the different types of prevention identified by the Centers for Disease Control and Prevention.
AHRQ-funded; HS000029.
Citation: Predmore Z, Hatef E, Weiner JP .
Integrating social and behavioral determinants of health into population health analytics: a conceptual framework and suggested road map.
Popul Health Manag 2019 Dec;22(6):488-94. doi: 10.1089/pop.2018.0151..
Keywords: Social Determinants of Health, Risk, Research Methodologies
Vanderlaan J, Dunlop A, Rochat R
Methodology for sampling women at high maternal risk in administrative data.
This study compared the net benefits of using the Obstetric Comorbidity Index (OCI) to identify women at high maternal risk compared to conventional risk identification methods. Hospitalization discharge and vital records data for women experience singleton births in George from 2008 to 2012 was used. Results found there was a small but positive net benefit in using the OCI and conventional risk identification methods actually performed worse than using no risk identification methods at all. The researchers suggest that using OCI helps reduce misclassification.
AHRQ-funded; HS024655.
Citation: Vanderlaan J, Dunlop A, Rochat R .
Methodology for sampling women at high maternal risk in administrative data.
BMC Pregnancy Childbirth 2019 Oct 21;19(1):364. doi: 10.1186/s12884-019-2500-7..
Keywords: Research Methodologies, Health Services Research (HSR), Pregnancy, Maternal Care, Risk, Women
Goodman KE, Lessler J, Harris AD
A methodological comparison of risk scores versus decision trees for predicting drug-resistant infections: a case study using extended-spectrum beta-lactamase (ESBL) bacteremia.
Timely identification of multidrug-resistant gram-negative infections remains an epidemiological challenge. Statistical models for predicting drug resistance can offer utility where rapid diagnostics are unavailable or resource-impractical. The investigators previously reported on a decision tree for predicting extended-spectrum beta-lactamase bloodstream (ESBL) infections. Their objective in the current study was to develop a risk score from the same ESBL dataset to compare these 2 methods and to offer general guiding principles for using each approach.
AHRQ-funded; HS025089.
Citation: Goodman KE, Lessler J, Harris AD .
A methodological comparison of risk scores versus decision trees for predicting drug-resistant infections: a case study using extended-spectrum beta-lactamase (ESBL) bacteremia.
Infect Control Hosp Epidemiol 2019 Apr;40(4):400-07. doi: 10.1017/ice.2019.17..
Keywords: Research Methodologies, Risk, Infectious Diseases