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Research Studies is a monthly compilation of research articles funded by AHRQ or authored by AHRQ researchers and recently published in journals or newsletters.
Results1 to 8 of 8 Research Studies Displayed
Davidson KW, Krist AH, Tseng CW
AHRQ Author: Mills J, Borsky A
Incorporation of social risk in US Preventive Services Task Force Recommendations and identification of key challenges for primary care.
The authors assessed how social risks have been considered in USPSTF recommendation statements and identified current gaps in evidence needed to expand the systematic inclusion of social risks in future recommendations. They concluded that their report serves as a benchmark and foundation for ongoing work to advance the goal of ensuring that health equity and social risks are incorporated into USPSTF methods and recommendations.
Citation: Davidson KW, Krist AH, Tseng CW . Incorporation of social risk in US Preventive Services Task Force Recommendations and identification of key challenges for primary care. JAMA 2021 Oct 12;326(14):1410-15. doi: 10.1001/jama.2021.12833..
Keywords: U.S. Preventive Services Task Force (USPSTF), Primary Care, Social Determinants of Health, Risk, Evidence-Based Practice, Research Methodologies, Guidelines
Predmore 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.
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.
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.
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
Desai RJ, Wyss R, Jin Y
Extension of disease risk score-based confounding adjustments for multiple outcomes of interest: an empirical evaluation.
Use of disease risk score (DRS)-based confounding adjustment when estimating treatment effects on multiple outcomes is not well studied. In this empirical cohort study, the investigators compared dabigatran initiators and warfarin initiators with respect to risks of ischemic stroke and major bleeding in 12 sequential monitoring periods (90 days each), using data from the Truven Marketscan database (Truven Health Analytics, Ann Arbor, Michigan).
Citation: Desai RJ, Wyss R, Jin Y . Extension of disease risk score-based confounding adjustments for multiple outcomes of interest: an empirical evaluation. Am J Epidemiol 2018 Nov;187(11):2439-48. doi: 10.1093/aje/kwy130.
Keywords: Blood Thinners, Cardiovascular Conditions, Medication, Outcomes, Research Methodologies, Risk, Stroke
Desai RJ, Glynn RJ, Wang S
Performance of disease risk score matching in nested case-control studies: a simulation study.
The authors investigate whether or not matching on a disease risk score (DRS), which includes many confounders, results in greater precision than matching on only a few confounders. Their results suggest that DRS matching might increase the statistical efficiency of case-control studies, particularly when the outcome is rare.
Citation: Desai RJ, Glynn RJ, Wang S . Performance of disease risk score matching in nested case-control studies: a simulation study. Am J Epidemiol 2016 May 15;183(10):949-57. doi: 10.1093/aje/kwv269.
Keywords: Research Methodologies, Risk, Patient-Centered Outcomes Research
Bennette CS, Ramsey SD, McDermott CL
Predicting low accrual in the National Cancer Institute's cooperative group clinical trials.
The study’s objective was to evaluate the empirical relationship and predictive properties of putative risk factors for low accrual in the National Cancer Institute's (NCI's) Cooperative Group Program, now the National Clinical Trials Network (NCTN). It identified multiple characteristics of NCTN-sponsored trials associated with low accrual and developed a prediction model that can provide a useful estimate of accrual risk based on these factors.
Citation: Bennette CS, Ramsey SD, McDermott CL . Predicting low accrual in the National Cancer Institute's cooperative group clinical trials. J Natl Cancer Inst 2016 Feb;108(2). doi: 10.1093/jnci/djv324.
Keywords: Research Methodologies, Risk
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.
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