Objective: To demonstrate use of the electronic health record (EHR) for health insurance surveillance and identify factors associated with lack of coverage.
Materials And Methods: Using EHR data, we conducted a retrospective, longitudinal cohort study of adult patients (n = 279 654) within a national network of community health centers during a 2-year period (2012-2013).
Results: Factors associated with higher odds of being uninsured (vs Medicaid-insured) included: male gender, age >25 years, Hispanic ethnicity, income above the federal poverty level, and rural residence (P < .01 for all). Among patients with no insurance at their initial visit (n = 114 000), 50% remained uninsured for every subsequent visit.
Discussion: During the 2 years prior to 2014, many patients utilizing community health centers were unable to maintain stable health insurance coverage.
Conclusion: As patients gain access to health insurance under the Affordable Care Act, the EHR provides a novel approach to help track coverage and support vulnerable patients in gaining and maintaining coverage.
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http://dx.doi.org/10.1093/jamia/ocv179 | DOI Listing |
Genet Med
January 2025
Genomics Ethics, and Translational Research Program, RTI International, Research Triangle Park, NC; Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, OR. Electronic address:
Purpose: Limited evidence evaluates parents' perceptions of their child's clinical genomic sequencing (GS) results, particularly among individuals from medically underserved groups. Five Clinical Sequencing Evidence-Generating Research (CSER) consortium studies performed GS in children with suspected genetic conditions with high proportions of individuals from underserved groups to address this evidence gap.
Methods: Parents completed surveys of perceived understanding, personal utility, and test-related distress after GS result disclosure.
Genet Med
January 2025
Newborn Screening Ontario, Children's Hospital of Eastern Ontario, Ottawa, ON, Canada; Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa. Electronic address:
Purpose: Universal newborn hearing screening (UNHS) programs using audiometric techniques alone are limited in ability to detect non-congenital childhood permanent hearing loss (PHL). In 2019, Ontario launched universal newborn screening (NBS) for PHL risk factors: congenital cytomegalovirus (cCMV) and 22 common variants in GJB2 and SLC26A4. Here we describe our experience with genetic risk factor screening.
View Article and Find Full Text PDFObjective: This quality improvement initiative aimed to increase the rate of provider screening and documentation of contraception use for reproductive-aged women seen in an academic rheumatology fellows' clinic to >50% by 24 weeks, with sustained improvement at one year.
Methods: With a multidisciplinary team, we devised and implemented six interventional cycles over 24 weeks informed by key stakeholder survey responses. The primary outcome measure was the percentage of eligible visits with contraception information documented in the structured electronic health record field.
JMIR Form Res
January 2025
ICMR-National Institute for Research in Digital Health and Data Science, Ansari Nagar, New Delhi, 110029, India, 91 7840870009.
Background: Verbal autopsy (VA) has been a crucial tool in ascertaining population-level cause of death (COD) estimates, specifically in countries where medical certification of COD is relatively limited. The World Health Organization has released an updated instrument (Verbal Autopsy Instrument 2022) that supports electronic data collection methods along with analytical software for assigning COD. This questionnaire encompasses the primary signs and symptoms associated with prevalent diseases across all age groups.
View Article and Find Full Text PDFCirc Genom Precis Med
January 2025
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT (A.A., L.S.D., E.K.O., R.K.).
Background: While universal screening for Lp(a; lipoprotein[a]) is increasingly recommended, <0.5% of patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a; ARISE), a validated machine learning tool, to health system electronic health records to increase the yield of Lp(a) testing.
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