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Medicaid coverage accuracy in electronic health records

Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristi...

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Autores principales: Marino, Miguel, Angier, Heather, Valenzuela, Steele, Hoopes, Megan, Killerby, Marie, Blackburn, Brenna, Huguet, Nathalie, Heintzman, John, Hatch, Brigit, O'Malley, Jean P., DeVoe, Jennifer E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082971/
https://www.ncbi.nlm.nih.gov/pubmed/30116701
http://dx.doi.org/10.1016/j.pmedr.2018.07.009
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author Marino, Miguel
Angier, Heather
Valenzuela, Steele
Hoopes, Megan
Killerby, Marie
Blackburn, Brenna
Huguet, Nathalie
Heintzman, John
Hatch, Brigit
O'Malley, Jean P.
DeVoe, Jennifer E.
author_facet Marino, Miguel
Angier, Heather
Valenzuela, Steele
Hoopes, Megan
Killerby, Marie
Blackburn, Brenna
Huguet, Nathalie
Heintzman, John
Hatch, Brigit
O'Malley, Jean P.
DeVoe, Jennifer E.
author_sort Marino, Miguel
collection PubMed
description Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristics are associated with accurate documentation. Our objective was to evaluate the validity of EHR data for monitoring longitudinal Medicaid coverage and assess variation by patient demographics, visit types, and clinic characteristics. We conducted a retrospective, observational study comparing Medicaid status agreement between Oregon community health center EHR data linked at the patient-level to Medicaid enrollment data (gold standard). We included adult patients with a Medicaid identification number and ≥1 clinic visit between 1/1/2013–12/31/2014 [>1 million visits (n = 135,514 patients)]. We estimated statistical correspondence between EHR and Medicaid data at each visit (visit-level) and for different insurance cohorts over time (patient-level). Data were collected in 2016 and analyzed 2017–2018. We observed excellent agreement between EHR and Medicaid data for health insurance information: kappa (>0.80), sensitivity (>0.80), and specificity (>0.85). Several characteristics were associated with agreement; at the visit-level, agreement was lower for patients who preferred a non-English language and for visits missing income information. At the patient-level, agreement was lower for black patients and higher for older patients seen in primary care community health centers. Community health center EHR data are a valid source of Medicaid coverage information. Agreement varied with several characteristics, something researchers and clinic staff should consider when using health insurance information from EHR data.
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spelling pubmed-60829712018-08-16 Medicaid coverage accuracy in electronic health records Marino, Miguel Angier, Heather Valenzuela, Steele Hoopes, Megan Killerby, Marie Blackburn, Brenna Huguet, Nathalie Heintzman, John Hatch, Brigit O'Malley, Jean P. DeVoe, Jennifer E. Prev Med Rep Regular Article Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristics are associated with accurate documentation. Our objective was to evaluate the validity of EHR data for monitoring longitudinal Medicaid coverage and assess variation by patient demographics, visit types, and clinic characteristics. We conducted a retrospective, observational study comparing Medicaid status agreement between Oregon community health center EHR data linked at the patient-level to Medicaid enrollment data (gold standard). We included adult patients with a Medicaid identification number and ≥1 clinic visit between 1/1/2013–12/31/2014 [>1 million visits (n = 135,514 patients)]. We estimated statistical correspondence between EHR and Medicaid data at each visit (visit-level) and for different insurance cohorts over time (patient-level). Data were collected in 2016 and analyzed 2017–2018. We observed excellent agreement between EHR and Medicaid data for health insurance information: kappa (>0.80), sensitivity (>0.80), and specificity (>0.85). Several characteristics were associated with agreement; at the visit-level, agreement was lower for patients who preferred a non-English language and for visits missing income information. At the patient-level, agreement was lower for black patients and higher for older patients seen in primary care community health centers. Community health center EHR data are a valid source of Medicaid coverage information. Agreement varied with several characteristics, something researchers and clinic staff should consider when using health insurance information from EHR data. Elsevier 2018-07-27 /pmc/articles/PMC6082971/ /pubmed/30116701 http://dx.doi.org/10.1016/j.pmedr.2018.07.009 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Marino, Miguel
Angier, Heather
Valenzuela, Steele
Hoopes, Megan
Killerby, Marie
Blackburn, Brenna
Huguet, Nathalie
Heintzman, John
Hatch, Brigit
O'Malley, Jean P.
DeVoe, Jennifer E.
Medicaid coverage accuracy in electronic health records
title Medicaid coverage accuracy in electronic health records
title_full Medicaid coverage accuracy in electronic health records
title_fullStr Medicaid coverage accuracy in electronic health records
title_full_unstemmed Medicaid coverage accuracy in electronic health records
title_short Medicaid coverage accuracy in electronic health records
title_sort medicaid coverage accuracy in electronic health records
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082971/
https://www.ncbi.nlm.nih.gov/pubmed/30116701
http://dx.doi.org/10.1016/j.pmedr.2018.07.009
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