Supporting health insurance expansion: do electronic health records have valid insurance verification and enrollment data?

John Heintzman, Miguel Marino, Megan Hoopes, Steffani Bailey, Rachel Gold, Jean O'Malley, Heather Angier, Christine Nelson, Erika Cottrell, Jennifer Devoe

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

RESULTS: Compared to reimbursement data and Medicaid coverage data, EHR coverage data had high agreement (87% and 95%, respectively), sensitivity (0.97 and 0.96), positive predictive value (0.88 and 0.98), but lower kappa statistics (0.32 and 0.49), specificity (0.27 and 0.60), and negative predictive value (0.66 and 0.45). These varied among clinics.

DISCUSSION/CONCLUSIONS: EHR coverage data for children had a high overall correspondence with Medicaid data and reimbursement data, suggesting that in some systems EHR data could be utilized to promote insurance stability in their patients. Future work should attempt to replicate these analyses in other settings.

MATERIALS AND METHODS: Subjects Children visiting any of 96 CHCs (N = 69 189) from 2011 to 2012. Analysis The authors measured correspondence (whether or not the visit was covered by Medicaid) between EHR coverage data and (i) reimbursement data and (ii) coverage data from Medicaid.

OBJECTIVE: To validate electronic health record (EHR) insurance information for low-income pediatric patients at Oregon community health centers (CHCs), compared to reimbursement data and Medicaid coverage data.

Original languageEnglish (US)
Pages (from-to)909-913
Number of pages5
JournalJournal of the American Medical Informatics Association : JAMIA
Volume22
Issue number4
DOIs
StatePublished - Jul 1 2015

Fingerprint

Electronic Health Records
Medicaid
Health Insurance
Insurance
Community Health Centers
Pediatrics

Keywords

  • children
  • community health centers
  • electronic health records
  • health insurance
  • health insurance claims
  • Medicaid expansion

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Supporting health insurance expansion : do electronic health records have valid insurance verification and enrollment data? / Heintzman, John; Marino, Miguel; Hoopes, Megan; Bailey, Steffani; Gold, Rachel; O'Malley, Jean; Angier, Heather; Nelson, Christine; Cottrell, Erika; Devoe, Jennifer.

In: Journal of the American Medical Informatics Association : JAMIA, Vol. 22, No. 4, 01.07.2015, p. 909-913.

Research output: Contribution to journalArticle

@article{48415387e4274233843400c140366384,
title = "Supporting health insurance expansion: do electronic health records have valid insurance verification and enrollment data?",
abstract = "RESULTS: Compared to reimbursement data and Medicaid coverage data, EHR coverage data had high agreement (87{\%} and 95{\%}, respectively), sensitivity (0.97 and 0.96), positive predictive value (0.88 and 0.98), but lower kappa statistics (0.32 and 0.49), specificity (0.27 and 0.60), and negative predictive value (0.66 and 0.45). These varied among clinics.DISCUSSION/CONCLUSIONS: EHR coverage data for children had a high overall correspondence with Medicaid data and reimbursement data, suggesting that in some systems EHR data could be utilized to promote insurance stability in their patients. Future work should attempt to replicate these analyses in other settings.MATERIALS AND METHODS: Subjects Children visiting any of 96 CHCs (N = 69 189) from 2011 to 2012. Analysis The authors measured correspondence (whether or not the visit was covered by Medicaid) between EHR coverage data and (i) reimbursement data and (ii) coverage data from Medicaid.OBJECTIVE: To validate electronic health record (EHR) insurance information for low-income pediatric patients at Oregon community health centers (CHCs), compared to reimbursement data and Medicaid coverage data.",
keywords = "children, community health centers, electronic health records, health insurance, health insurance claims, Medicaid expansion",
author = "John Heintzman and Miguel Marino and Megan Hoopes and Steffani Bailey and Rachel Gold and Jean O'Malley and Heather Angier and Christine Nelson and Erika Cottrell and Jennifer Devoe",
year = "2015",
month = "7",
day = "1",
doi = "10.1093/jamia/ocv033",
language = "English (US)",
volume = "22",
pages = "909--913",
journal = "Journal of the American Medical Informatics Association",
issn = "1067-5027",
publisher = "Oxford University Press",
number = "4",

}

TY - JOUR

T1 - Supporting health insurance expansion

T2 - do electronic health records have valid insurance verification and enrollment data?

AU - Heintzman, John

AU - Marino, Miguel

AU - Hoopes, Megan

AU - Bailey, Steffani

AU - Gold, Rachel

AU - O'Malley, Jean

AU - Angier, Heather

AU - Nelson, Christine

AU - Cottrell, Erika

AU - Devoe, Jennifer

PY - 2015/7/1

Y1 - 2015/7/1

N2 - RESULTS: Compared to reimbursement data and Medicaid coverage data, EHR coverage data had high agreement (87% and 95%, respectively), sensitivity (0.97 and 0.96), positive predictive value (0.88 and 0.98), but lower kappa statistics (0.32 and 0.49), specificity (0.27 and 0.60), and negative predictive value (0.66 and 0.45). These varied among clinics.DISCUSSION/CONCLUSIONS: EHR coverage data for children had a high overall correspondence with Medicaid data and reimbursement data, suggesting that in some systems EHR data could be utilized to promote insurance stability in their patients. Future work should attempt to replicate these analyses in other settings.MATERIALS AND METHODS: Subjects Children visiting any of 96 CHCs (N = 69 189) from 2011 to 2012. Analysis The authors measured correspondence (whether or not the visit was covered by Medicaid) between EHR coverage data and (i) reimbursement data and (ii) coverage data from Medicaid.OBJECTIVE: To validate electronic health record (EHR) insurance information for low-income pediatric patients at Oregon community health centers (CHCs), compared to reimbursement data and Medicaid coverage data.

AB - RESULTS: Compared to reimbursement data and Medicaid coverage data, EHR coverage data had high agreement (87% and 95%, respectively), sensitivity (0.97 and 0.96), positive predictive value (0.88 and 0.98), but lower kappa statistics (0.32 and 0.49), specificity (0.27 and 0.60), and negative predictive value (0.66 and 0.45). These varied among clinics.DISCUSSION/CONCLUSIONS: EHR coverage data for children had a high overall correspondence with Medicaid data and reimbursement data, suggesting that in some systems EHR data could be utilized to promote insurance stability in their patients. Future work should attempt to replicate these analyses in other settings.MATERIALS AND METHODS: Subjects Children visiting any of 96 CHCs (N = 69 189) from 2011 to 2012. Analysis The authors measured correspondence (whether or not the visit was covered by Medicaid) between EHR coverage data and (i) reimbursement data and (ii) coverage data from Medicaid.OBJECTIVE: To validate electronic health record (EHR) insurance information for low-income pediatric patients at Oregon community health centers (CHCs), compared to reimbursement data and Medicaid coverage data.

KW - children

KW - community health centers

KW - electronic health records

KW - health insurance

KW - health insurance claims

KW - Medicaid expansion

UR - http://www.scopus.com/inward/record.url?scp=84964695223&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964695223&partnerID=8YFLogxK

U2 - 10.1093/jamia/ocv033

DO - 10.1093/jamia/ocv033

M3 - Article

C2 - 25888586

AN - SCOPUS:84964695223

VL - 22

SP - 909

EP - 913

JO - Journal of the American Medical Informatics Association

JF - Journal of the American Medical Informatics Association

SN - 1067-5027

IS - 4

ER -