Comparison of Electronic Health Record–Based and Claims‐Based Diabetes Care Quality Measures: Causes of Discrepancies

Objective To investigate magnitude and sources of discrepancy in quality metrics using claims versus electronic health record (EHR) data. Study Design Assessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review...

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Veröffentlicht in:Health services research 2018-08, Vol.53 (4), p.2988-3006
Hauptverfasser: Laws, Michael Barton, Michaud, Joanne, Shield, Renee, McQuade, William, Wilson, Ira B.
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container_end_page 3006
container_issue 4
container_start_page 2988
container_title Health services research
container_volume 53
creator Laws, Michael Barton
Michaud, Joanne
Shield, Renee
McQuade, William
Wilson, Ira B.
description Objective To investigate magnitude and sources of discrepancy in quality metrics using claims versus electronic health record (EHR) data. Study Design Assessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review of EHRs of discrepant cases. Data Collection/Extraction Claims submitted to Rhode Island Medicaid by three practice sites in 2013; program‐coded EHR extraction; manual review of selected EHRs. Principal Findings Of 21,030 adult Medicaid beneficiaries attributed to a primary care patient at a site by claims or EHR data, concordance on assignment ranged from 0.30 to 0.41. Of patients with concordant assignment, the ratio of patients ascertained as diabetic by EHR versus claims ranged from 1.06 to 1.14. For patients with concordant assignment and diagnosis, the ratio based on EHR versus claims ranged from 1.08 to 18.34 for HbA1c testing, and from 1.29 to 14.18 for lipid testing. Manual record review of 264 patients discrepant on diagnosis or testing identified problems such as misuse of ICD‐9 codes, failure to submit claims, and others. Conclusions Claims data underestimate performance on these metrics compared to EHR documentation, by varying amounts. Use of claims data for these metrics is problematic.
doi_str_mv 10.1111/1475-6773.12819
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Study Design Assessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review of EHRs of discrepant cases. Data Collection/Extraction Claims submitted to Rhode Island Medicaid by three practice sites in 2013; program‐coded EHR extraction; manual review of selected EHRs. Principal Findings Of 21,030 adult Medicaid beneficiaries attributed to a primary care patient at a site by claims or EHR data, concordance on assignment ranged from 0.30 to 0.41. Of patients with concordant assignment, the ratio of patients ascertained as diabetic by EHR versus claims ranged from 1.06 to 1.14. For patients with concordant assignment and diagnosis, the ratio based on EHR versus claims ranged from 1.08 to 18.34 for HbA1c testing, and from 1.29 to 14.18 for lipid testing. Manual record review of 264 patients discrepant on diagnosis or testing identified problems such as misuse of ICD‐9 codes, failure to submit claims, and others. Conclusions Claims data underestimate performance on these metrics compared to EHR documentation, by varying amounts. Use of claims data for these metrics is problematic.</description><identifier>ISSN: 0017-9124</identifier><identifier>EISSN: 1475-6773</identifier><identifier>DOI: 10.1111/1475-6773.12819</identifier><identifier>PMID: 29282723</identifier><language>eng</language><publisher>United States: Health Research and Educational Trust</publisher><subject><![CDATA[Analysis ; Assignment ; Beneficiaries ; claims data ; Data Accuracy ; Data collection ; Data Collection - methods ; Data Collection - standards ; Diabetes ; Diabetes mellitus ; Diabetes Mellitus - therapy ; Diabetes therapy ; Diagnosis ; Diagnostic tests ; Discrepancies ; Documentation ; EHRs ; Electronic health records ; Electronic Health Records - standards ; Electronic Health Records - statistics & numerical data ; Electronic medical records ; Electronic records ; Extraction ; Glycated Hemoglobin A - analysis ; Glycosylated hemoglobin ; Government programs ; Health care ; Health Care Quality and Measurement ; Health promotion ; Humans ; Insurance Claim Review - standards ; Insurance Claim Review - statistics & numerical data ; Lipids - blood ; Low density lipoprotein ; Low density lipoproteins ; Medicaid ; Medicaid - standards ; Medicaid - statistics & numerical data ; Medical diagnosis ; Medical records ; Office Visits - statistics & numerical data ; Patients ; Primary care ; Primary Health Care - standards ; Primary Health Care - statistics & numerical data ; Qualitative analysis ; Quality Indicators, Health Care - standards ; Quality Indicators, Health Care - statistics & numerical data ; Quality management ; Quality measurement ; Quality of care ; Rhode Island ; United States]]></subject><ispartof>Health services research, 2018-08, Vol.53 (4), p.2988-3006</ispartof><rights>Health Research and Educational Trust</rights><rights>Health Research and Educational Trust.</rights><rights>COPYRIGHT 2018 Health Research and Educational Trust</rights><rights>COPYRIGHT 2018 Health Research and Educational Trust</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c7139-c4d8e02d023a8ebe77bac990dd7ff7ce546570d9a75c5ffcb2b7e2a6d98d372c3</citedby><cites>FETCH-LOGICAL-c7139-c4d8e02d023a8ebe77bac990dd7ff7ce546570d9a75c5ffcb2b7e2a6d98d372c3</cites><orcidid>0000-0002-0790-5879</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056571/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056571/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,1411,27901,27902,30976,45550,45551,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29282723$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Laws, Michael Barton</creatorcontrib><creatorcontrib>Michaud, Joanne</creatorcontrib><creatorcontrib>Shield, Renee</creatorcontrib><creatorcontrib>McQuade, William</creatorcontrib><creatorcontrib>Wilson, Ira B.</creatorcontrib><title>Comparison of Electronic Health Record–Based and Claims‐Based Diabetes Care Quality Measures: Causes of Discrepancies</title><title>Health services research</title><addtitle>Health Serv Res</addtitle><description>Objective To investigate magnitude and sources of discrepancy in quality metrics using claims versus electronic health record (EHR) data. Study Design Assessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review of EHRs of discrepant cases. Data Collection/Extraction Claims submitted to Rhode Island Medicaid by three practice sites in 2013; program‐coded EHR extraction; manual review of selected EHRs. Principal Findings Of 21,030 adult Medicaid beneficiaries attributed to a primary care patient at a site by claims or EHR data, concordance on assignment ranged from 0.30 to 0.41. Of patients with concordant assignment, the ratio of patients ascertained as diabetic by EHR versus claims ranged from 1.06 to 1.14. For patients with concordant assignment and diagnosis, the ratio based on EHR versus claims ranged from 1.08 to 18.34 for HbA1c testing, and from 1.29 to 14.18 for lipid testing. Manual record review of 264 patients discrepant on diagnosis or testing identified problems such as misuse of ICD‐9 codes, failure to submit claims, and others. Conclusions Claims data underestimate performance on these metrics compared to EHR documentation, by varying amounts. 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numerical data</topic><topic>Lipids - blood</topic><topic>Low density lipoprotein</topic><topic>Low density lipoproteins</topic><topic>Medicaid</topic><topic>Medicaid - standards</topic><topic>Medicaid - statistics &amp; numerical data</topic><topic>Medical diagnosis</topic><topic>Medical records</topic><topic>Office Visits - statistics &amp; numerical data</topic><topic>Patients</topic><topic>Primary care</topic><topic>Primary Health Care - standards</topic><topic>Primary Health Care - statistics &amp; numerical data</topic><topic>Qualitative analysis</topic><topic>Quality Indicators, Health Care - standards</topic><topic>Quality Indicators, Health Care - statistics &amp; numerical data</topic><topic>Quality management</topic><topic>Quality measurement</topic><topic>Quality of care</topic><topic>Rhode Island</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Laws, Michael Barton</creatorcontrib><creatorcontrib>Michaud, Joanne</creatorcontrib><creatorcontrib>Shield, Renee</creatorcontrib><creatorcontrib>McQuade, William</creatorcontrib><creatorcontrib>Wilson, Ira B.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale Business Insights</collection><collection>Business Insights: Essentials</collection><collection>Gale In Context: High School</collection><collection>Applied Social Sciences Index &amp; 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Study Design Assessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review of EHRs of discrepant cases. Data Collection/Extraction Claims submitted to Rhode Island Medicaid by three practice sites in 2013; program‐coded EHR extraction; manual review of selected EHRs. Principal Findings Of 21,030 adult Medicaid beneficiaries attributed to a primary care patient at a site by claims or EHR data, concordance on assignment ranged from 0.30 to 0.41. Of patients with concordant assignment, the ratio of patients ascertained as diabetic by EHR versus claims ranged from 1.06 to 1.14. For patients with concordant assignment and diagnosis, the ratio based on EHR versus claims ranged from 1.08 to 18.34 for HbA1c testing, and from 1.29 to 14.18 for lipid testing. Manual record review of 264 patients discrepant on diagnosis or testing identified problems such as misuse of ICD‐9 codes, failure to submit claims, and others. Conclusions Claims data underestimate performance on these metrics compared to EHR documentation, by varying amounts. Use of claims data for these metrics is problematic.</abstract><cop>United States</cop><pub>Health Research and Educational Trust</pub><pmid>29282723</pmid><doi>10.1111/1475-6773.12819</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-0790-5879</orcidid><oa>free_for_read</oa></addata></record>
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source Applied Social Sciences Index & Abstracts (ASSIA); MEDLINE; Wiley Online Library All Journals; PubMed Central; Alma/SFX Local Collection; EZB Electronic Journals Library
subjects Analysis
Assignment
Beneficiaries
claims data
Data Accuracy
Data collection
Data Collection - methods
Data Collection - standards
Diabetes
Diabetes mellitus
Diabetes Mellitus - therapy
Diabetes therapy
Diagnosis
Diagnostic tests
Discrepancies
Documentation
EHRs
Electronic health records
Electronic Health Records - standards
Electronic Health Records - statistics & numerical data
Electronic medical records
Electronic records
Extraction
Glycated Hemoglobin A - analysis
Glycosylated hemoglobin
Government programs
Health care
Health Care Quality and Measurement
Health promotion
Humans
Insurance Claim Review - standards
Insurance Claim Review - statistics & numerical data
Lipids - blood
Low density lipoprotein
Low density lipoproteins
Medicaid
Medicaid - standards
Medicaid - statistics & numerical data
Medical diagnosis
Medical records
Office Visits - statistics & numerical data
Patients
Primary care
Primary Health Care - standards
Primary Health Care - statistics & numerical data
Qualitative analysis
Quality Indicators, Health Care - standards
Quality Indicators, Health Care - statistics & numerical data
Quality management
Quality measurement
Quality of care
Rhode Island
United States
title Comparison of Electronic Health Record–Based and Claims‐Based Diabetes Care Quality Measures: Causes of Discrepancies
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