Comparing chronic condition rates using ICD-9 and ICD-10 in VA patients FY2014-2016.
Identifieur interne : 000890 ( Main/Corpus ); précédent : 000889; suivant : 000891Comparing chronic condition rates using ICD-9 and ICD-10 in VA patients FY2014-2016.
Auteurs : Jean Yoon ; Adam ChowSource :
- BMC health services research [ 1472-6963 ] ; 2017.
English descriptors
- KwdEn :
- Alzheimer Disease (classification), Alzheimer Disease (epidemiology), Cardiovascular Diseases (classification), Cardiovascular Diseases (epidemiology), Chronic Disease (classification), Chronic Disease (epidemiology), Clinical Coding (MeSH), HIV Infections (classification), HIV Infections (epidemiology), Humans (MeSH), International Classification of Diseases (MeSH), Mental Disorders (classification), Mental Disorders (epidemiology), Prevalence (MeSH), Spinal Cord Injuries (classification), Spinal Cord Injuries (epidemiology), United States (epidemiology), United States Department of Veterans Affairs (MeSH), Veterans (MeSH).
- MESH :
- classification : Alzheimer Disease, Cardiovascular Diseases, Chronic Disease, HIV Infections, Mental Disorders, Spinal Cord Injuries.
- epidemiology : Alzheimer Disease, Cardiovascular Diseases, Chronic Disease, HIV Infections, Mental Disorders, Spinal Cord Injuries, United States.
- Clinical Coding, Humans, International Classification of Diseases, Prevalence, United States Department of Veterans Affairs, Veterans.
Abstract
BACKGROUND
Management of patients with chronic conditions relies on accurate measurement. It is unknown how transition to the ICD-10 coding system affected reporting of chronic condition rates over time. We measured chronic condition rates 2 years before and 1 year after the transition to ICD-10 to examine changes in prevalence rates and potential measurement issues in the Veterans Affairs (VA) health care system.
METHODS
We developed definitions for 34 chronic conditions using ICD-9 and ICD-10 codes and compared the prevalence rates of these conditions from FY2014 to 2016 in a 20% random sample (1.0 million) of all VA patients. In each year we estimated the total number of patients diagnosed with the conditions. We regressed each condition on an indicator of ICD-10 (versus ICD-9) measurement to obtain the odds ratio associated with ICD-10.
RESULTS
Condition prevalence estimates were similar for most conditions before and after ICD-10 transition. We found significant changes in a few exceptions. Alzheimer's disease and spinal cord injury had more than twice the odds of being measured with ICD-10 compared to ICD-9. HIV/AIDS had one-third the odds, and arthritis had half the odds of being measured with ICD-10. Alcohol dependence and tobacco/nicotine dependence had half the odds of being measured in ICD-10.
CONCLUSION
Many chronic condition rates were consistent from FY14-16, and there did not appear to be widespread undercoding of conditions after ICD-10 transition. It is unknown whether increased sensitivity or undercoding led to decreases in mental health conditions.
DOI: 10.1186/s12913-017-2504-9
PubMed: 28818082
PubMed Central: PMC5561575
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Comparing chronic condition rates using ICD-9 and ICD-10 in VA patients FY2014-2016.</title><author><name sortKey="Yoon, Jean" sort="Yoon, Jean" uniqKey="Yoon J" first="Jean" last="Yoon">Jean Yoon</name><affiliation><nlm:affiliation>Health Economics Resource Center, VA Palo Alto, 795 Willow Rd, 152 MPD, Menlo Park, CA, 94025, USA. jean.yoon@va.gov.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Center for Innovation to Implementation, VA Palo Alto, Menlo Park, CA, USA. jean.yoon@va.gov.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>UC San Francisco School of Medicine, San Francisco, CA, USA. jean.yoon@va.gov.</nlm:affiliation></affiliation></author><author><name sortKey="Chow, Adam" sort="Chow, Adam" uniqKey="Chow A" first="Adam" last="Chow">Adam Chow</name><affiliation><nlm:affiliation>Health Economics Resource Center, VA Palo Alto, 795 Willow Rd, 152 MPD, Menlo Park, CA, 94025, USA.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28818082</idno><idno type="pmid">28818082</idno><idno type="doi">10.1186/s12913-017-2504-9</idno><idno type="pmc">PMC5561575</idno><idno type="wicri:Area/Main/Corpus">000890</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000890</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Comparing chronic condition rates using ICD-9 and ICD-10 in VA patients FY2014-2016.</title><author><name sortKey="Yoon, Jean" sort="Yoon, Jean" uniqKey="Yoon J" first="Jean" last="Yoon">Jean Yoon</name><affiliation><nlm:affiliation>Health Economics Resource Center, VA Palo Alto, 795 Willow Rd, 152 MPD, Menlo Park, CA, 94025, USA. jean.yoon@va.gov.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Center for Innovation to Implementation, VA Palo Alto, Menlo Park, CA, USA. jean.yoon@va.gov.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>UC San Francisco School of Medicine, San Francisco, CA, USA. jean.yoon@va.gov.</nlm:affiliation></affiliation></author><author><name sortKey="Chow, Adam" sort="Chow, Adam" uniqKey="Chow A" first="Adam" last="Chow">Adam Chow</name><affiliation><nlm:affiliation>Health Economics Resource Center, VA Palo Alto, 795 Willow Rd, 152 MPD, Menlo Park, CA, 94025, USA.</nlm:affiliation></affiliation></author></analytic><series><title level="j">BMC health services research</title><idno type="eISSN">1472-6963</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Alzheimer Disease (classification)</term><term>Alzheimer Disease (epidemiology)</term><term>Cardiovascular Diseases (classification)</term><term>Cardiovascular Diseases (epidemiology)</term><term>Chronic Disease (classification)</term><term>Chronic Disease (epidemiology)</term><term>Clinical Coding (MeSH)</term><term>HIV Infections (classification)</term><term>HIV Infections (epidemiology)</term><term>Humans (MeSH)</term><term>International Classification of Diseases (MeSH)</term><term>Mental Disorders (classification)</term><term>Mental Disorders (epidemiology)</term><term>Prevalence (MeSH)</term><term>Spinal Cord Injuries (classification)</term><term>Spinal Cord Injuries (epidemiology)</term><term>United States (epidemiology)</term><term>United States Department of Veterans Affairs (MeSH)</term><term>Veterans (MeSH)</term></keywords><keywords scheme="MESH" qualifier="classification" xml:lang="en"><term>Alzheimer Disease</term><term>Cardiovascular Diseases</term><term>Chronic Disease</term><term>HIV Infections</term><term>Mental Disorders</term><term>Spinal Cord Injuries</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Alzheimer Disease</term><term>Cardiovascular Diseases</term><term>Chronic Disease</term><term>HIV Infections</term><term>Mental Disorders</term><term>Spinal Cord Injuries</term><term>United States</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Clinical Coding</term><term>Humans</term><term>International Classification of Diseases</term><term>Prevalence</term><term>United States Department of Veterans Affairs</term><term>Veterans</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>Management of patients with chronic conditions relies on accurate measurement. It is unknown how transition to the ICD-10 coding system affected reporting of chronic condition rates over time. We measured chronic condition rates 2 years before and 1 year after the transition to ICD-10 to examine changes in prevalence rates and potential measurement issues in the Veterans Affairs (VA) health care system.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>We developed definitions for 34 chronic conditions using ICD-9 and ICD-10 codes and compared the prevalence rates of these conditions from FY2014 to 2016 in a 20% random sample (1.0 million) of all VA patients. In each year we estimated the total number of patients diagnosed with the conditions. We regressed each condition on an indicator of ICD-10 (versus ICD-9) measurement to obtain the odds ratio associated with ICD-10.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Condition prevalence estimates were similar for most conditions before and after ICD-10 transition. We found significant changes in a few exceptions. Alzheimer's disease and spinal cord injury had more than twice the odds of being measured with ICD-10 compared to ICD-9. HIV/AIDS had one-third the odds, and arthritis had half the odds of being measured with ICD-10. Alcohol dependence and tobacco/nicotine dependence had half the odds of being measured in ICD-10.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>Many chronic condition rates were consistent from FY14-16, and there did not appear to be widespread undercoding of conditions after ICD-10 transition. It is unknown whether increased sensitivity or undercoding led to decreases in mental health conditions.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">28818082</PMID><DateCompleted><Year>2018</Year><Month>04</Month><Day>02</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1472-6963</ISSN><JournalIssue CitedMedium="Internet"><Volume>17</Volume><Issue>1</Issue><PubDate><Year>2017</Year><Month>Aug</Month><Day>17</Day></PubDate></JournalIssue><Title>BMC health services research</Title><ISOAbbreviation>BMC Health Serv Res</ISOAbbreviation></Journal><ArticleTitle>Comparing chronic condition rates using ICD-9 and ICD-10 in VA patients FY2014-2016.</ArticleTitle><Pagination><MedlinePgn>572</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12913-017-2504-9</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Management of patients with chronic conditions relies on accurate measurement. It is unknown how transition to the ICD-10 coding system affected reporting of chronic condition rates over time. We measured chronic condition rates 2 years before and 1 year after the transition to ICD-10 to examine changes in prevalence rates and potential measurement issues in the Veterans Affairs (VA) health care system.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We developed definitions for 34 chronic conditions using ICD-9 and ICD-10 codes and compared the prevalence rates of these conditions from FY2014 to 2016 in a 20% random sample (1.0 million) of all VA patients. In each year we estimated the total number of patients diagnosed with the conditions. We regressed each condition on an indicator of ICD-10 (versus ICD-9) measurement to obtain the odds ratio associated with ICD-10.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Condition prevalence estimates were similar for most conditions before and after ICD-10 transition. We found significant changes in a few exceptions. Alzheimer's disease and spinal cord injury had more than twice the odds of being measured with ICD-10 compared to ICD-9. HIV/AIDS had one-third the odds, and arthritis had half the odds of being measured with ICD-10. Alcohol dependence and tobacco/nicotine dependence had half the odds of being measured in ICD-10.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Many chronic condition rates were consistent from FY14-16, and there did not appear to be widespread undercoding of conditions after ICD-10 transition. It is unknown whether increased sensitivity or undercoding led to decreases in mental health conditions.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Yoon</LastName><ForeName>Jean</ForeName><Initials>J</Initials><Identifier Source="ORCID">http://orcid.org/0000-0001-8565-2881</Identifier><AffiliationInfo><Affiliation>Health Economics Resource Center, VA Palo Alto, 795 Willow Rd, 152 MPD, Menlo Park, CA, 94025, USA. jean.yoon@va.gov.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Innovation to Implementation, VA Palo Alto, Menlo Park, CA, USA. jean.yoon@va.gov.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>UC San Francisco School of Medicine, San Francisco, CA, USA. jean.yoon@va.gov.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chow</LastName><ForeName>Adam</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Health Economics Resource Center, VA Palo Alto, 795 Willow Rd, 152 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IdType="doi">10.1186/s12913-017-2504-9</ArticleId><ArticleId IdType="pii">10.1186/s12913-017-2504-9</ArticleId><ArticleId IdType="pmc">PMC5561575</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Med Care Res Rev. 2003 Sep;60(3 Suppl):146S-167S</Citation><ArticleIdList><ArticleId IdType="pubmed">15095551</ArticleId></ArticleIdList></Reference><Reference><Citation>Med Care. 2005 Nov;43(11):1130-9</Citation><ArticleIdList><ArticleId IdType="pubmed">16224307</ArticleId></ArticleIdList></Reference><Reference><Citation>J Am Med Inform Assoc. 2013 Jul-Aug;20(4):708-17</Citation><ArticleIdList><ArticleId IdType="pubmed">23645552</ArticleId></ArticleIdList></Reference><Reference><Citation>Popul Health Manag. 2011 Dec;14(6):293-8</Citation><ArticleIdList><ArticleId IdType="pubmed">22044350</ArticleId></ArticleIdList></Reference><Reference><Citation>BMC Health Serv Res. 2008 Jan 14;8:12</Citation><ArticleIdList><ArticleId 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