Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases‐10 coding system: A brief review
Background and purpose The transition from International Classification of Diseases, 9th revision, clinical modification (ICD‐9‐CM) to ICD‐10‐CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outco...
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| Veröffentlicht in: | Pharmacoepidemiology and drug safety 2021-07, Vol.30 (7), p.838-842 |
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| creator | Nam, Young Hee Mendelsohn, Aaron B. Panozzo, Catherine A. Maro, Judith C. Brown, Jeffrey S. |
| description | Background and purpose
The transition from International Classification of Diseases, 9th revision, clinical modification (ICD‐9‐CM) to ICD‐10‐CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition.
Methods
We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD‐9‐CM and ICD‐10‐CM eras by visual inspection.
Results
We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time‐series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD‐9‐CM and ICD‐10‐CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency.
Conclusions
Researchers using ICD‐10‐CM algorithms obtained by standardized mappings from ICD‐9‐CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates.
Key points
We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD‐9‐CM) and ICD‐10‐CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic).
More than a third of the 140 time‐series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence.
Studies using ICD‐9‐CM‐based algorithms mapped to ICD‐10‐CM codes nee |
| doi_str_mv | 10.1002/pds.5216 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8251911</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2494302972</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4386-9d2036c4f2336f1a8f6f6fc0936b791f177ff5489e6bb0ef450efa446822b1c63</originalsourceid><addsrcrecordid>eNp1kt1qFDEUgAdRbK2CTyABL_Rman5mshMvCsuutYWCwtrrkJk52U3JJGuSadk7H6Fv0_fxSczutvUHJJCEnC8f5ySnKF4TfEwwph_WfTyuKeFPikOChShJXU-ebvc1K5uai4PiRYxXGOeYqJ4XB4xx1tCKHRZ3Z6BsWiE_ps4PEFHne-OWKAVwfUTGobQCdLlAp973SLkezcO4RNN-MM7EFFQy3r2LaAEuGQcWLTYxwYD6Mew1ykWzZVDy6NwlCG53RVk0sypGo023O0Beo7mJoCLEnz9uCX7IJO6EH9EUtcGARgGuDdy8LJ5pZSO8ul-PisvTT99mZ-XFl8_ns-lF2VWs4aXoKWa8qzTNJWuiGs3z6LBgvJ0IoslkonVdNQJ422LQVZ0nVVW8obQlHWdHxcneux7bAfoulxmUletgBhU20isj_444s5JLfy0bWhNBSBa8vxcE_32EmORgYgfWKgd-jJJWomKYignN6Nt_0Cs_5veymapZzSmnGP8WdsHHGEA_JkOw3HaDzN0gt92Q0Td_Jv8IPnx_Bso9cGMsbP4rkl_ni53wF2ZPwr0</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2535626200</pqid></control><display><type>article</type><title>Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases‐10 coding system: A brief review</title><source>Wiley Online Library - AutoHoldings Journals</source><creator>Nam, Young Hee ; Mendelsohn, Aaron B. ; Panozzo, Catherine A. ; Maro, Judith C. ; Brown, Jeffrey S.</creator><creatorcontrib>Nam, Young Hee ; Mendelsohn, Aaron B. ; Panozzo, Catherine A. ; Maro, Judith C. ; Brown, Jeffrey S.</creatorcontrib><description>Background and purpose
The transition from International Classification of Diseases, 9th revision, clinical modification (ICD‐9‐CM) to ICD‐10‐CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition.
Methods
We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD‐9‐CM and ICD‐10‐CM eras by visual inspection.
Results
We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time‐series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD‐9‐CM and ICD‐10‐CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency.
Conclusions
Researchers using ICD‐10‐CM algorithms obtained by standardized mappings from ICD‐9‐CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates.
Key points
We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD‐9‐CM) and ICD‐10‐CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic).
More than a third of the 140 time‐series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence.
Studies using ICD‐9‐CM‐based algorithms mapped to ICD‐10‐CM codes need to assess the performance of the mappings and conduct manual refinement of the algorithms as needed before using them.</description><identifier>ISSN: 1053-8569</identifier><identifier>EISSN: 1099-1557</identifier><identifier>DOI: 10.1002/pds.5216</identifier><identifier>PMID: 33638243</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Inc</publisher><subject>administrative health care claims ; Algorithms ; Classification ; code mapping ; coding trends ; Epidemiology ; health outcomes ; incidence ; International Classification of Diseases, 9th revision and 10th revision (ICD‐9, ICD‐10) ; Mapping ; Original ; prevalence ; Reviews ; Trends ; US FDA Sentinel</subject><ispartof>Pharmacoepidemiology and drug safety, 2021-07, Vol.30 (7), p.838-842</ispartof><rights>2021 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2021 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.</rights><rights>2021. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4386-9d2036c4f2336f1a8f6f6fc0936b791f177ff5489e6bb0ef450efa446822b1c63</citedby><cites>FETCH-LOGICAL-c4386-9d2036c4f2336f1a8f6f6fc0936b791f177ff5489e6bb0ef450efa446822b1c63</cites><orcidid>0000-0001-7537-0821 ; 0000-0002-4957-8204 ; 0000-0002-9340-7189</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpds.5216$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpds.5216$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33638243$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nam, Young Hee</creatorcontrib><creatorcontrib>Mendelsohn, Aaron B.</creatorcontrib><creatorcontrib>Panozzo, Catherine A.</creatorcontrib><creatorcontrib>Maro, Judith C.</creatorcontrib><creatorcontrib>Brown, Jeffrey S.</creatorcontrib><title>Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases‐10 coding system: A brief review</title><title>Pharmacoepidemiology and drug safety</title><addtitle>Pharmacoepidemiol Drug Saf</addtitle><description>Background and purpose
The transition from International Classification of Diseases, 9th revision, clinical modification (ICD‐9‐CM) to ICD‐10‐CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition.
Methods
We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD‐9‐CM and ICD‐10‐CM eras by visual inspection.
Results
We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time‐series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD‐9‐CM and ICD‐10‐CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency.
Conclusions
Researchers using ICD‐10‐CM algorithms obtained by standardized mappings from ICD‐9‐CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates.
Key points
We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD‐9‐CM) and ICD‐10‐CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic).
More than a third of the 140 time‐series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence.
Studies using ICD‐9‐CM‐based algorithms mapped to ICD‐10‐CM codes need to assess the performance of the mappings and conduct manual refinement of the algorithms as needed before using them.</description><subject>administrative health care claims</subject><subject>Algorithms</subject><subject>Classification</subject><subject>code mapping</subject><subject>coding trends</subject><subject>Epidemiology</subject><subject>health outcomes</subject><subject>incidence</subject><subject>International Classification of Diseases, 9th revision and 10th revision (ICD‐9, ICD‐10)</subject><subject>Mapping</subject><subject>Original</subject><subject>prevalence</subject><subject>Reviews</subject><subject>Trends</subject><subject>US FDA Sentinel</subject><issn>1053-8569</issn><issn>1099-1557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp1kt1qFDEUgAdRbK2CTyABL_Rman5mshMvCsuutYWCwtrrkJk52U3JJGuSadk7H6Fv0_fxSczutvUHJJCEnC8f5ySnKF4TfEwwph_WfTyuKeFPikOChShJXU-ebvc1K5uai4PiRYxXGOeYqJ4XB4xx1tCKHRZ3Z6BsWiE_ps4PEFHne-OWKAVwfUTGobQCdLlAp973SLkezcO4RNN-MM7EFFQy3r2LaAEuGQcWLTYxwYD6Mew1ykWzZVDy6NwlCG53RVk0sypGo023O0Beo7mJoCLEnz9uCX7IJO6EH9EUtcGARgGuDdy8LJ5pZSO8ul-PisvTT99mZ-XFl8_ns-lF2VWs4aXoKWa8qzTNJWuiGs3z6LBgvJ0IoslkonVdNQJ422LQVZ0nVVW8obQlHWdHxcneux7bAfoulxmUletgBhU20isj_444s5JLfy0bWhNBSBa8vxcE_32EmORgYgfWKgd-jJJWomKYignN6Nt_0Cs_5veymapZzSmnGP8WdsHHGEA_JkOw3HaDzN0gt92Q0Td_Jv8IPnx_Bso9cGMsbP4rkl_ni53wF2ZPwr0</recordid><startdate>202107</startdate><enddate>202107</enddate><creator>Nam, Young Hee</creator><creator>Mendelsohn, Aaron B.</creator><creator>Panozzo, Catherine A.</creator><creator>Maro, Judith C.</creator><creator>Brown, Jeffrey S.</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7537-0821</orcidid><orcidid>https://orcid.org/0000-0002-4957-8204</orcidid><orcidid>https://orcid.org/0000-0002-9340-7189</orcidid></search><sort><creationdate>202107</creationdate><title>Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases‐10 coding system: A brief review</title><author>Nam, Young Hee ; Mendelsohn, Aaron B. ; Panozzo, Catherine A. ; Maro, Judith C. ; Brown, Jeffrey S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4386-9d2036c4f2336f1a8f6f6fc0936b791f177ff5489e6bb0ef450efa446822b1c63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>administrative health care claims</topic><topic>Algorithms</topic><topic>Classification</topic><topic>code mapping</topic><topic>coding trends</topic><topic>Epidemiology</topic><topic>health outcomes</topic><topic>incidence</topic><topic>International Classification of Diseases, 9th revision and 10th revision (ICD‐9, ICD‐10)</topic><topic>Mapping</topic><topic>Original</topic><topic>prevalence</topic><topic>Reviews</topic><topic>Trends</topic><topic>US FDA Sentinel</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nam, Young Hee</creatorcontrib><creatorcontrib>Mendelsohn, Aaron B.</creatorcontrib><creatorcontrib>Panozzo, Catherine A.</creatorcontrib><creatorcontrib>Maro, Judith C.</creatorcontrib><creatorcontrib>Brown, Jeffrey S.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Pharmacoepidemiology and drug safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nam, Young Hee</au><au>Mendelsohn, Aaron B.</au><au>Panozzo, Catherine A.</au><au>Maro, Judith C.</au><au>Brown, Jeffrey S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases‐10 coding system: A brief review</atitle><jtitle>Pharmacoepidemiology and drug safety</jtitle><addtitle>Pharmacoepidemiol Drug Saf</addtitle><date>2021-07</date><risdate>2021</risdate><volume>30</volume><issue>7</issue><spage>838</spage><epage>842</epage><pages>838-842</pages><issn>1053-8569</issn><eissn>1099-1557</eissn><abstract>Background and purpose
The transition from International Classification of Diseases, 9th revision, clinical modification (ICD‐9‐CM) to ICD‐10‐CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition.
Methods
We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD‐9‐CM and ICD‐10‐CM eras by visual inspection.
Results
We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time‐series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD‐9‐CM and ICD‐10‐CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency.
Conclusions
Researchers using ICD‐10‐CM algorithms obtained by standardized mappings from ICD‐9‐CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates.
Key points
We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD‐9‐CM) and ICD‐10‐CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic).
More than a third of the 140 time‐series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence.
Studies using ICD‐9‐CM‐based algorithms mapped to ICD‐10‐CM codes need to assess the performance of the mappings and conduct manual refinement of the algorithms as needed before using them.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Inc</pub><pmid>33638243</pmid><doi>10.1002/pds.5216</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0001-7537-0821</orcidid><orcidid>https://orcid.org/0000-0002-4957-8204</orcidid><orcidid>https://orcid.org/0000-0002-9340-7189</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Wiley Online Library - AutoHoldings Journals |
| subjects | administrative health care claims Algorithms Classification code mapping coding trends Epidemiology health outcomes incidence International Classification of Diseases, 9th revision and 10th revision (ICD‐9, ICD‐10) Mapping Original prevalence Reviews Trends US FDA Sentinel |
| title | Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases‐10 coding system: A brief review |
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