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ICD-10 diagnosis codes in electronic health records do not adequately capture fracture complexity for proximal humerus fractures
The ability to do comparative effectiveness research (CER) for proximal humerus fractures (PHF) using data in electronic health record (EHR) systems and administrative claims databases was enhanced by the 10th revision of the International Classification of Diseases (ICD-10), which expanded the diag...
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| Published in: | Journal of shoulder and elbow surgery 2024-02, Vol.33 (2), p.417-424 |
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| container_title | Journal of shoulder and elbow surgery |
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| creator | Floyd, Sarah B. Walker, J. Todd Smith, Justin T. Jones, Patrick E. Boes, Nathan Lindros, Sydney Carroll, Maile Brooks, John M. Thigpen, Charles A. Pill, Stephan G. Kissenberth, Michael J. |
| description | The ability to do comparative effectiveness research (CER) for proximal humerus fractures (PHF) using data in electronic health record (EHR) systems and administrative claims databases was enhanced by the 10th revision of the International Classification of Diseases (ICD-10), which expanded the diagnosis codes for PHF to describe fracture complexity including displacement and the number of fracture parts. However, these expanded codes only enhance secondary use of data for research if the codes selected and recorded correctly reflect the fracture complexity. The objective of this project was to assess the accuracy of ICD-10 diagnosis codes documented during routine clinical practice for secondary use of EHR data.
A sample of patients with PHFs treated by orthopedic providers across a large, regional health care system between January 1, 2016, and December 31, 2018, were retrospectively identified from the EHR. Four fellowship-trained orthopedic surgeons reviewed patient radiographs and recorded the Neer Classification characteristics of displacement, number of parts, and fracture location(s). The fracture characteristics were then reviewed by a trained coder, and the most clinically appropriate ICD-10 diagnosis code based on the number of fracture parts was assigned. We assessed congruence between ICD-10 codes documented in the EHR and radiograph-validated codes, and assessed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for EHR-documented ICD-10 codes.
There were 761 patients with unilateral, closed PHF who met study inclusion criteria. On average, patients were 67 years of age and 77% were female. Based on radiograph review, 37% were 1-part fractures, 42% were 2-part, 11% were 3-part, and 10% were 4-part fractures. Of the EHR diagnosis codes recorded during clinical practice, 59% were “unspecified” fracture diagnosis codes that did not identify the number of fracture parts. Examination of fracture codes revealed PPV was highest for 1-part (PPV = 0.66, 95% confidence interval [CI] 0.60-0.72) and 4-part fractures (PPV = 0.67, 95% CI 0.13-1.00).
Current diagnosis coding practices do not adequately capture the fracture complexity needed to conduct subgroup analysis for PHF. Conclusions drawn from population studies or large databases using ICD-10 codes for PHF classification should be interpreted within this limitation. Future studies are warranted to improve diagnostic coding to support large observational st |
| doi_str_mv | 10.1016/j.jse.2023.08.022 |
| format | article |
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A sample of patients with PHFs treated by orthopedic providers across a large, regional health care system between January 1, 2016, and December 31, 2018, were retrospectively identified from the EHR. Four fellowship-trained orthopedic surgeons reviewed patient radiographs and recorded the Neer Classification characteristics of displacement, number of parts, and fracture location(s). The fracture characteristics were then reviewed by a trained coder, and the most clinically appropriate ICD-10 diagnosis code based on the number of fracture parts was assigned. We assessed congruence between ICD-10 codes documented in the EHR and radiograph-validated codes, and assessed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for EHR-documented ICD-10 codes.
There were 761 patients with unilateral, closed PHF who met study inclusion criteria. On average, patients were 67 years of age and 77% were female. Based on radiograph review, 37% were 1-part fractures, 42% were 2-part, 11% were 3-part, and 10% were 4-part fractures. Of the EHR diagnosis codes recorded during clinical practice, 59% were “unspecified” fracture diagnosis codes that did not identify the number of fracture parts. Examination of fracture codes revealed PPV was highest for 1-part (PPV = 0.66, 95% confidence interval [CI] 0.60-0.72) and 4-part fractures (PPV = 0.67, 95% CI 0.13-1.00).
Current diagnosis coding practices do not adequately capture the fracture complexity needed to conduct subgroup analysis for PHF. Conclusions drawn from population studies or large databases using ICD-10 codes for PHF classification should be interpreted within this limitation. Future studies are warranted to improve diagnostic coding to support large observational studies using EHR and administrative claims data.</description><identifier>ISSN: 1058-2746</identifier><identifier>EISSN: 1532-6500</identifier><identifier>DOI: 10.1016/j.jse.2023.08.022</identifier><identifier>PMID: 37774829</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; comparative effectiveness research ; Databases, Factual ; diagnosis coding ; Electronic Health Records ; Female ; Humans ; Humeral Fractures ; International Classification of Diseases ; Male ; Neer Classification ; observational studies ; Proximal humerus fracture ; Reproducibility of Results ; Retrospective Studies</subject><ispartof>Journal of shoulder and elbow surgery, 2024-02, Vol.33 (2), p.417-424</ispartof><rights>2023 Journal of Shoulder and Elbow Surgery Board of Trustees</rights><rights>Copyright © 2023 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-524e47ec97ec9790a88d941c76cbb0e6dc64d6d042e24e9ffef19f50c6badf193</citedby><cites>FETCH-LOGICAL-c353t-524e47ec97ec9790a88d941c76cbb0e6dc64d6d042e24e9ffef19f50c6badf193</cites><orcidid>0000-0002-6191-5920 ; 0000-0001-7365-4417 ; 0000-0002-0633-1527 ; 0000-0002-8327-9654 ; 0009-0002-1185-2682 ; 0000-0002-1627-5733 ; 0000-0001-7412-8136</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,786,790,27957,27958</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37774829$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Floyd, Sarah B.</creatorcontrib><creatorcontrib>Walker, J. Todd</creatorcontrib><creatorcontrib>Smith, Justin T.</creatorcontrib><creatorcontrib>Jones, Patrick E.</creatorcontrib><creatorcontrib>Boes, Nathan</creatorcontrib><creatorcontrib>Lindros, Sydney</creatorcontrib><creatorcontrib>Carroll, Maile</creatorcontrib><creatorcontrib>Brooks, John M.</creatorcontrib><creatorcontrib>Thigpen, Charles A.</creatorcontrib><creatorcontrib>Pill, Stephan G.</creatorcontrib><creatorcontrib>Kissenberth, Michael J.</creatorcontrib><title>ICD-10 diagnosis codes in electronic health records do not adequately capture fracture complexity for proximal humerus fractures</title><title>Journal of shoulder and elbow surgery</title><addtitle>J Shoulder Elbow Surg</addtitle><description>The ability to do comparative effectiveness research (CER) for proximal humerus fractures (PHF) using data in electronic health record (EHR) systems and administrative claims databases was enhanced by the 10th revision of the International Classification of Diseases (ICD-10), which expanded the diagnosis codes for PHF to describe fracture complexity including displacement and the number of fracture parts. However, these expanded codes only enhance secondary use of data for research if the codes selected and recorded correctly reflect the fracture complexity. The objective of this project was to assess the accuracy of ICD-10 diagnosis codes documented during routine clinical practice for secondary use of EHR data.
A sample of patients with PHFs treated by orthopedic providers across a large, regional health care system between January 1, 2016, and December 31, 2018, were retrospectively identified from the EHR. Four fellowship-trained orthopedic surgeons reviewed patient radiographs and recorded the Neer Classification characteristics of displacement, number of parts, and fracture location(s). The fracture characteristics were then reviewed by a trained coder, and the most clinically appropriate ICD-10 diagnosis code based on the number of fracture parts was assigned. We assessed congruence between ICD-10 codes documented in the EHR and radiograph-validated codes, and assessed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for EHR-documented ICD-10 codes.
There were 761 patients with unilateral, closed PHF who met study inclusion criteria. On average, patients were 67 years of age and 77% were female. Based on radiograph review, 37% were 1-part fractures, 42% were 2-part, 11% were 3-part, and 10% were 4-part fractures. Of the EHR diagnosis codes recorded during clinical practice, 59% were “unspecified” fracture diagnosis codes that did not identify the number of fracture parts. Examination of fracture codes revealed PPV was highest for 1-part (PPV = 0.66, 95% confidence interval [CI] 0.60-0.72) and 4-part fractures (PPV = 0.67, 95% CI 0.13-1.00).
Current diagnosis coding practices do not adequately capture the fracture complexity needed to conduct subgroup analysis for PHF. Conclusions drawn from population studies or large databases using ICD-10 codes for PHF classification should be interpreted within this limitation. Future studies are warranted to improve diagnostic coding to support large observational studies using EHR and administrative claims data.</description><subject>Aged</subject><subject>comparative effectiveness research</subject><subject>Databases, Factual</subject><subject>diagnosis coding</subject><subject>Electronic Health Records</subject><subject>Female</subject><subject>Humans</subject><subject>Humeral Fractures</subject><subject>International Classification of Diseases</subject><subject>Male</subject><subject>Neer Classification</subject><subject>observational studies</subject><subject>Proximal humerus fracture</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><issn>1058-2746</issn><issn>1532-6500</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PHDEQhq2IKHwkP4AGuaTZZez9tFJFRxKQkGiS2vKNZ3M-7a4P2xtxHT89hiOUFJbf4plXMw9j5wJKAaK92pbbSKUEWZXQlyDlB3YimkoWbQNwlDM0fSG7uj1mpzFuAUDVID-x46rrurqX6oQ93a6uCwHcOvNn9tFFjt5S5G7mNBKm4GeHfENmTBseCH2wkVvPZ5-4sfSwmETjnqPZpSUQH4LBl4B-2o306NKeDz7wXfCPbjIj3ywThSW-gfEz-ziYMdKX1_-M_f7x_dfqpri7_3m7-nZXYNVUqWhkTXVHqF6eAtP3VtUCuxbXa6DWYlvb1kItKZNqGGgQamgA27WxOVZn7PLQm1d5WCgmPbmINI5mJr9ELfsOlJKV7DMqDigGH2OgQe9CXj7stQD9LF5vdRavn8Vr6HUWn2cuXuuX9UT2beK_6Qx8PQCUj_zrKOiIjmYk67LWpK1379T_Ayvplqo</recordid><startdate>202402</startdate><enddate>202402</enddate><creator>Floyd, Sarah B.</creator><creator>Walker, J. Todd</creator><creator>Smith, Justin T.</creator><creator>Jones, Patrick E.</creator><creator>Boes, Nathan</creator><creator>Lindros, Sydney</creator><creator>Carroll, Maile</creator><creator>Brooks, John M.</creator><creator>Thigpen, Charles A.</creator><creator>Pill, Stephan G.</creator><creator>Kissenberth, Michael J.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-6191-5920</orcidid><orcidid>https://orcid.org/0000-0001-7365-4417</orcidid><orcidid>https://orcid.org/0000-0002-0633-1527</orcidid><orcidid>https://orcid.org/0000-0002-8327-9654</orcidid><orcidid>https://orcid.org/0009-0002-1185-2682</orcidid><orcidid>https://orcid.org/0000-0002-1627-5733</orcidid><orcidid>https://orcid.org/0000-0001-7412-8136</orcidid></search><sort><creationdate>202402</creationdate><title>ICD-10 diagnosis codes in electronic health records do not adequately capture fracture complexity for proximal humerus fractures</title><author>Floyd, Sarah B. ; Walker, J. 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Todd</creatorcontrib><creatorcontrib>Smith, Justin T.</creatorcontrib><creatorcontrib>Jones, Patrick E.</creatorcontrib><creatorcontrib>Boes, Nathan</creatorcontrib><creatorcontrib>Lindros, Sydney</creatorcontrib><creatorcontrib>Carroll, Maile</creatorcontrib><creatorcontrib>Brooks, John M.</creatorcontrib><creatorcontrib>Thigpen, Charles A.</creatorcontrib><creatorcontrib>Pill, Stephan G.</creatorcontrib><creatorcontrib>Kissenberth, Michael J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of shoulder and elbow surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Floyd, Sarah B.</au><au>Walker, J. Todd</au><au>Smith, Justin T.</au><au>Jones, Patrick E.</au><au>Boes, Nathan</au><au>Lindros, Sydney</au><au>Carroll, Maile</au><au>Brooks, John M.</au><au>Thigpen, Charles A.</au><au>Pill, Stephan G.</au><au>Kissenberth, Michael J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>ICD-10 diagnosis codes in electronic health records do not adequately capture fracture complexity for proximal humerus fractures</atitle><jtitle>Journal of shoulder and elbow surgery</jtitle><addtitle>J Shoulder Elbow Surg</addtitle><date>2024-02</date><risdate>2024</risdate><volume>33</volume><issue>2</issue><spage>417</spage><epage>424</epage><pages>417-424</pages><issn>1058-2746</issn><eissn>1532-6500</eissn><notes>ObjectType-Article-1</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-2</notes><notes>content type line 23</notes><abstract>The ability to do comparative effectiveness research (CER) for proximal humerus fractures (PHF) using data in electronic health record (EHR) systems and administrative claims databases was enhanced by the 10th revision of the International Classification of Diseases (ICD-10), which expanded the diagnosis codes for PHF to describe fracture complexity including displacement and the number of fracture parts. However, these expanded codes only enhance secondary use of data for research if the codes selected and recorded correctly reflect the fracture complexity. The objective of this project was to assess the accuracy of ICD-10 diagnosis codes documented during routine clinical practice for secondary use of EHR data.
A sample of patients with PHFs treated by orthopedic providers across a large, regional health care system between January 1, 2016, and December 31, 2018, were retrospectively identified from the EHR. Four fellowship-trained orthopedic surgeons reviewed patient radiographs and recorded the Neer Classification characteristics of displacement, number of parts, and fracture location(s). The fracture characteristics were then reviewed by a trained coder, and the most clinically appropriate ICD-10 diagnosis code based on the number of fracture parts was assigned. We assessed congruence between ICD-10 codes documented in the EHR and radiograph-validated codes, and assessed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for EHR-documented ICD-10 codes.
There were 761 patients with unilateral, closed PHF who met study inclusion criteria. On average, patients were 67 years of age and 77% were female. Based on radiograph review, 37% were 1-part fractures, 42% were 2-part, 11% were 3-part, and 10% were 4-part fractures. Of the EHR diagnosis codes recorded during clinical practice, 59% were “unspecified” fracture diagnosis codes that did not identify the number of fracture parts. Examination of fracture codes revealed PPV was highest for 1-part (PPV = 0.66, 95% confidence interval [CI] 0.60-0.72) and 4-part fractures (PPV = 0.67, 95% CI 0.13-1.00).
Current diagnosis coding practices do not adequately capture the fracture complexity needed to conduct subgroup analysis for PHF. Conclusions drawn from population studies or large databases using ICD-10 codes for PHF classification should be interpreted within this limitation. Future studies are warranted to improve diagnostic coding to support large observational studies using EHR and administrative claims data.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>37774829</pmid><doi>10.1016/j.jse.2023.08.022</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-6191-5920</orcidid><orcidid>https://orcid.org/0000-0001-7365-4417</orcidid><orcidid>https://orcid.org/0000-0002-0633-1527</orcidid><orcidid>https://orcid.org/0000-0002-8327-9654</orcidid><orcidid>https://orcid.org/0009-0002-1185-2682</orcidid><orcidid>https://orcid.org/0000-0002-1627-5733</orcidid><orcidid>https://orcid.org/0000-0001-7412-8136</orcidid></addata></record> |
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| source | ScienceDirect Journals |
| subjects | Aged comparative effectiveness research Databases, Factual diagnosis coding Electronic Health Records Female Humans Humeral Fractures International Classification of Diseases Male Neer Classification observational studies Proximal humerus fracture Reproducibility of Results Retrospective Studies |
| title | ICD-10 diagnosis codes in electronic health records do not adequately capture fracture complexity for proximal humerus fractures |
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