Validation of case identification for alopecia areata using international classification of diseases coding
Background: Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. Objectives: The aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 1...
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          | Published in | International journal of trichology Vol. 12; no. 5; pp. 234 - 237 | 
|---|---|
| Main Authors | , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        India
          Wolters Kluwer India Pvt. Ltd
    
        01.09.2020
     Medknow Publications and Media Pvt. Ltd Medknow Publications & Media Pvt. Ltd Wolters Kluwer - Medknow  | 
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| Online Access | Get full text | 
| ISSN | 0974-7753 0974-9241 0974-9241  | 
| DOI | 10.4103/ijt.ijt_67_20 | 
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| Abstract | Background: Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. Objectives: The aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 10 code for AA have a true diagnosis of AA. Materials and Methods: A multicenter retrospective review was performed at Columbia University Irving Medical Center, Brigham and Women's Hospital, and Massachusetts General Hospital to determine whether patients with an ICD 9 codes (704.01 - AA) or ICD 10 codes (L63.0 -Alopecia Totalis, L63.1 - Alopecia Universalis, L63.2 - Ophiasis, L63.8 - other AA, and L63.9 - AA, unspecified) for AA met diagnostic criteria for the disease. Results: Of 880 charts, 97.5% had physical examination findings consistent with AA, and 90% had an unequivocal diagnosis. AA was diagnosed by a dermatologist in 87% of the charts. The positive predictive value (PPV) of the ICD 9 code 704.01 was 97% (248/255). The PPV for the ICD 10 codes were 64% (75/118) for L63.0, 86% (130/151) for L63.1, 50% (1/2) for L63.2, 91% (81/89) for L63.8, and 93% (247/265) for L63.9. Overall, 89% (782/880) of patients with an ICD code for AA were deemed to have a true diagnosis of AA. Conclusions: Patients whose medical records contain an AA-associated ICD code have a high probability of having the condition. | 
    
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| AbstractList | Background: Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. Objectives: The aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 10 code for AA have a true diagnosis of AA. Materials and Methods: A multicenter retrospective review was performed at Columbia University Irving Medical Center, Brigham and Women's Hospital, and Massachusetts General Hospital to determine whether patients with an ICD 9 codes (704.01 - AA) or ICD 10 codes (L63.0 -Alopecia Totalis, L63.1 - Alopecia Universalis, L63.2 - Ophiasis, L63.8 - other AA, and L63.9 - AA, unspecified) for AA met diagnostic criteria for the disease. Results: Of 880 charts, 97.5% had physical examination findings consistent with AA, and 90% had an unequivocal diagnosis. AA was diagnosed by a dermatologist in 87% of the charts. The positive predictive value (PPV) of the ICD 9 code 704.01 was 97% (248/255). The PPV for the ICD 10 codes were 64% (75/118) for L63.0, 86% (130/151) for L63.1, 50% (1/2) for L63.2, 91% (81/89) for L63.8, and 93% (247/265) for L63.9. Overall, 89% (782/880) of patients with an ICD code for AA were deemed to have a true diagnosis of AA. Conclusions: Patients whose medical records contain an AA-associated ICD code have a high probability of having the condition. Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. The aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 10 code for AA have a true diagnosis of AA. A multicenter retrospective review was performed at Columbia University Irving Medical Center, Brigham and Women's Hospital, and Massachusetts General Hospital to determine whether patients with an ICD 9 codes (704.01 - AA) or ICD 10 codes (L63.0 -Alopecia Totalis, L63.1 - Alopecia Universalis, L63.2 - Ophiasis, L63.8 - other AA, and L63.9 - AA, unspecified) for AA met diagnostic criteria for the disease. Of 880 charts, 97.5% had physical examination findings consistent with AA, and 90% had an unequivocal diagnosis. AA was diagnosed by a dermatologist in 87% of the charts. The positive predictive value (PPV) of the ICD 9 code 704.01 was 97% (248/255). The PPV for the ICD 10 codes were 64% (75/118) for L63.0, 86% (130/151) for L63.1, 50% (1/2) for L63.2, 91% (81/89) for L63.8, and 93% (247/265) for L63.9. Overall, 89% (782/880) of patients with an ICD code for AA were deemed to have a true diagnosis of AA. Patients whose medical records contain an AA-associated ICD code have a high probability of having the condition. Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases.BACKGROUNDSearch algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases.The aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 10 code for AA have a true diagnosis of AA.OBJECTIVESThe aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 10 code for AA have a true diagnosis of AA.A multicenter retrospective review was performed at Columbia University Irving Medical Center, Brigham and Women's Hospital, and Massachusetts General Hospital to determine whether patients with an ICD 9 codes (704.01 - AA) or ICD 10 codes (L63.0 -Alopecia Totalis, L63.1 - Alopecia Universalis, L63.2 - Ophiasis, L63.8 - other AA, and L63.9 - AA, unspecified) for AA met diagnostic criteria for the disease.MATERIALS AND METHODSA multicenter retrospective review was performed at Columbia University Irving Medical Center, Brigham and Women's Hospital, and Massachusetts General Hospital to determine whether patients with an ICD 9 codes (704.01 - AA) or ICD 10 codes (L63.0 -Alopecia Totalis, L63.1 - Alopecia Universalis, L63.2 - Ophiasis, L63.8 - other AA, and L63.9 - AA, unspecified) for AA met diagnostic criteria for the disease.Of 880 charts, 97.5% had physical examination findings consistent with AA, and 90% had an unequivocal diagnosis. AA was diagnosed by a dermatologist in 87% of the charts. The positive predictive value (PPV) of the ICD 9 code 704.01 was 97% (248/255). The PPV for the ICD 10 codes were 64% (75/118) for L63.0, 86% (130/151) for L63.1, 50% (1/2) for L63.2, 91% (81/89) for L63.8, and 93% (247/265) for L63.9. Overall, 89% (782/880) of patients with an ICD code for AA were deemed to have a true diagnosis of AA.RESULTSOf 880 charts, 97.5% had physical examination findings consistent with AA, and 90% had an unequivocal diagnosis. AA was diagnosed by a dermatologist in 87% of the charts. The positive predictive value (PPV) of the ICD 9 code 704.01 was 97% (248/255). The PPV for the ICD 10 codes were 64% (75/118) for L63.0, 86% (130/151) for L63.1, 50% (1/2) for L63.2, 91% (81/89) for L63.8, and 93% (247/265) for L63.9. Overall, 89% (782/880) of patients with an ICD code for AA were deemed to have a true diagnosis of AA.Patients whose medical records contain an AA-associated ICD code have a high probability of having the condition.CONCLUSIONSPatients whose medical records contain an AA-associated ICD code have a high probability of having the condition.  | 
    
| Audience | Academic | 
    
| Author | Lee, Eunice Christiano, Angela Mostaghimi, Arash Li, Sara Lavian, Jonathan Bordone, Lindsey G. Polubriaginof, Fernanda  | 
    
| AuthorAffiliation | 2 Department of Dermatology, Brigham and Woman's Hospital, Harvard Medical School, Boston, MA, USA 3 Division of Health Informatics, Memorial Sloan Kettering Cancer Center, New York, NY, USA 4 Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY, USA 1 Department of Dermatology, Columbia University Irving Medical Center, New York, NY, USA  | 
    
| AuthorAffiliation_xml | – name: 3 Division of Health Informatics, Memorial Sloan Kettering Cancer Center, New York, NY, USA – name: 4 Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY, USA – name: 1 Department of Dermatology, Columbia University Irving Medical Center, New York, NY, USA – name: 2 Department of Dermatology, Brigham and Woman's Hospital, Harvard Medical School, Boston, MA, USA  | 
    
| Author_xml | – sequence: 1 givenname: Jonathan surname: Lavian fullname: Lavian, Jonathan organization: Department of Dermatology, Columbia University Irving Medical Center, New York, NY – sequence: 2 givenname: Sara surname: Li fullname: Li, Sara organization: Department of Dermatology, Brigham and Woman's Hospital, Harvard Medical School, Boston, MA – sequence: 3 givenname: Eunice surname: Lee fullname: Lee, Eunice organization: Department of Dermatology, Columbia University Irving Medical Center, New York, NY – sequence: 4 givenname: Lindsey surname: Bordone fullname: Bordone, Lindsey organization: Department of Dermatology, Columbia University Irving Medical Center, New York, NY – sequence: 5 givenname: Fernanda surname: G. Polubriaginof fullname: G. Polubriaginof, Fernanda organization: Division of Health Informatics, Memorial Sloan Kettering Cancer Center, New York, NY – sequence: 6 givenname: Angela surname: Christiano fullname: Christiano, Angela organization: Department of Dermatology; Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY – sequence: 7 givenname: Arash surname: Mostaghimi fullname: Mostaghimi, Arash organization: Department of Dermatology, Brigham and Woman's Hospital, Harvard Medical School, Boston, MA  | 
    
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33531746$$D View this record in MEDLINE/PubMed | 
    
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| CitedBy_id | crossref_primary_10_1159_000533247 crossref_primary_10_1007_s00403_024_03042_9 crossref_primary_10_1111_jocd_70076 crossref_primary_10_1001_jamadermatol_2021_0144 crossref_primary_10_36469_jheor_2022_36229 crossref_primary_10_1016_j_bj_2025_100837 crossref_primary_10_1016_j_jaad_2022_05_005 crossref_primary_10_1001_jamadermatol_2024_2404 crossref_primary_10_1007_s00403_024_03477_0 crossref_primary_10_1080_13696998_2023_2188843 crossref_primary_10_36469_001c_36229 crossref_primary_10_1001_jamadermatol_2023_0016 crossref_primary_10_1002_pds_5782 crossref_primary_10_1001_jamadermatol_2023_3109 crossref_primary_10_1001_jamadermatol_2021_1570 crossref_primary_10_18553_jmcp_2022_28_4_426 crossref_primary_10_1002_jmv_29668 crossref_primary_10_1177_12034754241239907 crossref_primary_10_1001_jamadermatol_2023_0002 crossref_primary_10_1007_s13555_022_00710_4 crossref_primary_10_1007_s13555_024_01218_9 crossref_primary_10_1016_j_jaad_2023_09_012 crossref_primary_10_2340_actadv_v103_12445  | 
    
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| Keywords | positive predictive value database validation Alopecia areata international classification of diseases  | 
    
| Language | English | 
    
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| Snippet | Background: Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. Objectives: The aim of... Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. The aim of the study is to assess... Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases.BACKGROUNDSearch algorithms used to...  | 
    
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| StartPage | 234 | 
    
| SubjectTerms | Alopecia Baldness Charts Classification Codes Diagnosis Health care facilities Medical centers Medical research Medicine, Experimental Original Search algorithms Statistical analysis  | 
    
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| Title | Validation of case identification for alopecia areata using international classification of diseases coding | 
    
| URI | http://www.ijtrichology.com/article.asp?issn=0974-7753;year=2020;volume=12;issue=5;spage=234;epage=237;aulast=Lavian;type=0 https://www.ncbi.nlm.nih.gov/pubmed/33531746 https://www.proquest.com/docview/2532639436 https://www.proquest.com/docview/2487152417 https://pubmed.ncbi.nlm.nih.gov/PMC7832161 https://www.ncbi.nlm.nih.gov/pmc/articles/7832161  | 
    
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