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Development of the Children With Disabilities Algorithm
A major impediment to understanding quality of care for children with disabilities (CWD) is the lack of a method for identifying this group in claims databases. We developed the CWD algorithm (CWDA), which uses International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM...
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Published in: | Pediatrics (Evanston) 2015-10, Vol.136 (4), p.e871-e878 |
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creator | Chien, Alyna T Kuhlthau, Karen A Toomey, Sara L Quinn, Jessica A Houtrow, Amy J Kuo, Dennis Z Okumura, Megumi J Van Cleave, Jeanne M Johnson, Chelsea K Mahoney, Lindsey L Martin, Julia Landrum, Mary Beth Schuster, Mark A |
description | A major impediment to understanding quality of care for children with disabilities (CWD) is the lack of a method for identifying this group in claims databases. We developed the CWD algorithm (CWDA), which uses International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify CWD.
We conducted a cross-sectional study that (1) ensured each of the 14,567 codes within the 2012 ICD-9-CM codebook was independently classified by 3 to 9 pediatricians based on the code's likelihood of indicating CWD and (2) triangulated the resulting CWDA against parent and physician assessment of children's disability status by using survey and chart abstraction, respectively. Eight fellowship-trained general pediatricians and 42 subspecialists from across the United States participated in the code classification. Parents of 128 children from a large, free-standing children's hospital participated in the parent survey; charts of 336 children from the same hospital were included in the abstraction study.
CWDA contains 669 ICD-9-CM codes classified as having a ≥75% likelihood of indicating CWD. Examples include 318.2 Profound intellectual disabilities and 780.72 Functional quadriplegia. CWDA sensitivity was 0.75 (95% confidence interval 0.63-0.84) compared with parent report and 0.98 (0.95-0.99) compared with physician assessment; its specificity was 0.86 (0.72-0.95) and 0.50 (0.41-0.59), respectively.
ICD-9-CM codes can be classified by their likelihood of indicating CWD. CWDA triangulates well with parent report and physician assessment of child disability status. CWDA is a new tool that can be used to assess care quality for CWD. |
doi_str_mv | 10.1542/peds.2015-0228 |
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We conducted a cross-sectional study that (1) ensured each of the 14,567 codes within the 2012 ICD-9-CM codebook was independently classified by 3 to 9 pediatricians based on the code's likelihood of indicating CWD and (2) triangulated the resulting CWDA against parent and physician assessment of children's disability status by using survey and chart abstraction, respectively. Eight fellowship-trained general pediatricians and 42 subspecialists from across the United States participated in the code classification. Parents of 128 children from a large, free-standing children's hospital participated in the parent survey; charts of 336 children from the same hospital were included in the abstraction study.
CWDA contains 669 ICD-9-CM codes classified as having a ≥75% likelihood of indicating CWD. Examples include 318.2 Profound intellectual disabilities and 780.72 Functional quadriplegia. CWDA sensitivity was 0.75 (95% confidence interval 0.63-0.84) compared with parent report and 0.98 (0.95-0.99) compared with physician assessment; its specificity was 0.86 (0.72-0.95) and 0.50 (0.41-0.59), respectively.
ICD-9-CM codes can be classified by their likelihood of indicating CWD. CWDA triangulates well with parent report and physician assessment of child disability status. CWDA is a new tool that can be used to assess care quality for CWD.</description><identifier>ISSN: 0031-4005</identifier><identifier>EISSN: 1098-4275</identifier><identifier>DOI: 10.1542/peds.2015-0228</identifier><identifier>PMID: 26416938</identifier><identifier>CODEN: PEDIAU</identifier><language>eng</language><publisher>United States: American Academy of Pediatrics</publisher><subject>Algorithms ; Care and treatment ; Child ; Child Development ; Child, Preschool ; Children ; Children with disabilities ; Cross-Sectional Studies ; Disabilities ; Disability ; Disability Evaluation ; Disabled Children ; Health aspects ; Humans ; International Classification of Diseases ; Learning disabilities ; Medical care ; Medical care (Private) ; Observational studies ; Parents & parenting ; Pediatrics ; Quality management ; Quality of care ; Quality of Health Care ; Sensitivity and Specificity ; United States</subject><ispartof>Pediatrics (Evanston), 2015-10, Vol.136 (4), p.e871-e878</ispartof><rights>Copyright © 2015 by the American Academy of Pediatrics.</rights><rights>Copyright American Academy of Pediatrics Oct 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c401t-bc16f1b9296f2af3140ca43cf10cb9d717f5f87f304b4d7c6e8fafd9ef23fd313</citedby><cites>FETCH-LOGICAL-c401t-bc16f1b9296f2af3140ca43cf10cb9d717f5f87f304b4d7c6e8fafd9ef23fd313</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26416938$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chien, Alyna T</creatorcontrib><creatorcontrib>Kuhlthau, Karen A</creatorcontrib><creatorcontrib>Toomey, Sara L</creatorcontrib><creatorcontrib>Quinn, Jessica A</creatorcontrib><creatorcontrib>Houtrow, Amy J</creatorcontrib><creatorcontrib>Kuo, Dennis Z</creatorcontrib><creatorcontrib>Okumura, Megumi J</creatorcontrib><creatorcontrib>Van Cleave, Jeanne M</creatorcontrib><creatorcontrib>Johnson, Chelsea K</creatorcontrib><creatorcontrib>Mahoney, Lindsey L</creatorcontrib><creatorcontrib>Martin, Julia</creatorcontrib><creatorcontrib>Landrum, Mary Beth</creatorcontrib><creatorcontrib>Schuster, Mark A</creatorcontrib><title>Development of the Children With Disabilities Algorithm</title><title>Pediatrics (Evanston)</title><addtitle>Pediatrics</addtitle><description>A major impediment to understanding quality of care for children with disabilities (CWD) is the lack of a method for identifying this group in claims databases. We developed the CWD algorithm (CWDA), which uses International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify CWD.
We conducted a cross-sectional study that (1) ensured each of the 14,567 codes within the 2012 ICD-9-CM codebook was independently classified by 3 to 9 pediatricians based on the code's likelihood of indicating CWD and (2) triangulated the resulting CWDA against parent and physician assessment of children's disability status by using survey and chart abstraction, respectively. Eight fellowship-trained general pediatricians and 42 subspecialists from across the United States participated in the code classification. Parents of 128 children from a large, free-standing children's hospital participated in the parent survey; charts of 336 children from the same hospital were included in the abstraction study.
CWDA contains 669 ICD-9-CM codes classified as having a ≥75% likelihood of indicating CWD. Examples include 318.2 Profound intellectual disabilities and 780.72 Functional quadriplegia. CWDA sensitivity was 0.75 (95% confidence interval 0.63-0.84) compared with parent report and 0.98 (0.95-0.99) compared with physician assessment; its specificity was 0.86 (0.72-0.95) and 0.50 (0.41-0.59), respectively.
ICD-9-CM codes can be classified by their likelihood of indicating CWD. CWDA triangulates well with parent report and physician assessment of child disability status. CWDA is a new tool that can be used to assess care quality for CWD.</description><subject>Algorithms</subject><subject>Care and treatment</subject><subject>Child</subject><subject>Child Development</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Children with disabilities</subject><subject>Cross-Sectional Studies</subject><subject>Disabilities</subject><subject>Disability</subject><subject>Disability Evaluation</subject><subject>Disabled Children</subject><subject>Health aspects</subject><subject>Humans</subject><subject>International Classification of Diseases</subject><subject>Learning disabilities</subject><subject>Medical care</subject><subject>Medical care (Private)</subject><subject>Observational studies</subject><subject>Parents & parenting</subject><subject>Pediatrics</subject><subject>Quality management</subject><subject>Quality of care</subject><subject>Quality of Health Care</subject><subject>Sensitivity and Specificity</subject><subject>United States</subject><issn>0031-4005</issn><issn>1098-4275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNpd0cFr2zAUBnAxVtYs23XHYtilF6fvSbJkH0O6roNCLi07Clt-SlRkK7Wcsv73tUnbw04PxO-Jj_cx9gNhhYXkVwdq04oDFjlwXn5iC4SqzCXXxWe2ABCYS4DinH1N6REAZKH5F3bOlURViXLB9DU9U4iHjvoxiy4b95Rt9j60A_XZXz_us2uf6sYHP3pK2Trs4jC9dt_YmatDou9vc8kebn7db27zu-3vP5v1XW4l4Jg3FpXDpuKVcrx2AiXYWgrrEGxTtRq1K1ypnQDZyFZbRaWrXVuR48K1AsWSXZ7-PQzx6UhpNJ1PlkKoe4rHZFBjWaEohZzoz__oYzwO_ZRuVpWUQoGeVH5SuzqQ8b2N_Uj_RhtDoB2ZKfxma9ZSiEIpBWryq5O3Q0xpIGcOg-_q4cUgmLkCM1dg5grMXMG0cPEW49h01H7w95uLV_ycgBo</recordid><startdate>201510</startdate><enddate>201510</enddate><creator>Chien, Alyna T</creator><creator>Kuhlthau, Karen A</creator><creator>Toomey, Sara L</creator><creator>Quinn, Jessica A</creator><creator>Houtrow, Amy J</creator><creator>Kuo, Dennis Z</creator><creator>Okumura, Megumi J</creator><creator>Van Cleave, Jeanne M</creator><creator>Johnson, Chelsea K</creator><creator>Mahoney, Lindsey L</creator><creator>Martin, Julia</creator><creator>Landrum, Mary Beth</creator><creator>Schuster, Mark A</creator><general>American Academy of Pediatrics</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>7TS</scope><scope>7U9</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope><scope>NAPCQ</scope><scope>U9A</scope><scope>7X8</scope></search><sort><creationdate>201510</creationdate><title>Development of the Children With Disabilities Algorithm</title><author>Chien, Alyna T ; Kuhlthau, Karen A ; Toomey, Sara L ; Quinn, Jessica A ; Houtrow, Amy J ; Kuo, Dennis Z ; Okumura, Megumi J ; Van Cleave, Jeanne M ; Johnson, Chelsea K ; Mahoney, Lindsey L ; Martin, Julia ; Landrum, Mary Beth ; Schuster, Mark A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c401t-bc16f1b9296f2af3140ca43cf10cb9d717f5f87f304b4d7c6e8fafd9ef23fd313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Care and treatment</topic><topic>Child</topic><topic>Child Development</topic><topic>Child, Preschool</topic><topic>Children</topic><topic>Children with disabilities</topic><topic>Cross-Sectional Studies</topic><topic>Disabilities</topic><topic>Disability</topic><topic>Disability Evaluation</topic><topic>Disabled Children</topic><topic>Health aspects</topic><topic>Humans</topic><topic>International Classification of Diseases</topic><topic>Learning disabilities</topic><topic>Medical care</topic><topic>Medical care (Private)</topic><topic>Observational studies</topic><topic>Parents & parenting</topic><topic>Pediatrics</topic><topic>Quality management</topic><topic>Quality of care</topic><topic>Quality of Health Care</topic><topic>Sensitivity and Specificity</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chien, Alyna T</creatorcontrib><creatorcontrib>Kuhlthau, Karen A</creatorcontrib><creatorcontrib>Toomey, Sara L</creatorcontrib><creatorcontrib>Quinn, Jessica A</creatorcontrib><creatorcontrib>Houtrow, Amy J</creatorcontrib><creatorcontrib>Kuo, Dennis Z</creatorcontrib><creatorcontrib>Okumura, Megumi J</creatorcontrib><creatorcontrib>Van Cleave, Jeanne M</creatorcontrib><creatorcontrib>Johnson, Chelsea K</creatorcontrib><creatorcontrib>Mahoney, Lindsey L</creatorcontrib><creatorcontrib>Martin, Julia</creatorcontrib><creatorcontrib>Landrum, Mary Beth</creatorcontrib><creatorcontrib>Schuster, Mark A</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Physical Education Index</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Pediatrics (Evanston)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chien, Alyna T</au><au>Kuhlthau, Karen A</au><au>Toomey, Sara L</au><au>Quinn, Jessica A</au><au>Houtrow, Amy J</au><au>Kuo, Dennis Z</au><au>Okumura, Megumi J</au><au>Van Cleave, Jeanne M</au><au>Johnson, Chelsea K</au><au>Mahoney, Lindsey L</au><au>Martin, Julia</au><au>Landrum, Mary Beth</au><au>Schuster, Mark A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of the Children With Disabilities Algorithm</atitle><jtitle>Pediatrics (Evanston)</jtitle><addtitle>Pediatrics</addtitle><date>2015-10</date><risdate>2015</risdate><volume>136</volume><issue>4</issue><spage>e871</spage><epage>e878</epage><pages>e871-e878</pages><issn>0031-4005</issn><eissn>1098-4275</eissn><coden>PEDIAU</coden><abstract>A major impediment to understanding quality of care for children with disabilities (CWD) is the lack of a method for identifying this group in claims databases. We developed the CWD algorithm (CWDA), which uses International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify CWD.
We conducted a cross-sectional study that (1) ensured each of the 14,567 codes within the 2012 ICD-9-CM codebook was independently classified by 3 to 9 pediatricians based on the code's likelihood of indicating CWD and (2) triangulated the resulting CWDA against parent and physician assessment of children's disability status by using survey and chart abstraction, respectively. Eight fellowship-trained general pediatricians and 42 subspecialists from across the United States participated in the code classification. Parents of 128 children from a large, free-standing children's hospital participated in the parent survey; charts of 336 children from the same hospital were included in the abstraction study.
CWDA contains 669 ICD-9-CM codes classified as having a ≥75% likelihood of indicating CWD. Examples include 318.2 Profound intellectual disabilities and 780.72 Functional quadriplegia. CWDA sensitivity was 0.75 (95% confidence interval 0.63-0.84) compared with parent report and 0.98 (0.95-0.99) compared with physician assessment; its specificity was 0.86 (0.72-0.95) and 0.50 (0.41-0.59), respectively.
ICD-9-CM codes can be classified by their likelihood of indicating CWD. CWDA triangulates well with parent report and physician assessment of child disability status. CWDA is a new tool that can be used to assess care quality for CWD.</abstract><cop>United States</cop><pub>American Academy of Pediatrics</pub><pmid>26416938</pmid><doi>10.1542/peds.2015-0228</doi><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Care and treatment Child Child Development Child, Preschool Children Children with disabilities Cross-Sectional Studies Disabilities Disability Disability Evaluation Disabled Children Health aspects Humans International Classification of Diseases Learning disabilities Medical care Medical care (Private) Observational studies Parents & parenting Pediatrics Quality management Quality of care Quality of Health Care Sensitivity and Specificity United States |
title | Development of the Children With Disabilities Algorithm |
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