Predicting timely transfer to adult care in a cohort of autistic adolescents and young adults
The transition from pediatric to adult care is a challenge for autistic adolescents and young adults. Data on patient features associated with timely transfer between pediatric and adult health care are limited. Our objective was to describe the patient features associated with timely transfer to ad...
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| Veröffentlicht in: | PloS one 2023-09, Vol.18 (9), p.e0289982 |
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| creator | Hart, Laura C Sirrianni, Joseph Rust, Steve Hanks, Christopher |
| description | The transition from pediatric to adult care is a challenge for autistic adolescents and young adults. Data on patient features associated with timely transfer between pediatric and adult health care are limited. Our objective was to describe the patient features associated with timely transfer to adult health care (defined as |
| doi_str_mv | 10.1371/journal.pone.0289982 |
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Data on patient features associated with timely transfer between pediatric and adult health care are limited. Our objective was to describe the patient features associated with timely transfer to adult health care (defined as </ = 6 months between first adult visit and most recent prior pediatric visit) among a cohort of autistic adolescents and young adults. We analyzed pediatric and adult electronic medical record data from a cohort of adolescents and young adults who established with a primary-care based program for autistic adolescents and young adults after they transferred from a single children's hospital. Using forward feature selection and logistic regression, we selected an optimal subset of patient characteristics or features via five repetitions of five-fold cross validation over varying time-frames prior to the first adult visit to identify patient features associated with a timely transfer to adult health care. A total of 224 autistic adolescents and young adults were included. Across all models, total outpatient encounters and total encounters, which are very correlated (r = 0.997), were selected as the first variable in 91.2% the models. These variables predicted timely transfer well, with an area under the receiver-operator curve ranging from 0.81 to 0.88. Total outpatient encounters and total encounters in pediatric care showed good ability to predict timely transfer to adult health care in a population of autistic adolescents and young adults.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0289982</identifier><identifier>PMID: 37703269</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Adolescents ; Adults ; Autism ; Biology and Life Sciences ; Blood pressure ; Codes ; Datasets ; Electronic health records ; Electronic medical records ; Emergency medical care ; Evaluation ; Health aspects ; Health care ; Hospitals ; Immunization ; Medicaid ; Medical records ; Medicare ; Medicine and Health Sciences ; Narcotics ; Patients ; Pediatrics ; People and Places ; Psychological aspects ; Regression analysis ; Social Sciences ; Standard deviation ; Teenagers ; Transitional care ; Uninsured people ; Vaccines ; Web portals ; Young adults ; Youth</subject><ispartof>PloS one, 2023-09, Vol.18 (9), p.e0289982</ispartof><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Hart et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Copyright: © 2023 Hart et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>2023 Hart et al 2023 Hart et al</rights><rights>2023 Hart et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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><cites>FETCH-LOGICAL-c619t-c27fec193c8578c63ea0cfbd278846672476647db770563e515f42c57f13fe8a3</cites><orcidid>0000-0001-8492-7337 ; 0000-0003-0987-7258</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499209/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499209/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids></links><search><creatorcontrib>Hart, Laura C</creatorcontrib><creatorcontrib>Sirrianni, Joseph</creatorcontrib><creatorcontrib>Rust, Steve</creatorcontrib><creatorcontrib>Hanks, Christopher</creatorcontrib><title>Predicting timely transfer to adult care in a cohort of autistic adolescents and young adults</title><title>PloS one</title><description>The transition from pediatric to adult care is a challenge for autistic adolescents and young adults. Data on patient features associated with timely transfer between pediatric and adult health care are limited. Our objective was to describe the patient features associated with timely transfer to adult health care (defined as </ = 6 months between first adult visit and most recent prior pediatric visit) among a cohort of autistic adolescents and young adults. We analyzed pediatric and adult electronic medical record data from a cohort of adolescents and young adults who established with a primary-care based program for autistic adolescents and young adults after they transferred from a single children's hospital. Using forward feature selection and logistic regression, we selected an optimal subset of patient characteristics or features via five repetitions of five-fold cross validation over varying time-frames prior to the first adult visit to identify patient features associated with a timely transfer to adult health care. A total of 224 autistic adolescents and young adults were included. Across all models, total outpatient encounters and total encounters, which are very correlated (r = 0.997), were selected as the first variable in 91.2% the models. These variables predicted timely transfer well, with an area under the receiver-operator curve ranging from 0.81 to 0.88. Total outpatient encounters and total encounters in pediatric care showed good ability to predict timely transfer to adult health care in a population of autistic adolescents and young adults.</description><subject>Adolescents</subject><subject>Adults</subject><subject>Autism</subject><subject>Biology and Life Sciences</subject><subject>Blood pressure</subject><subject>Codes</subject><subject>Datasets</subject><subject>Electronic health records</subject><subject>Electronic medical records</subject><subject>Emergency medical care</subject><subject>Evaluation</subject><subject>Health aspects</subject><subject>Health care</subject><subject>Hospitals</subject><subject>Immunization</subject><subject>Medicaid</subject><subject>Medical records</subject><subject>Medicare</subject><subject>Medicine and Health Sciences</subject><subject>Narcotics</subject><subject>Patients</subject><subject>Pediatrics</subject><subject>People and Places</subject><subject>Psychological aspects</subject><subject>Regression analysis</subject><subject>Social Sciences</subject><subject>Standard deviation</subject><subject>Teenagers</subject><subject>Transitional care</subject><subject>Uninsured people</subject><subject>Vaccines</subject><subject>Web portals</subject><subject>Young 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Data on patient features associated with timely transfer between pediatric and adult health care are limited. Our objective was to describe the patient features associated with timely transfer to adult health care (defined as </ = 6 months between first adult visit and most recent prior pediatric visit) among a cohort of autistic adolescents and young adults. We analyzed pediatric and adult electronic medical record data from a cohort of adolescents and young adults who established with a primary-care based program for autistic adolescents and young adults after they transferred from a single children's hospital. Using forward feature selection and logistic regression, we selected an optimal subset of patient characteristics or features via five repetitions of five-fold cross validation over varying time-frames prior to the first adult visit to identify patient features associated with a timely transfer to adult health care. A total of 224 autistic adolescents and young adults were included. Across all models, total outpatient encounters and total encounters, which are very correlated (r = 0.997), were selected as the first variable in 91.2% the models. These variables predicted timely transfer well, with an area under the receiver-operator curve ranging from 0.81 to 0.88. Total outpatient encounters and total encounters in pediatric care showed good ability to predict timely transfer to adult health care in a population of autistic adolescents and young adults.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>37703269</pmid><doi>10.1371/journal.pone.0289982</doi><tpages>e0289982</tpages><orcidid>https://orcid.org/0000-0001-8492-7337</orcidid><orcidid>https://orcid.org/0000-0003-0987-7258</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adolescents Adults Autism Biology and Life Sciences Blood pressure Codes Datasets Electronic health records Electronic medical records Emergency medical care Evaluation Health aspects Health care Hospitals Immunization Medicaid Medical records Medicare Medicine and Health Sciences Narcotics Patients Pediatrics People and Places Psychological aspects Regression analysis Social Sciences Standard deviation Teenagers Transitional care Uninsured people Vaccines Web portals Young adults Youth |
| title | Predicting timely transfer to adult care in a cohort of autistic adolescents and young adults |
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