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Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years

IMPORTANCE: Readmission is often considered a hospital quality measure, yet no validated risk prediction models exist for children. OBJECTIVE: To develop and validate a tool identifying patients before hospital discharge who are at risk for subsequent readmission, applicable to all ages. DESIGN, SET...

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Autores principales: Goodman, Denise M., Casale, Mia T., Rychlik, Karen, Carroll, Michael S., Auger, Katherine A., Smith, Tracie L., Cartland, Jenifer, Davis, Matthew M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652755/
https://www.ncbi.nlm.nih.gov/pubmed/36367725
http://dx.doi.org/10.1001/jamanetworkopen.2022.41513
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author Goodman, Denise M.
Casale, Mia T.
Rychlik, Karen
Carroll, Michael S.
Auger, Katherine A.
Smith, Tracie L.
Cartland, Jenifer
Davis, Matthew M.
author_facet Goodman, Denise M.
Casale, Mia T.
Rychlik, Karen
Carroll, Michael S.
Auger, Katherine A.
Smith, Tracie L.
Cartland, Jenifer
Davis, Matthew M.
author_sort Goodman, Denise M.
collection PubMed
description IMPORTANCE: Readmission is often considered a hospital quality measure, yet no validated risk prediction models exist for children. OBJECTIVE: To develop and validate a tool identifying patients before hospital discharge who are at risk for subsequent readmission, applicable to all ages. DESIGN, SETTING, AND PARTICIPANTS: This population-based prognostic analysis used electronic health record–derived data from a freestanding children’s hospital from January 1, 2016, to December 31, 2019. All-cause 30-day readmission was modeled using 3 years of discharge data. Data were analyzed from June 1 to November 30, 2021. MAIN OUTCOMES AND MEASURES: Three models were derived as a complementary suite to include (1) children 6 months or older with 1 or more prior hospitalizations within the last 6 months (recent admission model [RAM]), (2) children 6 months or older with no prior hospitalizations in the last 6 months (new admission model [NAM]), and (3) children younger than 6 months (young infant model [YIM]). Generalized mixed linear models were used for all analyses. Models were validated using an additional year of discharges. RESULTS: The derivation set contained 29 988 patients with 48 019 hospitalizations; 50.1% of these admissions were for children younger than 5 years and 54.7% were boys. In the derivation set, 4878 of 13 490 admissions (36.2%) in the RAM cohort, 2044 of 27 531 (7.4%) in the NAM cohort, and 855 of 6998 (12.2%) in the YIM cohort were followed within 30 days by a readmission. In the RAM cohort, prior utilization, current or prior procedures indicative of severity of illness (transfusion, ventilation, or central venous catheter), commercial insurance, and prolonged length of stay (LOS) were associated with readmission. In the NAM cohort, procedures, prolonged LOS, and emergency department visit in the past 6 months were associated with readmission. In the YIM cohort, LOS, prior visits, and critical procedures were associated with readmission. The area under the receiver operating characteristics curve was 83.1 (95% CI, 82.4-83.8) for the RAM cohort, 76.1 (95% CI, 75.0-77.2) for the NAM cohort, and 80.3 (95% CI, 78.8-81.9) for the YIM cohort. CONCLUSIONS AND RELEVANCE: In this prognostic study, the suite of 3 prediction models had acceptable to excellent discrimination for children. These models may allow future improvements in tailored discharge preparedness to prevent high-risk readmissions.
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spelling pubmed-96527552022-11-28 Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years Goodman, Denise M. Casale, Mia T. Rychlik, Karen Carroll, Michael S. Auger, Katherine A. Smith, Tracie L. Cartland, Jenifer Davis, Matthew M. JAMA Netw Open Original Investigation IMPORTANCE: Readmission is often considered a hospital quality measure, yet no validated risk prediction models exist for children. OBJECTIVE: To develop and validate a tool identifying patients before hospital discharge who are at risk for subsequent readmission, applicable to all ages. DESIGN, SETTING, AND PARTICIPANTS: This population-based prognostic analysis used electronic health record–derived data from a freestanding children’s hospital from January 1, 2016, to December 31, 2019. All-cause 30-day readmission was modeled using 3 years of discharge data. Data were analyzed from June 1 to November 30, 2021. MAIN OUTCOMES AND MEASURES: Three models were derived as a complementary suite to include (1) children 6 months or older with 1 or more prior hospitalizations within the last 6 months (recent admission model [RAM]), (2) children 6 months or older with no prior hospitalizations in the last 6 months (new admission model [NAM]), and (3) children younger than 6 months (young infant model [YIM]). Generalized mixed linear models were used for all analyses. Models were validated using an additional year of discharges. RESULTS: The derivation set contained 29 988 patients with 48 019 hospitalizations; 50.1% of these admissions were for children younger than 5 years and 54.7% were boys. In the derivation set, 4878 of 13 490 admissions (36.2%) in the RAM cohort, 2044 of 27 531 (7.4%) in the NAM cohort, and 855 of 6998 (12.2%) in the YIM cohort were followed within 30 days by a readmission. In the RAM cohort, prior utilization, current or prior procedures indicative of severity of illness (transfusion, ventilation, or central venous catheter), commercial insurance, and prolonged length of stay (LOS) were associated with readmission. In the NAM cohort, procedures, prolonged LOS, and emergency department visit in the past 6 months were associated with readmission. In the YIM cohort, LOS, prior visits, and critical procedures were associated with readmission. The area under the receiver operating characteristics curve was 83.1 (95% CI, 82.4-83.8) for the RAM cohort, 76.1 (95% CI, 75.0-77.2) for the NAM cohort, and 80.3 (95% CI, 78.8-81.9) for the YIM cohort. CONCLUSIONS AND RELEVANCE: In this prognostic study, the suite of 3 prediction models had acceptable to excellent discrimination for children. These models may allow future improvements in tailored discharge preparedness to prevent high-risk readmissions. American Medical Association 2022-11-11 /pmc/articles/PMC9652755/ /pubmed/36367725 http://dx.doi.org/10.1001/jamanetworkopen.2022.41513 Text en Copyright 2022 Goodman DM et al. JAMA Network Open. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the CC-BY License.
spellingShingle Original Investigation
Goodman, Denise M.
Casale, Mia T.
Rychlik, Karen
Carroll, Michael S.
Auger, Katherine A.
Smith, Tracie L.
Cartland, Jenifer
Davis, Matthew M.
Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years
title Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years
title_full Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years
title_fullStr Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years
title_full_unstemmed Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years
title_short Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years
title_sort development and validation of an integrated suite of prediction models for all-cause 30-day readmissions of children and adolescents aged 0 to 18 years
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652755/
https://www.ncbi.nlm.nih.gov/pubmed/36367725
http://dx.doi.org/10.1001/jamanetworkopen.2022.41513
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