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Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records

BACKGROUND: Preventive quality measures for the foster care population are largely untested. The objective of the study is to identify healthcare quality measures for young children and adolescents in foster care and to test whether the data required to calculate these measures can be feasibly extra...

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Autores principales: Deans, Katherine J., Minneci, Peter C., Nacion, Kristine M., Leonhart, Karen, Cooper, Jennifer N., Scholle, Sarah Hudson, Kelleher, Kelly J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5822488/
https://www.ncbi.nlm.nih.gov/pubmed/29471817
http://dx.doi.org/10.1186/s12887-018-1064-4
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author Deans, Katherine J.
Minneci, Peter C.
Nacion, Kristine M.
Leonhart, Karen
Cooper, Jennifer N.
Scholle, Sarah Hudson
Kelleher, Kelly J.
author_facet Deans, Katherine J.
Minneci, Peter C.
Nacion, Kristine M.
Leonhart, Karen
Cooper, Jennifer N.
Scholle, Sarah Hudson
Kelleher, Kelly J.
author_sort Deans, Katherine J.
collection PubMed
description BACKGROUND: Preventive quality measures for the foster care population are largely untested. The objective of the study is to identify healthcare quality measures for young children and adolescents in foster care and to test whether the data required to calculate these measures can be feasibly extracted and interpreted within an electronic health records or within the Statewide Automated Child Welfare Information System. METHODS: The AAP Recommendations for Preventive Pediatric Health Care served as the guideline for determining quality measures. Quality measures related to well child visits, developmental screenings, immunizations, trauma-related care, BMI measurements, sexually transmitted infections and depression were defined. Retrospective chart reviews were performed on a cohort of children in foster care from a single large pediatric institution and related county. Data available in the Ohio Statewide Automated Child Welfare Information System was compared to the same population studied in the electronic health record review. Quality measures were calculated as observed (received) to expected (recommended) ratios (O/E ratios) to describe the actual quantity of recommended health care that was received by individual children. RESULTS: Electronic health records and the Statewide Automated Child Welfare Information System data frequently lacked important information on foster care youth essential for calculating the measures. Although electronic health records were rich in encounter specific clinical data, they often lacked custodial information such as the dates of entry into and exit from foster care. In contrast, Statewide Automated Child Welfare Information System included robust data on custodial arrangements, but lacked detailed medical information. Despite these limitations, several quality measures were devised that attempted to accommodate these limitations. CONCLUSIONS: In this feasibility testing, neither the electronic health records at a single institution nor the county level Statewide Automated Child Welfare Information System was able to independently serve as a reliable source of data for health care quality measures for foster care youth. However, the ability to leverage both sources by matching them at an individual level may provide the complement of data necessary to assess the quality of healthcare.
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spelling pubmed-58224882018-02-26 Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records Deans, Katherine J. Minneci, Peter C. Nacion, Kristine M. Leonhart, Karen Cooper, Jennifer N. Scholle, Sarah Hudson Kelleher, Kelly J. BMC Pediatr Research Article BACKGROUND: Preventive quality measures for the foster care population are largely untested. The objective of the study is to identify healthcare quality measures for young children and adolescents in foster care and to test whether the data required to calculate these measures can be feasibly extracted and interpreted within an electronic health records or within the Statewide Automated Child Welfare Information System. METHODS: The AAP Recommendations for Preventive Pediatric Health Care served as the guideline for determining quality measures. Quality measures related to well child visits, developmental screenings, immunizations, trauma-related care, BMI measurements, sexually transmitted infections and depression were defined. Retrospective chart reviews were performed on a cohort of children in foster care from a single large pediatric institution and related county. Data available in the Ohio Statewide Automated Child Welfare Information System was compared to the same population studied in the electronic health record review. Quality measures were calculated as observed (received) to expected (recommended) ratios (O/E ratios) to describe the actual quantity of recommended health care that was received by individual children. RESULTS: Electronic health records and the Statewide Automated Child Welfare Information System data frequently lacked important information on foster care youth essential for calculating the measures. Although electronic health records were rich in encounter specific clinical data, they often lacked custodial information such as the dates of entry into and exit from foster care. In contrast, Statewide Automated Child Welfare Information System included robust data on custodial arrangements, but lacked detailed medical information. Despite these limitations, several quality measures were devised that attempted to accommodate these limitations. CONCLUSIONS: In this feasibility testing, neither the electronic health records at a single institution nor the county level Statewide Automated Child Welfare Information System was able to independently serve as a reliable source of data for health care quality measures for foster care youth. However, the ability to leverage both sources by matching them at an individual level may provide the complement of data necessary to assess the quality of healthcare. BioMed Central 2018-02-22 /pmc/articles/PMC5822488/ /pubmed/29471817 http://dx.doi.org/10.1186/s12887-018-1064-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Deans, Katherine J.
Minneci, Peter C.
Nacion, Kristine M.
Leonhart, Karen
Cooper, Jennifer N.
Scholle, Sarah Hudson
Kelleher, Kelly J.
Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records
title Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records
title_full Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records
title_fullStr Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records
title_full_unstemmed Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records
title_short Health care quality measures for children and adolescents in Foster Care: feasibility testing in electronic records
title_sort health care quality measures for children and adolescents in foster care: feasibility testing in electronic records
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5822488/
https://www.ncbi.nlm.nih.gov/pubmed/29471817
http://dx.doi.org/10.1186/s12887-018-1064-4
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