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Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol
INTRODUCTION: Children with medical complexity and their families are an important population of interest within the Canadian healthcare system. Despite representing less than 1% of the paediatric population, children with medical complexity require extensive care and account for one third of paedia...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935171/ https://www.ncbi.nlm.nih.gov/pubmed/35304399 http://dx.doi.org/10.1136/bmjopen-2021-057843 |
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author | McCulloch, Holly Breneol, Sydney Stewart, Samuel A Magalhaes, Sandra Somerville, Mari Sheriko, Jordan Best, Shauna Burgess, Stacy Jeffers, Elizabeth Standing, Mary-Ann King, Sarah Clegg, Julie Curran, Janet A |
author_facet | McCulloch, Holly Breneol, Sydney Stewart, Samuel A Magalhaes, Sandra Somerville, Mari Sheriko, Jordan Best, Shauna Burgess, Stacy Jeffers, Elizabeth Standing, Mary-Ann King, Sarah Clegg, Julie Curran, Janet A |
author_sort | McCulloch, Holly |
collection | PubMed |
description | INTRODUCTION: Children with medical complexity and their families are an important population of interest within the Canadian healthcare system. Despite representing less than 1% of the paediatric population, children with medical complexity require extensive care and account for one third of paediatric healthcare expenditures. Opportunities to conduct research to assess disparities in care and appropriate allocation of health resources relies on the ability to accurately identify this heterogeneous group of children. This study aims to better understand the population of children with medical complexity in the Canadian Maritimes, including Nova Scotia (NS), New Brunswick (NB) and Prince Edward Island (PEI). This will be achieved through three objectives: (1) Evaluate the performance of three algorithms to identify children with medical complexity in the Canadian Maritimes in administrative data; then using the ‘best fit’ algorithm (2) Estimate the prevalence of children with medical complexity in the Canadian Maritimes from 2003 to 2017 and (3) Describe patterns of healthcare utilisation for this cohort of children across the Canadian Maritimes. METHODS AND ANALYSIS: The research will be conducted in three phases. In Phase 1, an expert panel will codevelop a gold-standard definition of paediatric medical complexity relevant to the Canadian Maritime population. A two-gate validation process will then be conducted using NS data and the gold-standard definition to determine the ‘best fit’ algorithm. During phase 2 the ‘best fit’ algorithm will be applied to estimate the prevalence of children with medical complexity in NS, NB and PEI. Finally, in phase 3 will describe patterns of healthcare utilisation across the Canadian Maritimes. ETHICS AND DISSEMINATION: Ethics approval for this protocol was granted by the institutional research ethics board at the IWK Health Centre (REB # 1026245). A waiver of consent was approved. This study will use an integrated knowledge translation approach, where end users are involved in each stage of the project, which could increase uptake of the research into policy and practice. The findings of this research study will be submitted for publication and dissemination through conference presentations and with our end users. |
format | Online Article Text |
id | pubmed-8935171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-89351712022-04-01 Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol McCulloch, Holly Breneol, Sydney Stewart, Samuel A Magalhaes, Sandra Somerville, Mari Sheriko, Jordan Best, Shauna Burgess, Stacy Jeffers, Elizabeth Standing, Mary-Ann King, Sarah Clegg, Julie Curran, Janet A BMJ Open Paediatrics INTRODUCTION: Children with medical complexity and their families are an important population of interest within the Canadian healthcare system. Despite representing less than 1% of the paediatric population, children with medical complexity require extensive care and account for one third of paediatric healthcare expenditures. Opportunities to conduct research to assess disparities in care and appropriate allocation of health resources relies on the ability to accurately identify this heterogeneous group of children. This study aims to better understand the population of children with medical complexity in the Canadian Maritimes, including Nova Scotia (NS), New Brunswick (NB) and Prince Edward Island (PEI). This will be achieved through three objectives: (1) Evaluate the performance of three algorithms to identify children with medical complexity in the Canadian Maritimes in administrative data; then using the ‘best fit’ algorithm (2) Estimate the prevalence of children with medical complexity in the Canadian Maritimes from 2003 to 2017 and (3) Describe patterns of healthcare utilisation for this cohort of children across the Canadian Maritimes. METHODS AND ANALYSIS: The research will be conducted in three phases. In Phase 1, an expert panel will codevelop a gold-standard definition of paediatric medical complexity relevant to the Canadian Maritime population. A two-gate validation process will then be conducted using NS data and the gold-standard definition to determine the ‘best fit’ algorithm. During phase 2 the ‘best fit’ algorithm will be applied to estimate the prevalence of children with medical complexity in NS, NB and PEI. Finally, in phase 3 will describe patterns of healthcare utilisation across the Canadian Maritimes. ETHICS AND DISSEMINATION: Ethics approval for this protocol was granted by the institutional research ethics board at the IWK Health Centre (REB # 1026245). A waiver of consent was approved. This study will use an integrated knowledge translation approach, where end users are involved in each stage of the project, which could increase uptake of the research into policy and practice. The findings of this research study will be submitted for publication and dissemination through conference presentations and with our end users. BMJ Publishing Group 2022-03-18 /pmc/articles/PMC8935171/ /pubmed/35304399 http://dx.doi.org/10.1136/bmjopen-2021-057843 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Paediatrics McCulloch, Holly Breneol, Sydney Stewart, Samuel A Magalhaes, Sandra Somerville, Mari Sheriko, Jordan Best, Shauna Burgess, Stacy Jeffers, Elizabeth Standing, Mary-Ann King, Sarah Clegg, Julie Curran, Janet A Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol |
title | Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol |
title_full | Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol |
title_fullStr | Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol |
title_full_unstemmed | Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol |
title_short | Identifying children with medical complexity in administrative datasets in a Canadian context: study protocol |
title_sort | identifying children with medical complexity in administrative datasets in a canadian context: study protocol |
topic | Paediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935171/ https://www.ncbi.nlm.nih.gov/pubmed/35304399 http://dx.doi.org/10.1136/bmjopen-2021-057843 |
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