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Using Canadian administrative health data to examine the health of caregivers of children with and without health problems: A demonstration of feasibility

Authors :
Jamie C, Brehaut
Anne, Guèvremont
Rubab G, Arim
Rochelle E, Garner
Anton R, Miller
Kimberlyn M, McGrail
Marni, Brownell
Lucyna M, Lach
Peter L, Rosenbaum
Dafna E, Kohen
Source :
International Journal of Population Data Science
Publication Year :
2020

Abstract

Introduction Caregivers of children with health problems experience poorer health than the caregivers of healthy children. To date, population-based studies on this issue have primarily used survey data. Objectives We demonstrate that administrative health data may be used to study these issues, and explore how non-categorical indicators of child health in administrative data can enable population-level study of caregiver health. Methods Dyads from Population Data British Columbia (BC) databases, encompassing nearly all mothers in BC with children aged 6-10 years in 2006, were grouped using a non-categorical definition based on diagnoses and service use. Regression models examined whether four maternal health outcomes varied according to indicators of child health. Results 162,847 mother-child dyads were grouped according to the following indicators: Child High Service Use (18%) vs. Not (82%), Diagnosis of Major and/or Chronic Condition (12%) vs. Not (88%), and Both High Service Use and Diagnosis (5%) vs. Neither (75%). For all maternal health and service use outcomes (number of physician visits, chronic condition, mood or anxiety disorder, hospitalization), differences were demonstrated by child health indicators. Conclusions Mothers of children with health problems had poorer health themselves, as indicated by administrative data groupings. This work not only demonstrates the research potential of using routinely collected health administrative data to study caregiver and child health, but also the importance of addressing maternal health when treating children with health problems.

Details

ISSN :
23994908
Volume :
4
Issue :
1
Database :
OpenAIRE
Journal :
International journal of population data science
Accession number :
edsair.pmid..........d85377f7dbbc92b2fe90cfc798e888de