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

Authors :
Dafna E. Kohen
Kimberlyn McGrail
Rubab G. Arim
Jamie C. Brehaut
Peter Rosenbaum
Anton R. Miller
Lucyna M. Lach
Anne Guèvremont
Rochelle Garner
Marni Brownell
Source :
International Journal of Population Data Science. 4
Publication Year :
2019
Publisher :
Swansea University, 2019.

Abstract

IntroductionCaregivers 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. ObjectivesWe 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. MethodsDyads 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. Results162,847 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. ConclusionsMothers 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. KeywordsPopulation data, linked data, case-mix, children with special health care needs

Details

ISSN :
23994908
Volume :
4
Database :
OpenAIRE
Journal :
International Journal of Population Data Science
Accession number :
edsair.doi...........62fb055de0ff4beaa275b82f414214ae