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UID:pretalx-2024-HX9PGU@conferences.acspri.org.au
DTSTART;TZID=AEST:20241128T155000
DTEND;TZID=AEST:20241128T161000
DESCRIPTION:Individuals’ interactions with administrative systems (e.g.\, 
 health\, criminal justice\, and education systems) produce data about thos
 e interactions. In some jurisdictions these administrative data have been 
 aggregated\, deidentified\, linked at the person level across administrati
 ve systems\, and made available for research. \n\nSeveral features of link
 ed administrative data make them ideal for understanding life-course devel
 opment. First\, there are developmentally relevant data at all stages of t
 he life course\, from in utero development through to old age and death. S
 econd\, the data are longitudinal by design. Administrative records often 
 consist of a timeline of date-stamped events (e.g.\, births\, immunization
 s\, school enrollments\, hospitalizations\, and monthly earnings)\, essent
 ially forming a longitudinal record of people's lives as they develop. Thi
 rd\, data linkage across domains permits broad assessments of exposures an
 d outcomes. Fourth\, administrative data collections often permit intergen
 erational investigations through the ability to link between parents and c
 hildren (e.g.\, through birth records\, legal-parenting-status information
 \, census information\, and insurance records). Fifth\, administrative col
 lections which capture address or geographic information allow for neighbo
 rhood factors (e.g.\, disadvantage\, crime rates\, air pollution) to be li
 nked to individual records and assessed in relation to life-course outcome
 s.\n\nThis presentation will give example of how analysis of linked admini
 strative data resources has advanced our understanding of life-course deve
 lopment by utilizing the advantages of these data. Specifically\, I will h
 ighlight how advances have been made through: (a) understanding small or d
 ifficult-to-study populations\, (b) using causally-informative designs\, (
 c) identifying early factors predictive of outcomes later in the life-cour
 se\, and (d) identifying important neighborhood and environmental influenc
 es. \n\nI will finish by emphasizing that linked administrative data resou
 rces cannot answer all research questions and have a range of limitations\
 , including that (a) the data are not typically collected for research pur
 poses and can be of lower quality (and quality of the data may change over
  time)\; (b) the data primarily consist of service contacts\, and cases th
 at come into contact with services or seek treatment may form only the tip
  of the iceberg of those with the condition (e.g.\, those with more severe
  problems) and may represent a biased subset\; and (c) important factors t
 hat rely on observation\, self-report\, or subjective ratings (e.g.\, self
 -control\, attachment\, parenting quality\, loneliness\, social cohesion\,
  and measures of the home environment) are typically not captured in admin
 istrative systems\, so they cannot be the focus of investigations using po
 pulation-level administrative data.
DTSTAMP:20260912T203005Z
LOCATION:Sutherland Room
SUMMARY:Understanding life-course development using linked administrative d
 ata - Barry Milne
URL:https://conferences.acspri.org.au/2024/talk/HX9PGU/
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