2015 APHA Annual Meeting & Expo

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Recorded Annual Meeting Presentations (RAMP) are now available for purchase.
Only $90 for presenters, $140 for registered attendees and $200 for non-attendees.

Online Program

326536
Using Big Data for Health Policy Research: A Project of the Pathways to Health and Social Equity Program of Research


Monday, November 2, 2015 : 12:50 p.m. - 1:10 p.m.

Nathan Nickel, MPH, PhD, Manitoba Centre for Health Policy, College of Medicine, Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
Dan Chateau, PhD, Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
Marni Brownell, PhD, Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
Alan Katz, MBChB, MSc, CCFP, Manitoba Centre for Health Policy, College of Medicine, Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
Elaine Burland, PhD, Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
Randy Walld, Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
Mingming Hu, MSc, Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
Carole Taylor, MSc, Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
Joykrishna Sarkar, MSc, Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
Chun Yan Goh, MSc, Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
Audio (mp3) recording Recorded Presentation (mp4)
BACKGROUND

Big data that measure individuals’ exposure to policy/programs, follow recipients through time, and capture information on wide ranging social determinants of health can be effectively leveraged for policy-focused health equity research.

METHODS

Data files from several domains, comprising individual-level data, were assembled to develop the PATHS Data. These data include millions of data fields capturing administrative data on healthcare utilization, socioeconomic status, receipt of social services and/or housing, education, and involvement with the justice system. Data were linked – at the individual level – across domains and through time. Healthcare utilization data (physician visits, prescription drugs, and diagnostic/therapeutic codes from hospitalizations) were linked with social services data to identify the impact of programs’ impact on child health.

RESULTS

PATHS Data include information on 99% of individuals living in Manitoba born between 1984-2012 (N=584 255), including marginalized populations often missed in survey research. The median observation period for individuals from birth is 15.4 years. Maternal age at birth decreased from 1984 to 2012- 26.5 years to 23.8 years (p<0.01). The proportion of children from low-income families increased significantly 23.2% to 27.2% (p<0.01). When children were followed through time, residential mobility was highest at 2 years of age. Linking healthcare utilization data with social services and education data identified several programs associated with improved child health.

CONCLUSION

Routinely collected administrative data, linkable across domains, provide a unique and cost-effective opportunity for conducting policy-focused health equity research and for construction longitudinal health trajectories.

Learning Areas:

Conduct evaluation related to programs, research, and other areas of practice
Epidemiology
Program planning
Public health or related public policy

Learning Objectives:
Discuss the strengths and limitations of using linked administrative health data for health equity research. Formulate research questions which can be answered with big data. Describe how linking administrative data, across time and from a variety of domains – health, social services, justice – can be leveraged to implement sophisticated study designs for policy evaluation.

Keyword(s): Health Disparities/Inequities, Child Health

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a Co-PI and member of the Leadership Steering Committee of the PATHS Equity Program of Research- a federally funded research program comprising over 15 studies into health equity. I am PI or Co-PI on several additional studies using linked administrative data - linking dozens of data files from many domains including health, social services, child services, education, and justice. I have published articles & chapters on using linked administrative data for health research.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 3234.0: Big Data Analysis in Health Policy