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Leveraging Big Data to Understand Access and Use of Mental Health Services in Atlantic Canada

Dr. Amanda Slaunwhite Dr. Scott Ronis

David Miller Dr. Paul Peters

Funders

Supporters

Defining “Big” Data

“massive quantities of health care data accumulating from patients and populations and the advanced analytics that can give those data meaning”1

“..high volume, variety, and potential for the rapid accumulation of data and analytics, which is the discovery and communication of patterns in data”2

1Krumholz, H. M. (2014). Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system. Health Affairs, 33(7), 1163-1170. 2 Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123-1131.

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‘Big data’ -Electronic Medical Records

-  Diagnostic imaging -  Clinical notes -  Treatments

-  Physician Billing Data -  Pharmacy Records -  Mortality Data -  Tax Return Records -  Internet and Social Media Data -  Climate/environmental data

Supplementary data -  Population health surveys

-  CCHS -  CADUMS -  GSS

-  Geospatial files -  Road networks; civic

address files

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The Power of Big Data: Data Linkage

“Big data becomes transformative when disparate data sets can be linked at the individual person level.”

Health card # or SIN

Residence/Postal Code

Visits to family doctor

Hospital Admissions

Infant Health

Pharmaceutical Use

Weber, G. M., Mandl, K. D., & Kohane, I. S. (2014). Finding the missing link for big biomedical data. Jama, 311(24), 2479-2480.

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•  Big data supports geographical research and spatial analysis

•  Refined spatial scale

•  Helps to identify how place impacts mental health and access to mental health services

•  Common geographies: Postal

Codes; Forward Sortation Areas

The Power of Big Data: Time and Space

Tim

e

Space

Hospital  A  

Hospital  B  

Conceptualization: Mei-Po Kwan (2002) Feminist Visualization: Re-envisioning GIS as a Method in Feminist Geographic Research. Annals of the Association of American Geographers, (2002) 92(4):645-661

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Big Data and Youth Mental Health

-  Administrative health data addresses the limitations of commonly used surveys: -  No sampling of children -  Undersampling of youth -  Undersampling of rural/remote populations -  Self-reports (vs. actual diagnoses; health care use) -  Cross-sectional (vs. time series/panel data)

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Current Data Projects 1.  Time series variations in mental health-

related hospital admissions among youth in New Brunswick1

1.  Geographic variations in mental health-

related hospitalizations and access to primary health care1

2.  Distance Decay or Distance-Related

Delays? Travel distance to hospital and likelihood of mental health-related hospital admissions among youth in New Brunswick1

3.  Investigating the factors associated with adolescent readmission to acute psychiatric care services in Atlantic Canada

(David Miller, Student, UNB) 5.  Factors Associated with Perceived Need

and Use of Adolescents Mental Health Services: Does Atlantic Canada Differ from the Rest of the Country?

(Stephanie Douette, UNB); 6.  Using large data sets across sectors for

collective impact. (Luc Clair, McMaster University)

8  1PIs: Amanda Slaunwhite, PhD, Scott Ronis, PhD, Paul Peters, PhD, David Miller, Dan Crouse, PhD. (UNB)

Mental Health-Related Hospitalizations for Youth in New Brunswick

LegendCanadarate

334.200000 - 409.000000

409.000001 - 528.700000

528.700001 - 947.700000

LegendCanadarate

334.200000 - 409.000000

409.000001 - 528.700000

528.700001 - 947.700000

334.2-409.0 409.1-528.7 528.8-947.7

Legend: Mental Health-Related Hospitalizations per 100,00 for Youth (<24 years)

*National Average = 409

PIs: Amanda Slaunwhite, PhD, Scott Ronis, PhD, Paul Peters, PhD, David Miller, Dan Crouse, PhD. (UNB) 9  

High Rates of Mental Health-Related Hospitalizations

•  Minimal information on mental-health related hospital admissions over time or geography

•  High rates are problematic: –  Adult-oriented general hospitals and psychiatric units are

frequently unable to meet the needs of youth –  Treatment efficacy concerns –  Could be attributed to lack of primary health care or

community mental health services

10  PIs: Amanda Slaunwhite, PhD, Scott Ronis, PhD, Paul Peters, PhD, David Miller, Dan Crouse, PhD. (UNB)

Geography and Mental Health-Related Hospital Admissions

505

279

403

1159

1258

902

496 529

409

0

200

400

600

800

1000

1200

1400

Moncton Fredericton Campbelton Miramichi Canada

New

 Brunswick  

 

•  Variations in rates of mental health-related hospitalizations in NB for youth < 24

•  Research will measure: •  Geographic variations by

postal code; •  Relationship between

family physician density and hospitalizations

•  Distance to hospital and likelihood of service use St

.  Joh

n    

Edmun

dston  

  Bathurst  

 

11  PIs: Amanda Slaunwhite, PhD, Scott Ronis, PhD, Paul Peters, PhD, David Miller, Dan Crouse, PhD. (UNB)

Developing Data Infrastructure in Atlantic Canada

-  Infrastructure development is ongoing -  Health Data NS; NB-IRDT -  Data costs; personnel / expertise

-  Owners of Data -  Departments of Health; Government Agencies hold

different information -  Information silos and varying degrees of access -  Inter-Provincial linkages are challenging

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•  Linkages between datasets decreases confidentiality;

•  Geography and privacy is a challenging area

<19 with family doctor diagnosed mental health issue in Fredericton in 2014 (N=500) + female (N=250) + parents who earn less than $30,00 per year (N=150) + is one of 120 patient that lives in E3B 507 (N=50) + involuntarily admitted hospital 8 times in the past 2 years for self harm (N=1).

Big Data, Privacy and Access

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•  Release of data from data owners •  Privacy Legislation

-  Big data addresses many limitations of cross-sectional survey data

-  Much promise for using big data to research youth

mental health in Atlantic Canada -  Essential for evaluating health care reform efforts

(e.g. new investments in mental health services)

Developing Data Infrastructure in Atlantic Canada

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Thank you.

amanda.slaunwhite@unb.ca @prosretro @akslaun

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