epidemiology of health care using administrative data to gain understanding re: health of...
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Epidemiology of Health Care
Using Administrative Data To gain understanding re:Health of populations and
Use of Health Services
Purpose of Course
• Primer in how/why to use Manitoba’s
natural research resource
• Gain insights which come from a population focus
• Understand broader determinants of health
Examples of Administrative Data?? What exactly are we talking
about??
Research Approach
Research driven by insights and opportunities rather than hypotheses and preformed research agendas
Administrative DataAdvantages
• Able to study entire population
• Longitudinal follow-up easy
• Pre and Post Event Histories Easy
• Avoids the selection and recall
biases
• Relatively low cost
• Can study rare outcomes
Limitations
• Data not collected to answer your
research questions
• Quality of data – needs validation
and decision-making
• Individual initiates contact
• Amount of data – overwhelming
• Access to data – varies
Where to find Population-Based Administration Data
1. Several Canadian provinces
2. Rochester (Minnesota) Epidemiology Project
3. Oxford Record Linkage Study
4. Scottish Record Linkage System
5. Western Australia Health Services Research Linked Database Project
• The Manitoba Centre for Health Policy– University of Manitoba, Faculty of Medicine, Department
of Community Health Sciences since 1991
– Five-year contracts with Manitoba Health, 6 deliverables a year mutually negotiated, all publicly available
– External funding of researchers (e.g. CPHI funding)
– Mission: To provide accurate and timely information to health care decision-makers, analysts and providers, so they in turn can offer services which are effective and efficient in improving the health of Manitobans
The Manitoba Centre for Health Policy (MCHP): Who we are
ResearchRegistry
Medical
VitalStatistics
Home Care NursingHome
Hospital
ProviderPharmaceutical
Immunization Monitoring
The Manitoba Population Health Research Data Repository
1 A similar version of this figure appeared in Roos, Menec, and Currie 2004.
Inflammatory Bowel Disease Database
Sleep Lab Clinical Data
Alcoholism Panel Surveys
Cancer Registry Educational and Social Data
Heart Health Survey
Aging in Manitoba Study
National Population Health Survey
• Canada Foundation for Innovation and Manitoba Government funded Data Laboratory
• Highest standards of security, privacy & confidentiality of data
• No names, no addresses
• Probabilistic linkages across files as needed
• Data for research not for administrative use
• Provincial privacy offices kept fully informed
Respect for Privacy In Building Database
Incrementally Added –Gained Experience with Data Files:
• 1970’s: Hospital and medical files• 1980: Nursing home file• 1981: Vital Statistics file• 1990: Census file• 1991: Mental Health Information System• 1992: Physician Registry file• 1993: Nursing home drugs• 1994: Immunization histories• 1995: Pharmaceutical file• 1996: Ability to cost hospital stays; Manitoba Cost List• 1997: Pilot with Social Assistance file• 1999: Linked National Population Health Survey• 2000: Home Care file• 2002: Family Services, Education, Healthy Child
Education (Grades, Tests, Enrollment Data)
Income Assistance
Children in Care
Provincial Programs (Healthy Baby, Baby First)
Genetic Screening
Community Resources
New Population Data Sets Added to the Repository:
Number of Data Files in the Repository housed at MCHP (from 1991 to 2005)
0
10
20
30
40
50
60
70
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
year
nu
mb
er
of
dat
a fi
les
CFI Funding
Research Registry• Accurately defines coverage status for individuals since
1970• Can help distinguish between "well" individuals from
those who left province or died • Place of residence (merge to census data)• Cohort identification• Family identification• Case controls / comparison groups
Validating the Registry
• Comparisons made with 1986, 1991, 1996, 2001 census years by date of census.
• Registry populations are larger by 2-4% overall.• Difference is greater for early census years and getting
smaller.• Female registry population not as much difference as
males.• Age 25-34 registry population is much higher 4-6% with
males being higher than females.
Web-based knowledge tools:
Data Dictionaries:
• Restricted to MCHP staff• A comprehensive list of field names
and contents for the administrative data files housed in the Repository
Medical/Research Definitions
Glossary
Research Protocol
Research Resources
Project Web Pages
Concept Dictionary
Web-based knowledge tools:
Concept Dictionary:
• Provides details on how to measure/calculate/define/validate “something” such as a variable or indicator
Concept Dictionary
• Calculates event rates per 1000, adjusting for key population differences (e.g. age, sex)
• Suitable for comparisons across time and space
SAS Macros: RATES
Western Australia Data Linkage System
– In 2005, Minister for Science declared it a national centre of excellence in Australia
– Since 1995, more than 350 major health projects primarily in the area of health care
– Between 1995 and 2004, out-of-state revenue from research grants was $58.4 million (Australian)
– Child and youth topics (recent reports):• Temporal variation in rates and causes of infant
mortality among aboriginal and non-aboriginal• Health/ outcomes among children of mothers who
have schizophrenia and/or other affective disorders
Massachusetts Pregnancy to Early Life Longitudinal (PELL) Project
Boston University School of Public Health
Birth Certificate
Hospital Discharge (HD)
Mothers Birth
Fetal Death Hospital Discharge (HD)
Child’s Birth
(Core Linkage)
Maternal or Child Linked Longitudinal Capacity
Program Participation Data
1999, 2000, …
Program Participation Data,
PNC Usage
(1998, 1999)
Subsequent Records
Child’s Hospital Discharges, Observational Stay, ER Usage
Mother’s Hospital Discharges, Observational Stays, ER Usage
1999Prior Information
Mother’s Pregnancy Hospital Discharges, Observational Stays,
Emergency Room Usage 1998, 1999
Birth Certificate
Hospital Discharge (HD)
Mother’s Birth
Fetal Death Hospital Discharge (HD)
Child’s Birth
(Core, 1999)
Subsequent Records
Child’s Hospital Discharges, Observational Stay, ER Usage
Mother’s Hospital Discharges, Observational Stays, ER Usage
2000
Alberta
• Analysis of population registry and vital statistics • Analysis of hospital discharge data • Analysis of physician claims • Analysis of laboratory data • Analysis of drug data • Risk adjustment• Defining socio-demographic variables at
small geographic areas
HH
Utilization
Utilization
Utilization
Regionalpopulation - SES - Health
Physicians
PersonalCare Homes
Hospitals
PCHPCH
PCH
A Tool for Population-BasedAnalyses
Principals for Population Focus1. describe:
- supply
- access to care
- intensity of use
- differential use across areas
2. juxtapose indicators of: -socioeconomic risk
- use
- health
Turning Data into ConceptsCounting
– objects– events
Measurement– concepts
Examples:
# times patient admitted to hospital
# times patient admitted with MI
health/status severity of illness
# admissions to a given hospital
# admissions for acute MI to a given hospital
case-mix of a given hospital
Examples of Concepts
• Individual: health status
• Family: poverty, mobility
• Community: neighbourhood level SES;
• Health care: continuity of care; hospital case mix
• Graduation, grade retention
•Radiology Services Review
•Province-wide coronary angiography, adult MRI, BMD and screening mammography data are captured
•For all other modalities, data are incomplete (esp. outside Brandon and
Winnipeg)
Some Things Administrative Data Cannot Do
Data Rich Environment Provides Insights Re:
• Who has access to services
• Who is and who is not in system
• Those who are healthy and those who are not