measuring health system efficiency in canada sess… · measuring health system efficiency in...
TRANSCRIPT
-
Measuring Health System Efficiency in Canada
Multi-phased project
Phase I
1
Katerina GapanenkoApril 17, 2012
-
The increased cost of health is a great concern
0
50
100
150
200
250
1975 1981 1987 1993 1999 2005 2011
Health Care spendings in Canada
Actual Spending Inflation-Adjusted Spending ($1997)
2Source National Health Expenditure Database, CIHI.
-
The increased cost of health is a great concern
3
Total Health Expenditure per Capita (Source: OECD Health Data, 2011)
-
Health expenditure per capita varies
4
$5,261
$6,884
Total Health Expenditure per Capita, in current dollars, 2011 forecasted Source: National Health Expenditure Trends 1975-2011, CIHI
$11,929
$5,450
$8,996
$6,570
$5,792
-
5
Are we getting the most out of our health
system dollars?
-
Previous Studies
66
-
Project Big Picture
7
Defining
a model
Testing
the model
Working
with DMUs
Enhancing
the model
-
Common Approaches to Measuring Efficiency
System -level approach
Sub-sector approach
Disease-based approach
8
-
Common Steps
9
Estimating efficiency of
DMUs
efficiency
scores
Factors that might be
associated with score
variation
Regression Analysis
Correlations
Inputs Outputs
-
Model Components
10
Health System
DMU
DMU
DMU
DMU
Methods of measurement
SystemObjectives
-
Stakeholders’ Contribution to Defining System Objectives
• “Someone on behalf of society has to decide what
objectives ought to be pursued. That is rarely a
role for analysts or researchers – rather, it is the
legitimate role of politicians. In developing a
performance model, an important requirement is to
seek out a clear political statement on what is
valued from legitimate stakeholders.”
Smith and Street, 2009
11
-
Research Methods
12
• Broad theoretical literature review
• Review of applied studies
• Statistics Canada
• CIHI
• Stakeholder interviews (CHEPA, McMaster) o 17 senior health system officials from 9 provinces & 2 territories
• Stakeholder dialogue (McMaster Health Forum)o 16 health system decision-makers from 6 provincial, 1
territorial and federal governments
• Review of jurisdictional documents
Literature reviews
Qualitative studies
Data reviews
-
Model Components
13
What is the system objective?&
How can we measure it?
-
System Objective: To produce more services?
14
-
To improve overall population health?
15
-
To improve health services to people in need?
16
-
System Objectives
17
• Premature mortality • Avoidable mortality• Preventable mortality• Treatable mortality
-
Model Components
18
Health System
SystemObjectives
Throughputs (wait times)
-
19
Throughputs(wait times)
-
Inputs
20
• Cost of hospitals• Cost of other institutions• Cost of physicians• Cost of nurses• Cost of other health professionals• Inflow/outflow rate• Public health expenditures• Drugs public expenditure
-
Environmental Factors
21
• Population density• Unemployment rate• Average income• % of people over 65• % of Aboriginals• % of immigrants• Income inequality (GINI)• Gender distribution
-
Lifestyle Factors
22
• Proportion of smokers• Obesity rate• Physical activity• Fruit & vegetable consumption• Alcohol consumption
-
Throughputs (for regression analyses)
23
• 30-day AMI or stroke in-hospital mortality
• Readmission for AMI, asthma, mental illness and other diseases
• Wait time for certain procedures
•Concentration Indices for self-reported
•Access to family physicians
•Visits to GP and specialists
•Hospitalization
•Health status
Health
Inequalities
Performance
Indicators
-
Model Components
24
Health System
Methods of measurement
SystemObjectives
DMU
DMU
DMU
DMU
-
DMUs
25
• Policy creation
• Authority for use of resources
• Intra- and inter provincial/territorial better performers
• ~ 140 health regions versus 13 provinces/territories
•Health regions
-
Methods of estimating efficiency
26
Key Differences DEA SFA
Sensitivity to extreme observations
High Low
Assumption that some DMUs are 100% efficient
Present Absent
Sensitivity to underperformers None High
Separation of random error from inefficiency
Impossible Possible
Assumptions about functional form and error distribution
None Strong
Many system outcomes Yes No
Impact of the sample size Moderate Strong
•Both methods
-
Model
SFA & DEA
efficiency
scores
•Cost of hospitals
•Cost of other institutions
•Cost of physicians
•Cost of nurses
•Cost of other health professionals
•Inflow/outflow rate
•Public health expenditures
•Drugs expenditure
Inputs
•Premature mortality
•Preventable mortality
•Treatable mortality
•Avoidable mortality
•Population density
•Unemployment rate
•Average income
•% of people over 65
•% of Aboriginals
•% of immigrants
•Income inequality (GINI)
•Gender distribution
Outcomes
Env. Factors
DMUDMU
DMU
DMUDMU
DMU
•Proportion of smokers
•Obesity rate
•Physical activity
•Fruit & vegetable consumption
•Alcohol consumption
Lifestyle Factors
-
Regression analysis
28
•30-day AMI or stroke in-hospital mortality•Readmission for AMI, asthma, mental illness and other diseases
•Wait time for certain procedures
•Concentration Indices for self-reported •Access to family physicians•Visits to GP and specialists•Hospitalization•Health status
•Proportion of smokers•Obesity rate•Physical activity•Fruit and vegetable consumption•Alcohol consumption
Lifestyle factors
Health Inequalities
Performance Indicators
efficiency
scores
Regression
Analysis
Correlations
-
Challenges & Limitations
29
• Missing data
• Lack of real-time data
• Variations in responsibilities among health regions
• Information challenges
• Model acceptance challenges
-
Next Steps
30
Defining
a model
Testing
the model
Working
with DMUs
Enhancing
the model
-
Acknowledgment
31
Dr. Michel Grignon Dr. Sara Allin
Dr. Jeremy Veillard
Alexey Dudevich Jean Harvey
-
Thank you
32