Topics . AHS Organization, PrioritiesExecution of Successful changeOrganizing Analytics and Performance MgmtAnalytic Examples. Quick Facts. $11 Billion operating budget90,000 staff members7,200 physicians3.5 million Albertans served97 acute care hospitals; 5 psychiatric facilities9,000 acute care/sub-acute care beds19,000 long-term care/supportive living beds1,500 addiction/mental health beds7 urgent care centres.
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1. Alberta Health Services ‘Measure to Improve’
AHS Approach to Analytics and Performance Management
3. Quick Facts $11 Billion operating budget
90,000 staff members
3.5 million Albertans served
97 acute care hospitals; 5 psychiatric facilities
9,000 acute care/sub-acute care beds
19,000 long-term care/supportive living beds
1,500 addiction/mental health beds
7 urgent care centres
AHS implemented a new organizational structure June 1, 2009 arranged in the following areas:
Quality and Service Improvement
Strategy and Performance
Rural, Public & Community Health
Senior Physician Executive
Clinical Support Services
4. Vision To become the best performing publicly funded health system in Canada
Improving health for ALL Albertans
6. Strategic Improvement What
How are we doing
7. Alberta Health Services Measurement – Past
8. Alberta Health Services Measurement Plan Unite analytical/measurement resources across the province.
Develop one data repository to meet multiple reporting needs.
Develop a data governance structure and process
Shift from largely administrative data to clinical and operational data
Align measurement resources to clinical services – our core business.
Collect data once, at the most granular level and use it for health services delivery management and external reporting requirements.
Measure outcomes and activities/process and attach costs to activities
9. Things to consider when choosing an indicator
Does it measure an important health issue?
Strategic: Someone is actioning it (accountable)?
Is it timely?
Measurement Burden relative to value
11. Hybrid Model
12. Why Organize Analytics? Analytical Talent – need to organize analysts so that they are working “close to the business” on critical analytical initiatives while also keeping them “close to each other” for purposes of coordination, mutual learning and support. Making both happen at once is the challenge. (How to Organize Analytical Talent, Analytics Magazine, Jan/Feb 2010)
Interviews with dozens of executives and 700 analysts found that companies with a strong commitment to an analytical workforce are best served by greater centralization and coordination of analysts. (How to Organize Analytical Talent, Analytics Magazine, Jan/Feb 2010)
Companies and organizations that compete on analytics don’t entrust the analytical activities to just one group within the company or to a collection of disparate employees across the organization. (Competing on Analytics, 2007)
13. Proposed New Functions Performance Management:
Measures alignment of enterprise transformational initiatives with AHS strategic goals and the degree to which performance targets are being met
Works with AHS decision makers to set performance targets, identify benchmarks and create a culture of accountability
Simulation modelling, matching of capacity to demand to ensure acceptable patient flow across the continuum of care
Health Economics & Forecasting:
Cost per weighted patient methods and reporting, health service event costing, linking costs to outcomes
Population Health Observatory:
Population pathway modelling, analyses to understand the determinants of health and reduce inequities in the distribution of risk conditions across the province
Clinical Networks Support:
Will involve common approach for the networks to access analytic support, as well as standards for performance reporting deliverables
14. Significant Projects Utilization index for acute sector- Allocative and Technical - primary care /ASC/Day Surg/QI/EoL/ALC’s
Programs, Populations and Pathways- priorities using CRG analysis
Performance reporting dash boards, drill down
Q&S, HR, Finance, Board
15. Method – Provincial Programs of Care - $ & CRG - KPI across - Population -Red Flag = - Evidence
- Focus on Continuum Profiles Response Based
Large - Evidence- - Sub-geography - Green = - Research/Lit
Variation Based Sub-Population Share Model - Experts
- KPI from AHS - Profile with - Amber = - HTA
Clinical Networks other info e.g. monitor trend - Reallocation of
& Experts Service Inventory, (up or down) Resources
PH Surveillance - Design / etc. Re- design by Networks
17. VLADs Introduction to Alberta
18. A statistical monitoring tool which graphically displays clinical outcomes for selected clinical indicators with an alerting mechanism to identify pre-determined variation between a hospital and the province average What is a VLAD?
19. VLAD = Variable Life Adjusted Display
A type of Statistical Process Control methodology
A graphical tool that detects variation in patient outcomes
Assist in identifying potential safety & quality issues & identifying excellent practice
A systematic approach to quality improvement
Doesn’t replace other quality tools 6 Quick VLAD Facts
20. Introduction of VLADs to AHS
21. How to make a VLAD
22. How is a level of variation detected?
the VLAD plot touches the control limit
indicates a certain level of variation
prompts a review of patient charts
NOTE: A flag does not indicate one case only is to be reviewed, it is cumulative – prior cases also for review How to make a VLAD
23. How to make a VLAD
24. VLAD Process – Flagged VLADs