1. Strengthening Performance Management through Enhanced Wait Time Reporting Haim Sechter: Manager, Reporting and Analytics Jennifer Liu: Team Lead, Reporting and Analytics

2. Presentation Summary 1. Cancer Care Ontario background 2. Wait Time Reporting  Current data collection and reporting  New reporting solution 3. Project delivery, benefits, and lessons learned 4. Next steps 2

3. Cancer Care Ontario (CCO) Ontario government agency Drives quality and continuous improvement in cancer, chronic kidney disease, and access to care for key health services o Disease prevention and screening o Delivery of care o Patient experience 3

4. Performance Management and Wait Times CCO monitors and manages wait time performance for various treatments and diagnostic procedures at the provincial and LHIN levels Works with cancer care providers to continually improve access, and publically reports wait times 1. Data/Information 2. Knowledge 3. Transfer 4. Performance Management 4

5. Background: Data Collection Systemic and Radiation Wait Time information calculated from Activity Level Reporting Data (ALR) Minor Procedures 14 Regional Cancer Programs > 165,000 radiation and systemic activity records Monthly submission frequency Radiation Treatment Systemic Treatment Clinic Visits Health Care Provider data Disease Information Patient Information 5

6. Background: historical reports 6

7. Problem Historical radiation and systemic treatment wait time reporting: Labour intensive Sub-optimal user experience Inefficient reporting process: information available through multiple channels Limited Access to information Delayed after monthly submissions 1 FTE 7

8. Future radiation and systemic treatment wait time reporting: Solution Wait Times reports available through single web-based application Information flows directly from EDW Interactive dashboard summaries at various levels Increased functionality through drilling, custom metrics, report subscriptions, detailed analysis etc. 8

9. Merging of reports into one source 9

10. Interactive dashboards 10

11. v Increased Functionality 11

12. Detailed Analysis 12

13. Integrated Data Quality 13

14. Project Delivery Project elapsed tine: 24 months elapsed Actual time: 6-8 months Project team: BI Developer, Data Analyst, Data Architect, ETL Developers, IT Operations, Business Analyst Project tracking: weekly core team meetings Weekly working group meetings 14

15. Benefits ½ FTE redirected to advanced analytics Time to delivery reduced by 1 week each month Development of decision support tool New report structure appeals to a variety of audiences Easily scalable 15

16. Challenges Project too big to run through operations Stakeholders satisfied with status quo Difficult to gain organizational buy-in Underlying data not fit for BI reporting Too many competing priorities Too difficult to continually leverage operation resources Business must be constantly part of working group Improve organization understanding of BI Proper data infrastructure is critical Strict Project management approach has to be leveraged Lessons Learned 16

17. Next Steps Provincial view of systemic wait times Improve accuracy of indicators through standardization factors Integration with automated scorecard 17