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Strengthening Performance Management through Enhanced Wait Time Reporting. Haim Sechter: Manager, Reporting and Analytics Jennifer Liu: Team Lead, Reporting and Analytics. Presentation Summary. 1. Cancer Care Ontario background 2. Wait Time Reporting Current data collection and reporting
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Strengthening Performance Management through Enhanced Wait Time Reporting Haim Sechter: Manager, Reporting and Analytics Jennifer Liu: Team Lead, Reporting and Analytics
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
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 • Disease prevention and screening • Delivery of care • Patient experience
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
Background: Data Collection • Systemic and Radiation Wait Time information calculated from Activity Level Reporting Data (ALR) 14 Regional Cancer Programs > 165,000 radiation and systemic activity records Monthly submission frequency Patient Information Disease Information Health Care Provider data Clinic Visits Systemic Treatment Minor Procedures Radiation Treatment
Problem • Labour intensive • Sub-optimal user experience • Inefficient reporting process: information available through multiple channels • Limited Access to information • Delayed after monthly submissions • Historical radiation and systemic treatment wait time reporting: 1 FTE
Solution • Future radiation and systemic treatment wait time reporting: • 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.
v Increased Functionality
Project Delivery • Projectelapsed 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
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
Lessons Learned Challenges • 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 • 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
Next Steps • Provincial view of systemic wait times • Improve accuracy of indicators through standardization factors • Integration with automated scorecard