BC’s LOCAL RISK-ADJUSTED MODEL

1. BC’s LOCAL RISK-ADJUSTED MODEL January 2012

2. Background • Most BC sites joined NSQIP in mid 2011 • 1st NSQIP risk-adjusted semi-annual report – Mar 2012 • 2nd NSQIP risk-adjusted semi-annual report – July 2012 • 3rd NSQIP risk-adjusted semi-annual report – Mar 2013 • Data analysis using non-risk-adjusted data • - SPC chart • - customized reports from workstation

3. Background • NSQIP’s Semi-annual report limitations and challenges • SMH’s attempt in replicating NSQIP’s SAR • Jonathan Berkowitz, BSc, MSc, PhD • Sauder School of Business, University of British Columbia

4. BC NSQIP Timeline and Important Dates

5. PLAN: Overall Mortality Observed Rate: 2.20% Pred. Obs. Rate: 2.48% Expected Rate: 2.75% Odds Ratio: 0.84 Status: Non-Outlier REPLICATE ? * Includes General and Vascular Surgery Cases

6. PLAN: Establish a local risk-adjusted model using BC data

7. Advantages • Identify local predictors • Timely reports - release of BC’s hierarchical odds-ratio report will be ~3 months ahead of NSQIP’s SAR • The current program is scheduled to end on Mar 2013. Using NSQIP data alone, sites will receive 2 SAR from NSQIP. Participating sites in the BC Collaborative accelerated plan will receive 5 risk-adjusted reports. • Provides valid statistical advice and certified accelerated process that meets statistical requirements in comparing sites in BC • A consistent provincial reporting template will be used to foster dialogue between sites, to identify and share best practices leading to improved outcomes.

8. PROPOSED TIMELINE: BC NSQIP Timeline and Important Dates

9. Expectations VOLUNTARY • Timely submission of data • Data transmission to NSQIP workstation and data cleaning for all 2011 cases done by April 29, 2012 • Submit de-identified data download to BCPSQC by May 1st, 2012

10. Jonathan Berkowitz, BSc, MSc, PhD Sauder School of Business, University of British Columbia

11. Data, data, data! I cannot make bricks without clay! -Sherlock Holmes

12. SPC Charts

13. Q&A

14. Data Analysis Workshop • February 8, 2012 • 8:30am-4:00pm • Delta Airport Hotel Richmond, BC • Highlights: • Finding QI opportunities in your NSQIP data • Communicating NSQIP Data • Promoting ideas, identifying project advocates and securing resources

15. Learning Objectives: • Improved understanding about the NSQIP dataset, including: • Why specific data is captured (intent and purpose of data). • Using non risk‐adjusted [and adjusted data] to identify QI opportunities. • Techniques to “ask the right questions” when working with the data.

16. Learning Objectives: • Improved skills to: • Identify project advocates. • Identify required and available resources. • Improved critical thinking and analytical skills: • To search for previously un‑seen patterns and trends. • To identify the potential causes behind patterns and trends. • To discover connections and stories in the data not previously considered.

17. Learning Objectives: • Improved communication and data presentation skills: • To tell stories with data correctly, clearly and compellingly in reports with tables and graphs and an increased awareness of the power of dashboards • To communicate information “at a glance.” • Understand of the importance of NSQIP non risk‐adjusted data • Concepts of how to communicate non risk‐‐adjusted data.

18. Q&A