BC’S LOCAL RISK-ADJUSTED MODEL

JANUARY 2012

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

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

BC NSQIP Timeline and Important Dates

* Includes General and Vascular Surgery Cases

Observed Rate: 2.20%Pred. Obs. Rate: 2.48%Expected Rate: 2.75%Odds Ratio: 0.84Status: Non-Outlier

PLAN:Overall Mortality

PLAN:

Establish a local risk-adjusted model using BC data

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.

BC NSQIP Timeline and Important Dates

PROPOSED TIMELINE:

Expectations

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

VOLUNTARY

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

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

SPC Charts

Q&A

Data Analysis Workshop • February 8, 2012• 8:30am-4:00pm• Delta Airport Hotel Richmond, BC

Highlights:

1. Finding QI opportunities in your NSQIP data2. Communicating NSQIP Data3. Promoting ideas, identifying project advocates and securing

resources

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.

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.

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.‐‐

Q&A