H E A L T H W E A L T H C A R E E R Driven by Data C H A N G I N G W O R L D O F W O R K I N H E A L T H C A R E - K E Y T R E N D S F O R H R L E A D E R S I N 2 0 1 8 Matt Stevenson, PhD Matthew.Stevenson@mercer.com NOT PEER REVIEWED

© MERCER 2018 2 A G E N D A Macro Trends Planning for Growth The External Market The Right Staffing Model & Workforce Planning Approach

© MERCER 2018 3 — Technology — — Pressure on Costs and Outcomes — — Value Over Volume — — Consolidation And Expansion — Macro Trends are Disrupting the US Healthcare Industry — Rise of Retail — — Rise of Consumerism — Regulatory Uncertainty

© MERCER 2018 4 CLINICAL EDUCATION SUPPLY TECHNOLOGY, JOBS AND SKILLS ROLE SHIFTS: TOP OF LICENSE SHORTAGE OF SKILLED IT PROFESSIONALS PHYSICIAN DISSATISFACTION SHORTAGE OF CLINICAL STAFF LACK OF NEW TALENT IMPENDING TURNOVER …and Transforming the Future Healthcare Workforce

© MERCER 2018 5 I M PA C T O N T H E B O T TO M L I N E …

Four Common Questions 1. How ready am I to define and create my future workforce? 2. What initiatives am I planning that will most impact my future workforce? 3. What will I need to do differently to attract, develop and retain the talent needed? 4. How this will impact patient care and safety? 6

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Growth: The Internal Labor Market (ILM) Concept A sample ILM map Active Headcount Promotions 2,093 650 273 195 (9.5%) (12.0%) (5.6%) (16.9%) (11.5%) 52 91 299 65 (19.0%) (14.0%) (21.1%) (29.9%) (19.2%) 20 (10.2%) 442 52 65 403 221 39 (19.0%) (10.0%) (19.3%) (22.1%) (11.5%) 12 (6.1%) 26 78 117 169 HIRES EXITS CAREER LEVEL 6 5 4 3 2 1 1,001 338 39 Disguised case example

The gap between supply and demand could range between 552 and 658 by 2021, depending on the attrition rate assumption used, and assuming people who leave are not replaced. Demand Supply 0 200 400 600 800 1000 1200 2013 2014 2015 2016 2017 2018 2019 2020 2021 Headcount G R O W T H : T H I S H E A LT H O R G A N I Z AT I O N N E E D E D T O P L A N F O R N E W F A C I L I T I E S …

Understand the External Market

Our Approach on the Right Staffing Model: The Factors Affecting Outcomes Employee and Patient Outcomes

Sample: People factors play a key role in driving performance outcomes—as is the case for healthcare organizations Factors affecting patient care 63% Compensation FT/PT ratio Overtime Turnover 35% 2% Transitory effects Lack of data Measurement error Capital- and technology- related factors

Case Study: in this System, the staffing model substantially influenced financial performance and quality of patient care Estimated changes in financial performance and improvements in quality of patient care Increase proportion of registered nurse employees Increase hours worked by agency nurses – IMPACT + Increase number of licensed practical nurse employees Increase employee tenure Increase ratio of executives to total employees Quality of patient care Financial performance

-56% -30% -12% -3% 5% 9% 12% 12% 15% 17% 48% -80% -60% -40% -20% 0% 20% 40% 60% 80% Is a supervisor Professional (vs. Mgr) Rating: Excellent (vs. Avg) Base Pay ($70K vs. $60K) Tenure in job (+1 yr) Non-white Hired in year Promoted in year Female Rating: Needs Improvement (vs. Avg.) Supervisor's span (+10 EEs) Percentage difference in voluntary turnover probability Predictive Turnover Analysis® identifies the drivers of key workforce outcomes Less Likely to Quit More Likely to Quit (subset of results) Disguised client example

Right data Results Answers Right questions Next Steps: Use the data you already have to get the right answers to the right questions: What predicts outcomes in my organization? What are the quantifiable drivers of quality and safety? How do we turn these findings into measurable interventions?

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