Talent Under Pressure — Lakeshore Regional Health

A four-round, advanced healthcare-leadership simulation set inside Lakeshore Regional Health — Medicine & Acute Care, a 480-bed teaching hospital in mid-size Ontario (6 inpatient units, 210 beds, 620 clinical FTEs, a CAD 118M operating budget). On 11 June 2026, over one week, 9 experienced RNs (8% of the nursing workforce) resign or go on stress leave, concentrated on two units. The agency-staffing cap is maxed (no net new agency FTEs), competency coverage on the worst unit has fallen to 62%, the well-being index sits at 41/100 against a network target of 65, overtime is up 38%, four more senior nurses are job-searching (each experienced-RN replacement costs ~CAD 65,000 and 4–6 months to competency), and only CAD 1.4M of in-year flexibility is left for stabilisation. The network CEO wants a plan in 5 days; a regional newspaper is preparing a story on ER offload delays. Playing the Unit Director, you (1) diagnose the crisis as a competency-distribution problem rather than a headcount shortfall, naming which senior/charge competency loss is most safety-critical; (2) redesign roles, models of care and skill mix to restore safe coverage within CAD 1.4M and inside scope-of-practice and the 1:4 safe ratio — testing every efficiency move against the burnout spiral, because stripping autonomy worsens the well-being it was meant to relieve; (3) choose a responsible AI-adoption stance (full go, scoped pilot, defer, or no) into a distrustful unit scarred by a botched IT rollout, designing human-in-the-loop guardrails and deciding where the ~40 min/shift of AI time-savings go — reinvested to patients or to cutting overtime, or extracted as headcount cuts that confirm the union's fears; and (4) integrate the three levers into a 90-day plan with a leading/lagging KPI dashboard and a CEO pitch, stating the trade-off you accepted. The math rewards a competency-first diagnosis, an autonomy-protecting redesign, a trust-aware scoped AI pilot whose dividend is reinvested, and a dashboard that tracks well-being and turnover-intent — and punishes the five classic errors: chasing capped agency hires, efficiency that deepens burnout, AI as a silver bullet, extracting the AI dividend as cost, and a throughput-only scorecard. Final KPIs track Safe Coverage, Well-being, Retention (turnover-intent held), and Trust.