TEM Expands Partnership With Northwestern Medicine Amid AI Boom
Tempus AI (TEM) has deepened its work with Northwestern Medicine, becoming the first health system to embed David - Tempus' generative AI clinical co-pilot - directly into its EHR. This move puts AI assistance where clinicians already work, reducing clicks, speeding decisions, and tightening documentation.
Why this matters for care teams
AI and data analytics are moving care from reactive to proactive by improving precision medicine, diagnostics, and operations. The AI in healthcare market, estimated at $14.92 billion in 2024, is projected to reach $110.61 billion by 2030 at a 38.6% CAGR, driven by chronic disease and aging populations.
What David does inside the EHR
- Automates patient summaries and supports note-taking during visits.
- Streamlines post-visit documentation and treatment planning.
- Enables natural language queries across the EHR for patient data and trends.
- Supports custom AI agent development to adapt to service line needs.
Net effect: less administrative drag, clearer context at the point of care, and faster paths to informed decisions.
Peers pushing AI forward
- GE HealthCare (GEHC) continues to expand AI across devices and imaging workflows, including orchestration within True PACS and Centricity PACS. The company leads the count of AI-enabled devices cleared or authorized by FDA.
- Butterfly Network (BFLY) is scaling AI across handheld ultrasound, including an AI gestational age tool deployed in Malawi and Uganda, and participation in the CAD LUS4TB study for AI-assisted POCUS in tuberculosis triage.
FDA: AI/ML-enabled medical devices
Implementation checklist for health systems
- Define high-impact use cases: intake summaries, progress notes, triage, oncology pathways.
- Map workflows first, then insert AI steps to avoid adding friction.
- Set governance: PHI handling, audit trails, model update review, bias monitoring.
- Keep clinician-in-the-loop review for clinical outputs and orders.
- Measure outcomes: documentation time, throughput, time-to-diagnosis, denials, patient safety events.
- Plan training and change management for clinicians, scribes, and revenue cycle staff.
Market context
Health systems are under cost and staffing pressure while demand grows. AI that removes low-value administrative work and surfaces timely clinical insights is moving from pilot to standard practice, especially when embedded natively in EHR workflows.
TEM stock snapshot
- Performance: TEM is up 105.5% over the past year, versus 34.8% for its industry and 18.8% for the S&P 500.
- Valuation: Forward 12-month Price-to-Sales of 11.52x versus the industry average of 5.88x.
- Estimates: Loss per share estimate for 2025 has been unchanged over the last 30 days.
Translation for operators: markets are pricing in execution. Expect scrutiny on real-world outcomes, utilization, and margin impact from workflow gains.
Next steps for healthcare leaders
- Run a controlled pilot inside the EHR with clear KPIs and safety guardrails.
- Choose 1-2 service lines for focus (e.g., oncology, cardiology) and co-design with frontline clinicians.
- Stand up an AI governance council spanning clinical, IT, legal, and compliance.
- Invest in skills: prompt patterns, oversight workflows, and evaluation methods for AI outputs.
If you're building team capability around clinical AI, see curated options by role and skill at Complete AI Training.
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