These slides were presented at the December 2023 meeting of the KC Digital Drive Health Innovation Team. This presentation focuses on Children's Mercy's innovative use of data. Bill Saltmarsh, MBA, Vice President and Chief Data Officer says, "We are using data to create value for our patients, their families, and our community. We believe that the key to delivering that value is contingent upon our ability to capture, safeguard, and derive novel insights from our data. It is also contingent upon our ability to take advantage of advanced analytical methods and technologies, including the use of Artificial Intelligence. One example of this type of innovation is our Patient Progression Hub which is enabling us to improve the connected care experience for our patients by consistently providing the right information to the right people and the right time." Bill leads the Data Intelligence Team for Children's Mercy, which includes groups such as Data Science, Clinical Reporting and Analytics, Data Platform Engineering, and Data Governance. Before joining Children's Mercy in March of 2023, he led data teams at ResMed and Pluralsight.

1. Data-driven Innovation at
Children’s Mercy:
Patient Progression Hub
KC Digital Drive – Health Innovation
Bill Saltmarsh VP, Chief Data Officer for Children’s Mercy
December 6, 2023
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2. Children’s Mercy Kansas City Launches Nation’s First
Pediatric Hospital Command Center
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3. Patient Progression Hub
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Care team collaboration
Reduction of inefficient processes
and avoidable delays
Better use of data to
anticipate coordinated care
Better outcomes for
patients and families
Helps us address system bottlenecks and remove obstacles
that are known contributors to burnout
Improved access to
inpatient care
Refined patient flow

4. The Challenge
Ø Significant delays
depicted (grey bubbles)
Ø Major patient pathway
(emboldened line)

6. Vision
Children’s Mercy Patient Progression Hub
strives to further family and team member
trust.
We proactively work to improve accessibility
for patients, increase transparency to
predictive real-time information, and
streamline care coordination.
By maximizing the use of data and linking
quality, safety, and operations, Children’s
Mercy will be at the forefront of innovation
and outcomes in pediatric care both regionally
and nationally.
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7. Data that is currently driving Patient Outcomes
Capacity Expediter
• shows capacity levels of the total
hospital, both Adele Hall and
Kansas locations
• broken down by unit
• tracks clean and dirty beds,
confirmed and potential
discharges, and associated tasks
Patient Manager
• real-time awareness of how
patients are progressing
• facilitates handoffs between
caregivers
• dates, flags, alerts, tasks, and
notes that are relevant to
progression of care and patient
safety
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8. The Human-Machine Intelligence Continuum
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i.e., the tasks do not
change
Assisted
Intelligence
i.e., interaction
between human &
machine
Augmented
Intelligence
i.e., adaptive systems
based on data
Autonomous
Intelligence
LESS complex
tasks
MORE complex
tasks
PHASE 1 for Patient Progression
Augmented Intelligence:
• Predicting bed capacity
• Identifying potential candidates to move from ICUs
• Identifying patients at risk
• Identifying patients with potential health equity concerns

9. The Analytics Continuum
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What happened?
Descriptive Predictive
What’s the best that
could happen?
Cognitive
historically - oriented future - oriented
PHASE 1 for Patient Progression
• Predicting bed capacity
• Identifying potential candidates to move from ICUs
• Identifying patients at risk
• Identifying patients with potential health equity concerns
Diagnostic Prescriptive

10. 10
The possibilities are almost limitless…
• Census & staffing forecasts
• real-time awareness of staffing needs & scheduling insights
• this will inform our ability to ensure the right nurse is in the right place at the
right time
• Surgical capacity planning
• multi-week visibility into the surgical schedule, including planned demand &
utilization
• identifying & highlighting risks of cancellation or postponement
• Patient placement
• ensuring patients get placed expediently and appropriately, based on their
specific attributes and condition
• will help us prioritize when demand exceeds supply

11. Who is making up the rules?
(Traditional Programming vs Machine Learning)
Rules
Input Output Rules
Input Output
Data
Traditional Programming
Machine Learning

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Balancing Risk vs Benefits of AI
• Algorithmic decision-making moves the locus of control, and invites non-trivial
complexity:
• ethics (how to mitigate bias in the training data & identify it in the outputs)
• adoption & accountability
• workflow design
• Generative AI creates novel data, which then needs to be managed
• the value of solutions is highly dependent on quality of voluminous, underlying
data
• Monitoring of models is a non-trivial effort (both in terms of hours and
complexity)
• Explainability can be harder to achieve – failing to meet that bar can diminish
trust in the solution

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The Future of AI at Children’s Mercy
• Cross-functional AI Task Force – Transparency Statement
• Governance framework
• AI Strategy as part of CM’s Data Strategy
• Experimentation in lower-risk domains of the hospital
• AI as a facilitator for Enterprise Data Management
• Developing an ethical risk typology for Children’s Mercy

14. Children’s Mercy
Philanthropy
Imagine the Potential
• One-of-a-kind fundraiser events (e.g., donating
your birthday)
• Donate items (e.g., Happy Kits)
• Donate $$$$
• Volunteer
• for more info: www.childrensmercy.org/ways-to-
give/
• contact us: giving@cmh.edu
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