DIME PROJECT
Implementing AI in Healthcare
As a strategic leader, you need confidence that you are addressing problems that matter most to your organization. The following exercise will help you do just that and determine whether or not AI is an appropriate solution. You can use this as an individual reflection tool or team exercise, pulling in crossfunctional clinical, data, and IT team members for a complete picture. The process often requires looking beyond data and processes to the values that shape decisions.
PRO TIP | When AI isn’t the answer
Not implementing AI can be just as strategic and successful as implementing it. AI might not be a fit if:
- You lack access to quality, relevant data for training and localizing tools.
- Workflow changes alone could solve the issue, not the shiny new tool.
- The problem is too vague, general, or immeasurable (e.g. “burnout”).
- The expected ROI is unclear, marginal, or poorly defined.
“There’s a series of design questions that have to be answered, from ‘why this clinical outcome?’ to ‘where do you set the sensitivity and the specificity?’, but latent in those questions can be various values. How different stakeholders impacted by a proposed AI tool would answer those questions… Our chief supposition is this idea that where stakeholders’ values collide are the fault lines along which future problems are most likely to emerge.”
-Danton Char, MD, MAS, Stanford University
This exercise begins with foundational work
Before selecting an AI tool, let’s identify what truly matters to your organization. Use the prompts below to identify meaningful challenges or opportunities that align with your organization’s goals, operations, and patient needs.
Instructions: For each category below, jot down a few key ideas or discuss them together. Complete individually or with a team. At the end, we’ll guide you to prioritize one or two high-impact problems.
Strategic & clinical priorities
Where is the need urgent and meaningful?
- What are the top 2–3 strategic goals for your health system this year?
- Where are we falling short on outcomes, access, safety, or equity?
- Are there specific populations, departments, or services that are underserved or require an enhanced approach?
Operational & workflow pain points
Where is the system inefficient, costly, or draining staff time?
- Which processes feel slow, duplicative, or frustrating to staff?
- Where are clinicians experiencing burnout from administrative load?
- Which decisions (e.g., admissions, triage, discharge) cause delays or inconsistencies?
Data & insight gaps
Where is there too much data and not enough clarity?
- Where are we collecting lots of data but lacking actionable insight?
- Do we have visibility into trends like rising acuity, staffing risk, or patient deterioration?
- Do care teams need faster, more personalized information?
Example: “We run 4 weekly reports on avoidable readmissions—but don’t have real-time visibility to intervene before discharge.”
Innovation mindset & history
Where is there appetite (or skepticism) for trying something new?
- Where are we lagging behind peers on innovation or digital maturity?
- What AI or tech pilots failed to scale—and what did we learn?
- Are leaders and staff open to new tools if the value is clear?
Review your responses to the prompts above. Then, answer the following.
Which challenges:
- Showed up repeatedly?
- Align with strategic or clinical goals?
- Affect cost, efficiency, equity, or outcomes?
- Have measurable KPIs already tracked (or trackable)?
- Seem solvable with better insights, prediction, or workflow optimization?
Use this template to turn your ideas into a clear, actionable problem.
Our system is struggling with: [describe the problem in plain terms].
This impacts [patients/staff/outcomes/efficiency], leading to [measurable consequence].
We believe that improving this could result in [expected outcome or ROI].
Example: “Our system is struggling with identifying patients at high risk of deterioration in the ED. This impacts care teams’ ability to intervene early, leading to higher rates of ICU transfer and LOS. We believe that improving this could reduce preventable escalations by 20% and save $500,000 annually in acute care costs.”
The AI Fit Checklist
AI is not always the right solution for every problem, and that’s okay! Use this checklist to gauge whether your defined challenge is suited for an AI-enabled approach.
PRO TIP
AI is most useful when the problem involves:
- Patterns,
- Predictions,
- Personalization, or
- High data complexity
