DIME PROJECT

Implementing AI in Healthcare

SECTION 2 | CHOOSE THE RIGHT TOOL

Unlock cumulative AI value in healthcare workflows

Many systems overlook the power of incremental gains in high-volume, high-frequency workflows where AI thrives. By focusing on “stackable wins”, you can drive cumulative ROI while building institutional confidence and capability over time.

Look for AI tools that embed seamlessly into these workflows and free up frontline capacity. Think patient registration, prior authorization checks, routine medication refills, or discharge instructions. These repetitive, rules-based tasks are ripe for automation, and even a small time savings at the task level can “stack” into recovered staff time, reduced delays, and better throughput across the enterprise.

Common characteristics of tasks ripe for AI automation

High frequency (thousands of times per day)

Standardized or semi-structured processes

Low clinical ambiguity

Clear handoffs between systems or staff roles

Stackable Wins Pyramid

The interactive graphic below illustrates how cumulative efficiencies compound over time. Use it to prioritize implementation opportunities based on complexity, risk, and volume to de-risk early deployment and accelerate system-wide impact.

Personalized & precision AI (Few/week)

Use case: Pharmacogenomics, individualized pathways

AI role: Multi-modal data fusion for treatment optimization

Workflow integration: Embedded in clinical decision-making moments

Value: Tailored care, reduced waste, future-state transformation

Note: High complexity, low immediate ROI. Requires significant workflow adaptation.

Predictive & diagnostic tools (Dozens/day)

Use case: Readmission risk scoring, sepsis prediction, radiology triage

AI role: Predictive modeling based on health record or imaging data

Workflow integration: Alert delivery at natural decision points

Value: Proactive care, safety, resource optimization

Note: High governance burden. Must prove real-world value without workflow disruption.

Clinical documentation & workflow assistance (Hundreds/day)

Use case: Ambient scribing, discharge summary drafting, task routing

AI role: Summarization, predictive automation

Workflow integration: Background processing during natural clinical interactions

Value: Clinician satisfaction, revenue lift, burnout reduction

Note: Success depends entirely on preserving natural clinical conversation flows.

High-volume administrative tasks (Thousands/day)

Use case: Patient registration, insurance verification, appointment reminders, prior authorization

AI role: Automate structured processes

Workflow integration: Behind-the-scenes automation of routine processes

Value: Staff time recovery, fewer errors, faster throughput

Note: High reward, low risk.

Ideal entry point—minimal workflow disruption.

Where can AI deliver impact?

Not all AI domains integrate equally well with existing healthcare workflows. Use this overview to understand where AI is likely to perform reliably within current work patterns and where it may require significant workflow adaptation or introduce higher implementation risk.

Mature solutions should integrate smoothly; emerging tools require careful workflow redesign and piloting. Select vendors not just for features, but for their proven ability to integrate seamlessly, support workflow preservation, and evolve with your system’s natural work patterns.

Defining Maturity Status

Medical imaging & diagnostics

Status

Use cases

Enablers

Barriers

Business value

Widely deployed

Radiology triage, image interpretation, incidental findings detection

✅ FDA-cleared tools

✅ Mature data & infrastructure

❌ Commoditizing vendor space

❌ Integration costs still high

Faster, more accurate diagnoses

Workload reduction

Precision

Increased throughput

Workflow automation & clinical documentation

Status

Use cases

Enablers

Barriers

Business value

Scaling

Sepsis prediction, readmission risk, order recommendations

✅ Regulatory clarity emerging

✅ Strong clinical demand

❌ Alert fatigue risks

❌ Governance and validation burdens

Augmented decision-making

Improved outcomes

Efficiency

Cost containment

Remote monitoring & patient-generated data

Status

Use cases

Enablers

Barriers

Business value

Scaling

Chronic disease tracking, post-op monitoring, vitals from wearables

✅ RPM codes exist

✅ Consumer digital health technology adoption

❌ Data quality variability

❌ Integration with clinical systems

Early intervention

Cost reduction

Resource optimization

Patient retention

Patient communication & engagement

Status

Use cases

Enablers

Barriers

Business value

Scaling

AI chatbots, patient FAQs, education, and translation tools

✅ High patient demand

✅ Fast LLM evolution

❌ Risk of misinformation

❌ Cultural and accessibility gaps

24/7 support

Staff efficiency

Consistent and multilingual outreach

Increased retention

Treatment planning & personalization

Status

Use cases

Enablers

Barriers

Business value

Emerging

Precision oncology, pharmacogenomics, pathway optimization

✅ Scientific momentum

✅ Academic/industry partnerships

❌ Data standardization gaps

❌ Payer & clinical adoption slow

Tailored treatments

Timely care

Reduced waste

Better outcomes

Next steps

Now that you’ve identified where AI can deliver the greatest impact, the next step is deciding how to source your solution. Explore whether building, buying, or partnering best aligns with your workflows, capabilities, and long-term strategy.

Choose your procurement path

DIME PROJECT

Implementing AI in Healthcare

Unlock cumulative AI value in healthcare workflows

Common characteristics of tasks ripe for AI automation

Stackable Wins Pyramid

Personalized & precision AI (Few/week)

Predictive & diagnostic tools (Dozens/day)

Clinical documentation & workflow assistance (Hundreds/day)

High-volume administrative tasks (Thousands/day)

Where can AI deliver impact?

Defining maturity status

Next steps