Healthcare AI Quality Improvement Training Course

Name: Healthcare AI Quality Improvement Course
Availability: InStock

Apply AI to healthcare quality measures, data readiness, safety signals, root cause support, workflows, dashboards, human review, and escalation.

Healthcare AI Quality Improvement Training Course

At a glance

Duration: 5 days
Format: Classroom
Cities: Amsterdam, Amman, Johannesburg, Doha, Marbella, Rome and more
Next session: 5 – 9 October 2026, Amsterdam
Average fee: 5,800 €

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Healthcare AI Quality Improvement Course

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Overview

Healthcare AI Quality Improvement Course is a five-day foundation course for healthcare quality managers, clinical governance teams, patient safety personnel, hospital operations leaders, healthcare data analysts, and quality improvement coordinators, who leave with a Healthcare AI Quality Improvement Plan. Participants connect quality measures and data readiness with variation signals, root cause support, workflow improvement, patient safety review, human oversight, quality dashboards, and escalation. Agile Leaders Training Center provides training in healthcare AI quality improvement.

Who Should Attend

Healthcare quality personnel responsible for measures and improvement outcomes
Clinical governance personnel responsible for oversight and accountable decisions
Patient safety personnel responsible for event review and risk escalation
Hospital operations personnel responsible for workflows and service performance
Healthcare analytics personnel responsible for data quality and reporting
Improvement personnel responsible for testing changes and sustaining controls

The course assumes participants contribute to healthcare quality, safety, governance, operations, or analytics and leaves out clinical diagnosis, medical imaging, cybersecurity, virtual assistants, and technical model development.

Departments and Industries

The course supports governed AI use in quality improvement across healthcare delivery and related services.

Healthcare quality and clinical governance departments
Patient safety and risk management functions
Hospital operations and performance improvement teams
Healthcare data and digital health functions
Hospitals, clinics, and ambulatory care networks
Health insurance and care management organizations

Learning Objectives

By the end of this course, participants will be able to:

Build defined quality measures and traceable data registers
Analyze performance variation and patient safety signals
Use AI-assisted root cause analysis support with human review
Apply workflow mapping and improvement-cycle methods
Evaluate bias, explanations, monitoring, and escalation controls
Build a Healthcare AI Quality Improvement Plan

Course Agenda

Day 1: Quality Measures and Data Readiness

Quality Improvement Aim Charter
Healthcare Quality Measure Definition Sheet
Clinical and Operational Data Source Register
Data Quality and Lineage Checklist
Baseline Performance and Variation Chart

Day 2: Signals and Root Cause Support

Quality Variation Signal Review Card
Patient Safety Event Pattern Screen
Risk Signal Confidence and Limitation Record
AI-Assisted Root Cause Evidence Map
Human Review and Escalation Flow

Day 3: Workflow and Improvement Cycles

Care Process Workflow Map
Bottleneck and Handoff Analysis
Improvement Hypothesis Priority Matrix
Plan-Do-Study-Act Cycle Design
AI-Supported Change Test Plan

Day 4: Quality Governance and Dashboards

Healthcare Quality Improvement Dashboard
Bias and Equity Outcome Review
AI Explanation and Evidence Record
Third-Party Healthcare AI Review
Monitoring Threshold and Change Register

Day 5: Healthcare Quality Improvement Practice

Suggested Exercise: Define Measures and Validate Data
Suggested Exercise: Review Variation and Safety Signals
Suggested Exercise: Map Root Causes and Improve Workflows
Suggested Exercise: Set Dashboard and Governance Controls
Capstone Exercise: Healthcare AI Quality Improvement Plan

Practical Exercises

The course uses suggested activities that turn healthcare quality data and AI-supported signals into governed improvement decisions.

Suggested activity: define quality measures, register data sources, and test data readiness
Suggested activity: review variation, patient safety patterns, signal limits, and root cause evidence
Suggested activity: map workflows, prioritize hypotheses, and design a Plan-Do-Study-Act cycle
Suggested activity: assemble a healthcare quality improvement dashboard with bias, explanation, monitoring, and escalation controls

FAQs

Who suits healthcare AI quality improvement training, and what does it assume?

Healthcare AI quality improvement training suits personnel responsible for quality, clinical governance, patient safety, hospital operations, healthcare analytics, or improvement coordination. It assumes familiarity with healthcare processes or quality measures and requires no programming.

How does healthcare AI quality improvement differ from clinical AI training?

Healthcare AI quality improvement focuses on measures, process variation, safety signals, root cause support, workflows, dashboards, and governed improvement decisions, while clinical AI training may focus on diagnosis, treatment, imaging, or direct clinical decision support.

How should teams use AI-assisted root cause analysis support?

Teams should use AI-assisted root cause analysis support to organize evidence and surface patterns, then validate sources, test alternative explanations, include frontline knowledge, document uncertainty, and keep accountable people responsible for conclusions and actions.

What controls belong on a healthcare quality improvement dashboard?

A healthcare quality improvement dashboard should show measure definitions, baselines, trends, stratification, data limitations, alert thresholds, responsible owners, human review, improvement actions, and change history.

What belongs in a Healthcare AI Quality Improvement Plan?

The plan should include aims, measures, data sources, variation reviews, safety signals, root cause evidence, workflow maps, improvement cycles, bias checks, explanation records, dashboard measures, monitoring thresholds, escalation, owners, and review dates.

Conclusion

Participants take back a Healthcare AI Quality Improvement Plan connecting measures, data, signals, root cause evidence, workflows, improvement cycles, dashboards, human review, and escalation. It changes how teams select and govern AI-supported quality actions. The plan provides a basis for traceable evidence, visible limitations, accountable decisions, and monitored improvement.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Showing 21-40 of 76 events

Location	Dates	Duration	Mode	Price
Milan	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Onsite	€5,700
Muscat	Week 53, 2027 3 – 7 January 2027	5 Days	Onsite	€5,700
Barcelona	Week 02, 2027 11 – 15 January 2027	5 Days	Onsite	€5,700
Abu Dhabi	Week 02, 2027 11 – 15 January 2027	5 Days	Onsite	€4,700
Langkawi	Week 02, 2027 17 – 21 January 2027	5 Days	Onsite	€6,000
Trabzon	Week 02, 2027 17 – 21 January 2027	5 Days	Onsite	€6,800
London	Week 04, 2027 25 – 29 January 2027	5 Days	Onsite	€5,700
Cairo	Week 05, 2027 1 – 5 February 2027	5 Days	Onsite	€4,100
Lisbon	Week 05, 2027 1 – 5 February 2027	5 Days	Onsite	€5,700
Paris	Week 06, 2027 8 – 12 February 2027	5 Days	Onsite	€5,700
Dubai	Week 07, 2027 15 – 19 February 2027	5 Days	Onsite	€4,500
Nice	Week 07, 2027 15 – 19 February 2027	5 Days	Onsite	€5,700
Madrid	Week 08, 2027 22 – 26 February 2027	5 Days	Onsite	€5,700
Zoom	Week 09, 2027 1 – 5 March 2027	5 Days	Online	€1,500
Barcelona	Week 10, 2027 8 – 12 March 2027	5 Days	Onsite	€5,700
Munich	Week 10, 2027 8 – 12 March 2027	5 Days	Onsite	€5,700
Prague	Week 11, 2027 15 – 19 March 2027	5 Days	Onsite	€6,000
Accra	Week 11, 2027 21 – 25 March 2027	5 Days	Onsite	€4,100
Rome	Week 13, 2027 29 March – 2 April 2027	5 Days	Onsite	€5,700
Kuala Lumpur	Week 14, 2027 5 – 9 April 2027	5 Days	Onsite	€5,200

Frequently asked questions

What does this course cover?

OverviewHealthcare AI Quality Improvement Course is a five-day foundation course for healthcare quality managers, clinical governance teams, patient safety personnel, hospital operations leaders, healthcare data analysts, and quality improvement coordinators, who leave with a Healthcare AI Quality Improvement Plan. Participants connect quality measures an…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

Healthcare AI Quality Improvement Training Course