Healthcare Value Management Training Course

Participants can align a value initiative with organisational strategy, service priorities and measurable aims.

• Strategic objectives translated into measurable value-management aims
• Balanced Scorecard perspectives connected to healthcare value priorities
• Service-line strategies tested against population health needs
• Defining scope, boundaries, assumptions, and decision rights early
• Benefits logic maps linking interventions to intended outcomes
• Value charters specifying sponsors, resources, timescales, and success criteria

Participants can establish stakeholder engagement and governance arrangements for a value-management initiative.

• Stakeholder mapping across patients, clinicians, payers, and providers
• Power-interest grids used to plan engagement actions
• RACI matrices assigning accountability for value-management decisions
• Patient and family partners included in design governance
• Clinical leadership roles defined for pathway redesign
• Escalation routes established for contested priorities and risks

Participants can define priority populations and assess needs that shape service value.

• Population segmentation by condition, risk, complexity, and utilisation
• Risk stratification identifies patients requiring different care models
• Epidemiological rates interpreted for service planning decisions
• Needs assessment combines demand, prevalence, outcomes, and access data
• Health inequalities identified through demographic and geographic comparisons
• Priority populations selected using burden, variation, and feasibility criteria

Participants can map a patient journey and identify value loss across care transitions.

• Patient journey maps capture touchpoints, waits, hand-offs, and outcomes
• SIPOC diagrams define pathway suppliers, inputs, processes, outputs, customers
• Swimlane maps expose responsibilities across multidisciplinary care teams
• Failure demand distinguishes avoidable contacts from necessary care
• Bottlenecks located through demand, capacity, and flow analysis
• Future-state pathways specify coordinated care and escalation points

Participants can design an outcome framework for a condition, pathway or service.

• Outcome hierarchies separate survival, recovery, and sustainable health
• Clinical outcome indicators selected for validity and actionability
• PROMs and PREMs incorporated into outcome measurement sets
• Process measures distinguished from outcomes and balancing measures
• Indicator definitions specify numerator, denominator, source, and frequency
• Measurement plans assign ownership, baselines, targets, and reporting cycles

Participants can assess whether healthcare data is fit for value-management decisions.

• Data quality dimensions assess completeness, accuracy, timeliness, and consistency
• Case-mix adjustment prevents misleading comparisons between patient groups
• Run charts reveal performance patterns over time
• Benchmarking compares outcomes, costs, and utilisation with appropriate peers
• Data dictionaries standardise definitions across reporting teams
• Missing data and coding biases documented before interpretation

Participants can incorporate patient experience, access and equity into value assessments.

• Experience measures identify communication, dignity, and coordination failures
• Access metrics track waits, travel, affordability, and eligibility barriers
• Equity stratification compares outcomes across protected and underserved groups
• Co-design methods capture lived experience and service priorities
• Patient-reported barriers converted into pathway improvement requirements
• Equity impact assessments test proposed service changes before approval

Participants can apply function analysis to distinguish essential service functions from unnecessary cost.

• Functions expressed as active verb and measurable noun
• Primary and secondary functions distinguished within care services
• FAST diagrams show logical relationships between pathway functions
• Function-cost matrices identify expensive functions requiring review
• Unnecessary functions separated from regulatory and clinical requirements
• Creative alternatives generated without compromising safety or outcomes

Participants can estimate the cost of care pathways and identify major resource drivers.

• Direct, indirect, fixed, and variable costs classified correctly
• Time-driven activity-based costing maps capacity cost rates
• Process time estimates linked to staff, equipment, and space
• Cost-to-charge ratios distinguished from actual resource consumption
• Pathway cost profiles identify high-cost steps and rework
• Sensitivity analysis tests uncertain cost and volume assumptions

Participants can compare intervention options using healthcare economic evaluation methods.

• Cost-effectiveness analysis compares incremental costs and health outcomes
• Incremental cost-effectiveness ratios interpreted with stated limitations
• QALYs explained as a common health outcome measure
• Budget impact analysis estimates affordability over defined planning periods
• Opportunity costs identified when resources move between services
• Decision criteria combine economics, equity, evidence, and feasibility

Participants can analyse demand and capacity constraints affecting pathway value.

• Demand profiles distinguish scheduled, urgent, and variable activity
• Capacity models account for staffing, rooms, equipment, and opening hours
• Utilisation rates interpreted without assuming higher is always better
• Little’s Law connects work-in-progress, throughput, and waiting time
• Queue analysis identifies delay risks at constrained pathway stages
• Demand-capacity actions prioritise flow improvements before additional resources

Participants can integrate quality and safety risks into value-management decisions.

• Donabedian structure, process, and outcome measures applied
• Failure modes and effects analysis prioritises preventable pathway risks
• Root cause analysis separates system factors from individual error
• Balancing measures detect unintended consequences of service changes
• Statistical process control distinguishes common and special cause variation
• Safety cases document controls for higher-risk redesign proposals

Participants can assess how digital systems and technologies affect healthcare value.

• Digital workflow maps identify duplicate entry and information delays
• Interoperability requirements linked to pathway coordination and safety
• Clinical decision support evaluated against outcomes and workflow burden
• Technology adoption costs include training, maintenance, and change impacts
• Data governance addresses privacy, access, ownership, and quality
• Benefits realisation plans track digital value after implementation

Participants can incorporate supplier, contract and partnership decisions into value management.

• Total cost of ownership assesses purchase, use, support, disposal
• Outcome-based specifications define required results rather than inputs
• Supplier evaluation balances quality, cost, resilience, and sustainability
• Contract KPIs align provider performance with patient outcomes
• Make-buy analysis tests internal delivery against external options
• Partnership governance clarifies data sharing, accountability, and dispute routes

Participants can prioritise value opportunities and prepare an evidence-based value case.

• Weighted decision matrices rank opportunities against agreed criteria
• Impact-effort matrices separate quick actions from major programmes
• Value cases state problems, options, costs, outcomes, and risks
• SMART benefits measures define expected service and financial results
• Assumptions registers record evidence gaps and validation actions
• Recommendation papers distinguish preferred options from rejected alternatives

Participants can convert a value case into a practical implementation and adoption plan.

• Theory of Change links activities, outputs, outcomes, and assumptions
• Implementation roadmaps sequence pilots, scale-up, and review points
• ADKAR assessments identify individual adoption barriers and actions
• Training needs analyses define capability requirements by role
• Risk registers assign owners, controls, triggers, and contingencies
• Communications plans tailor messages for clinical and operational groups

Participants can monitor implementation performance and verify value achieved after change.

• Benefits realisation plans assign measures, owners, and review dates
• Dashboard designs combine outcome, cost, access, and experience indicators
• Leading indicators provide early warning before outcome deterioration
• Plan-Do-Study-Act cycles test changes under controlled conditions
• Review cadences link operational meetings to corrective actions
• Post-implementation evaluations compare realised results with original value cases

Participants can build, review and present a complete value-management work package for a healthcare service, pathway or population.

• Value problem statement validated against patient and organisational priorities
• Stakeholder map, pathway analysis, and function model assembled
• Outcome, experience, equity, and cost measures specified
• Intervention options assessed through evidence, feasibility, and economic criteria
• Implementation roadmap, governance, risks, and benefits controls completed
• Peer review challenges assumptions, recommendations, and presentation evidence