Appointment no-show reduction
Predict and reduce missed appointments.
No-show reduction analyses historical appointment data, patient characteristics and external factors to estimate absence probability, targeting reminders and replacement appointments.
- Higher efficiency
- Higher customer satisfaction
- Cost reduction
no-shows
utilisation
payback
patient satisfaction
Calculated from additional treated patients and reduced idle capacity.
- 01
Data integration
Consolidate data from ERP, MES and further sources for Appointment no-show reduction.
- 02
Data quality
Clean, harmonise and validate data for plausibility.
- 03
Model development
Train and validate the Appointment no-show reduction model on historical data.
- 04
Pilot
Pilot Appointment no-show reduction in one area and collect feedback.
- 05
Rollout
Scale the solution and integrate it into operational processes.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
Patient data
Treatment data, appointments and resource use.
Appointment data
Patient and customer appointments with history.
ERP data
Master and transaction data from ERP.
HR data
Shift plans, qualifications and absences.
Documents
Specifications, quotes, contracts and reports.
Customer data
Contracts, cases and communication.
Patient management
Improves processes and resource utilisation.
HR
Plans personnel and qualifications better.
Controlling
Quantifies effects and supports budgeting.
IT
Builds on a scalable and secure data infrastructure.
Higher efficiency
Higher customer satisfaction
Cost reduction
Better planning
More transparency
With a solid data foundation this use case gets faster, cheaper and far more stable.
Central data platform
Real-time data integration
Scalable analytics pipelines
Reusable data products
Demand forecasting
Data flow enables more precise forecasts.
Automated reporting
Metrics are provided without manual effort.
BI reporting
Metrics are delivered in dashboards.