HomeIndustriesHealthcare
Healthcare · SAP Analytics Cloud

SAP Analytics Cloud templates for Healthcare

4 ready-to-use SAC and SAC Planning templates for Healthcare — each with the KPIs, dimensions and realistic data your function actually tracks. Import in minutes, or generate a tailored one. No sign-up.

KPIs we cover for Healthcare

Patient volumeAverage length of stayReadmission rateBed occupancy rateCost per stayHospital-acquired infection ratePatient satisfaction

Analysis dimensions

Hospital departmentConditionProcedure typeAge bandRegionFacility

4 Healthcare templates

Each opens with a live preview and a one-click download (.xlsx, .csv, .package).

SAC Analytics

Hospital activity

Manage activity: patient volume, average length of stay, case-mix and activity by department.

Patient volumeAverage length of stayCase-mix
Open template →
SAC Analytics

Quality of care

Monitor quality: hospital-acquired infections, early readmissions and adverse events.

Hospital-acquired infection rate30-day readmission rateRisk-adjusted mortality
Open template →
SAC Analytics

Hospital costs

Break down your costs by stay, DRG and payroll relative to revenue.

Cost per stayCost per DRGPayroll/Revenue
Open template →
SAC Analytics

Hospital capacity

Manage capacity: bed occupancy rate, length of stay and ER flow.

Bed occupancy rateAverage length of stayAvailable beds
Open template →

How to model Healthcare in SAP Analytics Cloud

A solid Healthcare model starts with the right grain. Build your dimensions first (Hospital department, Condition, Procedure type), then add the measures that matter (Patient volume, Average length of stay, Readmission rate). The trap is aggregation: amounts and volumes sum, but rates and percentages must use AVERAGE, and stocks or balances must use a LAST exception on the time dimension — otherwise your yearly totals come out wrong.

Set those aggregations once in the Modeler, import your data, and build a Story from the KPIs above. For the full method, see our guides on importing a CSV into SAC and choosing the right aggregation.