Healthcare Predictive Analytics
Consulting

The four main types are:

• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics

1. Descriptive- It gives information about something that has already happened (e.g., patient visits, outcomes).
2. Diagnostic- It is used to determine the causes for trends in a patient (e.g., identifying factors for readmission).
3. Predictive- A forecast of what is to come next in events (e.g., risk of any disease).
4. Prescriptive- This is the advice for taking measures for the best possible care pathway for the patient.

The analytics consultant helps organisations locate data-driven opportunities, design fit-to-purpose solutions, and build models that yield insights along business objectives. In healthcare, this most often means aligning predictive models to clinical, operational, and financial outcomes while ensuring compliance and scalability.

Readmission prediction is among the most accepted applications. Hospitals take into consideration the history of the patient along with comorbidities and treatment patterns in determining risk and intervening early with the intent of bringing about favourable outcomes while reducing costs.

An example would be predictive analytics being used by the Mayo Clinic for predicting patient deterioration, ICU management, and customising treatment pathways. The use of predictive models for staff optimisation, population health, and operational optimisation is common across most health systems.

A common use case, length of stay forecast, enables hospitals to plan discharges, optimise bed utilisation, and coordinate care better in high-volume areas such as emergency or surgical departments.