Healthcare Analytics

Nigam Shah, MBBS, PhDnigam@stanford.edu

Analytics uses Big DataData Size

Big

Small

Small Large

Number of samples

Next gen-seq, iPOP,

Claims, EMR, Clinical

notes

?

Think about samples vs. variables

P

ati

ents

Variables

Genome Expression Metabolome

Millions (Billions?)

??

Diseases

Procedures

Drugs Devices

About 100,000

M

illions

Themes in Healthcare Analytics

Precision of diagnosis/treatment

A lot of research and disruptive technologies are emerging to enable data-driven decisions.

• Personalization is the mantra

• Total awareness about patients to provide the care they need proactively. Using behavior profile, social profile, contextual / spatial orientation

• Patients come in seeking particular option .. how do you counter that?

Quality, cost and operations

Real time monitoring of acuity, staffing, resources & outcomes for operational transparency.

• System efficiency is the mantra

• Frequent fliers to the ER .. how to identify them and intervene?

• End of life care is 50% of the spend .. how to form a 'circle of care' at home?

• What fraction of care is 'defensive care'?

Both of these are data problems in some fashion and can be tackled with either lots of data on one patient, or some data on lots of

people.