Post on 05-Dec-2014
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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.