emma grundy: decision-making with predictive analytics
DESCRIPTION
Emma Grundy, IBM Predictive Analytics, on how evidence-based decision-making in health can be driven by predictive analytics software.TRANSCRIPT
© 2011 IBM Corporation
Business Analytics software
Driving evidence-based decision-making with predictive analytics
Emma Grundy
IBM Predictive Analytics Solution Architect for SPSS Software
© 2011 IBM Corporation
Business Analytics software
“To understand God's thoughts we must study statistics, for these are the measure of
His purpose”
© 2011 IBM Corporation
Business Analytics software
© 2011 IBM Corporation
Business Analytics software
© 2011 IBM Corporation
Business Analytics software
Cardiac department at Sequoia Hospital, California has several treatment options for patients both pre and post surgery.
Every individual patient cold react differently to treatment options based on factors such as age and weight, family history, previous treatment etc.
They wanted to be able to predicts risk the of mortality an individual patient would have for each treatment option to allow patients to make fully informed decisions.
They needed also to apply global rules to patients based on medical knowledge and patient preference to influence outcome.
Prior to implementation it could take up to two weeks for doctors to obtain this information.
© 2011 IBM Corporation
Business Analytics software
How do I chose the best post-op care for Mr Jones?
A B C
© 2011 IBM Corporation
Business Analytics software
Who did the treatment A work for in the past?
© 2011 IBM Corporation
Business Analytics software
Age
Weight
Family history
Treatment history
Medication
Doctor
Hospital
Days in hospital
Case Notes
Who did the treatment A work for in the past?
© 2011 IBM Corporation
Business Analytics software
How well does Mr Jones fit the profile?
© 2011 IBM Corporation
Business Analytics software
Treatment Chance of
Success
Patient Preferences
Cost Decision
78%
3
£90
81%
1
£80
64%
4
£50
How do I chose the best post-op care for Mr Jones?
Profile for each treatment
Mr Jones preferences
© 2011 IBM Corporation
Business Analytics software
Treatment Chance of
Success
Patient Preferences
Cost Decision
78%
3
£90
81%
1
£80
64%
4
£50
How do I chose the best post-op care for Mr Jones?
Profile for each treatment
Mr Jones preferences
© 2011 IBM Corporation
Business Analytics software
“The hospital detected a pattern that certain heart patients developed problems with bleeding during surgery if they received a particular blood clot prevention drug in the days before the procedure. The analysis led physicians to delay surgery for those who have been on the drug”
Audrey Fisher, MPH, director of cardiovascular services at Sequoia Hospital.
How do I chose the best post-op care for Mr Jones?
© 2011 IBM Corporation
Business Analytics software
Outcome for Sequoia Hospital
The hospital's mortality rate for cardiac surgery, decreased from 3.8% to 1.7%
Since implementation the Society of Thoracic Surgeons, which tracks and evaluates procedures and outcomes for hospitals nationwide, gave Sequoia Hospital the highest ranking in America for their cardiac mortality and post op complications rate.
"IBM predictive analytics is a life-saving technology as it allows us to quickly uncover the intelligence that matters most to allow our surgeons to make the best decision with precision and accuracy. Applying IBM predictive analytics to enormous amounts of information allows us to take evidenced-based diagnosis and patient care to the next level.“
Audrey Fisher, MPH, director of cardiovascular services at Sequoia Hospital.
© 2011 IBM Corporation
Business Analytics software
© 2011 IBM Corporation
Business Analytics software
For further information on IBM’s Smarter Healthcare Solutions please contact:
IBM Healthcare Portal:
http://www-01.ibm.com/software/uk/analytics/spss/healthcare/
Marios Hajipavlou IBM SPSS Healthcare Account Manager
e-mail: [email protected]
Phone: 020 8818 4776