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Innovation in the use of decision technologies in health care

Dr Geraint Lewis Senior Fellow

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Decision Technology

Preferences

Information

Question

Answer

Decision technology

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How do I get to the Millennium

Stadium in Cardiff?

• Current position • Destination • Route map UK • Average journey

times at different times of day, and different days of the week

• Current time • Live feed of traffic

conditions Turn right at the roundabout, third

exit

• Avoid motorways? • Avoid toll roads? • Speed or fuel

efficiency? • Car share lanes?

Question

Answer

Satellite navigation as an example of decision technology

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Questions

Patients Clinicians

Managers Commissioners

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Emma Grundy IBM Predictive Analytics Solution Architect

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How do I choose the best post-operative care for Mr Jones?

A B C Source: Emma Grundy, IBM Predictive Analytics

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Who did treatment A work for in the past?

Source: Emma Grundy, IBM Predictive Analytics

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Who did treatment A work for in the past?

Age

Weight

Family history

Treatment history

Medication

Doctor

Hospital

Days in hospital

Case Notes

Source: Emma Grundy, IBM Predictive Analytics

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How do I choose the best post-operative care for Mr Jones?

Treatment Chance of

Success

Patient Preferences

Cost Decision

78%

3

£90

81%

1

£80

64%

4

£50 Mr Jones’

preferences

Source: Emma Grundy, IBM Predictive Analytics

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Detecting patterns of complications

“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

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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.

Source: Emma Grundy, IBM Predictive Analytics

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Dionisio Acosta Centre for Health Informatics and Multiprofessional Education, UCL Vivek Patkar Cancer Institute, UCL Mo Keshtgar Department of Surgery, Royal Free Hospital John Fox Department of Engineering Science, University of Oxford

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Multi-disciplinary Assistant & Treatment sElector (MATE)

Source: Dr Dionisio Acosta, University College London

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Multidisciplinary Assistant & Treatment sElector (MATE)

Source: Dr Dionisio Acosta, University College London

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Data input

Source: Dr Dionisio Acosta, University College London

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Recommended treatments

Source: Dr Dionisio Acosta, University College London

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Differential expected life-expectancy

Source: Dr Dionisio Acosta, University College London

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Results

Source: Dr Dionisio Acosta, University College London

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geraint.lewis@nuffieldtrust.org.uk