"insourcing innovation - presentation by sansum's david kerr at the summer 2014...
DESCRIPTION
David Kerr, new director of research & innovation at the Sansum Diabetes Research Institute in Santa Barbara, discusses "insourcing innovation" at the June 2014 DiabetesMine D-Data event in San Francisco.TRANSCRIPT
Can Machines Think?
“Can machines help people think?”
“Can people help machines help people think?
http://smart.inf.ed.ac.uk/category/video/
Diabetes Care TodayADA recommendations•<8.0% 6-12 years•<7.5% 13-17 years•<7.0% adults
“while avoiding recurrent hypoglycemia”
“patients with type 1 diabetes are capable of achieving target HbA1c levels”
N = 6229 13-18 year olds 8.8%N= 6862 6-13 year olds 8.4%
Beck R et al J Clin Endocrinol Metab 2012; 12: 11
25,390 children and young people with diabetes
HbA1c <7.5% 17%
HbA1c 7.5 - 9.0% 56%
HbA1c >9.0% 27%
Personal DiabetesAged 46•Type 1 diabetes 35 years•HbA1c 6.1%•Mother, athlete, researcher•CSII, CGMS•No complications•No severe hypoglycemia
20 minutes
Diabetes Care Today
• Unattractive technology• consumer electronics• Impersonal technology• make it mine• Inaccessible technology• visual, functional, cognitive• One-size-fits-all technology• reservoirs, tubing, strips• Unconnected technology• sync with phone, records, social• Unintelligent technology
• Education, learning http://www.diabetesmine.com/2012/11/patients-call-for-innovation-diabetesmine-summit-2012.html
“65% of all time downloads from the diabetes app market are generated by only 14 app publishers. The majority are small app developers”
“Mobile diabetes apps are currently used by only 1.2% of
the target group”
The current approach to technology for diabetes care is not working
Insourcing Innovation – 4 Stage Design
• Contextual enquiry • Embed in the life of users• Social component
• Problem definition• What is the exact problem• Avoid expensive premature anchoring
• Exploration of alternatives• Divergence in alternatives• Real-time user feedback
• Rapid validation• Does it make a difference• Hours and days
Asch D et al N Eng J Med May 8th 2014
Diabetes Care Today
People – process information, creative, abstract – high level
Machines – organize , analyze, process, present information – low level
Social – supportive, alternative, non-hierarchical –high level
The Rise of Social Machines
http://sociam.org/
Smart Society
http://smart.inf.ed.ac.uk/
“Society is moving towards a socio-technical ecosystem in which the physical and virtual dimensions of life are more and more intertwined and where people interaction, more often than not, takes place with or is mediated by machines”
Natural Pancreas
Glucose
Artificial Pancreas
Doyle F J et al. Dia Care 2014;37:1191-1197
Fully Automated Closed-Loop SystemKudva, Diabetes Care May 2014
Problem Solving• Hypo unaware• Metabolic memory• New onset T1DM• Pregnancy planning
Adaptive Diabetes Systems
Non-Adaptive Systems
Adaptive Diabetes Systems
Device
Data Interpreted
Shared
Elaborated
InformationExperienceConsumer
Data
Humans as Consumers Adaptive, Individual, Scalable, Societal
Adaptive Diabetes Systems- Roadblocks
Human
Machine
Outcomes
Device Semantic Gap
Evidenced
TrustworthyWorthwhile
Provenance
Smart Diabetes Society
• Devices (open, interoperable)• Data (semantics)• Architecture (cloud)• Adaptation – (physiological)• Adaptation – (learned)• Social (big data)• Effectiveness (evidence, trust)• Incentives (stickiness)
Creating a Smart Diabetes Society-Contextual Enquiry and Problem Definition
Creating a Smart Diabetes Society-Exploration of alternatives
Information Here and Now
$
$
$
Creating a Smart Diabetes Society-Rapid Validation
Data
New DataNew ExperienceNew OutcomesGlucocentricPerfomanceQualitative
Share
Smart Diabetes Society - Travel
Smart Diabetes Society – Mass Gatherings
Smart Diabetes Society
Life Moments
Human Experience
Knowledge
Social Interaction
Adaptive Machines
Devices Data
Crowd
Kerr D, Deus Ex Machina Prim Care Diab 2011
UCSanta Barbara/Sansum Consortium for Diabetes Innovation
• Chemical Engineering (Artificial Pancreas)• Computer Science (Cloud Computing)• Digital Games Research (Health Games)
Smart Diabetes Society
Open DataInteroperability
Smart Diabetes Society
