mhealth israel_roy malka, scientific director, sheba, tel ha shomer, innovation center
TRANSCRIPT
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Innovation in HealthcareROY MALKA, PHDSCIENTIFIC DIRECTOR, INNOVATION CENTERTHE SHEBA MEDICAL CENTER, ISRAEL
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mHealth June, 7, 2017
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The Need for innovation
u All over the world the costs of healthcare are rising, with the increase fraction of elderly in the population the trend is expected to continue.
u Within a public healthcare system, Israel an example, most medical services are not lucrative, some of the services are generating negative revenue.u Thus, Hospitals must be resourceful to stay balanced, hence the need for
innovation
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The Need for innovation
u A joint study by The World Bank’s, Chinese government & the World Health Organization recommends:u shift away from its current hospital-centric model.
u Health spending are expected to increase in real terms from 3.5 trillion yuan in 2014 to 15.8 trillion yuan in 2035— 9% of GDP.u 60 % of growth would come from increased inpatient services in hospitals.
u Naturally, this is true all over the world – Hospitals services are expensive!
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Idea-genesis
Animal modeling of human diseases – Tissue Bank
Feasibility studies on animal models - Pathology
Helsinki Committee documentation
Clinical studies
Establishing IP
Developing IP with partners
"“One Stop Shop
Translational Research PowerhouseFrom Idea to a ProductTraditional medical innovation
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How can we overcome the high costs of innovation?
1. Collaborate– preferably with experienced individuals and institutions
2. Focus our efforts– build domain expertise within your hospital
3. Support multidisciplinary work– Rephrase the problem to adopt tools from other disciplines
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The characterization of the solution
u Current hospitals services are:
u responsive & expensive
u New services should be proactive:
u which requires predicting the right action, at the right time to the right person.
u New services need to be scalable and not expensive
u Can we increase the physicians productivity?
Technology!!
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On the verge of a paradigm shift
u The computer revolution changed the way we do many things:u Many things today are transformed into computations
u For example, 30 years ago it was not clear what is the connection between taking pictures and computational power.
u Today, it is hard to find film based cameras, or film.
Historical perspective
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On the verge of a paradigm shift
u Now, we are on the verge of transforming driving into prediction
u How can we change medicine to be prediction based?
Predictions for all
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Focusing on Sheba Medical Center (SMC)
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Transforming Big Data to Knowledge (BD2K) The Challenge
We Must Analyze Exponentially Growing Healthcare Data Assets
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Finance
Pharmacy
Supply System
Health IT
Clinic
EMR
Labs
Imaging
Vital Signs
Research
A mixture of many subsystems that document different aspects of the shared processes
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Sheba IT systems
Vital Signs Systems
EMR
Laboratory -AutoLIMS
Imaging- Pacs, Carestream, C-Pacs
Medical Admin.Logistics
HR
FinanceSupply Systems
Information exchange-Between healthcare providers
EnterpriseData
Warehouse
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Analysis of millions of patient records to match patients to medication and identify prescription errors
Preventing Medication Errors
Real WorldExample
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Preventing Medication Errors
Real WorldExample
An interpretable working principle
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Preventing Medication ErrorsAvoiding ‘Alert fatigued’ is a key feature in adopting
such a system
The Sheba Experience (Pilot Study):q One alert / department / day (~0.5% of prescriptions)q Most alerts accepted by physicians and cause a change in prescription (~80%)
Real WorldExample
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Preventing Medication ErrorsIndependent Validation
Real WorldExample
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Tele-Medicine
u Providing remote specialty servicesu Doctor to doctor consultation
u Using technology to provide objective measurements remotely
u Patient generated data
u Rehabilitation services from the comfort of one’s home
u Management of chronic conditions
Established technology
Real WorldExample
Bridginggeographical
distance
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100 150 200 250 300 350AG- Average Glucose (mg/dL)
4
5
6
7
8
9
10
11
12
13
14H
bA1c
- G
lyca
ted
Hem
oglo
bin
fract
ion
(%) non-diabetic
type 1type 2linear regression
7%- Treatmentthreshold
6.5%- Diagnosisthreshold
Why glycated hemoglobin (HbA1c/A1c) is used to monitor diabetes? A1c has a linear relation with the average blood glucose
Nathan et al. Diabetes Care 2008
Clinicallysignificantvariability
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The missing measurement: assuming all patients have the same RBC lifespan
AG (g/dL)100 150 200 250 300 350 400
HbA
1c (%
)
2
4
6
8
10
12
14
A
Input
Output
p = 0.85
Simulationmeasurement
Roy Malka et al., Sci Transl Med 2016;8:359ra130
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AG (g/dL)100 150 200 250 300 350 400
HbA1
c (%
)
2
4
6
8
10
12
14
A
Input
Output
p = 0.927
Simulationmeasurement
!
High degree of consistency between the model simulations and the data when adding variability in the mean RBCs age
Roy Malka et al., Sci Transl Med 2016;8:359ra130
The missing measurement (RBC age – not measured clinically) can not be revealed by ‘big data’ approaches!
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The approach to innovationat the Sheba Medical Center
Applied and Basic ResearchTo Improve patients outcomes
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The three pillars of innovation in medicine Clinical
InventorsImplementation
1. Unmet clinical need
2. Invention that answers a clinical need
3. Real life implementationthat can be integrated in the clinic and change the patient’s outcome.
Sheba innovation center is standing on these three pillars
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“The real voyage of discovery consists not in
seeking new landscapes, but in having new eyes”
Marcel Proust
ROY MALKA, [email protected]
Scientific Director Innovation Center
Sheba Medical Center