Geber Brand Consulting

格博品牌行銷顧問公司

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About Us關於我們

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2008

Affinity-Asia Brand

Consulting established.

Richard deVries成立愛芬尼品牌顧問公司

2010 2011 2012

Film department

established.

成立設計及影片部門

Awarded as a Preferred

Vendor for Marketing

Excellence in the

Semiconductor Industry

榮獲半導體產業行銷首選顧問公司

Selected as one of the

top brand consulting

companies by TAITRA

獲選為TAITRA優質品牌顧問公司

Our History - Timeline

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2013 2014 2016

Shanghai office成立上海辦公室

Selected by TIER as a key

branding consultancy for

"Branding Taiwan 2.0”

獲選為TIER「台灣品牌2.0計畫」重點品牌顧問公司

Rebranded as "Geber

Brand Consulting” to

reflect our growing

global presence

改名為格博品牌顧問，並重建品牌，呈現更國際化的服務

Dallas, Texas Leipzig,

Germany

成立德州、德國辦公室

Cooperated with

Microsoft Taiwan for

internal training and

branding

台灣微軟內部培訓首選顧問公司

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Your ‘virtual marketing team’

您的“虛擬營銷團隊”Full-Solution Brand Consultancy

全方位解決方案的品牌顧問

Offices in Taipei and Shanghai, and

a list of affiliates in major markets.

於台北、上海擁有辦公據點並在每個主要市場都有子公司

North America New York (6) Toronto (6) Los Angeles (5) San Francisco (4) Vancouver (3) Europe

• United Kingdom (5)• Germany (3)• Denmark (2)• Italy (2)• Austria (2)• Netherland (2)• Finland (1)• France (1)

Other• Sydney (2)• Buenos Aires (1)

Asia• Hong Kong (4)• Kuala Lumpur (2)• Singapore (2)• Tokyo (2)• Mumbai (1)

Global Network of PR Contacts

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WHERE DOES THE DATA COME FROM?

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Blood pressureGlucoseTempCalories StepsSkinetc.

SENSORS

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Blood pressureGlucose Fitness etc. sensors

DOCTORDATA

CENTER

COMPARE IMPROVE

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Predict impending

heart attacks?

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Fitness dataPatient dataImaging technologyInsurance dataOutbreak dataGenetic dataSocial media

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Passive sensors = no electricity Nanosensors?

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Patient data

Compare and analyze

Develop models

Preventative medicine

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Cost down

due to

efficient

data use

Cost down

due to

prevention

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Staff

Patient

Insurance

Government

Time

Care

Money

Votes

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WATSON

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168000 doctors free to do more important work

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Teleradiology

AI Radiology

Faster?

More efficient?

More correct?

Cheaper?

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Robotic

medicine

Can we create

blueprints for

automated

surgeries?

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DOCTORS TODAY DOCTORS TOMORROW

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Example: ITU (United Nations)

Official data from national Mobile Network Operators (MNOs)

Combine with social network data

All data is anonymized

Data is then stored locally or in cloud

Processed and turned into a dynamic map by ITU

=> Better outbreak management

CLINICAL TRIALS

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RANDOM SELECTION ANALYSIS-BASED SELECTIOn

OPTIMIZED CANDIDATE SELECTION

FASTER ORGAN DONOR MATCHING

ANONYMOUS COMPARISON OF PATIENT DATA

BETTER, FASTER TREATMENT AND …

AI SOLUTIONS

“DOCTOR

IN

THE

MACHINE”

EXAMPLE: DERMATOLOGY

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80% involve simple visual diagnosis

Upload a picture using cellphone

AI system quickly compares picture to database of millions

Suggests right course of treatment

Doctors heed the computer’s advice about 2/3 of the time

Current algorithms are already very good

90% of doctors say “It was smarter than my intuition.”

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85% of all procedures

in a hospital are routine

and can be automated

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90% of patients would trust

AI if it’s faster and cheaper

免掛號，免付費，免等候

阿公阿嬤 真歡喜

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Big data based

automation can

theoretically free up 50%

doctors’ and 70% of

nurses’ time to care better

for patients

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US will lead in AI medicine

Other countries can develop

- Indigenous systems

- Consultative systems

- Asia = Asian American?

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If you don’t do it …

Startups and AI

will steal your patients

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Medicine without borders

EXAMPLE: GENERAL CHECKUP

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Blood, urine, tests for STIs, glucose, liver and kidney

function etc.

+ age, ethnicity, health status, habits

=> compare to millions of other patients

= Early warning system

EXAMPLE: CANCER MARKERS

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No we are testing for 40-100 specific cancer markers

We can soon scan for 20000+

Combined with overall genetic information, we will detect

cancer before onset

PATIENTS LIE

DATA DOES NOT

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BIGGEST TRENDS 2016

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• Data visualization

• Cloud-based solutions (pay as you go)

• Privacy

• Data collection (IoT)

• Digitalization of patient records

• Interdisciplinary data structures

28% OF CANCERS ARE MISDIAGNOSED

THE PROBLEMS

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CURRENT HOSPITAL IT

SQL based

Relational

Structured

Outdated

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FUTURE HOSPITAL IT

Multi-query

Unrelational

Unstructured

Interdisciplinary

National and global

standards

INDIVIDUAL HEALTHCARE PROVIDERS

WILL HAVE TO …

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Invest in hardware and software

Hire data analysis experts

Hire computer security experts

Develop privacy protection systems

ALL ON A MASSIVE SCALE

Healthcare transition in Taiwan:

realities and

future trends

Global Healthcare: Dramatic reforms

Fee for Service

Physician

Turf warsSilos

Outcome

Based

Patient Centric

Collaboration

Team-work

Old Environment New Ecosystem

Taiwan ’s un ique prob lems

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• High-performance universal health system with no vision

• No understanding of cost-down advantage of big data

• Every hospital a kingdom

• Overworked doctors and nurses have no time for patients

• Up to 40% cost wasted on unnecessary doctor’s visits

• Ageing population averse to technology

• Rise of NCDs

Taiwan ’s NCD paradox

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NCDs accounts for 79.3 % of all deaths in Taiwan

Cancer 29 percent of all deaths in 2013

Three major NCDs—cancer, cardio- and cerebral-vascular disease 45%

These are the areas where big data brings the biggest benefits

These are the areas where Taiwan invests the least

Catas t roph ic i l lness = h ighest cos t

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Exempts all copayments and coinsurance to patients with one or more

of 30 catastrophic diseases, residents of remote mountainous areas

and offshore islands, pregnant women and child delivery,

children under three, veterans and their dependents,

and low-income households.

Chronic renal failure and cancer have the highest outpatient costs

(45% and 33.5%) of NHI outpatient and 30% of inpatient (incl. LT ventilation)

Both renal failure and cancer can be greatly reduced by investing in

big-data solutions, i.e. monitoring and preventive models

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