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Epidemic Communicator

Uncertainty as a Trigger for Service Innovations

Gordon Müller-Seitz, Carsten Reuter, Christoph Stöckmann, Wotan Wilden and Gil Breth

Munich, October 22, 2012

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Agenda

Introducing the epicomm -Team

Introducing the Issue

What We Promised

What We Deliver

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Epicomm - Team

Gordon Müller-Seitz Carsten Reuter

Pre-studies (automotive) FHG distribution channels

Qualitative empirical studies Information flow

Teaching cases Possibilities to promote the

theme

Christoph Stöckmann Wotan Wilden

App production Product Design

Empirical study Prototyping

Multi-channel marketing Usability

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Agenda

Introducing the epicomm -Team

Introducing the Issue

What We Promised

What We Deliver

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Ebola

Deepwater Horizon Fukushima 9/11

Tsunamis Eyjafjallajökull

Uncertainty in the run-up or during events can take many forms,

is managerially relevant and represents an omnipresent phenomenon

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After the crisis is before the next crisis

Uncertainty remains a latent key concern for many health care actors

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Uncertainty risk

Uncertainty in our setting is diffuse and critical hystery prone setting

reducing uncertainty (public authorities etc.)

Overarching research question: How do actors cope with uncertainty in the face of HC disasters?

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Specific case

The invisible is EHEC

Leadership is needed to introduce innovative services Call center hotline

Receipe-based cohort study

EHEC Task Force (innovative form of collaboration for the PuMa sector)

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Agenda

Introducing the epicomm -Team

Introducing the Issue

What We Promised

What We Deliver

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Our promise – outputs will occur in the following areas

Teaching Case studies for three diseases

Research A conference paper

Dissemination Gaining attention for the PPS

Product App

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Agenda

Introducing the epicomm -Team

Introducing the Issue

What We Promised

What We Deliver

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Investment of 40.000 € funding by Peter Pribilla-Foundation

Travelling 8.000 € Epicomm Team

Research/teaching 12.000 € Student assistants for data collection and analysis purpose

Freie Universität Berlin, Institut für Management

Product research/design 5.000 € Student assistants for user research and app design

Technische Universität München, Lehrstuhl für Industrial Design

App implementation 15.000 € netSTART Systems GmbH and Hag&Hagal

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Teaching output - generating visibility of the PPF-theme

Case studies EHEC: „EHEC-Ausbruch 2011 in Deutschland – Der Kampf gegen den unsichtbaren Feind “

SARS: „SARS-Pandemie 2002/2003: Die Angst reist um die Welt “

BSE: „Der schiere Wahnsinn – Die BSE-Epidemie in Großbritannien und ihre weitreichenden

Folgen für Europa “

Research seminars Freie Universität Berlin

(„Forschungsseminar“ / summer term 2012/13)

Universität Hamburg

(„Public Risk Management“ / winter term 2012/13)

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Research output - crafting output for the scientific arena

Exchange fora with leading experts from the field Joe Lampel (Cass Business School)

Bridget Hutter (LSE)

Presentations/papers 2012 Public Management Colloquium/WK ÖBWL

„Interorganisationale Praktiken im Umgang mit Unsicherheit am Beispiel des EHEC-Ausbruchs“

OLKC

„Situated Learning during Uncertain Events: The Case of the German EHEC outbreak 2011“

EURAM

„Managing Uncertainty in the Case of Food-borne Disease Outbreaks:

Explorative Evidence from Public Health Insittutions“

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Dissemination - leverage existing resources and facilities

DocCheck

Leads pursued (ongoing) Fire department Düsseldorf

Departmental authority for Health and Consumer Protection (Hamburg)

Inquired / existing contacts Apothekenrundschau

Computer Bild

Bild

FU Berlin online magazine

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Product - App developing process

Generation of user stories

Survey of experts

Definition of main functions

App design

App implementation

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App - Generation of 12 user stories

Example 1 Information on health status of family members and friends

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App - Generation of 12 user stories

Example 2 Location-based concentration of site-specific symptoms triggers alarm

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App - Survey of experts

Contacts Bayerische Landesärztekammer

Bundesamt für Bevölkerungsschutz und Katastrophenhilfe

Deutsche Lebens-Rettungs-Gesellschaft e.V.

Deutscher Wetter Dienst

Deutsches Rotes Kreuz

Europäisches Zentrum für Krankheitsprävention und Kontrolle (ECDC)

Feuerwehr Branddirektion München

GDACS (Global Disaster Alert and Coordination System)

Helmholtz Zentrum München, Epidemiologie Abteilung

Johanniter (Unfall-Hilfe e. V.)

Malteser

„MediCare“ / Flughafen München Medizinisches Zentrum GmbH

Polizeipräsidium München

Referat für Gesundheitsschutz und Infektionsschutz der Landeshauptstadt München

Referat für Gesundheit und Umwelt der Landeshauptstadt München

Technisches Hilfswerk

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App - Survey of experts

Results Interest in the use of the app is given.

Responsible source must be trustworthy and reliable! Who is the competent, trustworthy source?

The app is not useful for travelers.

Still possible: recommendations of the Foreign Office warnings instead (this is the full

responsibility of the national authorities and of some international public health institutions!)

Behavioral advice instead of standard information, with which the user is left alone.

Location-based data is desirable, but only anonymously and not exactly but as a display of the

relative density.

It would be great to have the system able not just to register the single case but to identify

geographical/timing clusters.

In terms of warning, users should have the possibility to clearly distinguish what they find on

media from what they find from any authority or reliable source.

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App - definition and design of main functions

Basic settings When you start using the app you will be asked which information is used

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App - definition and product design of main functions

Behavior of the app on Warnings Warnings appear as push messages on the smartphone

The home screen is focused on the most important functions to reduce panic:

messages, behavioral advice and search for a doctor

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App - definition and design of main functions

General information within the app General topics and articles serve as a supplement to the warnings and reduce panic

Already read information fades to gray, for a better overview

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App - definition and design of main functions

Self examination Result consists of the analysis of symtoms and the location-based risk assessment

With a worrying result the user is forwarded to "behavioral advice “

Results are anonymously recorded and displayed in a interactive map

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App - definition and design of main functions

Interactive map Possible setting at the beginning are „choose filter" (which diseases to be shown) and

„select period" to (in the last 24hours / year)

The evaluated data of the self examination results appear alongside official sources in the charts

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App - definition and design of main functions

Doctor Locator Only relevant specialists are shown (e.g. virologists)

When you click on a desired pin on the map, the contact of the doctor will be displayed

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App - Implementation

netSTART Systems GmbH and Hag&Hagal

Gil Breth Geschäftsführer

netSTART Systems GmbH

Oststr. 11-13 (Rhein-Carré),

D-50996 Köln-Rodenkirchen

www.netstart-systems.de

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App - Technology

In 2012 Apple integrated a wireless emergency alert system into iOS 6

service provides alert

iOS warns user

Information is independent of time and location

Collects and provides

emergency alerts

Emergency Alert Service

user

Only in the USA

Only emergency warnings

No direct support

Client

Base-System

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App - Technology

Epicomm provides a back-channel for users to receive user-generated data

service provides alert

iOS warns user

Epicomm Service

Country independent

Comparsion of user data

Analysis of user data

User generates data

Self examination

doctor search

Direct support

Client

Base-System

user

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App - Functions

General information

News Integration of various online news sources

Aggregation of news

Cross-platform deployment (XML, RSS)

Not personalized content

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App - Functions

Self examination

Symptom query Provision of symptoms

Detection of symptoms depending on the user location

Anonymous online data storage

Location based analysis of the symtoms

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App - Functions

Location based doctor search

Doctors Overview Display of appropriate doctors in the own area

Direct contact opportunities

Location based results

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App - Functions

Symptom radar

Message summary Displaying messages in the own area

Time and location dependent

Visualization of message types

(confirmed vs. non-confirmed)

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App - Demonstration

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Epicomm can visualize and react on spread of viruses in real time

Video source: Adam Sadilek, Predicting Spread of Disease from Social Media,http://www.cs.rochester.edu/~sadilek/research

x

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What’s next?

Partner Network Integration of data sources

Quality of service/data

Media and PR News in our news/social media network (approx. 6.000 members)

PR-partners: Computer Bild, Center.TV, VDI News

Data, data and even more data Support for other plattforms (Android and Windows Phone)

User generated content

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Thank you for your attention and support