Deloitte Case Competition final

Case Competition 2015

Amazon Cloud Service based Infectious Disease Detection and Predictability Algorithm.

Group:

A. Chang, D. Jacob, A. Moawad, H. O’Byrne, K. Wright1

Copyright © 2010 Deloitte Development LLC. All rights reserved.2 A. Chang, D. Jacob, A. Moawad, H. O’Byrne, K. Wright

Contents

Our Understanding of the Situation 3

Approach 5

The Solution 8

• Objectives

• Project schedule, budget, and delivery method

• Training, maintenance, and operations

• Future enhancements

Appendices 18


Our Understanding of The Situation


Our Understanding of the Situation

• The AIDC currently has a method of diagnosis that is “not intuitive and the hardware was bulky and difficult to handle at patient bedside.”

• This application collects data, which is then sent to a central database.

• We hope to implement a more efficient and secure analytics platform capable of:

‒ Logging patient symptoms and other information.

‒ Diagnosing infectious diseases efficiently and accurately.

‒ Predicting the development of disease in surrounding areas.


Our Approach


Our Approach: Two-Pronged

Improve Existing Technologies• More Intuitive User Experience• Compact Devices

‒ Tablets for staff• More Efficient Telecommunication

‒ Cloud Storage‒ Upgrade Hospital Servers/Devices

Establish Global Network• Via Cloud Services

• Secured Access granted to AIDC, other hospitals

• Storage for past, current and future medical records

• Mobile Interface for On-site Responders• Real-time

communication/feedback• Prompts faster treatment

plans


Our Solution


The Solution Objectives

• Quick and efficient bedside manner ‒User Friendly Interface‒Data Integration

• Disease Determination‒Diagnostic Tool

• More Effective Treatment‒Predictability Models‒Reference Library


The Solution Huffman Trees

Diagnosis

• Input: Patient information– Each node of tree contains ranges of

symptoms – Each symptom has weight that contribute

to probability that patient has Ebola

• Output: Probability Patient has Ebola

– Boolean variable of each symptom

– Count symptoms: integer that counts the number of symptoms of patient that correlate to Ebola

– Cross-references to other patients

Prediction

• Origin: time when symptoms began– New permanent residence– Extensive stay ( >6 months)– Short term stay ( < 6 months)

• Each node contains:– Location– Date of residence/travels

• Output: Visual of spread of Ebola based on:

– Population density

– Patient’s time spent at location

– Can be combined with other patient inputs


Patients

Symptoms logged

On-site Personnel

MDs/ EMTs

Cloud Storage

Allows access to past/current dataTies together network

Prediction Models

Live FeedbackAlerts to trendsDiagnosis

Data collected forCloudPrediction Models

Mobile AppLocal Servers

Can be updated before the cloud or in case cloud is unavailable

Disease Centres

AIDCCan alert other regions if threats are detected

Regional MDs

Other MDs can receive the data alerts from AIDC

The Solution Information Flow/Delivery method


The SolutionBudget

Tablets

Amazon Web Services

Total

Asus Google Nexus 7• Tablet Price: $149.99• Cost of 750 Tablets: $299,992.50

All Ebola Cases• 0.078 TB Data Transfer In/Out Yearly Price: $68.04All of Africa• 300 TB Data Transfer In/Out Yearly Price: $246,145.68Amazon Support• Yearly Price: $180,068

Yearly Cost• Including enough memory for all Ebola cases: $300,060.54• Including enough memory for all of Africa: $546,138.18


Month1 2 3 4 5 6 7 8 9 10 11 12

App R&D

• Data Collection

• Algorithm

Coding

• Debugging

β Testing

• Pilot

• Debugging

Expanding

Operation

• Marketing

• Deployment

• Disease

Management

Maintenance

• Updates

The Solution Project Schedule


The Solution Training, Operations, and Maintenance

Training

• Doctors in infected countries will be taught:– How to use app:

• Create, record, and search patient information

– How to store/upload data• On both hospital

servers and cloud storage

– Downloading and installing app updates/fixes

Maintenance

• App Maintenance– Updated app versions to

response to errors/crashes/bugs

• Cloud storage maintenance

Operations

• Doctors collecting data in the field and treating patients

• Cloud storage that holds data for all patients and uses data to track spread of disease

• HQ and other US AIDC locations that maintain app and use analyzed data to stop spread of disease


The Solution SWOT Analysis

Strengths Weaknesses

• Easy to use • Surplus of data storage• Affordable• Efficient

• Doctors require training• App may not handle beta

testing• Availability of internet

connection

Opportunities Threats

• User feedback system• Expansion to diagnose and

predict other infectious diseases

• Budget allows for expansion

• Cloud storage provider may not handle data influx

• Infringement of confidentiality• Constant data flow


The Solution Future Enhancements

• Expansion of data library

• Augmented prediction models

‒Environmental factors

‒Genetic factors

‒ Increased computational power

• Expanding global network


Questions?


Appendices


Appendix A Diagnosis Huffman Tree

Temperature

Origin

Symptom 2

Reaches this node with 98-100 F temperature

Symptom 3

Reaches this node at a certain range

Symptom 3

Reaches this node at a certain rangeReaches this node at a

certain range

Symptom 3

Symptom 2


Symptom 4


Symptom 4


Symptom 4


Symptom 4


Symptom 4


Symptom 2



Appendix B Prediction Huffman Tree

Place 1

Origin

Type 1 Place

DatePeriod of timeDensity of population

Type 0 Place


Type 2 Place



Type 1 Place

Type 2 Place


Type 0 Place


Type 1 Place


Type 2 Place


Type 0 Place


Time

Copyright © 2010 Deloitte Development LLC. All rights reserved.

Asus Google Nexus 7 Specifications

Operating SystemAndroidTM 4.1Display7" WXGA (1280x800) Screen

IPS Panel10 finger multi-touch support

CPUNVIDIA® Tegra® 3 T30L Quad-Core @1.2GhzMemory1GBStorage16GB*1Wireless Data NetworkWLAN 802.11 b/g/[email protected]

BluetoothCamera1.2 MP Front CameraInterface2-in-1 Audio Jack (head-out/MIC),

1x micro-USB, 2x Digital microphone,2x High Quality Speakers,1x Docking PIN

SensorG-Sensor, Light Sensor, Gyroscope,E-compass, GPS, NFC, Hall Sensor

Battery9.5 hours, 4325mAh,*216Wh Li-polymer

Dimensions198.5 x 120 x 10.45 mmWeight340 g

20 A. Chang, D. Jacob, A. Moawad, H. O’Byrne, K. Wright

Copyright © 2010 Deloitte Development LLC. All rights reserved.

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A. Chang, D. Jacob, A. Moawad, H. O’Byrne, K. Wright21

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Deloitte Case Competition final

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