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BIG DATA IN HEALTHCARE
MSc. Information Systems
2014 / 2015
Presented by:
Younes Hamdaoui (Std_ID 21266804)
Supervised by:...
INTRODUCTION
 Clinics and health organisations have more reasons to become data-driven.
 Patients are expecting quality ...
PLAN
INTRODUCTION
WHY BIG DATA IN HEALTHCARE (HC) ?
• HISTORY OF DATA USAGE IN HC
• BIG DATA IN HC TODAY
BIG DATA APPLICAT...
WHY BIG DATA IN HEALTHCARE ?
HISTORY OF DATA USAGE IN HC (1)
 Paper based forms are still used in many developing countri...
 Today health organisations use more developed tools to deal with the huge amount
of data created daily, to track their d...
BIG DATA IN HEALTHCARE TODAY
Real cases :
 Propeller Health: Uses data from sensors for asthma inhalers and
from mobile a...
Other Examples:
 Comparative Effectiveness research: analysing clinical and financial efficiency of
interventions to enha...
THE ETL PROCESS
 The extract, transform and load process is a crucial component for populating
data systems.
 An ETL pro...
BIG DATA APPLICATION IN HEALTH SECTOR
COLLECTING DATA
% sqoop import
--connect jdbc:mysql://localhost/UWLHealth 
--table B...
PROCESSING AND ANALYSING DATA
Refining the
extracted
data using
Hive Query
Language
CREATE TABLE UWL_BloodPressure as sele...
FUTURE OF BIG DATA IN HC
SENSORS
Real-time
visualization
HEALTH
DATA
Real-time Interaction
with patients
Real-time trackin...
Conclusion
References
 Transforming Health Care Through Big Data. (n.d.) .Institute for Health Technology
Transformation. Available ...
Big-Data in HealthCare _ Overview
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Big-Data in HealthCare _ Overview

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A simple introduction to the usage of Big-Data technologies within the healthcare sector.

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Big-Data in HealthCare _ Overview

  1. 1. BIG DATA IN HEALTHCARE MSc. Information Systems 2014 / 2015 Presented by: Younes Hamdaoui (Std_ID 21266804) Supervised by: Dr Samia Oussena Dr Wei Jie
  2. 2. INTRODUCTION  Clinics and health organisations have more reasons to become data-driven.  Patients are expecting quality and safety in treatments, fast clinical results and doctors need electronic systems and analytical tools to make precise and rapid judgements.  The size of data generated in healthcare sector is rapidly growing. “U.S. health care data alone reached 150 exabytes in 2011”. (Institute for Health Technology Transformation. Transforming Health Care Through Big Data. (2013))
  3. 3. PLAN INTRODUCTION WHY BIG DATA IN HEALTHCARE (HC) ? • HISTORY OF DATA USAGE IN HC • BIG DATA IN HC TODAY BIG DATA APPLICATION IN HEALTH SECTOR • COLLECTING DATA • PROCESSING AND ANALYSING DATA FUTURE OF BIG DATA IN HC CONCLUSION
  4. 4. WHY BIG DATA IN HEALTHCARE ? HISTORY OF DATA USAGE IN HC (1)  Paper based forms are still used in many developing countries (Knocking on doors to collect information). The collected data needs to be moved to a computerized system;  The process of computerizing data affects the quality of data and takes time;  Most of the decisions in global health are based on old data;  HC sector lacked important data that could help improve this area, questions like : How many people are affected by diseases and disasters ? How many children were born or died last week? And under what circumstances ? Were impossible to answer rapidly.
  5. 5.  Today health organisations use more developed tools to deal with the huge amount of data created daily, to track their data and use it for analysis. • Microsoft Excel monitoring spreadsheets • Electronic Health Record (EHR) • Relational Database Management Systems (RDBMS) • Business Intelligence (BI) tools (SAP Business Objects, SQL Server Integration/Analysis/Reporting Services, IBM Cognos)  Complex, slow, very expensive and no real-time analysis. HISTORY OF DATA USAGE IN HC (2) “80% of the development effort in a traditional big data project goes into data integration and only 20% percent goes toward data analysis.”(Big Data Analytics. Extract, Transform, and Load Big Data with Apache Hadoop. (n.d.) INTEL White Paper.)
  6. 6. BIG DATA IN HEALTHCARE TODAY Real cases :  Propeller Health: Uses data from sensors for asthma inhalers and from mobile applications to help determine patients with asthma risks before an attack arises. Collects weather and air quality information to classify risk-level and risk factors by area.  NextBio: Uses personal patients information, molecular and genomic data to help making personalised medical decisions. (http://profitable-practice.softwareadvice.com/what-is-big-data-in-healthcare- 0813/)
  7. 7. Other Examples:  Comparative Effectiveness research: analysing clinical and financial efficiency of interventions to enhance clinical care services in terms of quality and performance.  Clinical Operation Intelligence: find misuse in clinical operations in order to improve them.  Public Health Analysis: analysing health data sets of populations to determine the overall effectiveness of medications. (http://big-project.eu/blog/potential-big-data-applications-healthcare-sector)
  8. 8. THE ETL PROCESS  The extract, transform and load process is a crucial component for populating data systems.  An ETL process recaptures data from various systems, refine and prepare it for future investigation by using analytic and reporting tools. ETL, Songini, M.L. (2004)
  9. 9. BIG DATA APPLICATION IN HEALTH SECTOR COLLECTING DATA % sqoop import --connect jdbc:mysql://localhost/UWLHealth --table BloodPressure -m 1 Importing a single Table Source Channel Sink Specifying the path to the locations of log files Holding area where events flows are defined through interceptors and channel selectors -Process events only through the channel -Writes data to HDFS or HBase Agent e v e n t s Processed Logs Hadoop Image Processing Interface
  10. 10. PROCESSING AND ANALYSING DATA Refining the extracted data using Hive Query Language CREATE TABLE UWL_BloodPressure as select *, normalerate – stdrate as rate_diff, IF((normalerate - stdrate) > 20, ‘LOW', IF((normalerate – stdrate) < -20, ‘HIGH', 'NORMAL')) AS BPressure, IF((normalerate - stdrate) > 20, ‘NOTOK', IF((normalerate - stdrate) < -20, ‘NOTOK', ‘OK’)) AS BPressure_variation from UWL_Health; “The Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL.” (https://hive.apache.org/) ODBC DRIVER Visualization of the UWL_BloodPressure table Analysis
  11. 11. FUTURE OF BIG DATA IN HC SENSORS Real-time visualization HEALTH DATA Real-time Interaction with patients Real-time tracking of health Real-time detection of anomalies Real-time recommendations Automatic urgency detection Doctors will diagnose patients the minute they step in hospitals Real-time prescriptions, advices and response to emergencies Disease surveillance
  12. 12. Conclusion
  13. 13. References  Transforming Health Care Through Big Data. (n.d.) .Institute for Health Technology Transformation. Available at: http://ihealthtran.com/big-data-in-healthcare [Accessed 5 Mar. 2015].  Big Data Analytics. Extract, Transform, and Load Big Data with Apache Hadoop. (n.d.) INTEL White Paper.  Profitable-practice.softwareadvice.com. What is “Big Data” in Healthcare, and Who’s Already Doing It?. Available at: http://profitable-practice.softwareadvice.com/what-is- big-data-in-healthcare-0813/ [Accessed 11 Mar. 2015].  Big-project.eu. The Potential of Big Data Applications for the Healthcare Sector | BIG - Big Data Public Private Forum. Available at: http://big-project.eu/blog/potential-big- data-applications-healthcare-sector [Accessed 11 Mar. 2015].  Songini, M.L. 2004, "ETL", Computerworld, [Online], vol. 38, no. 5, pp. 23.  Reach1to1 Technologies, (2015). Hive, Pig and Sqoop. [online] Available at: http://reach1to1.com/technology/hive-pig-sqoop/ [Accessed 11 Mar. 2015].  Hortonworks, (2015). Apache Flume. [online] Available at: http://hortonworks.com/hadoop/flume/ [Accessed 11 Mar. 2015].  Wikipedia, (2015). Apache Hive. [online] Available at: http://en.wikipedia.org/wiki/Apache_Hive [Accessed 11 Mar. 2015].  Wikipedia, (2015). Pig (programming tool). [online] Available at: http://en.wikipedia.org/wiki/Pig_%28programming_tool%29 [Accessed 11 Mar. 2015].

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