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About the case study


Affiliated with the University of Toronto, The Hospital for Sick Children (SickKids) is Canada’s most research-intensive hospital and largest centre dedicated to the improvement of children’s health in the country. By staffing professionals from all disciplines within both health care and research.
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SickKids provides the best in complex and specialized care through creating scientific and clinical advancements, sharing knowledge and expertise, as well as championing the development of accessible, comprehensive and sustainable child health systems.

About the case study

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Affiliated with the University of Toronto, The Hospital for Sick Children (SickKids) is Canada’s most research-intensive hospital and largest centre dedicated to the improvement of children’s health in the country. By staffing professionals from all disciplines within both health care and research.
section1-image2
SickKids provides the best in complex and specialized care through creating scientific and clinical advancements, sharing knowledge and expertise, as well as championing the development of accessible, comprehensive and sustainable child health systems.

Overview

Industry-2

Industry

Health Care Services
Companysize

Company size

5001 to 10000
Location

Location

Toronto – Ontario
Keystats

Key stats

  • • 400M ES documents
  • • 30-40 properties in each ES document mapping
  • • 15B data elements imported
  • • 40 import asynchronous jobs (run time: 5 m to 30 h)
  • • Jobs combined paper mapping, electronic file, and a database dump
ProjectAreas

Project Areas

  • • Microservices
  • • DevOps
  • • Machine Learning

Combine process and cloud native development

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The Challenge

SickKids decommissioned an electronic medical chart application (CIMS) which ran in the Neonatal, Pediatric and Cardiac Intensive Care Units since 1999.

The hospital now requires the migration of billions of records from CIMS to a new system that will allow physicians and researchers to find, examine and analyze this complex data.
dataDefragment
Data defragmentation
CIMS data was stored in multiple file sources, including flat text files, mapping text files, b-tree file structures, and oracle database data extracts with over 1000 tables.
dataVolume
Data volume
Billions of records stored over 20 years for over 50,000 patients needed to be reindexed in a new system with novel requirements such as sub-second searching, data analytics, reporting and metrics.
mappings
Mappings
Manual cross mapping between text files, b-tree records, and database extract:
icon file1000’s of text files
icon file50,000+ Patients
icon file400,000,000+ Patients raw data
icon file2,000,000,000+ eletrônic chart inputs
infoStructure
Infostructure
Only single VM was available to process and import all data. TC ES exports had to fine tune the ES to make sure the system would import data without running out of memory which was a challenge to accomplish.
The hospital now requires the migration of billions of records from CIMS to a new system that will allow physicians and researchers to find, examine and analyze this complex data.
  • dataDefragment

    Data defragmentation

    CIMS data was stored in multiple file sources, including flat text files, mapping text files, b-tree file structures, and oracle database data extracts with over 1000 tables.
  • dataVolume

    Data volume

    Billions of records stored over 20 years for over 50,000 patients needed to be reindexed in a new system with novel requirements such as sub-second searching, data analytics, reporting and metrics.
  • mappings

    Mappings

    Manual cross mapping between text files, b-tree records, and database extract:
    icon file1000’s of text files
    icon file50,000+ Patients
    icon file400,000,000+ Patients raw data
    icon file2,000,000,000+ eletrônic chart inputs
  • infoStructure

    Infostructure

    Only single VM was available to process and import all data. TC ES exports had to fine tune the ES to make sure the system would import data without running out of memory which was a challenge to accomplish.
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The Solution

Digital Transformation

MICROSERVICES | DEVOPS | MONITORING

iconcheck See how we indexed, analyzed and transformed half a billion records of Neonatal Intensive Care Unit data for Sick Kids Hospital.

Given the complexity of the challenge Translucent broke up the project in to 4 phases:

Mapping Importing Testing Searching and Analytics
mapping

TC Consultants carefully mapped out the whole system in 40+ excel import files that combine layouts, labels and groups from a flat file, complex cross functional lookups between text files and DB lookups

Is your company still using hand tools?

These import files were the bases for system import

TC engineers created asynchronous importers that executed up to 30 hours

Is your company still using hand tools?

The importer used the mappings and DB data dump from the old system to construct ES documents

data_process
0025_images_kam_export_banner01

Careful testing was done by TC team to match the old system with the new system.

Is your company still using hand tools?
Group-9944 SK team is now using the system for searching patients for data lookups.
Group-9943 SK Research team is using the system to chart, graph and data mind the system.
Group-9942 Kibana is one of tools used for dashboards.
Given the complexity of the challenge Translucent broke up the project in to 4 phases:
  • Is your company still using hand tools?

    1. Mapping

    TC Consultants carefully mapped out the whole system in 40+ excel import files that combine layouts, labels and groups from a flat file, complex cross functional lookups between text files and DB lookups

    These import files were the bases for system import

    mapping
  • #

    2. Importing

    TC engineers created asynchronous importers that executed up to 30 hours

    The importer used the mappings and DB data dump from the old system to construct ES documents

    data_process
  • Is your company still using hand tools?

    3. Testing

    Careful testing was done by TC team to match the old system with the new system.

    0025_images_kam_export_banner01
  • #

    4. Searching and Analytics

    Group-9944 SK team is now using the system for searching patients for data lookups.
    Group-9943 SK Research team is using the system to chart, graph and data mind the system.
    Group-9942 Kibana is one of tools used for dashboards.
TheResults

The Results

A new Electronic Medical Chart Platform based on data transformation, mapping and migration of billions of charts inputs from legacy electronic medical chart application (CIMS).
New electronic charts allow physicians and researchers to find 20 years of historical patient data with sub second searching, analytics and reporting.
CIMS_05_DesktopMonitor
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