Data Extraction & Archival

Background

The client is a hospital system which serves Mississauga, Ontario, and western Toronto in Canada. They have two hospitals and a Health Centre and offer the full range of acute care hospital services, as well as a variety of community-based, specialized programs.

The client rolled out Epic EHR which resulted in the sunsetting of their Pharmacy Information System and Oncology EMR. They decided to archive last 2 years’ data from these systems as indexed PDF documents, which would then be available to view from Epic Hyperspace. Neither retiring systems had any ability to generate pdf documents.

Challenges

  • The understanding data model of both the Pharmacy  Information System and the Oncology EMR
  • Identifying how many document types are needed to present the information
  • Generating PDF layout that matches the application’s user interface
  • Application awareness
  • Aggressive project delivery timelines

Solution

314e Corporation undertook the project to extract patient data from the Pharmacy Information System and the Oncology EMR and generate PDF files to load them into a new EMR. Both retiring software was highly proprietary systems with little or no documentation about their database schemas. 314e’s team wrote custom python code which queried data from the Oracle database of one system and MS SQL Server database of the other system, to generate PDF reports with all relevant data.

314e developed this solution using Python programming language utilizing Oracle native driver as well SQL Server ODBC driver. We wrote SQL queries to retrieve relevant data from the database and generated high-quality PDF files using technologies like LaTeX. The program used a high degree of separation between PDF generation and data composition.

Business Outcomes

The end solution that was created was optimized thoroughly for performance such that the need for “catch-up” extracts was obviated. All data were extracted, converted to pdf, and loaded into the new EMR over the cut-over weekend.

Key Technologies involved

microsoft sql server - key technology data extraction
Python - key technology data extraction

314e’s Cloud Adoption Services

Infrastructure Migration

Converting existing VM or physical machine into cloud computing instance and containerize workloads

Application Migration
Application Migration

Desktop apps virtualizing via app streaming; Web app migration using APIs and service mesh technologies

Data Migration
Data Migration

Migrating existing data marts and application-specific relational database silos into the cloud

Platforms Supported
Platforms Supported

314e has extensive expertise for migration to any of the big three – AWS, GCP, and Azure platforms

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