Abstract

The key components of this project were data analysis and data extraction from EPIC software. Provided with the limited access to database connection and the server it was challenging to get the data out of EPIC and migrate to IMS.

Introduction

• The important phases of the data migration project are the analysis of the source system, extraction of the data from the source system and converting the data in the destination database.
• We have been provided with the server access where the EPIC system can be accessed along with the credentials to login into EPIC and crystal reports.
• During the initial analysis phase, we found that it was not helpful for us to extract the required data from EPIC and available reports in SAP Business Objects.
• Only available option to proceed with was to create the reports using crystal report to get the required data out from the EPIC.
• Thorough analysis our systematic structured methods helped us to get the required data out of the EPIC database using the crystal reports and migrate it to IMS.

Challenges

• Unavailability of useful data reports in EPIC to extract the data from front-end.
• Limited access to the Crystal reports server i.e. only to create and run crystal reports.
• The Complex data structure of EPIC database.
• Having no direct access to the database and a large amount of data present in the EPIC which increases the time of analysis and limit the ways to explore and analyze data.

No direct way to transfer the extracted report result data from Crystal report server. 

Solutions

• Created Crystal reports to extract the desired data from the EPIC.
• Extracted the Database Information schema to understand the database design and analyzed recursively with the front end to understand the database structure of EPIC.
• Tried using the available options to handle a large amount of available data from the database and found an efficient way to work with the database.
• Transferring the extracted data from the EPIC crystal reports server with no option available to connect with the server was a tricky task. We have found a way to transfer the data.

Outcomes

• Converted the EMR data in the discrete format including Prescriptions, Diagnosis, Vitals, Allergy.
• Converted the EMR data per visit of the patient including Social History, Medical/ Surgical History, Lab results, Family History, Immunization.
• Converted other Data including Patient demographics, Appointments, Insurance, Pharmacy, Accounts.

Requirement:

The Agenda is to convert the data from the four different EHR Systems into a single EHR system which includes the PM and EMR data.

• ECW
• Advanced MD
• Kareo
• HealthNautica

Challenges:

• Each System has its own workflow so in order to convert the data, we need to do a very detailed Analysis on how each system behaves.
• Deciding the strategy on how we can convert the same records found in four different systems as a single record in the destination.
• Avoid converting the redundant data found in the source systems.

Solution:

• Assisting the stakeholders to take the correct decision on which data needs to be converted from which system.
• Incremental conversion can be performed which helps the stakeholders to avoid loss of data.
• Choosing the correct system to be converted first based on their workflow which will result in getting the most recent data reflected in the destination and then performing the successive conversion from other EHR systems.

Result:

The end users can now access and manage the EHR records found in four different systems in one single system which helps to manage the workflow efficiently. Smooth conversion is the best practice for an EHR company and the stakeholders are really happy with the work and the approach we follow.