EHR patient data extraction has been challenging for physicians and providers in recent times. Due to the COVID-19 pandemic, sending and receiving patient data has been hindered by the inability to extract and transmit EHR data securely. Seamless patient data exchange is essential for healthcare providers and payers to curb the spread of COVID-19 and ensure that care gaps are resolved quickly with reliable patient data.

When an automated data extraction system is in place, it:

  • Eliminates the lag arising from claim systems
  • Promotes bi-directional communication between provider and payer
  • Enhances transition of care by providing a complete patient history

It is essential for healthcare providers and practices to have a reliable and experienced data extraction solution provider to take full advantage of patient data extraction benefits. Here are some of the most important factors to consider when looking for a patient data extraction solution.

1. Extraction Experience With a Wide Range of EHR Brands

EHR brands have distinct ways of capturing, storing and retrieving data. While most of them claim to support HL7 and other interoperability formats, they implement them differently. That’s why it is vital to work with a company that has migrated or extracted patient, business, and personnel records from different EHR brands.

Your solution provider must have worked with leading EHR vendor products such as Cerner, EPIC, AllScripts, GE, Medhost, Meditech, Greenway, NextGen, and eClinicalWorks.

However, the company’s experience should not be limited to the major market holders. Your solution provider should be able to work with proprietary EMRs due to their expertise in the healthcare industry.

2. Experience With Multiple Databases

Clinical information systems are developed with a wide range of database management systems. Some of the database schemas used are also complex, making the extraction project more challenging to execute. Your provider should be able to the following popular database management systems:

  • Btrieve
  • Cache
  • MUMPS
  • Firebird
  • IBM DB2
  • Informix
  • SQL Server
  • Oracle
  • MySQL
  • Sybase
  • PostgreSQL

Unfortunately, some databases may not be accessible without permission from the software vendor. When there’s no existing relationship between the EHR vendor and your organization, your solution provider should be able to strip out data from reports.

3. Ability to Work in Different Areas of Healthcare

Choose an EMR extraction service provider that can work in all aspects of clinical data management. Ensure that you check their portfolio to see the type of healthcare organizations they have worked with before. If you have an extensive enterprise healthcare system, select a company that can select, extract, migrate, and archive data from your current EHR and legacy systems.

4. Adoption of an Efficient Extraction Process

Your partner needs to have a proven process for releasing valuable information trapped in your EHR. Examples of such information include faxed results, scanned documents, or media attachments. Your service provider needs to help you pull essential data from any part of a document, transform it, and store it in discrete database fields to aid diagnosis and treatment.

Connect With a Patient Data Extraction Expert Today

Contact MediQuant now to learn more about efficient patient data extraction. Call us now at 844.286.8683 to schedule a free consultation. We are ready to show you how to optimally use all the critical information stored in your organization’s EHR.

MediQuant

Data Migration, Archival, and Conversion Services

About the Author:
Founded in 1999, and headquartered in Brecksville, Ohio, MediQuant provides industry-leading data archiving solutions and comprehensive system transition data management services to help hospitals and health systems liberate their data from legacy clinical, patient accounting and ERP systems. Its flagship product, DataArk, available as a cloud-based or an on-premises platform, provides users the ability to access and work with legacy data without the legacy system security risks and expense.