The Importance of Data Management  in Healthcare

The Importance of Data Management in Healthcare

John’s Healthcare Journey 

John Smith is your average consumer searching for health insurance through the Affordable Care Act (ACA). John shops for a plan through the Health Insurance Marketplace (HIM) and finds a plan perfect for he and his wife, Jane. John clicks submit and realizes he forgot to add his wife. John edits his plan and sits back, relieved to see he was able to fix his plan accordingly. A few weeks later, John gets his first bill in the mail, but it’s missing Jane! John is confused and spent quite some time working with a customer service representative to get his policy corrected. Once his policy was corrected, he received his ID card, but Jane does not! Confused again, John gets back on the phone with a customer service representative.

While seemingly silly, John’s case is not uncommon. Unfortunately, not many consumers are as patient as John. Most systems aren’t wise enough to swiftly take care of John’s account to ensure no bad data is transferred. As you can imagine, the remediation of poor data management is a costly endeavor; from the loss of a customer, impact of poor social media ratings, cost of material, and even time spent by customer service representatives. 

How is Data Exchanged in the ACA? 

The EDI Benefit Enrollment and Maintenance Set (EDI 834), is the standard file that allow issuers to know who has signed up for their insurance plan through the state or federal exchanges. This file contains the consumer information required for the issuer to generate a member ID card, send correspondence, and pay claims to their medical providers. Once the member submits a successful application for health insurance, an EDI is generated with that consumer’s information and is passed on to the selected issuer. 

Challenges of Data Management 

Although the intention of HIPAA through EDI is to ensure transactions distributed through trading partners are accurate, organized, compliant, and efficient – it is often not that simple. Data can go very wrong, very fast. Data can be: 

  • Miscoded or misinterpreted 
  • Transmitted or received out of order 
  • Completely missed in transmission  
  • Redundant or corrupted  

In the case that data transfer fails at any point, the consumer and issuer can be greatly impacted. In the example of John, although he corrected his data in the system, something went wrong along the way. Without a solid core EDI system in place, issuers can become easily overwhelmed with chaos and misleading data.

Data Lifecycle 

A member’s data gets transmitted through a number of systems. The member’s journey starts at the marketplace, continues to the insurance provider, to their medical provider, into a claims management system, and back to the Centers for Medicare & Medicaid Services (CMS). Often, there are Third-Party Administrator (TPA)/vendor handoffs pieced in-between each step as well! With so many handoffs, it is important to establish best practices to make sure data is processed timely and accurately.

Best Practices  

With data that has multiple handoffs through its lifecycle, it’s important to establish best practices that surround the intake and processing of data. Some practices to consider when data is being exchanged and processed are:

  • Source Preservation: Preserving the initial dataset prior to ingestion into your system is integral to ensure you always have a baseline dataset to compare to what is processed into your system. It also ensures if you ever need to roll back data or have an issue in your environment, you have a set of data to reprocess.  
  • Operational Controls: Ensure that you dot your I’s and cross your T’s at each data point handoff. The consumer is the most important person in the journey of data through your system. If data moves slow or is mis-mapped, the consumer sees an immediate negative impact. It is important to establish controls to ensure the minimum efficiency of your platform. If you have a vendor partnership, make sure you have controls outlined in your Service Level Agreements (SLAs).  
  • Simple Controls to Consider:  
    • Inbound and outbound data has stringent data validation  
    • All expected data received is parsed into your system and transferred out 
    • Data is parsed timely into and out of your system once received 
    • Data mapping through the system has controls surrounding it 

Automation: While scary to some, the more automation you focus on implementing reduces administrative overhead and room for error. Additionally, if you include proper auditing along with your automation, you will have the history needed to review any action taken on a data set, should anything go wrong with your automation. It should be designed in a way that it is easy to be remediated. 

Data Reconciliation: Reconciliation highlights deficiencies within health systems and is a must-have safety net to ensure data integrity. Reconciliation processes typically are one of the most challenging and one of the last processes to be designed or implemented when setting up a partnership with a vendor or trading partner. Those who struggle to design and successfully implement reconciliation practices display a multitude of downstream impacts with costly nuances, as seen in the case with John. 

What Else is Done with this Data? 

Today, Big Data is quite the industry buzzword. This means that we’re moving towards an industry that focuses more on the wholistic insights our data can produce rather than what specific elements of data are for a transaction. Before a platform can be utilized in such a manner, it’s critical for the data stored in the system of record to be correct, so that the production of a true system of insights can occur. The most efficient way of getting organized with coherent data is finding an all-in-one EDI solution.

Choosing the Right System to Manage 

Many factors should be considered prior to beginning to implement an EDI solution. While most EDI systems provide an organized repository of information, they should be able to easily extract transform and load large amounts of data with efficient automation while simultaneously eliminating bad data from the process. The following topics are some things to look out for when selecting or creating a solution to best manage your inbound data: 

  • The security of data in transit and at rest 
  • System compliance with federal and state regulations 
  • Feasibility of implementation & seamless cohesion with existing partners 
  • Reduce/eliminate existing manual operations through automation 
  • Cost benefit analysis of integration 

For additional information on how Softheon’s EDI solution can help support your participation in the ACA, as well as reduce operational cost, please reach out to Hamoon Hadavand at hhadavand@softheon.com or Danielle Tedesco at dtedesco@softheon.com

The views and opinions expressed by the authors on this blog website and those providing comments are theirs alone, and do not reflect the opinions of Softheon. Please direct any questions or comments to research@softheon.com. 

Danielle Tedesco

Danielle Tedesco serves as the Director of Product Management, specializing in Healthcare Reform and Health Plan Services. Danielle manages and sets the overall vision for Softheon’s Clarity, Gateway, Remedy and Foundry solutions. She is responsible for overseeing a team of Product Owners who are responsible for executing the product roadmap. She collaborates with the development, marketing, sales, and operations teams to ensure customer needs are met. Danielle has experience with implementing ACA policies and regulations for 40+ health plans.

Leave a Reply

Close Menu