Healthcare provider organizations that have yet to plan a legacy data management strategy are missing key opportunities to address the new wave of cost pressures, merger and acquisition activity, and transformation initiatives coming into our industry.
KLAS Research reported that 85% of healthcare organizations choosing to retire systems and archive their data found positive financial impacts of doing so. The costs tied up in maintaining legacy systems make it easy to justify a legacy data project. But the complexity of health IT environments, the number of disparate systems, and heavy lifting associated with data extraction and mapping make these initiatives easier said than done. And here is where we miss the longer-term opportunities such as archiving data in a way that is pertinent to AI algorithms or how data access plays into interoperability.
The Pitfalls of Legacy System Archiving
Whether a single site healthcare provider or multi-faceted health system, there are common pitfalls in archiving a legacy system. These include:
- Not understanding the time and resources needed for data extraction.
- Not fully understanding the functionality needed after extraction and implementation.
- Under-estimating the total cost of ownership.
- Short-term planning that doesn’t include plans for long-term management or for retiring data when it’s no longer needed.
Defining Legacy Data Requirements – Questions to Ask
Developing a legacy data strategy asks and answers relevant questions around your requirements so that your organization can move forward effectively and determine the return on investment. These questions are designed to help you avoid the common pitfalls I’ve mentioned:
- Do you have legacy data opportunities, and how might you address them?
- What constitutes a “legacy system?” What is it costing you to keep them up and running? What are your target legacy systems?
- Are you moving data out of these legacy systems so they may be discontinued and funding reallocated?
- Are you going to implement a new solution that allows you to retain legacy data access?
- Do you have the bandwidth or the technical capabilities in-house for this initiative, or do you require help?
- What data do you need to retain?
- What are the legal and regulatory requirements for maintaining legacy data within the state(s) where your care facilities are operating? Be sure to document patient data requirements as well as other regulated data such as financial and HR records.
- How long (how far back) must your data be retained? (Note, retention periods vary and can be as high as 30 years in the case of a juvenile hospital patient.)
- What data needs to be kept and what doesn’t? Who in your organization is responsible for the oversight of these requirements? The volume and types of data you keep impact the cost of your strategy. Your strategy should balance the cost of determining what MUST be kept with the cost of retaining data you aren’t required to keep.
- What are the requirements of the solution you are moving to?
- What is the purpose of the retention of this legacy data? Is it needed by clinicians in real-time for medical reference? Or is it primarily for HIIM personnel handling ROI and legal inquiries? Do you need to manage AR?
- Where are you comfortable storing this data? Would you consider storing your legacy patient medical data in the Cloud?
- How will you extract your data?
- What services are offered by the legacy system vendor to provide your legacy data outside of their system? Do they have a standard “exit extract” package? Are you allowed to extract it yourself or have a partner extract it for you?
- How will you budget for this?
- What are the short and long-term costs of implementing a new proprietary software solution?
- How long will this process and the project(s) take? How long for an ROI?
- How far in advance of this timeline do I need to begin working on strategy tasks?
What does success look like?
The best strategies target legacy applications, prioritizing them for decommissioning based on a calculation of risk and the cost to do so. The organizations we’ve seen achieve the most success addressing legacy data recognize the liability of storing patient data that isn’t required or clinically useful, as well as the need to get ahead of end-of-life infrastructure. Determining what must be archived/retained versus archiving everything often presents a cost-saving as well as a risk management tactic. With an active strategy effort, implementation of a go-forward archive solution becomes easier, less expensive, and time-consuming, and therefore returns a faster ROI, ideally in 6-9 months.
Bottom line, Health IT leaders must choose a legacy data archive solution that is cost-effective, industry-standard based, works with your data sets, and helps you move into the future efficiently. There are many solutions and approaches in the market for legacy data archiving and well-defined requirements can help you choose the right approach for your organization.
This article was originally published on CereCore and is republished here with permission.