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Data Conversions (DC) are necessary to ensure availability of Meaningful Use (MU) data, increased quality of care, and overall improved performance. Transferring data from an old system to a new or current one requires care and a knowledgeable project team to meet all standards of the organization for their go-live.
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Data Conversions – Convert With Confidence Wednesday, July 9, 2014
Disclaimer: Nothing that we are sharing is intended as legally binding or prescrip7ve advice. This presenta7on is a synthesis of publically available informa7on and best prac7ces.
• Why are conversions necessary? – Lack of MU Cer5fica5on
• Federal Funding – Improved Performance
– Increased Quality of Care – Lack of Func5onality in Outdated Systems
Introduc5on
• Why are changes needed? – Solu5on does not meet needs.
– Needs not adequately assessed when original implementa5on occurred.
– Designed not suited for prac5ce specialty – Unresponsive Vendor
Why the pain?
• Legal Record – Maintaining pa5ent records for legal purposes
• Con5nuity of Care – Easy access to pa5ent informa5on – BeMer Pa5ent Care
• Proper Planning – Data conversion is an o=en 7mes an a=erthought
• Conversion Exper5se – Many organiza5ons are not familiar with the data conversion process
– Suitable op5ons that meet specific needs
Considera5ons
• Unsuccessful planning process • Data assessment not performed
• Lack of complete tes5ng process
• Not involving the clinical staff • Timing issues
• Conversion size considera5ons • And more.
Why Do Conversions Fail?
• Leave old system up and running – Pros
• Don’t have to dedicate funds or resources for a conversion
– Cons • Ongoing maintenance and support costs can be huge
• Risk of not being able to access the data if issues occur • Requires physicians having to log into another system and search for the pa5ent
You Always Have Op5ons
• Manual Entry (Hand type data from old EMR into new EMR) – Pros
• Enables full EMR func5onality on legacy data • Ease of access
– Cons • May poten5ally take a VERY long 5me and is resource intensive
• Greater chances of error when manually entering informa5on
Op5ons to consider
• Discrete Data Conversion (Clinical data electronically transferred and physically resides in new database ) – Pros
• Enables full EMR func5onality on legacy data • Legacy data is easily accessible • Faster implementa5on 5me over manual conversion • Less resource intensive than manual • Higher degree of accuracy • Legacy data can be incorporated for clinical intelligence purposes (i.e. PQRS)
– Cons • Can be cost-‐prohibi5ve for smaller prac5ces • Requires conversion exper5se • Garbage in, garbage out
Op5ons to consider
• Summary Report Documents (Summarized documents created as PDFs and physically reside in new EMR database ) – Pros
• More cost-‐effec5ve than discrete conversion • Doesn’t require logging into another system
– Cons • Hard to find informa5on quickly in large summary documents
• Does not receive benefit of full EMR func5onality on legacy data
• Cannot report on the data
Op5ons to consider
• Interface the data during transi5on – Pros
• More cost-‐effec5ve than discrete conversion • Real-‐5me system sync
– Cons • Interface systems can take a long 5me to create and test
• Certain data elements may not be interfaced precisely as needed due to vendor system inadequacy.
Op5ons to consider
Common Conversion Process
• 1) Discovery • 2) Requirements • 3) Build • 4) Test • 5) Go-‐live.
• Risks – Make a list of risks and their con5ngency plans.
– What would jeopardize your deliverables or schedule?
• Service Level Agreements – Agreements in place for quick turn around on decisions
Discovery
• Data content issues – Plan for late discoveries of data content issues
• Conversion and mapping teams – The project team requires a combina5on of people with clinical, technical and project management skills
Discovery
• Data mapping – Plan to deliver the EHR build based on the schedule needed for the conversion data mapping effort
• Documenta5on – Document everything. – This includes: status reports, dashboards and other visual aids
Requirements
• Format – Many clients have standards for specifica5on formats. Since there will be many specifica5ons, it’s important to enforce a standard so that all specifica5ons are consistent.
• Content – Every detail must be defined on a field-‐by-‐field basis
Requirements
• Mapping – There will be mul5ple versions of mapping documenta5on. It is important to manage these so that team members always have the latest version available to them.
Build
• Conversion design – Demographics
• Determine the trusted source of your demographic data
• Consider how new and updated registra5on data will flow to the new EMR in real 5me once the ini5al registra5on conversion is complete.
– Encounters • All chart data that gets loaded is associated with an encounter or “visit.”
• Pa5ent contact or visit entries may not necessarily be an exact match
Build
• Full volume tes5ng – Work with technical support to plan disc space. – Perform incremental tests at increasing volumes up to full volume.
• Test environments – 2 are necessary – A primary test environment for incremental volume tests
– A secondary test environment for simulated produc5on
Test
• Tracking – Good tes5ng requires good tracking. Use tracking tools to monitor tes5ng progress, defect countdown, issue resolu5on, etc.
• Clinician sign-‐off – Tes5ng is not complete un5l the clinicians sign off.
Test
• Bulk and gap conversions – Bulk conversions some5mes take days to complete. – a smaller bulk conversion is needed, ofen called a “gap conversion”
• Big-‐bang vs. rollout: – If the go-‐live approach is a “big bang”, the legacy system must be locked out to prevent any new transac5ons
– If the go-‐live approach is a “rollout”, there must be real-‐5me conversion interfaces that transfer all new manual ac5vity
Go-‐Live
