Interoperability, yes, but with truly accurate data
A mid-Atlantic hospital’s transplant program recently went live with Epic Phoenix to better track pre and post-transplant patients. Prior to the Epic implementation, all patient data was maintained manually on paper flowsheets.
It is worthy of note that a significant percentage of the transplant patient population travels to this institution for treatment from outside the hospital’s network. So even with the incorporation of the Epic EHR and links to national labs like Quest Diagnostics and LabCorp, there is still a large number of tests received at the hospital via fax, courier or hand-carried by the patient.
As the conversion to electronic health record and decision support tools came on line, it became apparent that entering and tracking certain data, even patient demographics, would change. Part of this has to do with meeting Meaningful Use Stage 2 requirements and part of it needed to be modified as a function of going electronic.
Meaningful Use and discrete data
First, with the MU2 requirement that lab test results are to be logged as discrete data, the hospital has been using a team of seven data coordinators to manually enter results data. As is often the case, in the interest of time, the key components sought by the provider from a test result are captured and the rest are left. It is already a sizable task to capture the panel with values, units, reference ranges, flags and comments. Above and beyond the results, it’s necessary to capture the patient demographics and performing lab information to correlate the result to the order in Epic.
Connecting the dots
In the United States, there are approximately 251,000 certified laboratories today according to CLIA – consisting of large diagnostic labs, labs in medical group practices and even mobile labs for community outreach and ambulances. While the list does not radically change, it does fluctuate from time to time as labs open, close or move. It is incumbent upon the hospital to properly identify and code the performing lab for each test.
We determined that the best course of action is to identify all of the in-state labs as well as those in the surrounding states to capture a significant share of potentials to be found on the results. This list is updated nightly to incorporate any changes and comprises about 45,000 labs, a more manageable number for the hospital.
Calling it what it is
A more daunting task is mapping the naming conventions of the test components to those currently in Epic. Labs are not always consistent in what certain tests are called, or even what components are included in a test order. Standards such as LOINC and SNOMED-CT have been developed to normalize these names, but are still not in universal use.
The hospital integrated our software to automatically classify and capture lab results arriving on their fax server, route them to the appropriate solid organ team, interpret all lab results data and, using crosswalk tables, validate the patient information, performing lab and test components to properly marry that discrete data in Epic. The image of the lab is also stored in an electronic document management system (Hyland OnBase) which is tied to Epic so that providers can view the entire result if desired. The new system even recognizes duplicate or update results as they arrive, significantly and accurately improving the process.
This software solution has been deployed at the largest of the transplant programs in the U.S., improving accuracy of pre and post-transplant patients’ results for effective waitlist management and long-term tracking of outcomes.
Does your program see any of these issues in your day-to-day operations? Bet we could help you as well! If you’d like us to show you the workflow described for this healthcare system, please comment below and I’ll send it for your review.
About the Author: Ellen Bzomowski
With 20 years of experience in data capture and voice recognition, Ellen’s experience has focused on achieving higher efficiency and automation in getting data where it will be most useful to an organization. At Extract Systems, she continues to focus on the same ideas and works to get the word out about how Extract Systems’ advanced data capture and redaction solutions make more data valuable and accessible, while securing anything that is private. She holds an MBA from Northeastern University and lives and works in Boston.