HL7: Solving Old Problems with New Tools

One of the benefits of working at Switchbox is gaining exposure to many  technologies, both new and old.  Recently, one of our developers had the opportunity to learn and work with HL7.  HL7, which stands for Health Level-7, is a set of standards used to transmit data between different healthcare providers.

HL7 has been around since the late 80’s and can be very complex and difficult at times.  There are different versions, various message types and data that can be interpreted or mapped in different systems. Meaning, important information, specifically dates, can easily be misconstrued. Health information is particularly sensitive and the smallest error could mean the difference between a right or wrong prescription dosage or incorrect birth date.

One of our clients was faced with this exact problem. This particular client received many HL7 messages sent to them from a local hospital. Often the hospital sending the messages mapped incorrect data to certain fields which were crucial to our client’s system, causing inaccurate name information which cost our client time and resources. In order to fix this issue, it took a developer to manually fix and resubmit these invalid messages.  To be frank, it was a major headache for our client as their development team remains limited and they simply did not have the resources.

Luckily our client was using a handy tool from Interfaceware ( called Iguana.  Iguana is used to send, receive, parse and handle HL7 messages. This tool is both powerful and lightweight in that it handles various errors in real time and runs in the browser so it does not require a lot of system resources. By utilizing Iguana, our client was able to add custom logic and filter out any invalid messages they received. However, they still needed a way to keep track of, fix and resubmit these invalid messages in order to get them in their system and this is where Switchbox stepped in.

With our extensive knowledge and experience, we were able to build an easy-to-use interface which tracked messages and allowed users to view, edit and resubmit the updated message. We accomplished this by finding an open-source tool for .NET called nHapi ( nHapi allowed us to get the invalid messages our client now is storing in a database and ensure the patient information matched from the hospital to the client’s intake system.  

While continuing to use Iguana, coupled with our nHapi tool, our client no longer needs a developer to intervene in order to fix and resubmit invalid messages and patient information. This fix saves our client an enormous amount of time. Going forward, not only can they manually fix an error, they can also look for common error trends by running a data report internally which has the potential to fix problems at their root. Overall, Switchbox was able to save a client time and we were able to expand our skill set by gaining more knowledge of HL7 and the inter-workings of nHapi.