Interoperability & Healthcare Information Systems

Tip 2 in the Interoperability Tip Series

Data and Information Challenges

Learn how this tip boils down to speed and dollars.

In Tip 1 of our Interoperability Tip Series, we talked about the HL7 interface standards and their 3 challenges.

Dig deeper, and you find that underlying challenge with interoperability in healthcare information systems is at – you guessed it — the information level.

To tackle the challenge of interoperability within healthcare information systems, analysts need to ask: What information is needed by whom, when, and in what format?

Once analysts have these answers, they need to validate that information being transferred through the interface has the same meaning in both healthcare information systems. In technical terms, the information would have the same semantics in both systems.

4 Data and Information Issues

Here are the 4 data and information issues that analysts tackle when they work on interfacing and interoperability for healthcare information systems:




Data structure

The HL7 standard specifies a data structure based on trigger events, segments, fields, and data types. The recommended structure must account for complex clinical workflows and data representations.

There might be a gap based on the maximum length of data elements. A field in one hospital system specifies a maximum length of 50 characters. The same field in the system under implementation is set at maximum length of 20.

Data tables

HL7 provides a recommended set of data values. These can be modified.

HL7 v2.6 “suggests” six different values for patient gender.

Data semantics

Good data semantics implies that the meaning or intent of the data is exchanged accurately – not simply the data value itself. It’s essential for HL7 interfaces to convey their interpretation of the HL7 standard in use.

Patient identification is the classic example. It is important to determine which fields are in use. Possibilities include: PID-2 Patient ID, PID-3 Patient Identification List, PID-18 Patient Account Number, PV1-19 Visit Number, or a combination thereof.


Z-segments are custom message segments. They are used when an application must convey information outside the scope of the HL7 standard. Development teams also resort to Z-segments to work around technical limitations.

By definition, all Z-segments result in gaps. If Z-segments aren’t mapped accurately, critical information can be lost.

Why This Matters to Healthcare Leaders

If you’re speaking with a leader with profit and loss responsibility, let them know that these data and information issues boil down to speed and dollars.

We talked about best-practice requirements-gathering in Tip 1 of our series. In interoperability projects that complete on time and at/under budget, analysts get all their requirements upfront. They don’t hand off partial or “good-enough” requirements.

Best-practice requirements cover the data and information issues listed above – data structure, tables, semantics, Z-segments. Typically, they are covered in a gap analysis between two or more healthcare information systems: the sending and receiving systems.

The more completely an analyst identifies the gaps, the faster a developer will get to a production-ready interface.

If that gap analysis is less than complete, the developer will spend time testing that interface looking for bugs and defects before it goes live. And if that happens, your entire go-live slips.

That’s why we say it boils down to speed and dollars.

Download the HL7 Survival Guide

Download the HL7 Survival Guide