What Is HL7? Everything You Need to Know

Seamless data exchange between systems is more critical than ever in the healthcare industry. That’s where HL7 comes in. Health Level Seven (HL7) is the gold standard for healthcare interoperability, enabling different software systems like Electronic Health Records, lab systems, and pharmacies to communicate effectively. Whether you’re a healthcare provider, IT professional, or simply curious about how patient data moves behind the scenes, understanding HL7 is essential. 

In this comprehensive guide, we’ll break down what HL7 is, why it matters, how it works, its different versions, including FHIR, and the tools and challenges involved in HL7 integration.

What Is HL7?

HL7 (Health Level Seven) is a set of international standards that define how healthcare information is structured and exchanged between different systems​. In simpler terms, HL7 is like a common language that lets healthcare software (EHRs, lab systems, billing systems, etc.) “communicate” with each other. 

These standards focus on the application layer (layer 7 of the OSI model), which is why it’s called Level Seven​. HL7 was created by a non-profit organization (Health Level Seven International) to make data sharing easier and more uniform across healthcare​. 

Instead of each system using its proprietary format, HL7 provides a standard format so data like patient demographics, lab results, or appointment information can be understood by any compliant system. This means when one system sends patient data to another system, the receiving system knows exactly how to interpret and import that information. 

Ultimately, HL7 exists to break down data silos and enable healthcare interoperability – the seamless exchange of health information between software applications.

Why HL7 Is Important in Healthcare

In modern healthcare, a single patient’s journey can involve many different IT systems. For instance, a patient’s data might be in an: 

• Electronic health record (EHR)  
• Lab information system 
• Pharmacy system
• Billing system. 

HL7 is important because it ensures all these systems can share data accurately and efficiently. Without a standard like HL7, hospitals used to face a situation akin to “independent states each speaking their language,” leading to inefficient, error-prone data exchange​. 

HL7 was designed to fix this by providing structure and consistency to clinical data, making the process of collecting, interpreting, and exchanging information more reliable​.

The benefits of HL7-driven interoperability are significant. With HL7, critical patient information travels with the patient – if they go from one department or facility to another, their records can follow electronically. This reduces duplicate tests and ensures every provider sees the same medical history (preventing errors like drug interactions or missing allergy info)​. It also cuts down on manual data entry and paperwork, saving time and reducing transcription mistakes. 

In short, HL7 helps healthcare organizations deliver better coordinated care: doctors get quick access to up-to-date records, labs and pharmacies receive orders instantly, and patients don’t have to carry printouts between appointments.

In an era where healthcare outcomes and efficiency are paramount, HL7 is the backbone of healthcare data interoperability, ensuring the right information gets to the right place at the right time.

HL7 Versions Explained (v2, v3, CDA, and FHIR)

Over the years, HL7 has evolved through different versions and standards. Here’s a quick rundown of the major HL7 versions and related standards you should know:

1. HL7 Version 2 (V2)

HL7 v2 is the oldest and by far the most widely used HL7 standard. First released in the late 1980s, it defines a text-based messaging format (using segments and delimiters like pipes | and carets ^) for exchanging health data. It covers a range of clinical message types: 

• Admissions 
• Discharges 
• Lab results 
• Orders, etc. 

HL7 v2 is widely adopted in hospitals worldwide for day-to-day system integrations​. It was developed pragmatically, which means it’s very flexible but not always plug-and-play. 

HL7 v2 is sometimes called a “non-standard standard” because about 80% of an interface might follow the standard, and the remaining 20% often requires site-specific customization​. Each healthcare organization can enable optional fields or add custom segments (often labeled “Z-segments”) in v2 messages, which means HL7 v2 interfaces often need careful mapping and tweaking to work between different systems​.

2. HL7 Version 3 (V3)

HL7 v3 was a major redesign initiated in the 1990s to address some of v2’s shortcomings. It introduced a more rigorous approach with a formal Reference Information Model (RIM) underpinning it. HL7 v3 messages are often XML-based (making them more human-readable than HL7 v2’s pipe-delimited text) and were intended to be more consistent and “out-of-the-box” interoperable​. However, v3 proved complex and had a steep learning curve, and importantly, it was not backward compatible with v2​. 

This lack of compatibility made it hard for organizations with extensive v2 integrations to switch over. As a result, pure HL7 v3 messages saw limited adoption. 

The main place you’ll encounter HL7 v3 is in specific document standards (see CDA below) or certain country-specific implementations. In summary, HL7 v3 was an ambitious improvement, but its complexity meant it never achieved the ubiquity of v2.

3. CDA (Clinical Document Architecture)

CDA is an HL7 standard for structured clinical documents, and it’s part of the HL7 v3 family. A CDA document is essentially an XML document that contains clinical information (for example, a discharge summary or a progress note) in a standardized format. The idea is to have a human-readable document that can also be parsed by machines. 

CDA gained traction through uses like the Continuity of Care Document (CCD) for sharing patient summary data, especially in the U.S., and Meaningful Use programs​. 

Many EHR systems can generate or import CDA/CCD documents (for example, when sending a patient referral or a care summary to another provider). While CDA did improve document exchange, it shares v3’s complexity – implementations can be challenging, and making the data fully computable across systems (beyond just viewing the document) isn’t always easy​. Still, CDA is an important HL7 standard whenever clinical documents need to be exchanged in a consistent format.

4. FHIR (Fast Healthcare Interoperability Resources)

FHIR is the newest member of the HL7 standards family, first released in the mid-2010s. Pronounced “fire,” FHIR was created with modern web technology in mind to address the limitations of earlier HL7 versions. It combines the best features of HL7 v2, v3, and CDA, while adding significant improvements​. 

FHIR is built around the concept of “resources” – small, modular pieces of data (like a Patient resource, an Observation resource for lab results, a Medication resource, etc.) – that can be individually accessed via RESTful APIs. In practice, this means FHIR allows healthcare systems to exchange data in a more web-friendly way (often using JSON or XML over HTTP). 

For example, instead of sending a big text message over an interface, a system can simply make a web API call to query a patient’s data in real time. FHIR was designed to be easier to implement, more scalable, and more flexible than previous HL7 standards​. It’s also free and supported by a large community. FHIR has rapidly gained adoption, especially as government regulations (like the U.S. ONC/CMS interoperability rules) now require exposing certain data via FHIR APIs​. 

While FHIR is not a direct “replacement” for HL7 v2 in all cases yet, it represents the future of health data exchange. Many vendors and HealthTech developers are building new applications with FHIR for easier integration with EHR systems.

How HL7 Works

So how do these HL7 standards actually get used in practice? HL7 works by defining a common format for data and a workflow for exchanging messages between systems. 

In a classic HL7 v2 scenario, the process goes like this: when a certain event happens in one system, it triggers an HL7 message to another. 

• For example, if a patient is admitted to the hospital registration system, that system will create an ADT message (Admission, Discharge, Transfer message) with the patient’s details. 
• This HL7 message is a text string with segments (lines) and fields separated by special characters. It might look cryptic, but it’s highly structured. 
• The message is then sent over a network (often via a TCP/IP connection on a specific port, or sometimes via file drops or web services) to the receiving system, such as the lab system or an imaging system. 
• The receiving system’s HL7 interface will parse the message, understand each field (because it follows the standard format), and then update its database (e.g., create the new patient record or order) accordingly.
• HL7 is the behind-the-scenes traffic controller for health data. It makes sure that when System A says “John Doe’s blood pressure is 120/80” or “John Doe is allergic to penicillin,” System B can understand it and put that information in the right place. 
• HL7 defines what format the data should be in (so things like patient name, ID, lab test codes, dates, etc., are in expected positions within the message).
• The standards also define acknowledgments (so the receiving system can reply with an ACK message to confirm receipt, or NACK if something went wrong).

Common Use Cases for HL7

Because HL7 is all about connecting healthcare systems, it comes into play in countless real-world scenarios. Here are some of the most common use cases where HL7 standards are used to exchange data:

1. Integrating EHR and Lab systems

One classic use of HL7 is connecting Electronic Health Records (EHRs) with Laboratory Information Systems (LIS). For example, when a doctor orders a lab test in the EHR, an HL7 order message (ORM) can send that order to the lab system automatically. Once the lab runs the test, the result is sent back via an HL7 result message (ORU) so the EHR gets the results instantly. 

This integration means no one has to manually re-enter lab results into the EHR. Labs and EHRs speaking HL7 can share orders and results seamlessly, speeding up diagnoses and ensuring the patient’s record is up to date​. It’s also used for other diagnostic systems – for instance, radiology systems sending imaging reports to the main hospital EHR.

2. Pharmacy data exchange

Pharmacies (whether in-hospital or external) need to receive medication orders and share dispense status or medication histories. HL7 messaging allows prescription details to flow electronically from a doctor’s order entry system (CPOE) to the pharmacy’s system​. 

This is crucial for e-prescribing: when a physician prescribes a drug in the EHR, an HL7 message can transmit that to the pharmacy without someone picking up the phone or fax. 

Pharmacies can likewise send back an HL7 message updating the medication record (e.g., to indicate a prescription was filled or if a substitution was made). HL7 also helps with medication reconciliation by sharing medication lists between systems​. All of this leads to faster prescription fulfillment and a reduction in medication errors since the process is electronic and standardized.

3. Telemedicine integration

Telehealth platforms and remote patient monitoring devices generate health data that often needs to end up in the primary care EHR or be shared with providers. Many telemedicine and remote monitoring solutions use HL7 (or HL7 FHIR) under the hood to transmit patient data​. 

For example, a telemedicine visit summary (notes, diagnoses, etc.) can be sent as an HL7 CDA document or a FHIR bundle into the patient’s record at the clinic. Remote monitoring devices (like a blood pressure cuff or glucose monitor that a patient uses at home) might send periodic readings to a central system using HL7 messages, which then integrate into the EHR for the doctor to review​. 

By using HL7 standards, telehealth systems ensure that data captured remotely isn’t stuck in a silo – it becomes part of the patient’s continuous health record. This integration is key for things like chronic disease management, where home-collected data needs to inform in-clinic decisions.

4. Hospital-to-hospital data sharing

When patients move between hospitals or when different healthcare organizations collaborate, HL7 provides a common language for data exchange. Hospitals can share patient records (demographics, clinical summaries, test results) during transfers or referrals using HL7 messages or documents​. 

• For instance, if a patient is transferred from a local hospital to a specialist center, an HL7 interface can transmit the patient’s info so the receiving hospital’s systems are populated with an up-to-date medical history. 
• Similarly, health information exchange (HIE) networks often rely on HL7 v2 and CDA messages to allow hospital A’s EHR to query or receive data from hospital B’s EHR.

This uninterrupted flow of electronic health data is a core benefit of HL7, ensuring continuity of care across organizations​. Instead of faxing records or burning CDs of images, providers use HL7-based exchange to get what they need in near real-time.

5. Public health reporting

HL7 is also critical for transmitting data to public health authorities and registries. Many countries and states mandate that hospitals and labs send certain data to government health departments – for example, 

• Reporting infectious diseases 
• Sending immunization records to a state registry 
• Submitting data to cancer registries. 

HL7 standards are widely used for public health reporting, allowing electronic lab systems to automatically send reportable disease results to the health department in an HL7 message​. Immunization interfaces use HL7 v2 messages to update centralized vaccine registries with patient vaccination records. 

By using HL7, these reports can be sent promptly and in a structured way, which improves surveillance and response. Public health agencies, in turn, can aggregate data from many sources because they’re all coming in a standard format. In short, HL7 helps bridge healthcare providers with public health systems, supporting faster and more accurate reporting for population health.

Related: The Use of HL7 FHIR in OpenEMR: An Exclusive Comprehensive Guide

HL7 vs FHIR: What’s the Difference?

You might often hear HL7 mentioned in the same breath as FHIR. It’s important to clarify the relationship: FHIR is one of the HL7 standards, but it represents a new approach compared to “classic” HL7 messaging. Here’s how they differ:

1. Technology and Format

Traditional HL7 (like v2 messages) is a primarily text-based, delimited format often sent over lower-level protocols (MLLP over TCP, for example). It’s very domain-specific to healthcare. FHIR, on the other hand, is built on modern web technologies – it typically uses RESTful APIs, HTTP, and data formats like JSON or XML that are common in web development. 

This means a hospital system using HL7 v2 might send a lab result via a text message to another system, whereas a system using FHIR could expose a web service endpoint where that result can be queried or pushed via an HTTP call.

2. Data Structure

HL7 v2 organizes data in messages with segments, each message usually covering one event (e.g., an ADT A01 for patient admit). FHIR organizes data into resources – small chunks that represent specific entities (Patient, Observation, Medication, Appointment, etc.). 

These resources can be individually accessed or bundled as needed. FHIR resources are also extensible and can carry rich data (including human-readable narrative). 

In practice, this means FHIR can be more granular and flexible. For example, if you want just patient demographics, you can query the Patient resource via FHIR, instead of parsing a full HL7 ADT message.

3. Ease of Use

One of the driving goals of FHIR was to be easier and faster for developers to learn and implement​. HL7 v2 has a steep learning curve and requires understanding a lot of custom conventions; working with it often involves specialized interface analysts. 

FHIR, being JSON/XML-based with lots of online documentation and using familiar API patterns, is more approachable for modern software developers. This lower barrier is encouraging new entrants and innovations in health tech, as developers can build health apps without mastering legacy HL7 messaging. FHIR is also considered more cost-effective and scalable for integrating complex networks of systems​.

4. Use Cases and Adoption

HL7 v2 is deeply entrenched in existing systems – virtually every hospital system today supports HL7 v2 messaging for things like lab results, admissions, orders, etc. It’s reliable and proven over decades, but also somewhat dated. FHIR is rapidly being adopted for new use cases, especially ones involving mobile apps, patient-facing applications, and interoperability between organizations (like patients accessing their records via smartphone, or data exchange between hospitals and insurers). 

Regulators are pushing FHIR for patient data access and interoperability, so its adoption curve is steep. That said, HL7 v2 isn’t going away overnight – it still powers many internal workflows. 

We’re in a period where HL7 v2 and FHIR coexist: for example, 

• An interface engine might receive HL7 v2 messages from an old lab system  
• Then convert and expose that data via a FHIR API for a newer application. 
• Over time, more systems will likely communicate directly with FHIR, but understanding both is important right now.

Related: HL7 to FHIR Conversion: Complexities in Automating Health Data Conversion

Challenges with HL7 Integration

While HL7 has greatly improved interoperability, it’s not a plug-and-play panacea. Healthcare IT teams often encounter several challenges when working with HL7 integrations:

1. Complexity of parsing and mapping messages

HL7 messages (especially v2) can be quite complex. They are essentially large, delimited strings that require proper parsing to extract fields. The HL7 standard documentation spans thousands of pages, covering countless message types and optional fields. 

For newcomers, the syntax can be intimidating. Even for veterans, writing custom code to parse and generate HL7 can be error-prone if done from scratch. Moreover, mapping data from one system’s format to another’s can be tedious – e.g., ensuring that the “patient class” or “facility code” in the sending system’s message correctly maps to a code the receiving system recognizes. 

Small mismatches (like different date formats or unit conventions) can cause big headaches. In short, working with HL7 requires specialized knowledge, and building an interface involves careful data mapping and extensive testing to ensure every field lines up correctly.

2. Custom implementations by vendors

One ironic truth about HL7 v2 is that it’s a standard that’s implemented in many non-standard ways. The standard intentionally allows optional segments and custom extensions to accommodate different needs. As a result, each vendor or healthcare provider might have their own “flavor” of HL7. 

• For example, two lab systems might both claim to send HL7 results, but one uses a custom Z-segment to send an extra piece of information or
• They use slightly different coding systems for test names. 

This variability means interfaces often require negotiation and tweaking – the systems have to agree on which segments and fields to use. It’s common to have an interface specification document for each connection, basically a profile of how HL7 will be used in that instance. 

If not managed, these differences lead to interoperability issues when connecting disparate systems​. In practice, teams spend a lot of time on interface mapping and “translation” rules to get systems in sync. 

HL7 v3 and CDA tried to enforce more consistency, but they introduced complexity; FHIR aims to reduce optionality. Still, in today’s environment, anyone integrating systems must deal with the reality that one vendor’s HL7 is not the same as another’s.

3. Data quality and semantic mismatches

Even if the technical format aligns, the meaning of the data can differ between systems. One system might use one set of codes for diagnoses, another might use a different coding standard. 

Units of measure might differ (mg/dL vs mmol/L, for instance). There may be slight differences in how data is captured (e.g. one EHR might allow free-text entries for race or ethnicity, whereas another expects coded values – sending that via HL7 can result in inconsistent data). 

These semantic mismatches can lead to situations where data is technically exchanged but not truly interoperable (the receiving system gets it but can’t fully make sense of it in an automated way). Ensuring data quality requires not just moving data, but often normalizing it to common codesets and formats. 

HL7 messages do support standardized code systems (like LOINC for lab tests, SNOMED for problems, etc.), but usage of these standards is not uniform. 

So, integration projects often have to include data cleanup or use interface engines to translate codes (e.g., map “MRI” in one system to “Magnetic Resonance Imaging” code in another). Poor data quality or inconsistent semantics can undermine the benefits of HL7 by requiring manual reconciliation, so it’s a constant challenge to address during integration.

4. Need for HL7 interface engines (e.g., Mirth Connect)

Given the complexity and variability above, most healthcare organizations rely on interface engines (integration engines) to manage HL7 data flow. An interface engine is a middleware solution that routes, filters, and transforms HL7 messages between systems. 

The need for these arises because directly connecting every system to every other (point-to-point interfaces) becomes unmanageable and fragile over time. Instead, interfaces funnel through an engine that can handle different formats and perform translations on the fly. 

• For example, if one system sends a slightly non-standard HL7 message, the engine can transform it into the expected format of the receiving system. 
• Engines can also handle things like queuing, retries on failures, and monitoring of interfaces. 

While these tools greatly help, they introduce their complexity and cost. Small clinics might try to get by without an engine, but any medium or large provider finds an HL7 engine indispensable for reliable integration​. The challenge here is twofold: acquiring a good interface engine, and having skilled personnel to configure and maintain the interfaces. 

It’s a specialized skill set to build HL7 interface routes and mappings. Additionally, interface engines (aside from some open-source options) can be expensive, and even open-source ones require maintenance and expertise. Nonetheless, in today’s healthcare IT landscape, navigating HL7 integration without an interface engine is rare – these tools have become a must to mitigate HL7’s complexity and variability.

Related: 5 Challenges Associated with HL7 FHIR and How CapMinds Helps to Solve

Popular HL7 Integration Tools & Middleware

To tackle HL7 integration challenges, healthcare organizations use specialized tools known as integration engines or interface middleware. There are several popular HL7 integration engines in the industry, each with its strengths. Here are a few well-known ones:

1. Mirth Connect (Now NextGen)

Mirth Connect is one of the most widely used interface engines, especially notable because it originated as an open-source tool. It’s now maintained by NextGen Healthcare (and sometimes called NextGen Connect). Mirth is prized for its flexibility and cost-effectiveness – it can handle HL7 v2, HL7 v3, FHIR, X12 (claims), and more. 

Mirth allows you to build channels that filter and transform messages, so you can map one system’s output to another’s input with JavaScript or built-in transformers. It is highly scalable, but like many powerful tools, it has a learning curve, and setting it up requires some integration know-how

2. Rhapsody

Rhapsody is an enterprise-grade integration engine originally developed by Orion Health and now part of Lyniate (after merging with another engine, Corepoint). Rhapsody is known for its strong performance and a user-friendly interface for designing interfaces. It supports all the major healthcare standards (HL7 v2/v3, CDA, FHIR, DICOM, etc.) and is designed to be highly reliable in mission-critical environments. 

Rhapsody emphasizes easy deployment and comprehensive tools for monitoring interfaces, which is valuable for large health systems that might be processing millions of messages a day​. It offers features like high availability clustering and can be run on-premises or in the cloud.

3. Corepoint Integration Engine

Corepoint is another leading integration engine, which has historically been very popular in the US hospital market (particularly with radiology and ancillary system integrations). 

Corepoint Health (the company) merged with Rhapsody under Lyniate, but the Corepoint engine is still offered as a distinct product. Corepoint built a reputation for an easy-to-use visual interface and a focus on healthcare standards. It provides a friendly GUI to map HL7 fields and orchestrate workflows, which reduces the need for custom scripting. Corepoint is often praised for its proactive monitoring and alerting features, making it easier for interface analysts to spot and fix issues before they become big problems​.

4. Interfaceware Iguana

Iguana is an integration engine by Interfaceware. It’s known for being developer-friendly and highly adaptable. Unlike some engines that have a heavy GUI focus, Iguana allows integration engineers to use scripting (Lua language) for very fine-grained control, which some teams prefer for complex transformations. 

Iguana is designed for real-time data transfer and custom workflows, and many describe it as simple yet powerful. It has an intuitive dashboard and is lightweight to deploy. Iguana is often chosen by organizations that have strong technical teams who want flexibility without sacrificing reliability.

Who Uses HL7?

HL7 is ubiquitous in healthcare – a behind-the-scenes workhorse used by a wide range of stakeholders. Here are some of the key players who use HL7 standards in their daily operations:

1. Hospitals

Virtually every hospital uses HL7 interfaces within its IT infrastructure. For example, a hospital will use HL7 to connect its EHR with lab analyzers, imaging (radiology) systems, pharmacy systems, billing software, and more. 

When a patient is admitted, HL7 messages distribute that info to all departments. When labs are completed or medications administered, HL7 messages send updates back to the central record. Hospitals rely on HL7 to ensure all their various departmental systems work as one cohesive whole.

2. HealthTech companies

Companies that build healthcare software almost always build HL7 capabilities into their products. If you develop a new medical app – say a radiology reporting system or a digital pharmacy system – you need to support HL7 standards so your product can integrate with the existing ecosystem. 

HealthTech vendors implement HL7 to exchange data with EHRs or other third-party systems, which is a selling point for their software.

3. Government health departments

Public health entities are big users of HL7 for gathering data from the healthcare system. Health departments use HL7 messages to receive electronic lab reporting (ELR) for infectious diseases, immunization data submissions, syndromic surveillance data from ERs, and more. 

For example, during the COVID-19 pandemic, labs and hospitals sent HL7 lab result messages (per HL7 v2 standards) to state and federal systems for case reporting. Government agencies rely on HL7 to collect standardized data for population health monitoring, disease registries, and regulatory reporting.

4. Insurance companies

While insurance companies historically use other standards (like X12 EDI for claims), they are increasingly consuming clinical data to support care management, authorization decisions, and value-based care models. HL7 comes into play for payers in scenarios such as receiving HL7 CDA documents or FHIR data from providers about patient health status.

5. Developers building healthcare apps

A broad category, but worth mentioning – the developers, consultants, and integration engineers who implement HL7. These individuals and teams use HL7 every day to build and maintain the interfaces that connect systems. They might work within a hospital’s IT department, for a software vendor, or for a consulting firm that specializes in healthcare interoperability. 

Whenever a new interface or digital health project is launched, developers fluent in HL7 standards are the ones who make it happen. They use tools (like the integration engines mentioned) and HL7 specifications to write transformations, configure message flows, and test connectivity.

CapMinds HL7 FHIR Service for Healthcare Practice

CapMinds offers the best all-in-one health interoperability solution for healthcare practices. Our HL7 FHIR service will understand your clinical needs and requirements to cater to our solution. 

We have years of experience in this field, faced many challenges, and tackled them with ease. Why can CapMinds be your Go-to Interoperability Solution?

• We are experienced professionals with years of experience in the field.
• Our technical team is an expert who will analyze your healthcare practice thoroughly to tailor the Interoperability solution.
• We prioritize safety, security, encryption, and authentication to protect your healthcare practice’s patients’ data.
• Our comprehensive solution ensures seamless interoperability, adhering to industry standards and using standard protocols.
• We offer comprehensive training sessions to healthcare staff.
• Our affordable health interoperability solution benefits healthcare practices at all levels.

If you are searching for the best interoperability service for your practice, CapMinds is your choice. We can assist you by navigating all potential challenges and ensuring seamless health data exchange.

Reach out to CapMinds Health Data Exchange Solutions for your Healthcare Practice.