HL7 demystified for founders. The reality of healthcare interoperability

HL7 is one of the most important but misunderstood interoperability standards in modern digital healthcare. Startups and owners must learn how it works, why hospitals still rely on it, and the operational realities of integrating digital healthcare systems at scale.

Why this matters

Although the healthcare industry generates approximately 30% of the global data volume, most of that data remains trapped in highly fragmented systems, inaccessible to the organizations and professionals who could use it to truly improve patient outcomes. The main challenge here is that medical data is spread across hundreds of incompatible platforms, including Electronic Health Records (EHRs) from different vendors and countless disparate lab and pharmacy information systems, billing software, patient portals, mobile healthcare apps, and even wearables. Each of these systems uses different data formats, interoperability standards, and security requirements, among other differences, creating significant barriers to seamless healthcare data exchange and integration.

This is where HL7 (Health Level Seven) comes in. Developed in the 1980s, HL7 is one of the foundational standards behind healthcare interoperability. Its purpose is to facilitate the exchange of healthcare information between hospitals, laboratories, clinics, imaging centers, billing systems, EHRs, and other healthcare technologies operating across disconnected environments. However, most founders blindly nod along when they hear “HL7” without fully understanding what it is or why it matters. As a result, they often underestimate the complexity of healthcare interoperability, leading to architectural decisions that can limit scalability, hinder integration efforts, and become costly to correct as their digital health products grow.

The real challenges

The real challenge with HL7 is that most founders encounter it in ways that confuse and frustrate them, and rightfully so. HL7 sounds conceptually simple, but in reality, its implementation involves several details that can be confusing.

Confusion as to which HL7 version to use. HL7 is the first version of the standard, but it has since undergone several transformations and improvements. Understanding which version they actually need and why is critical. Depending on their needs, founders can use:
- HL7 v2: A highly flexible, pipe-delimited message-based standard for real-time data exchange.
- HL7 v3: Based on the Reference Information Model (RIM), this third iteration of HL7 is XML-based, improving its interoperability capabilities but making it harder to implement.
- HL7 FHIR: The latest HL7 version, FHIR (Fast Healthcare Interoperability Resources), is built on RESTful APIs, JSON, and XML, making it much easier to implement, test, and scale.
There are different implementations of the same standard. While HL7 has official specifications, every healthcare setting and organization implements it slightly differently. As a result, healthcare app developers can’t expect their HL7 implementations to work everywhere, forcing teams to map separately for the internal data model of each organization.
HL7 requires operational infrastructure and investment that most startups don’t have. Getting any version of HL7, especially FHIR, up and running involves monetary resources, time, and specialized staff, which some companies, especially startups, might struggle to handle early on.
HL7 can create unforeseen compliance obligations. HL7 messages between platforms and organizations typically carry protected health information (PHI), meaning founders must ensure they meet HIPAA compliance, secure data handling, audit logging, and other appropriate legal agreements.

Our perspective

At Foonkie Monkey, we understand that HL7 is the key to moving healthcare data between systems reliably. To ensure our team can successfully implement and work with HL7, we educate them in:

How healthcare data moves across organizations and different healthcare settings.
How clinical workflows generate and consume healthcare data.
How different settings have different systems.
How those systems may interpret the same information differently.
How fragmented healthcare environments behave in real-world production environments.

Furthermore, we teach our teams to view HL7 as more than a messaging standard. Every HL7 message represents a real clinical event, such as an admission or a discharge, and each one requires understanding the operational context behind the data. Validating that information is interpreted correctly and ensuring it supports the workflows of healthcare professionals is critical in all our workflows and processes. By approaching HL7 from both a technical and clinical perspective, we build integrations that are not only functional but also reliable, scalable, and meaningful within real healthcare environments.

Practical breakdown

In our experience, here are the real-world considerations and fundamentals of mastering HL7 in healthcare mobile apps and software.

HL7 fundamentals

HL7 models work like this: Clinical event - HL7 message is generated - receiving system processes HL7 message - patient record is updated.
These messages are pipe-delimited text with line breaks separating segments.
Each segment has a 3-letter code: - PID: Patient Identification - OBX: Observation/Result - ADT: Admission/Discharge/Transfer
Fields are separated by pipes (|), subfields by carets (^), and repetitions by tildes (~).
Example: PID|1||12345^^^MRN^MR||PARKER^JOHN^||19000101|M|||
Translation: This is Patient John Parker, born Jan 1, 1990.

HL7 message types

ADT (Admission/Discharge/Transfer): When patients enter, leave, or transfer between units.
ORU (Observation Result): Lab results and other clinical notes.
ORM (Order): Medication, lab, or imaging orders.
RGV (Pharmacy/Give): Medication and pharmacy updates.
DFT (Detailed Financial): Billing information and charges.
BAR (Billing Account Record): Billing.

Infrastructure requirements for HL7

A queue-based messaging infrastructure, such as AWS SQS, that enables the reliable ingestion, processing, and delivery of HL7 messages across healthcare systems.
A robust message parsing layer capable of interpreting HL7 syntax with all its variations.
A validation framework that detects errors and verifies all data before it enters downstream workflows.
A transformation and normalization layer that translates organization-specific HL7 messages into a consistent internal data mode.
Comprehensive error-handling mechanisms.
Secure data storage that incorporates encryption, role-based access controls, audit logging, and other safeguards necessary to protect sensitive healthcare information.
Continuous monitoring and alerting systems that identify issues before they affect clinical operations.
A dedicated testing environment.

Common mistakes we see

We’ve seen most founders misunderstand the fundamentals of HL7 and fall into these mistakes when implementing it:

1. Thinking HL7 alone guarantees interoperability: Most founders think that implementing HL7 automatically guarantees interoperability and fail to understand that implementations vary heavily between vendors and healthcare organizations. Moreover, many healthcare organizations still operate under older legacy systems that behave differently from modern API-driven architectures.

2. Assuming data is always clean: Real HL7 messages from hospitals are often chaotic and plagued with missing required fields or incorrect segment sequences.

3. Not planning for HL7 overhead: HL7 integration requires considerable infrastructural and operational changes that must be taken into account when planning for implementation.

4. Ignoring the security and compliance implications of HL7: HL7 messages contain protected health information, meaning you need to meet HIPAA compliance.

How to do it right

We have ample experience in healthcare mobile app development and have mastered the art of implementing HL7. Here’s how to do it right:

1. Determine if you need HL7 and which version is best for your product.

Identify the healthcare organizations you’ll be working with and determine their HL7 capabilities.
Assess your infrastructure requirements and how they will support your HL7 version of choice.
Define if you need real-time HL7 feeds or if FHIR API access is enough.
Define your compliance requirements.

2. Map your architecture and data management strategy.

Design for variability from the start, recognizing that healthcare organizations, EHR vendors, and HL7 implementations change.
Build abstraction and normalization layers that convert incoming HL7 messages into a consistent internal data model.
Always assume healthcare data will be incomplete, inconsistent, duplicated, or fragmented.
Plan for hybrid interoperability environments where traditional HL7 messaging can coexist with modern standards such as FHIR.

3. Align integrations with clinical workflows.

Ensure data is delivered in a readable way that supports healthcare professionals and patient care processes.
Work closely with other healthcare organizations to understand their HL7 configurations.
Get sample HL7 messages in their format to design accordingly.
Customize your configurations for each organization’s different needs.
Understand the clinical context behind the data being exchanged, not just the message structure itself.

4. Design a strong security and compliance strategy.

Establish strong security controls to protect sensitive healthcare information.
Ensure all your interoperability strategies support HIPAA compliance.
Implement logging and traceability mechanisms that provide visibility into how data moves between systems and who has access to it.

5. Define your ongoing operations and maintenance.

Treat HL7 as a long-term interoperability capability.
Continuously monitor integration performance, message quality, and system health.
Allocate resources for ongoing updates as healthcare systems, standards, and vendor implementations evolve.
Build flexible architectures that can adapt to future interoperability requirements.

Founders must understand that the healthcare environments that their product connects to will inevitably change over time, and successful integrations are those designed to adapt alongside them. In healthcare mobile apps, the goal is to ensure that information moves reliably, accurately, and securely in support of real clinical care.

Building something similar?

HL7 sounds complicated, but in reality, it’s just about understanding the needs of each different healthcare setting. If you’re building a healthcare mobile app or software that needs to receive and process HL7 messages and you’re facing interoperability challenges, we can help you design a secure, scalable healthcare integration architecture that supports real-world clinical workflows and long-term system reliability.