How to Achieve True Interoperability in Healthcare Systems
Summary
TLDRThe video script addresses the challenge of achieving interoperability in healthcare systems, distinguishing between syntactic and semantic interoperability. Syntactic focuses on the structure of data exchange, exemplified by HL7 V2 and FHIR standards, which enable systems to communicate despite different formats. Semantic interoperability, however, ensures that data has a consistent meaning across systems, avoiding discrepancies in interpretation. The script emphasizes the importance of human agreement and FHIR's machine-readable profiles in advancing towards true semantic interoperability in healthcare IT.
Takeaways
- 🔄 Achieving interoperability between healthcare systems is an ongoing challenge due to numerous digital systems across facilities.
- 🖥️ Software solutions, including InterSystems technologies, help improve interoperability between these systems.
- 🔗 There are two types of interoperability: syntactic and semantic.
- 🔧 Syntactic interoperability focuses on the structure of messages but does not interpret their meaning, allowing systems to send and receive data in different formats.
- 📤 An intermediary system can transform data between formats, such as converting HL7 V2 messages to FHIR format, to achieve syntactic interoperability.
- 🌍 HL7 V2 is the most widely used interoperability standard, with InterSystems exchanging over one billion messages daily.
- 📜 Compatibility with FHIR is federally mandated in many countries, representing the future of healthcare IT interoperability.
- 🧠 Semantic interoperability ensures that data has the same meaning across systems, reducing discrepancies caused by human interpretation.
- 🦓 Human decision-making plays a key role in interpreting nuanced data, but semantic interoperability seeks to eliminate the need for this.
- 🏥 FHIR's machine-readable profiles enable healthcare systems to share data concepts and move toward semantic interoperability if common agreements are reached.
Q & A
What is the main challenge of achieving interoperability in healthcare systems?
-The main challenge is enabling communication between dozens of digital systems at a given facility and across multiple facilities within a network. These systems often use different formats and structures, making data exchange difficult.
What are the two types of interoperability mentioned in the script?
-The two types of interoperability are syntactic interoperability and semantic interoperability.
What is syntactic interoperability?
-Syntactic interoperability ensures that systems can send and receive data in different formats by defining the structure of a message, but it does not address the meaning of the data being exchanged.
Why is syntactic interoperability crucial for healthcare IT infrastructure?
-Syntactic interoperability allows systems to exchange data using standardized formats like HL7 V2 and FHIR, which are essential for communication between different healthcare systems.
What solution is typically used to achieve syntactic interoperability between systems using different data formats?
-An intermediary system that transforms data from one format to another, such as converting HL7 V2 messages into FHIR format, is commonly used to achieve syntactic interoperability.
What is semantic interoperability?
-Semantic interoperability ensures that data exchanged between systems has the same meaning and can be used directly within the receiving system's workflow without needing human interpretation.
Can you provide an example that illustrates the importance of semantic interoperability?
-An example involves three different electronic health record systems documenting suspected lung cancer. Each system structures the data differently, making it difficult to determine that they all refer to the same medical condition, highlighting the need for common data definitions.
Why is it difficult to achieve semantic interoperability in healthcare?
-Achieving semantic interoperability is challenging because systems may define the same concept in different ways, and there must be human agreement on standard definitions to ensure consistent meaning across systems.
What is the role of FHIR in promoting interoperability?
-FHIR plays a key role by making everything machine-readable, including FHIR profiles, which allows for easier sharing of data concepts across organizations, moving them closer to semantic interoperability.
What must medical networks do to achieve semantic interoperability using FHIR?
-Medical networks must agree on common FHIR profiles to use in their systems, which will help standardize data definitions and bring them closer to achieving semantic interoperability.
Outlines
🔄 Achieving Syntactic and Semantic Interoperability in Healthcare
The paragraph discusses the ongoing challenge of achieving interoperability between various healthcare systems. It highlights the importance of syntactic interoperability, which involves the structure of data exchange but not its meaning, and is essential for systems to communicate effectively. The use of standards like HL7 V2 and FHIR is crucial for syntactic interoperability. However, the paragraph also emphasizes the need for semantic interoperability, where data has the same meaning across systems, eliminating the need for human interpretation and reducing discrepancies. The example of different systems describing a 'zebra' differently illustrates the challenge of achieving semantic interoperability. The FHIR standard's machine-readable nature is noted as a valuable aspect for sharing data concepts across organizations, which could help in achieving semantic interoperability.
Mindmap
Keywords
💡Interoperability
💡Syntactic Interoperability
💡HL7 V2
💡FHIR
💡Semantic Interoperability
💡Data Transformations
💡Healthcare IT Infrastructure
💡Human Decision-Making
💡Data Elements
💡Electronic Health Record Systems
💡Machine-Readable
Highlights
Achieving interoperability between healthcare systems is a constantly evolving challenge due to the variety of digital systems in medical facilities.
Interoperability can be categorized into two types: syntactic and semantic interoperability.
Syntactic interoperability allows systems to send and receive data in different formats, but does not define the meaning of the data.
HL7 V2 and FHIR are common standards that enable syntactic interoperability in healthcare.
HL7 V2 is the most widely used interoperability standard globally, with over one billion HL7 V2 messages exchanged daily.
InterSystems technologies are designed to improve interoperability between healthcare systems.
FHIR compatibility is now federally mandated for healthcare IT systems in many countries, signaling a shift toward standardization.
Syntactic interoperability alone is not sufficient; semantic interoperability is needed to ensure consistent data meaning across systems.
Semantic interoperability ensures that data from different systems has the same meaning and can be used within the workflow of the receiving system.
Discrepancies can arise when different systems define or describe the same data elements in varying ways, leading to potential miscommunication.
A real-world example involves documenting suspected lung cancer, where three different systems model the condition using different data elements.
Semantic interoperability focuses on establishing common meanings for data elements to avoid misinterpretation across systems.
A key challenge in healthcare IT is balancing efficient data schema setup for developers with accurate data entry for clinicians.
Achieving semantic interoperability is an ongoing effort requiring not just technological solutions but also human consensus.
The FHIR standard's machine-readable format and FHIR profiles help organizations share consistent data concepts, aiding in semantic interoperability.
Transcripts
Achieving interoperability between healthcare systems
is a constantly evolving challenge.
With dozens of digital systems at a given medical facility
and numerous facilities within a medical network,
the challenge of enabling systems to communicate
is significant.
Software products--including multiple InterSystems
technologies--have been built to improve interoperability
and facilitate these connections.
As we look more closely at the challenges of connecting
systems and facilities, we will distinguish
two types of interoperability: syntactic and semantic.
Syntactic interoperability--where
the structure of a message is defined,
but its meaning is not--makes it possible for systems to send
and receive data in different formats.
Without this, systems cannot communicate effectively.
For instance, System A sends and receives patient information
as HL7 V2 messages, and a patient-facing application
on System B uses a FHIR repository
with data represented in a JSON format.
As it stands, System A cannot contribute data to the FHIR
repository, and thus, the application on System B cannot
utilize that system's patient data.
A tried-and-true solution for this problem is to have
an intermediary system that transforms data from one format
to another--such as from the HL7 V2 format into the FHIR
format--via data transformations.
By creating such a mapping, we achieve
syntactic interoperability; that is, the two systems
have a standardized way of exchanging data.
The HL7 V2 and FHIR standards have paved the way
for syntactic interoperability, which
is critical to healthcare IT infrastructure.
HL7 V2 is the most used interoperability standard
in the world, with InterSystems technology
being used to exchange over one billion HL7 V2
messages each day.
And as we enter a future focused on FHIR,
consider that compatibility with the FHIR standard
is now federally mandated for healthcare IT
systems in many countries.
But syntactic interoperability, while critically important,
is not enough on its own.
Healthcare interoperability always depends
upon human decision-making; for example, an engineer
might determine how to set up a mapping for two health systems
that use different data formats to communicate.
As a result, discrepancies can arise across a chain
of mapped systems.
Achieving semantic interoperability
can help avoid some of these discrepancies.
With true semantic interoperability,
data from systems has the same meaning,
and can be used in the workflow of the receiving system.
Data elements are consistently defined,
and human interpretation is not required.
Imagine one system describing a zebra to another system.
In System A, the zebra is described as a white horse
with black stripes.
System B, meanwhile, defines a zebra
as a black horse with white stripes.
It's great that these systems can communicate clearly
with each other, and that this information can be transmitted
in an understandable language.
But how does each system know that they
are describing the same thing?
The ability to interpret nuanced language is one trait that
separates humans from machines .
Humans excel at disambiguating data like this,
and most humans could identify that the two animals described
are actually one and the same.
In the world of healthcare, there
are millions of zebras that systems need to describe,
and semantic interoperability requires an agreement
on which description to use.
Let's consider how this concept applies
to a real-world example from three
separate electronic health record systems.
Each clinician is documenting the same issue:
suspected lung cancer.
One system models this data as three different elements:
the health concern of cancer, the body site, lung,
and the status, suspected.
Another system may have a health concern of its own called
suspected cancer, leaving the body site--lung--to be
documented.
And yet another system may have suspected lung cancer
as a standalone entry for the clinician
to select as a health concern.
In the end, the data storage across the three systems
in this example would have only one element in common:
the body site of lung on systems #1 and #2.
Beyond that, there is no way for these systems
to determine, given the way this data is entered,
that the entries all mean the same thing.
Establishing common meaning is at the heart
of semantic interoperability.
As healthcare IT systems scale, the balancing act
becomes more challenging between efficient setup of data
schemas for IT developers and accurate data entry
for clinicians.
Achieving semantic interoperability will be a work
in progress for the foreseeable future that involves not just
technology, but also a certain level of human agreement--which
can go a long way.
One of the most valuable aspects of the FHIR standard
is that everything is machine-readable,
including FHIR profiles.
This makes it possible to share FHIR implementations of data
concepts across organizations.
And if medical networks can agree on the FHIR profiles
to use in their systems, they will
be one step closer to achieving semantic interoperability.
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