542 - Improving Healthcare Systems: Using Structured Data to Enhance Quality and Safety
In a healthcare landscape obsessed with the next big thing, structured data quietly holds the keys to safer care, smarter systems, and real innovation. Often overlooked, this unassuming foundation shapes everything from clinical decisions to hospital operations, and understanding its power is essential for any healthcare provider serious about the future of digital health.
In this episode of Talking HealthTech, Peter Birch speaks with Viti Handyside , ANZ Country Product Manager for ORBIS at Dedalus , and Dennis Rausch , Chief Medical Officer at Dedalus . Together, they explore the importance and benefits of structured data in health IT, highlighting how structured data improves patient care, drives operational efficiency, and enables innovation. The discussion covers the evolving needs of clinicians, the challenges in implementing structured data, and the role of emerging technologies such as AI, voice recognition, and digital twins.
Structured Data: The Underrated Powerhouse of Digital Healthcare
Healthcare is going through a major digital transformation, where the quality and organisation of information can shape outcomes for clinicians and patients alike. While the spotlight often falls on AI, wearables, and flashy tech, structured data is the quieter force working behind the scenes to drive meaningful change.
This episode of Talking HealthTech explores why structured data, cleanly organised, coded, and machine-readable information, is not just a back-office concern, but a critical ingredient for better clinical care, operational efficiency, and all those high-tech promises the sector keeps making. Drawing on global experience, product leadership, and clinical insights, the discussion outlines both the value and messy reality of getting structured data right.
Understanding the Value of Structured Data in Digital Healthcare
At first glance, structured data might seem like a matter for administrators and data analysts: neat boxes in forms, ticked checklists, or drop-down menus. It’s often seen as the opposite of flexible, narrative “free text”, where clinicians jot down thoughts as they would on paper.
On the contrary, this isn’t just a technical detail. Structured data is what makes digital health systems actually work. Without it, automation breaks down, reports lose accuracy, and clinical decision tools become hard to trust. As Dr Dennis Rausch, Chief Medical Officer at Dedalus, puts it:
“The main magic actually is that it allows the machine to understand what has happened… You need good input data to get good output.”
Structured data plays a big role delivering safer care on a day-to-day basis. Features like diagnosis suggestions, medication alerts, and quick population health reports all depend on having clean, well-organised information. When a system catches a dangerous drug interaction, it’s usually because the right data was in place to begin with.
“If we get the structured data right, there are multiple benefits for the system and various stakeholders.” says Viti Handyside, ANZ Country Product Manager for Dedalus’ Orbis platform.
Beyond direct care, hospitals and health systems benefit from structured data in essential ways, like more accurate billing, compliance with safety standards, easier communication across teams, and efficient resource allocation.
The Trouble with Free Text and Unstructured Data
Today, a majority of clinical information is still recorded as free text. A patient admitted with chest pain may have a succinct note that makes sense to a human:
“Patient is admitted with acute chest pain. He has a hx of COPD, asthma, and HTN. The pt is on Lisinopril, Celebrex, Amitriptyline and Prednison. MS. He also had a previous MI 3 years ago. Reports occasional SOB and mild dyspnoea with exertion. LFT normal. No known drug allergies.”
But for software, or any future use of this data, such a note may be ambiguous and cause misunderstandings. “What does MS mean? Magnesium sulfate? Multiple sclerosis?” asks Dr Dennis, highlighting the risks.
“LFT” could be a lung or liver function test. Errors in medication names, laboratory test orders, and treatment plans among others are likely. The non-standard abbreviations and the context-specific language make it hard to extract meaning consistently.
This ambiguity doesn’t just slow things down. It can lead to dangerous errors, missed trends, or outright useless data when the time comes to aggregate information for research, funding, or large-scale public health work.
Fixing the Disconnect Between Clinicians and Structured Data
If structured data is so important, why do so many clinicians skip it or enter just the basics? The answer often comes down to practicality. Most health IT systems require users to navigate long and complicated forms filled with mandatory fields that rarely match the way clinicians actually work.
“It’s not fun to enter a detailed and structured data set into a screen that has been built with, let’s say, 50 different boxes,” Dr Dennis admits.
When things get busy, clinicians do what they need to keep things moving, and speed often takes precedence over completeness. They learn the quickest way to get past the system, even if that means using vague shortcuts or dropping everything into a free text box just to get on with patient care.
“People almost rote learn how to go like cancel, cancel, cancel or put a dot in this field.” says Viti.
The solution isn’t to force more fields or stricter validation, but to build systems that reflect how real-world clinicians think and work. Engaging clinical users early in design and embedding structured data into natural workflows is essential.
“If the structured data is embedded in the natural workflow, then it doesn’t feel like it’s an add-on, it doesn’t feel like it’s an extra task.” Viti notes.
Smart defaults, pre-filled information, and context-aware suggestions can make a huge difference. So can better communication about why the data matters. When clinicians understand how structured input improves patient safety, reduces duplication, or speeds up referrals, they’re more likely to engage with it.
Ultimately, making structured data easier to use isn’t just a design challenge; it’s a matter of building trust. Clinicians need to feel that the system is working with them, not against them. And when that happens, structured data stops feeling like a burden and starts becoming part of better care.
Balancing Structure with Flexibility
Deciding what to structure and what to leave as free text isn’t always straightforward. Not everything in a clinical note fits into a drop-down menu. More complex assessments, especially in areas like mental health, often need room for context, narrative, and a bit of storytelling. On the other hand, routine details like vital signs, medication lists, and discharge summaries are usually clearer and more useful when they follow a standard format.
“Conversational notes are great… But if you’re doing a nursing care plan or a discharge summary, it’s where we really need structured data in place so that we can capture the information that we need to share it downstream with other systems,” says Viti.
The best approach is often a mix of both. Clinicians should be able to speak or type naturally, while smart tools work in the background to pull out the important structured details. This not only saves time but also helps keep the data clean and useful.
Beyond Forms: How Smart EMRs Support Real-World Care
Health IT is developing away from rigid systems that try to control how people work. Instead, the focus is shifting toward smarter tools that adapt to the way clinicians think and practice. New-generation electronic medical records (EMRs) are helping close the gap between structured and unstructured data by using natural language processing and artificial intelligence to make sense of information without adding extra burden.
Ambient AI tools can listen in the background as clinicians work or consult with patients, pulling out diagnoses, medications, and vital findings without needing manual entry. Dennis sees promise here, but he’s pragmatic:
“AI is not everything… I’m quite sceptical about the proposition that AI will take over completely.”
Voice interfaces may be helpful in some settings, but they are not a one-size-fits-all solution. Clinicians still play the key role in reviewing and confirming what the system picks up. That said, the direction is clear. As more data becomes structured, EMRs can handle more of the workload, such as filling in forms with existing information, suggesting possible diagnoses, or identifying patients who may be eligible for clinical trials.
“It’s really about better understanding the context and the situation of the user. If you’re working with a system that doesn’t have any understanding of that, you will be very often confronted with stupid proposals,” says Dennis.
How Structured Data Improves Operations, Billing, and Safety
It's not just clinical insights that benefit from structured data. When hospitals can tag and track what’s really happening on the ground, they’re better equipped to manage staffing, anticipate patient flow, and cut down on repeated tests.
Billing becomes more accurate when coded diagnoses and procedures are fed through from the point of care. Fewer claims are denied due to inconsistent documentation. The same is true for regulatory compliance, risk management, and safety audits.
This is particularly relevant in jurisdictions like Australia, where the appetite for digital tools is strong but the digital maturity varies between regions and institutions.
“Before we start offering those sorts of [advanced AI] solutions, we make sure that they’re set up for success.” Viti emphasises.
Strong Foundations Make Smarter Systems
Even with all the excitement around smart tech, the basics still matter most. Getting things like data quality, structure, and usability right lays the groundwork for everything else. When those foundations are solid, the benefits start to flow: fewer mistakes, better teamwork between care providers, clearer insights into population health, simpler research processes, and more responsive healthcare systems.
Too often, digital tools are designed to patch over problems that came from paper-based workflows. But as Dennis points out, we might not need to keep working around those limitations anymore.
“A lot of the regulations, the procedures, processes, the systems, how they have been set up so far, have been set up with the shortcomings of paper and human work in mind. We have a lot of things that actually try to cope with those, let’s say, principal error sources and tediousness of working in such an environment, which might no longer be necessary in the future.”
By building better systems on strong data foundations, we’re not just keeping up with technology. We’re creating a healthcare environment that’s smarter, safer, and more efficient for everyone involved.
Making Data Work Harder So People Don’t Have To
When health IT systems are designed to support clinicians rather than slow them down, structured data stops feeling like an extra burden. Instead, it becomes a tool that helps make work easier, care safer, and teams more connected. Viti puts it plainly:
“We need to show them [clinicians] benefits and we need to show them those benefits early on so that they engage with it. So things like, you know, showing how structured data can decrease duplicate testing.”
If the industry gets this right, the vision is within reach. Picture digital health records that reflect real-life patient journeys, update automatically, and give clinicians meaningful insights instead of just more information.
The message is clear: For digital healthcare to truly deliver on its potential through smarter AI, personalised treatment, or better coordination of care, it needs a strong foundation of structured data. Putting in the effort now will make healthcare safer, more reliable, and more connected in the long run.
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