Industry View: Innovating our way through the healthcare data tsunami
Monday, 11 November 2019
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Picture: Dimitri Fane, director of product management for the InterSystems TrakCare® unified healthcare information system
Guest column by Dimitri Fane and Kathleen Aller, InterSystems

We need creative solutions to harness the incredible volume of patient health data now available so it can be used to serve up clinical insights in real time.
In the early days of computerised healthcare analytics, we were thrilled when summarised billing data and tabular reporting delivered insights, albeit fuzzy ones, into care processes, costs and opportunities for improvement. Even those blurry pictures strained computing capacity at the time, forcing us to rethink data management.
As healthcare information systems have become more sophisticated, along with greater storage and computing power, we’ve been able to measure and monitor care with greater clarity, leveraging ever more granular clinical data and better visualisations.
Now we face almost the opposite processing challenge. Computing capacity isn’t the issue any more. Rather, the rate at which we are collecting healthcare information is outstripping our ability to make sense of and act on it.
Health data collection accelerating
Meanwhile, the pace of healthcare data collection continues to accelerate well beyond that of other industries. There are a number of contributors to this growth.
- Most healthcare providers have now invested in electronic medical records. With the adoption of the more sophisticated operational and clinical decision-making capabilities of electronic medical record systems comes increasingly vast quantities of data.
- Standards for sharing information between EMR systems, such as HL7 and FHIR, facilitate interoperability, which drives information growth. SMART on FHIR also simplifies the creation of new innovative apps for patients and carers that connect to the EMR, generating additional valuable new streams of patient data.
- Once upon a time, nurses and clinicians manually entered a few observational data points during a consultation or treatment. Now embedded wireless capabilities are becoming ubiquitous within medical diagnostic devices. Bedside and wearable devices can efficiently upload data directly to the EMR. As a result, each patient now has thousands of high quality clinical observations from each care episode.
- Patient wearables and home devices can often contribute data in ways that were not practical even a few years ago.
More data doesn’t always mean better care
The problem is that simply having more data doesn’t necessarily lead to better clinical information. In a 2011 paper, Stead et al pointed out that we already have far too many data points available for clinical decisions than the human mind can process for a single decision.
For health IT to empower revolutionary healthcare transformation, it will require that creative innovators harness this incredible volume of big health data now available and create solutions that serve up clinical insights in real time in intelligent workflows and via multiple communication channels.
Our experiences outside the healthcare industry have given us a vision of what’s possible. Smart devices have changed our daily lives, increasing our expectations of information accessibility. It is now easy to fall into the habit of expecting detailed information to be readily available at our fingertips, at any moment.
Shift to point-of-care data collection
From a healthcare perspective, the same enabling technologies now put us in a position to actually follow through on that expectation. Thus healthcare providers are increasingly capturing patient information at the point of care.
The latest generation of tools allow clinicians to use mobile phones and tablets to directly record and access EMR data with just a few taps and swipes. Clinicians can also use their device’s camera to securely capture clinical images or documents without interrupting their workflows.
Decision-support logic based on artificial intelligence and machine learning can now automatically scan EMR data, to look for patient anomalies, and automatically alert clinicians when a patient’s health is deteriorating or deviates from normal parameters. Frequent automated upload of observations means that changes in a patient’s condition can be detected much faster and brought to the attention of clinicians in a timely and meaningful fashion.
Clinical studies have proven that early interventions can significantly improve clinical outcomes and lead to dramatic reductions in the overall cost of patient care. The impending tsunami of clinical data is likely to help healthcare providers do both. When patients require treatment, richer information will be immediately available to help clinicians determine the best path forward. And that means better outcomes for patients at a lower cost.
Ultimately, healthcare information systems will be even more intuitive than our smart devices are today. The tools to achieve this are now available. All we need is innovation.
Dimitri Fane is director of product management for the InterSystems TrakCare® unified healthcare information system. Kathleen Aller is director of healthcare market strategy at InterSystems.
If you want to contact eHealthNews.nz regarding this View, please email the editor Rebecca McBeth.
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