Despite the growth of the MedTech sector, one question continues to arise – why do so many companies struggle to make their data interoperable with other health devices and systems?
Research conducted by InterSystems among MedTech companies in the UK and Ireland has highlighted a consensus that interoperability is the future, with 100% of respondents saying they have a strategy and vision for interoperability.
However, the research also shows that realising that vision is hard because it requires a new skillset; and these difficulties are amplified by shortages of data talent.
In the research, 74% of organisations admitted they struggle to utilise healthcare standards to make data interoperable.
More than a third of companies (35%) lack sufficient in-house skills; and almost as many (34%) find obtaining data that is usable is still a significant problem.
Understanding the problem
These are major barriers for MedTech organisations.
Advances in technology are driving innovation in MedTech, resulting in an increasing number of connected medical devices that generate, collect, analyse, and transmit data.
And these emerging solutions offer the potential to address some of the cost, access, and care coordination challenges facing health care.
However, a lack of interoperability can lead to an incomplete understanding of an individual’s or a population’s health needs, thereby contributing to poorer outcomes and higher costs.
As life expectancy increases around the world and healthcare costs continue to spiral, interoperability and data sharing will become increasingly critical for delivering effective healthcare.
So, a data-driven enterprise business model, combining and using data from disparate sources, has never been more critical for a MedTech company’s success.
Data should meet evolving standards
Interoperability standards like HL7 FHIR (Fast Healthcare Interoperability Resources), are proving a boon to interoperability by facilitating the seamless flow of data, ensuring it is understood the same way from start to finish by systems and people.
A lack of interoperability can lead to an incomplete understanding of an individual’s or a population’s health needs, thereby contributing to poorer outcomes and higher costs
Nevertheless, there remains an abundance of legacy and customised healthcare systems in use whose data can be hard to convert to a standard format or shared with others.
With healthcare budgets coming under pressure and IT departments required to maximise the return on existing investments, many such legacy systems will remain in place for the foreseeable future.
Some of the third-party data a new solution needs may only comply with legacy data standards.
And the challenge grows each day as the volume of data grows.
Given the skills shortage, MedTech companies need to partner with a vendor that has deep, proven understanding and expertise in healthcare interoperability standards.
Routes to market
To resolve interoperability challenges, MedTech organisations may well opt for laborious point-to-point solutions, which are not scalable, or they may employ standalone solutions.
It would be wrong to generalise in this area, as business and clinical aims and internal capabilities differ between MedTech companies, as does understanding of data requirements imposed by the European Medicines Agency, MHRA, or US Food and Drug Administration.
Yet, if a regulated device does not comply with the regulatory requirements, it cannot be brought to market.
But there is clearly a problem here.
A MedTech company may use a third-party software platform to collect, prepare, and manage data.
In the research, however, nearly three-in-ten companies surveyed in the UK (30%), and more than a fifth surveyed in Ireland (22%), admitted their current data platform does not facilitate interoperability with healthcare data standards.
Given the skills shortage, MedTech companies need to partner with a vendor that has deep, proven understanding and expertise in healthcare interoperability standards
This is not surprising, as many MedTechs have chosen to work with general, all-purpose data platforms – rather than one that is specifically designed to extract value from healthcare data.
An average of 28% of MedTech companies in the two countries still find it difficult to find the time to clean and organise their data to render it useable.
Single platform advances in data management
MedTechs are at the gateway to a great opportunity. Yet, to avoid being felled by interoperability and data challenges, they need to fully assess whether their data strategy enables them to connect with device and clinical data from EMRs and other systems.
To deliver their interoperability vision, MedTech companies need high-quality and trustworthy data and this is possible with the right underlying infrastructure and data management platforms in place. Such a platform must have, or be able to:
- Aggregate data across the healthcare ecosystem regardless of data format
- Provide deep support for all major healthcare interoperability standards, including HL7 FHIR
- Deliver high-speed, multi-model data management
- Support natural language processing (to deal with unstructured data)
- Make it easy-to-develop and deploy Machine Learning (ML) solutions by providing tools that enable developers – with little-to-no ML - knowledge to use SQL to develop sophisticated ML models
Given the complexity of data-types, standards, and growing volumes, interoperability is always going to be a challenge for MedTechs unless they embrace advances in data management, preparation, and analytics by using a single comprehensive platform.
Simplification and automation are essential elements in this, which is what data platforms purpose built for the health sector provide.
Interoperability is always going to be a challenge for MedTechs unless they embrace advances in data management, preparation, and analytics by using a single comprehensive platform
Rather than scrambling for point solutions, or seeking to recruit highly-skilled data wranglers, who are in short supply; MedTechs adopting a single platform approach will almost immediately gain the robust connectivity, data management, and interoperability they need.
And this will enable them to achieve scalability, clinical acceptance, and potentially-huge commercial success in a rapidly-expanding global market.
