Five Data Management Questions for MedTech Leaders
By Andrew Aho, Regional Director of Data Platforms, InterSystems ANZ
Healthcare is awash in data – medical device data, electronic patient records, public-health surveillance data, clinical data, wearable data and more. By transforming it into meaningful and actionable information, MedTech companies can move up the value chain and gain a competitive advantage in a global digital health market projected to reach $US1 trillion by 2032.
However, digital health poses data management challenges. Interoperability barriers, scalability constraints and data privacy concerns can slow development and revenue growth.
Is your organisation prepared? Do you have the right development platforms, frameworks and tools in place? A new InterSystems White Paper poses five key data management questions to help assess your readiness and explains how a digital health development platform can help streamline development and accelerate returns.
Generate Additional Revenue Streams from Your Data
Digital health development platforms make it easy to collect and manage data and derive business value. This can open up new opportunities and improve business performance by introducing subscription-based, data-driven services that generate recurring revenue streams. For example, a lab management software provider found they could monetise operational data by offering a benchmark data subscription.
Another leading medical device manufacturer uses InterSystems IRIS for Health™ to gather and analyse device data at speed and scale. The solution transforms device performance data, patient-reported outcomes and other data into a common FHIR format for analysis. The solution’s built-in analytics repository helps the manufacturer eliminate expense and complexity, and accelerate time-to-market.
The solution provides evidence of device compliance to regulators, improves visibility into population health data, and helps patients better manage diseases and detect early warning signs. Unlike other approaches, the solution does not copy the data; it projects FHIR into SQL tables, which greatly reduces the cost of the solution and makes data available in real time.
Five Key Data Management Questions for MedTech
- Does your strategy include interoperability, data governance and analytics?
Digital health solutions access, manage, and analyse confidential healthcare data from disparate systems. Does your digital health strategy address interoperability, data governance, and analytics? How will you support diverse healthcare systems, safeguard protected health information (PHI) and analyse large datasets?
Digital health development platforms can connect to disparate systems and break down interoperability barriers. They also help you improve governance and compliance with privacy regulations by controlling access to PHI and encrypting data-at-rest and data-in-transit. Some platforms also include frameworks to efficiently analyse data so you can increase differentiation with value-added solutions that transform raw data into valuable insights.
- Can you connect device and clinical data from healthcare systems?
Integration issues can delay products, hamper customer deployments and impair business results. Do you have a strategy for interconnecting divergent systems and interworking dissimilar healthcare protocols and data formats?
Digital health development platforms support different data formats and standards, such as HL7® FHIR®, HL7® v2, C-CDA and IHE. Leading platforms provide built-in data transformations for common healthcare data standards and graphical user interfaces to simplify integration and free up technical resources.
Some include enterprise-class FHIR servers and other utilities that efficiently manage data and help develop applications based on the FHIR interoperability standard. Unlike previous standards, FHIR lets you easily build innovative applications incorporating diverse healthcare data from different sources.
- Can you easily consume and aggregate data in any format in real time, at scale?
Digital health solutions typically gather and process high volumes of real-time data from multiple sources. Data management platform capacity and scalability limitations can degrade application performance and impact functionality. Can your solutions meet stringent digital health price-performance and scalability requirements? Can you easily aggregate and act upon large, diverse datasets in real time?
Digital health development platforms efficiently and cost-effectively consume and aggregate diverse, real-time data at scale. Many are delivered as cloud-hosted services. This can accelerate time to market and improve margins by avoiding up-front capital equipment expenses, reducing infrastructure operations cost and complexity, and aligning recurring expenses with business demands and capacity requirements.
- Do you have one information system that can supply unified data from all sources?
Digital health application data is often scattered across systems and stored in different formats. Is a fragmented data architecture holding you back? Do you have a single information store that can supply unified data from all sources?
Digital health development platforms make collecting, harmonising and storing diverse data easy. You can create unified data records that improve data quality and consistency and provide a consolidated, holistic view of digital health information. This enhances efficiency, accuracy and effectiveness and lays the foundation for advanced analytics, artificial intelligence (AI) and machine learning (ML).
- Is your data AI-ready?
Many MedTech companies are looking to AI and ML to fuel the next wave of business growth. While AI can potentially transform healthcare, data management and integration challenges can impede development.
Many AI applications leverage data from diverse sources such as EMR systems, smart medical devices, hospital scheduling and billing systems, and public health databases. Data redundancies, inconsistencies and gaps can impact data quality and integrity and impair AI initiatives.
When building or deploying an AI-powered healthcare application, accessible, reliable and accurate data is critical. A digital health development platform can efficiently gather, unify and clean vast amounts of disparate healthcare data from diverse sources to prepare it for analysis or machine learning.
Finally, choosing the right vendor is as important as selecting the right platform. InterSystems has the knowledge, experience and tools to overcome the most complex data integration challenges and help you develop and deliver digital health applications quickly, easily and cost-effectively.
Whether you work for a medical device manufacturer, a life sciences company, a health IT vendor, a healthcare analytics company or other MedTech company, we can help you expand the market for your products, grow your customer base and increase sales by connecting to more systems and deriving business value from digital health data.
To learn more about InterSystems solutions for MedTech, please visit InterSystems.com/MedTech.
