Digital health continues to be a work in progress, but there have been some great developments in recent years. For example, the introduction of electronic health records (EHR) has greatly improved the collection, access and analysis of medical data for both physicians and patients. Cloud-based information systems have been a major contributor in driving this EHR adoption in both large and small institutions. However, there remain many areas of healthcare data handling and record keeping where system improvements are desperately needed.

The COVID-19 pandemic has highlighted the current inefficiencies in easily managing data exchange and analysis. With the associated rapid growth of decentralized testing locations, the ability for quick data access and analysis is more important than ever before.

• Focus on a minimum instrument hardware configuration that executes the assay workflow
• Everything peripheral to that, non-essential device elements, such as user management, data analysis and storage, Laboratory Information System (LIS) interfaces, are offloaded to the cloud and remove the need for complex user interfaces on the POC device.
• By moving user interactions to the cloud, both the device footprint and cost can be reduced. For example, our estimates show this can transition a device from a stand-alone configuration with a $2,200 to $2,500 COGS range to a cloud-enabled version with $1,500 to $1,800 of associated COGs.
• Adopting a cloud solution can also minimize development costs and the time needed to get the device to market.

• Identify those device software elements that could be characterized as “common” – more standardized or generally used.
• Leverage preexisting cloud functionality to replace those common elements and serve as part of the device software componentry – data management, user management, analyses and secure storage.
• Using this common IT infrastructure can pull expensive de novo software development out of the project as well as shorten timelines.
• Continued reuse of this framework across the product portfolio and instrument next generations can also speed up future product development and enable a consistent user experience.

• Utilizing a consistent cloud-based IT framework across a company’s full spectrum of products allows for broad data aggregation and mining, following the general IT rule “ABCD – Always Be Collecting Data”.
• Leveraging this data repository in conjunction with cloud computing capabilities can transition a device from a typically simple POC instrument to one with fairly sophisticated applications.
• There are varying levels of device data collection and analysis options from which to choose – from basic device monitoring all the way to complete autonomy:
  • Monitoring, with one-way collection of performance data such as device condition, operation and usage. Collecting this type of information across different instruments can provide insights not only for field service personnel, but also for marketing and product development functions in driving product improvements.
  • Control, where there is both data collection and connectivity to centrally push out device updates including firmware upgrades, calibration information or a new assay menu.
  • Optimization, that builds on data collection combined with two-way communication. Analytical tools and machine learning algorithms can be applied to extract additional value from this infrastructure, such as enhanced product performance and improved service support. One example is predictive device diagnostics and field service using historic data collected across an entire fleet, including types of instrumentation issues, alerts and alarms and device service records, to drive proactive service and repairs.
  • Autonomy, taking optimization to the next level with autonomous product operation. While not yet mainstream for POC device fleets, the Apple Watch is an example of what an autonomous IVD product might look like in the near future. The Watch collects electrocardiogram (ECG) waveforms to identify certain heart rate conditions such as atrial fibrillation and provide alerts to the wearer and that person’s cardiologist. Such autonomous operation and self-coordination with other products and systems can be expected in POC devices going forward.

The widespread adoption of cloud-based platforms over the last five years into daily life has been a driver in developing solutions that address both diagnostic instrument utilization issues and risk mitigation needs.

Healthcare data security concerns around EHR and patient privacy, once a hurdle in medical device use, have been addressed over the course of adapting these systems for general consumer shopping and financial applications.

Amazon, Google and Microsoft along with other large cloud organizations have all created high degrees of security on a global scale. In addition, all communication between devices and the cloud can be fully encrypted and traceable via unique identifiers. The question of how to connect individual devices with the cloud has also been answered. There is a wide range of connectivity solutions available, from wired to wireless.