The demand for medical devices is growing

By Julie Lockner, Global Data Platform Product Marketing, InterSystems

If you “follow the money” in the medical device and diagnostic industry, it’s very telling when over 90 venture capital firms are actively investing in the medical device field,¹ many of them reaching into connected-care applications startups.

As more medical devices come online, and more caregivers want to incorporate wearable data into treatment plans and medical records, more emphasis is being placed on device connectivity and data interoperability.

Even the American Medical Association (AMA) is taking an active role in seeding innovation in device interoperability. The AMA founded Health2047, an integrated innovation company, with one eye on “mobile as a platform to deliver care differently.”² In a recent interview, the CEO and Director of Health2047, Dr. Doug Given, commented that the next great thing in healthcare is “data integration and the solutions of ‘good hygiene,’ e.g., fixing the interoperability problem,” adding that interoperability will “open up entirely new innovation opportunities.”²

When providers want to incorporate device data into their EMR systems, the challenge goes beyond data integration and interoperability across devices; it’s about mapping that data to individual patients and their medical records. Hospitals don’t want to be in the business of maintaining device-specific code. They want to incorporate biometric data into medical records.

The challenge is to provide that interoperability layer between the device and an EMR system, and between EMR and the patient. Another challenge is to provide interoperability between inpatient and outpatient care, and between home and community-based care.

Startups like Validic, which raised $12.5 million in Series B funding last year, are well placed to give connected-care application developers a simplified path to interoperability. Validic integrates user-generated data from clinical in-home, wearable, and mobile health devices and applications through a cloud-based platform.³ As the number of device choices increases, leveraging this type of integration solution eliminates the number of application version iterations required.

Another example is Stanley Healthcare, which offers a real-time location solution (RTLS) platform that uses Wi-Fi sensors to track hospital assets.⁴ As the assets are moved, the hospital maintains full visibility into where items are located. Building on this Wi-Fi platform, they extended their solution to include capabilities like condition monitoring, such as temperature and humidity controls.

The next natural product evolution was looking at workflow of staff and patients. This could help people do their day-to-day jobs better while adding more value around efficiency and patient experience. Tracking patient flow added an entirely new level of complexity, because it involves individual patient data.

What type of information do they need to include? They were required to collect a significant number of data elements about patients. Patients, staff, and resources such as rooms and equipment all have attributes that need to be identified, integrated, and pushed into their mobile visibility platform. The platform has a real-time component that shares information such as how long patients have been waiting in a room, alerts a caregiver to visit the patient to improve patient experience, and potentially instructs the caregiver to move the patient to another room. In order to make this offering work, it required device and patient data interoperability.

Here is how it works: Caregivers wear a Wi-Fi badge so the system can track where caregivers are and how long they are with each patient. Patients are given a Wi-Fi badge when they are checked in, and their locations can be tracked. Wait times can be monitored, and if they are waiting too long the system can alert the closest caregiver to talk to that patient – ultimately improving the patient experience.

All of this data comes from multiple systems and is integrated with an analytics system that helps drive improvements. When the patient is checked out, a room is identified as “open,” driving improved workflow.

Correlating between a badge ID on a Wi-Fi device with the patient information takes time. By automating this correlation process, patients can go to a self-check-in kiosk and can scan the barcode from the check-in process with the Wi-Fi badge; the information can then be sent back to the patient healthcare record system. When clinicians and administrators pull up the patient record, they can accurately see where the patient is located in the EMR at any given time.

Now that the workflow is automatically captured, the data can be collected to conduct bottleneck analysis. Because the location data is based on real-time data collection, the accuracy of identifying bottlenecks is drastically increased. This is the type of data that can give analysts the ability to implement transformational change through advanced analytics.

The above are just a few examples of how innovations in medical devices are having a direct impact on improving patient experience and overall quality of care. This success is only driving an increasing need for continued innovation in the area of healthcare data interoperability.

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