Interoperability in Healthcare: How Medical Device Integration is Helping Tear Down Those Walls

True interoperability in healthcare remains elusive. For more than a decade, it's been called the "Holy Grail" only partly in jest. Much has changed over the years, but the quest continues. The COVID-19 pandemic made this quest all the more pressing: with increasingly sophisticated devices generating more data, the need for interoperability—and the need to integrate that data—has never been more urgent. This is why hospitals require medical device integration (MDI).

MDI solutions can streamline workflows and support patients across the care continuum, which can improve outcomes, enhance patient safety, and make hospital operations more efficient.

Integrated Patient Data Eases Administrative Burdens

MDI captures data from devices and populates electronic medical records (EMR) automatically. Physicians have complete, up-to-the-minute patient data from an array of sources—not only from the lab and bedside monitors, but also from wearables and at-home monitors. This more complete array of data allows them to make evidence-based decisions more quickly.

It also improves the care nurses can provide. By reducing the nurses' administrative workload, MDI frees them to devote more time to the hands-on medical care they're trained to do. Moreover, because medical assistants and other support staff don't have to key in the data manually, the chances of data-entry error decrease.

For successful integration to happen, the data must flow freely: medical devices, platforms, and software must communicate and cooperate with each other.1 Only then do clinicians have seamless access to the continuous data provided by devices to the EMR. However, much work needs to be done to improve the automation that supports interoperability in healthcare.

How an Interoperable MDI Solution Connects Devices and EMRs

Diagnostic and monitoring devices yield tremendous amounts of data. But too often, these medical devices don't "talk" to each other or to the hospital EMR. The result is disparate, siloed data. Clinicians who are already suffering from data overload don't benefit from having large amounts of fragmented data that's hard to access. They need aggregated, synchronized data that yields actionable information.

MDI connects data from previously disconnected devices to the EMR, as well as other systems and applications so that it is shareable across care teams. What's more, it provides only the information they need, eliminating data overload. This only happens when the apps, devices, and EMRs involved are compatible.

With devices from a multitude of vendors, hospitals need an interoperable MDI solution that converts medical device data into formats that the EMR can consume and synthesize. These formats are most often the Integrating the Healthcare Enterprise (IHE) Patient Care Device (PCD) profile and HL7 messaging standards, the set of international standards used to share health and medical data.

Improving Efficiency and Timely Response At Bedside or Remotely

Data integration provides a powerful way to improve patient care for individual patients and patient populations. It improves cross-team collaboration and support, streamlining care and allowing clinicians to better meet patients' needs.2 By leveraging MDI, virtual hospitals could unlock powerful insights about patients, patient populations, and their own clinical processes.

MDI can provide the necessary data to enable clinical surveillance systems that can help improve efficiency, decrease variation, and increase the quality of care by providing a near-real-time view of each patient's status in the hospital and across a multi-campus health system. MDI also feeds data into early warning score systems. The scores are calculated based on an array of vital signs and other relevant data. If the score indicates a patient's condition is worsening, clinicians can immediately assess the patient and determine the next steps, without having to cross-check multiple sources. This approach also allows health systems to apply rule-based clinical decision support tools to help assess patient conditions and administer more effective treatment.

MDI solutions can enable applications that allow clinicians to look at patients based on the department, the patient population, the clinical condition, and more – and can be scaled for both small and large facilities. Even for hospitals that provide data from medical devices into the EMR, many devices can remain disconnected (e.g. IV Pumps and Ventilators). MDI can help close the gap from these non-networked devices by digitizing relevant data (i.e. numeric values, alarms, and waveforms).

As such, clinicians can see what's happening at the patient level using the holistic view of specific patient records and at the population level across various patient types. Population-level insights can lead to system-wide improvements in clinical care and workflow.

Having a more complete patient picture can help improve care in specific ways as well. For instance, the ability to quickly aggregate data from lung X-rays and CT scans can lead to faster detection of COVID-19.3

The Future is Bright for MDI

Interoperability in healthcare has remained elusive because data is scattered, fragmented, and inaccessible. Unfortunately, greater advances in diagnostics and monitoring technology sometimes mean only building more sources of disparate data of much higher fidelity than before.

Medical device integration moves hospitals to the next level, freeing clinical staff to do what they were trained to do and allowing hospitals to reduce variations, become more efficient, and improve financial and clinical outcomes.

It's time to stop questing and start implementing. Tear down those walls.

 

REFERENCES
  1. The Future of the ICU? How Clinical Decision Support Is Advancing Care. HIT Consultant. hitconsultant.net/2020/10/19/future-icu-clinical-decision-support-advancing-care. Last accessed July 2021.
  2. Clinical Surveillance, A Concept Analysis: Leveraging Real-Time Data and Advanced Analytics to Anticipate Patient Deterioration. Bringing Theory in Practice. Online Journal of Nursing Informatics. www.himss.org/resources/clinical-surveillance-concept-analysis-leveraging-real-time-data-and-advanced-analytics-anticipate. Last accessed July 2021.
  3. How the Intelligence-Based Health System Will Become Critical to Meet Patient Needs Today and Post-Covid-19. MedCity News. https://medcitynews.com/2020/09/how-the-intelligence-based-health-system-will-become-critical-to-meet-patient-needs-today-and-post-covid-19/. Last accessed July 2021.