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Patient-Centered AI Redefines Continuum of Care

predictive analytics in healthcare

Healthcare professionals have a singular mission: provide the best possible care for patients. But from admittance to discharge and everything in between, they face countless challenges.

Persistent staff shortages, constrained resources, and tight budgets are just a few. The greatest challenge is access to essential information about a patient’s condition throughout their hospital journey, specifically the second-by-second time series waveform data generated from the biomedical devices monitoring a patient. When seconds matter, how do hospitals harness this data and make it easily accessible to their healthcare teams?

Why Time Series Data Matters

The answer to this challenge is a single, open platform that continuously collects, processes, and unifies disparate data and presents it to clinicians in real time. Take, for example, an eight-hospital system in Houston that was confronting staffing issues and limited provider coverage—especially overnight. This forced difficult decisions, like hiring more travel nurses and physicians or turning patients away. All that changed when the organization implemented the Sickbay® Clinical platform, a vendor-neutral, software-based monitoring and analytics solution, from Medical Informatics Corp. (MIC).

The platform enables flexible care models and the #development and deployment of patient-centered #AI at scale on a single, interconnected architecture. @sickbayMIC via @insightdottech

Sickbay is an FDA-cleared, software-based clinical platform that can help hospitals standardize patient monitoring. The platform enables flexible care models and the development and deployment of patient-centered AI at scale on a single, interconnected architecture. Sickbay redefines the traditional approach of storage and access to static data contained in EMR systems and PACS imaging. The web-based architecture brings near real-time streaming and standardized retrospective data to care teams wherever they are to support a variety of workflows with the same integration. This includes embedded EMR reporting and monitoring data on PCs and mobile devices.

“Out of about 800,000 data points generated each hour for a single patient from bedside monitoring equipment, only about two dozen data points are available for clinical use,” says Craig Rusin, Chief Product & Innovation Officer and cofounder at MIC. It’s not widely known that alarms from non-networked devices such as ventilators outside of a patient’s room are difficult for staff to hear or view remotely. Similarly, current patient monitoring doesn’t use AI tools with the existing data to inform patient care.

Measuring the Impact

Hospitals and healthcare systems using Sickbay have redefined patient monitoring and have created a new standard of flexible, data-driven care by demonstrating the ability to:

  • Rapidly add bed and staff capacity while creating flexible virtual care models that go beyond traditional tele-sitting, admit, and discharge.
  • Provide more near real-time and retrospective data to staff already on unit, on service, or on call to improve their workflows and delivery of care.
  • Create virtual nursing stations where one nurse can monitor 50+ patients on a single user interface across units and/or facilities.
  • Leverage the same infrastructure to create virtual command centers that monitor patients across the continuum of care.

No matter the method of deployment, Sickbay gives control back to healthcare teams and provides direct benefit back to the hospital. Benefits reported include reduced labor, capital, and annual maintenance costs as well as improved staff, patient, and family satisfaction. Most important, clients using Sickbay see direct impact on improvements in quality of care and outcomes, including reductions in length of stay, code blue events, ICU transfers, time on vent, time for dual sign-off, and time to treat.

Results such as these provide the pathway for other hospitals to rethink patient monitoring and realize the vision of near real-time, patient-centered AI. Healthcare leaders have proven that going back to team-based nursing by adding virtual staff can help reverse the staffing crisis. “This isn’t about taking nurses away from patients. This is about taking some of the tasks and centralizing them,” says Rusin. “There will never be enough nurses, physicians, and respiratory therapists to cover all of the demand required for the foreseeable future. We need to get bedside teams back to bedside care. Flexible, virtual care support makes that a reality.”

Changing the Economics of Care

Sickbay provides the ability to change the economics of monitoring patients and directly impact improvement in quality and outcomes.

The ability to integrate with different devices, regardless of function or brand, is the key. “We have created an environment that allows our healers to get access to data they have never had before and build content on top of that, in an economically viable way that has never been achieved,” Rusin says.

For healthcare providers, having the data available is game-changing, says MIC EVP of Strategic Market Engagement, Heather Hitchcock. As one doctor commented: “In a single minute, I have to process 300 data points. No machine is ever going to make a decision for me, but Sickbay helps me process that data faster so I can make the right decision and save more lives.”

From Scalable Patient Monitoring to Predictive Analytics

Sickbay’s value extends beyond near real-time patient monitoring and virtual care to long-term treatment improvements. Sickbay supports the ability to leverage the same data to develop and deploy predictive analytics to help get ahead of deterioration and risk.

Clients currently and continuously develop analytics on Sickbay. For example, one client integrates 32 near real-time, multimodal risk scores into its virtual care workflow. Another client created a Sickbay algorithm that analyzes data generated by two separate monitoring devices to determine ideal blood pressure levels in patients. “The particular analytic requires the blood pressure waveform from a bedside monitor and a measure of cerebral blood density from a different monitor,” says Rusin.

Saving Lives with Data

Treatment of patients across the care continuum today will lead to improved care tomorrow. To do that, reliable, specific data is the very starting block. Without it, clinicians are left to their best guesses to solve the body’s most urgent care needs without the data-driven decision-making support they desire. That’s slow, costly, unfair to caregivers, and ultimately not providing the best benefit for the patient.

To truly realize a future where treatment is as specific and individual as the person it serves, healthcare must harness patient data in a way that is most impactful—specific, accurate, near real-time, vendor-agnostic, transformable, and instantly accessible. Leveraging the power of time series data empowers healthcare providers to help more people than it ever has before, and more effectively. After all, saving lives is healthcare’s primary mission.

Edited by Georganne Benesch, Editorial Director for

About the Author

Pedro Pereira has covered technology for a quarter century. He has freelanced for some of the biggest names in IT publishing and an extensive list of marketing agencies and technology vendors. He was a pioneer in covering managed services and cloud computing, and currently writes about cybersecurity, IoT, cloud, and space. He holds a degree in Journalism from UMass/Amherst.

Profile Photo of Pedro Pereira