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Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity

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Read more about author Jeff Robbins.

In the healthcare industry, surgical capacity management is one of the biggest issues organizations face. Hospitals and surgery centers must be efficient in handling their resources. The margins are too small for waste, and there are too many patients in need of care. Data, particularly real-time data, is an essential asset. But it is only useful if the pieces fit together, solving a puzzle of coordinating schedules, operating room availability, and resource allocation, while ensuring immediate access to patient data for perioperative teams.

Data management demands are significant, complex, and dynamic. Because each patient is unique, anything can happen in an operating room (OR) at any moment. As such, real-time data capture is crucial for surgical workflows. When surgical teams have all the information they need in real time, they can make rapid decisions that not only maximize OR utilization and minimize delays but also enhance overall patient care and safety.

Data Management Integration Challenges

When data management goes right, it is a win for everyone. The hospital or surgery center fully leverages its facilities, earning maximum revenue to keep the surgical engine running smoothly; surgical teams have the tools and information they need to successfully execute the procedures they are assigned; and patients have a seamless experience that minimizes stress and promotes positive outcomes. The problem is many hospitals and surgery centers lack the ability to pull all the data they need into a single system, let alone in real time.

Data management classically partitions transactional or operational data from analytics data. The very term “extract, transform, and load” (ETL) speaks to this bifurcation. In healthcare, the electronic health record (EHR) is typically the operational data system. The EHR is the source for this ETL process, but EHRs, as we’ve typically viewed them, now must incorporate and manage additional information. Data from a patient’s medical history, lab results, and imaging are vitally important. The patient’s insurance data or data from other third-party providers must also be taken into account. Then, OR-specific data must be considered – how long certain procedures typically last, what kind of differences there are between providers, and which instruments or robots are needed in a given room for a given surgery. Systems don’t work as well as they could if this wide assortment of data points is not integrated into a single system from which insights, predictions, and recommendations can be extracted.

Because the data sources live in different applications, seamless integration remains a significant challenge, hindering the application of modern tools. For example, today’s sophisticated analytics and AI solutions become somewhat like driving solely with a rear-view mirror due to the latencies involved. Yet, continuing with the driving metaphor, a high-performance surgery department (and, by extension, all hospital departments) requires information about the road immediately and further ahead. So, how do we reconcile the existing gap?

Real-Time System of Engagement

A system of engagement is required. Such systems, which are available on the market today, provide the augmented data view necessary to enhance a surgical team’s situational awareness. They give teams access to the data they need at the moment to make the best decisions possible when lives are on the line. They also ensure that surgeries run smoothly.

So, what are the crucial components of a system of engagement? In addition to ETL processes, modern systems of engagement leverage innovative approaches to do two things:

  1. Safely and efficiently instrument the EHR to provide the latest possible information captured by the team.
  1. Instrument the process itself, using a variety of sensors and input devices to make it easier for the team to use, either actively or even passively, while engaged in surgery.

When done properly, these two approaches work together and enhance process instrumentation, providing that forward-looking view of “where are we now, and where do we need to be?” This approach also intelligently updates the EHR, preserving its role as the system of record in critical team workflows, institutional risk management, and governance. Systems of engagement also deliver more accurate time-stamped events and data for traditional ETL consumption.

Crucially, AI and analytics become far more useful by integrating real-time data. Issues can be spotted, crises averted, timelines updated, and more.

By addressing data management and integration issues with real-time data management systems, teams have the information they need to do their jobs better. With such systems in place, hospitals, surgery centers, their teams, and their patients will thrive.