Medical Device Data's Transformational Potential

Digital technology is a top priority among health system and hospital leaders. According to a Deloitte survey, one-third of respondents cited technology investments as a critical focus for 2025.[i] This digital transformation across healthcare operations and clinical care has resulted in vast volumes of data, which continue to grow as manual processes transition to electronic systems.

While this data has the potential to optimize resources and help drive more effective treatments, a staggering 97 percent of it currently goes unused. Medical devices, a ubiquitous component of healthcare administration, contain untapped reservoirs of information. Although clinicians rely on the data displayed on devices for decision-making, deeper insights embedded within these devices often remain inaccessible.

Unlocking the power of medical device analytics

Harnessing medical device data offers immense potential for delivering actionable insights directly into clinicians' workflows. This capability is particularly critical in high-stakes environments such as operating rooms (ORs) and critical care units (ICUs, PICUs, NICUs), where patient conditions can change rapidly. Real-time, data-driven insights from diagnostic, therapeutic and monitoring devices can support clinicians in making informed decisions quickly.

Medical device analytics can be categorized into two primary areas:

1. Direct device data and analytics

• Basic usage: For example, a bedside monitor displays vital signs, including temperature, blood pressure, pulse rate and SpO2, offering straightforward insights to clinicians.
• Advanced analytics: ICU teams can analyze ventilator-generated data, such as spontaneous respiratory rates and tidal volumes, to assess a patient’s readiness to wean off mechanical ventilation. Similarly, anesthesia workstations can provide actionable insights into fresh gas flows and anesthetic agent uptake, helping clinicians optimize care during surgery.

2. Connected data sharing and combined insights

• Integrated analytics go beyond individual device data, bringing together information from various systems to deliver comprehensive insights. For example, an ICU team with access to ventilator data alongside electronic health record (EHR) and financial system data can use this integrated information in efforts to link early mobilization of patients to outcomes, length of stay and costs.

Overcoming challenges in device connectivity and integration

Despite the promise of digital health, achieving seamless integration of medical devices into clinical workflows remains challenging. Healthcare’s historical reliance on fragmented legacy IT systems, its stringent data privacy and security requirements, and limited human resources to overcome roadblocks to technological advancements create significant hurdles.

To address these challenges, medical device manufacturers and healthcare organizations should consider the following factors.

Integration and data-sharing

In research conducted by leading global professional services company Accenture, 61% of clinicians cited lack of interoperability between different IT systems as a key barrier to digital tool adoption.[ii]

Digitally-forward medical devices are designed for streamlined integration and data sharing with hospital IT systems, including EHR systems, and other technology solutions, including centralized data repositories and analytics tools. Clinicians can easily access data points, monitor trends and take a deep dive into specific parameters to make informed decisions on a patient’s course of care.

Advanced digital technologies are designed to facilitate the sourcing of patient data from multiple medical device types (e.g., patient monitors, ventilators, anesthesia machines) and the application of analytics tools helps provide clinicians a broader picture of the patient’s health status.

Secure connectivity

Given the increased incidence of cyberattacks on U.S. health systems and hospitals, with many targeting patient data, medical device manufacturers must design for secure device connectivity and data-sharing.

Secure design features include:

·       Compliance to ISO 270001 risk management standards

·       Implementation of NIST 800-63 standards for secure credentialing

·       Encryption of all data in transit and at rest

·       Role-based access control and strict authentication protocols

Real-time, actionable insights

A recent HIMSS State and Future of Healthcare Clinician Survey revealed that 39 percent of clinicians didn’t believe digital health tools are effectively integrated into their workflows.

Device interoperability, data sharing and the application of analytics should be aimed at integrating actionable insights into clinical workflows. Medical devices and connected solutions should feature intuitive, easy to use interfaces that present clinicians with relevant and timely analytics. Clinicians shouldn’t be tasked with searching for answers; rather, the information should be presented to them when and where they need it.

Digitally-forward medical devices also support clinical teams in harnessing the power of historical insights and trends. Devices designed for cloud-based capture of usage and performance data across patient populations, clinical settings and procedures can help establish the foundational data set required for artificial intelligence (AI) algorithm training and insights generation.

In a recent survey by McKinsey & Company and the American Nurses Foundation, 64 percent of nurses said they would like to see more AI tools incorporated into their work.

Practical applications of medical device analytics

Hospitals and health systems can achieve significant benefits by adopting digitally forward medical devices. Below are five examples of how acute care clinicians are leveraging device analytics:

1.      OR readiness

The OR is the revenue generating engine of most hospitals; therefore, it is critical to keep equipment running effectively so surgical cases proceed on schedule. This includes anesthesia machines, which are a vital technology component for many surgical procedures.

Intelligent anesthesia machines that transmit live data on their readiness status via the cloud to a centralized anesthesia/OR workstation provide OR teams with insights to help quickly surface and address issues that could delay case starts.

2.      Anesthetic gas costs and environmental impact

U.S. hospitals, faced with cost constraints and pressures to reduce their environmental footprints, have targeted anesthesia as a focus to address both challenges.[iii] Anesthesia machines featuring integrated gas consumption analytics help support these efforts by providing anesthesia providers transparency into anesthetic gas consumption, uptake, efficiency, cost and applied fresh gas flows.

For example, the combination of data analytics and low-flow anesthesia technologies enabled Lexington Medical Center in Columbia, South Carolina to achieve hospital-wide savings of over $100,000 per year for anesthetic gases. With lower emissions of climate-damaging anesthetic gases, the hospital is also making a significant contribution to climate protection.[iv]

3.      Compliance with lung protective ventilation protocols

Lung protective ventilation practices during anesthesia are known to reduce the incidence of post-operative pulmonary complications, which are associated with negative outcomes, longer length of stay and increased cost of care.

Applying analytics to data generated by a hospital’s fleet of anesthesia machines, an anesthesia team can benchmark their ventilation performance against pre-defined goals to help achieve a high standard of lung protective ventilation therapy for patients undergoing surgical procedures.

4.      Alarm management

Again for 2025, The Joint Commission (TJC) named alarm management as one of its Hospital National Patient Safety Goals (NPSG), urging hospitals to “Reduce patient harm associated with clinical alarm systems.”[v]

Clinicians can leverage alarm history analytics to gain insights into alarms from medical devices that have occurred in an acute care environment. With this information, they can work to optimize systematic process flows and staff planning and improve alarm management efficiency. By identifying the sources of recurring alarms, clinicians can take measures to help reduce these alarms and show the results over time.

Avera Heart Hospital leveraged alarm history analytics when developing a NPSG-compliant clinical alarm management system with its patient monitoring vendor. Using the analytics to enact changes in alarm management, the Avera Heart Hospital team reduced average per bed/per day alarm count from 71 to 42 – a reduction of 30 percent.

5.      Patient monitoring

Given the challenge of ongoing clinical staffing shortages, hospitals need ways to help maximize clinical team efficiency and productivity while supporting effective patient safety and care.

Connecting monitors, ventilators and anesthesia devices to a consolidated monitoring solution facilitates remote access to near real-time data across care settings. Clinicians can use their mobile devices or desktop PCs to monitor patient status throughout the hospital, whether patients are in the emergency department (ED), OR, ICU or general care floor, which contributes to greater process efficiency and more timely interventions.

Conclusion

The integration of medical device data analytics has transformative potential for healthcare, which may help enable more effective, efficient and patient-centered care. Digitally forward devices that prioritize streamlined connectivity, advanced analytics and actionable insights, support hospitals in addressing critical challenges, such as resource optimization, improved patient outcomes, and cost management.

Chris Stauffer, BS RRT, CPFT, is marketing manager, hospital data analytics & digital solutions, at Dräger.