HT Snowday, director of hardware research and innovation at Midmark RTLS; Kevin Paroda, director of global hardware product management at CenTrak; and Jim Forbes, chief strategy officer of Vizzia Technologies, discuss how real-time location systems (RTLS) are improving equipment management, enhancing staff safety, and increasing efficiency through predictive analytics and integrated technologies.
24×7: What are the most significant advancements in RTLS technologies in the current landscape?
Jim Forbes: Healthcare staff badges are now RTLS-enabled to address growing concerns about workplace violence. Nurses and clinicians can activate a silent alarm, alerting security to their exact location with room-level accuracy when help is needed.
HT Snowday: For a modern approach to locating, Bluetooth low energy (BLE) technology has been a top contender in recent years, offering near-room accuracy at a fraction of the cost of proprietary locating solutions. However, an emerging trend we’re seeing is hybrid technology deployments that leverage both near-room BLE locating and precise, room-level or better locating technology.
At Midmark RTLS, we use infrared to deliver room-certain precision where it’s needed most (typically in patient care areas), while offering BLE for near-room accuracy elsewhere, creating a cost-effective, facility-wide RTLS deployment. We can deploy a location algorithm that leverages AI (specifically, machine learning) to deliver location data, or we can use third-party algorithms; for instance, if the health system has already invested in locating solutions provided via a BLE-capable Wi-Fi network.
Kevin Paroda: There are many advances happening in the RTLS landscape, but the most impactful in the near term will come from integrating various technologies into a single system that meets key customer requirements, supports multiple use cases, and reduces the barrier to entry.
Traditional solutions like infrared and ultrasound offer high accuracy but can be challenging to install, which has historically slowed industry adoption. In contrast, newer technologies like BLE provide easier installation and lower costs, though they come with trade-offs in accuracy that limit use-case expansion and value to customers. By combining these technologies, companies can deliver solutions that offer both the affordability and ease of installation of Bluetooth, along with the high precision of traditional systems. This hybrid approach can be optimized for customer preferences, enabling them to benefit from the strengths of multiple technologies.
Looking ahead, I anticipate that advancements in machine learning and AI, applied to standardized technologies like Bluetooth or existing infrastructure such as easily installed camera systems, will continue to enhance RTLS capabilities. The key transition point for these technologies will come when a single platform can generate data that supports a wide variety of critical use cases. As these technologies evolve, we expect to see a reduction in barriers to entry while maintaining high precision, making RTLS solutions more accessible and effective for a broader audience.
24×7: How does RTLS influence the cost efficiency and allocation of medical equipment in healthcare facilities?
Paroda: RTLS allows hospitals to monitor how equipment is used across various departments, such as sterilization, nursing, and patient interactions. This understanding is vital for hospitals to make informed decisions about resource allocation. For example, by tracking the utilization patterns of equipment, hospitals can identify underused assets and reallocate them where they are most needed, ensuring that critical resources are always available. The ability to locate equipment with enough granularity to accurately identify these utilization patterns is paramount to enabling this use case.
Additionally, RTLS supports effective management of rental equipment and helps establish PAR levels—standardized inventory thresholds—allowing hospitals to maintain optimal stock without overspending. By right sizing their equipment inventory based on real-time data, hospitals can reduce unnecessary costs and improve operational efficiency.
Forbes: Advanced, enterprise-grade data analytics are now providing powerful dashboards and utilization reports. This insightful information empowers hospital management to make well-informed decisions about renting or buying expensive medical equipment and planning for human capital support.
Snowday: Most health systems believe they should have enough equipment—they have the purchase records to prove it. Equipment should theoretically be everywhere, readily accessible. However, when biomedical teams or nursing staff go to retrieve equipment from where they think it should be, it’s nowhere to be found. This game of cat and mouse results not only in wasted time but also in over-purchasing new equipment or re-buying it with departmental budgets, based on the assumption that inventory is shrinking.
Spoiler alert: the rest of the fleet is likely hidden away or stored in places that aren’t easily accessible. RTLS technology can help. By providing real-time location information to both biomed and nursing teams, RTLS reduces non-value-added time spent searching and allows staff to focus on what matters most: maintenance and patient care activities. For administrators, utilization data helps the health system right-size their fleet—buying less, reducing shrinkage, and increasing utilization.
24×7: How do you ensure data security and patient privacy when implementing RTLS in healthcare environments?
Snowday: When RTLS vendors deliver data to health systems via the cloud, their security practices become critically important. Midmark cloud-hosted products incorporate industry best practices and regulatory compliance controls, including regular data backups, disaster recovery planning, penetration testing, data encryption (at rest and in transit), and third-party security assessments to ensure that data is secured to the highest extent possible.
With several years of cloud experience, we’ve learned that many healthcare entities still prefer to secure their own data. It’s important to also offer robust security controls in the on-premises applications we deploy, including identity federation, role-based authentication and access, and HIPAA controls when patient data is displayed (e.g., data masking.
Forbes: Vizzia utilizes System and Organization Controls (SOC) 2 industry audits, to ensure that mission-critical data is trusted and secure. SOC 2 compliance means that hospitals can be confident that their data is being handled with the proper security, confidentiality, and privacy controls.
Paroda: Protecting data security and patient privacy in healthcare settings should be a top priority for any RTLS vendor. Healthcare facilities should seek a partner with a clear strategy for keeping sensitive information separate from location data, ensuring patient privacy is safeguarded. This can be achieved by separating location names from individual identities.
Look for an RTLS system that does not store personal identifiers but instead relies on separate, HIPAA-compliant systems to manage and protect that information. This separation ensures that the core RTLS handles only non-sensitive data, reducing the risk of privacy breaches. Data from these systems should remain usable and compliant for healthcare staff while ensuring that backend systems do not have access to personal information.
24×7: What are the most common challenges hospitals face when implementing RTLS, and how can they be addressed?
Forbes: Leveraging experienced staff and industry best practices is crucial for properly deploying RTLS across a diverse healthcare facility. This includes integrating data applications with existing hospital workflow systems, such as electronic medical records (EMR) and CMMS platforms.
Paroda: When hospitals implement RTLS, a key first step is to clearly define their use case requirements and identify where to focus their efforts. It’s crucial for hospitals to pinpoint specific solutions and desired levels of location accuracy, as this information helps tailor the implementation for maximum impact.
One effective strategy to mitigate installation complexity is to use a multi-mode platform, allowing for flexible deployment across different areas of the hospital. This “paint-by-numbers” approach enables hospitals to choose varying levels of accuracy tailored to each department’s needs. For instance, higher accuracy may be prioritized in the emergency department or behavioral health units, while other areas may require less precision.
To prepare for the challenges of RTLS implementation, it’s beneficial to partner with a vendor that offers consulting services. A team composed of clinicians, Certified Leapfrog Group coaches, and operational experts should work closely with hospitals throughout the process to thoroughly understand their use cases and the implications of their choices.
Snowday: One common theme we see across health systems is that biomedical and nursing teams address their needs separately, with separate budgets and projects. Biomed may choose one RTLS to manage assets, but the health system later finds that the level of accuracy doesn’t quite meet the clinical needs to automate nurse call, manage patient flow, or improve caregiver safety. This lack of planning can be costly to the health system. Nursing must be included in the RTLS purchasing process early, so their workflow needs are identified and considered. Addressing both clinical and biomedical needs is a clear use case for the hybrid approach I discussed earlier.
Another common issue is battery lifecycles for both tags and sensors. The more frequently a tag emits a signal, the quicker the battery drains. However, even tags with a battery life of several years may not offer “real-time” location if they only emit a signal once every 10 minutes to conserve battery life. Weigh your options accordingly while also proactively considering a plan for battery management. Who is going to change the batteries? How often? Can it be part of existing workflows, like preventive maintenance routines, or will you need to establish a new process? How will you ensure that RTLS services aren’t disrupted? With the right tag and sensor mix, you can mitigate much of this effort. Your RTLS vendor should be well-prepared to walk you through your options and suggest the best course of action.
24×7: How does RTLS support compliance with regulatory standards in healthcare settings?
Snowday: RTLS can help health systems meet the standards set by The Joint Commission, which require that 100% of assets undergo preventive maintenance annually. This is impossible to achieve if the equipment cannot be located. When the health system cannot find the equipment, they may have to write it off, resulting in financial loss. RTLS for asset management provides the reliability needed to maintain compliance and stay within budget.
Joint Commission standards also include elements of performance related to staff safety, requiring hospitals to take appropriate action to mitigate or resolve risks associated with workplace violence, safety, and security. RTLS-powered staff duress technology equips staff with a discreet button, enabling them to instantly signal for help without escalating a situation. This technology helps health systems meet several TJC requirements related to workplace violence.
Forbes: Vital healthcare standards are mandated by The Joint Commission, FDA, and CDC, with strict reporting requirements. Vizzia provides automated alerts and reports to keep staff informed of hand hygiene compliance related to healthcare-acquired infections, as well as 24/7 environmental monitoring of expensive medical supplies and vaccines.
Paroda: The nature of RTLS as an always-on, real-time data collection system means it plays a vital role in supporting compliance with regulatory standards in healthcare. Operating 24/7, the system captures 100% of relevant events, including hand hygiene opportunities, vaccine and medication storage temperatures, and staff duress alerts. This extensive data collection enables hospitals to meet both internal and external reporting requirements effectively.
RTLS can also be used to track unauthorized infant movement, providing critical data that can be reported to the Joint Commission and other safety organizations for compliance. To support infection prevention, RTLS automatically captures all handwashing opportunities, allowing hospitals to report compliance to the Leapfrog Group and the Joint Commission while using the data internally for education and improvement.
24×7: How can RTLS data be leveraged for predictive analytics to optimize hospital operations?
Paroda: The future of RTLS holds tremendous potential, particularly in powering AI tools and predictive analytics to optimize hospital operations. Currently, location data from healthcare enterprises has not been fully utilized in operational contexts, but I believe that within the next three to five years, this will change dramatically. As AI models process ever-increasing amounts of training data, finding new data sources to enhance their output will become critical for continued advancements. Real-time location data is poised to be a crucial component in enabling healthcare operating systems that, in the future, will optimize care delivery in ways far beyond what is achievable or imaginable today.
Predictive analytics will be a major feature of these future tools. By leveraging RTLS data, hospitals will be able to anticipate resource needs, streamline workflows, and enhance patient care delivery. While historical data is necessary to build predictive models, the real-time nature of RTLS data allows trends to be identified in the moment, enabling proactive measures to be taken based on ever-changing conditions and scenarios. The potential for leaps in operational efficiency and cost reduction is immense, positioning RTLS as a critical component in the future of healthcare.
Forbes: Machine learning analytics are now used to optimize PAR levels of medical equipment throughout a hospital. Results of predictive analytics at a trauma hospital yielded substantial operational improvements across several inventory KPIs, including up to a 52% improvement in key out-of-stock metrics and a reduction in overstock rates by up to 20%.
Snowday: With the advent of widely available artificial intelligence tools, there is growing interest in utilizing RTLS data with AI. The first step is to incorporate RTLS data into a health system’s overall data model, enabling the data to be easily queried with AI data analysis solutions by asking simple questions, such as, “What did the distribution of IV pumps across the hospital look like last month?” However, without additional health system data, such as patient census, staffing, or other inputs, the value of historical location data for predictive analytics (e.g., “What distribution of IV pumps should I prepare for next month?”) is limited.
For example, RTLS can help with PAR management to track the inventory of key equipment on each nursing unit. Currently, these systems rely on the nursing manager of a unit to set a PAR (periodic automatic replenishment) level. The RTLS can send alerts when inventory nears or falls below that level, allowing equipment to be proactively redistributed and helping to avoid delays in patient care.
Forward-thinking health systems will combine this RTLS inventory data with patient census data. Instead of relying on nursing managers to estimate their PAR levels, AI-enabled RTLS software, with access to census data, can dynamically set PAR levels for each unit based on census trends. If the current inventory cannot meet projected demand, the RTLS could even suggest rental or purchase strategies to supplement the existing fleet.