The availability of technology for continuous temperature monitoring presents an opportunity to remove the human element from temperature taking, thereby reducing error and improving patient safety. Current inpatient care relies heavily on vital sign measurement to monitor for clinical deterioration. Temperature is one of the four primary vital signs and aids in assessing common complications, like sepsis–a leading cause of in-hospital death (Rhee). Nurses, the center of the healthcare team, are often responsible for monitoring temperature. The dependence on a person to take a temperature invites several sources of error such as variation between observers, inconsistent use of devices or methods, inaccurate measurements, and missed recordings. Further, nursing shortages and turnover add to the human error component of collecting this vital sign. Consequently, timely detection of fevers is difficult, delaying treatment and jeopardizing patient safety.
There’s more to temperature than a number
Despite its perception, body temperature is a complex vital sign. This physiological parameter is known to vary based on the time of day, the site of measurement, age, underlying conditions, menstrual cycle, and physical fitness (Obermeyer). These sources of biological variation make spot-check readings challenging to interpret and unreliable. Conversely, continuous temperature monitoring (CTM), also known as high-frequency temperature monitoring, overcomes many pitfalls of single, manual measurements. It is now possible to conduct CTM via a wireless, Blue-tooth-enabled wearable device. These devices greatly diminish the potential for variation and ensure the use of a single method and site for each patient. Thus, this technology dramatically standardizes temperature monitoring since different observers or measurement methods (e.g., oral, rectal, tympanic, etc.) can generate discordant readings. Furthermore, temperatures tend to run lower in the morning, usually peaking late afternoon to early evening. It is easy to recognize these diurnal variations with CTM, given that recordings occur seconds apart compared to hours for manual observation.
Further, the design of this technology allows for alerts triggered by individualized temperature thresholds, offering an opportunity to account for some of the natural variations in baseline temperatures. Presently, the use of population averages to set temperature thresholds ignores the impact of patient-specific characteristics that can influence baseline readings. For example, elevated baseline temperatures correlate with higher body mass. In contrast, older age and hypothyroidism correspond with lower baseline temperatures (Obermeyer). Additionally, individualized alert settings are invaluable when an illness or medication may dampen the body’s response to an infection. Still’s disease, for instance, involves uncontrolled cytokine production and is often treated with a drug intended to decrease recurrent high spiking fevers and other symptoms (Ortiz-sanjaun, Ma). In such cases, an alert for a low-grade temperature may be more appropriate to monitor for infection.
CTM technology can factor in demographics and co-morbidities that have a known appreciable effect on temperature. This ability will improve how this vital sign can be used for inpatient surveillance and promote personalized care. Simultaneously, continuous temperature monitoring is crucial to gaining a deeper understanding of these variables and their significance on baseline temperatures. Subsequently, it may reveal new ways to personalize temperature monitoring practices. Overall, CTM offers a straightforward solution that accounts for this vital sign’s inherent complexity and the limitations of manual collection, therefore presenting a more dependable monitoring strategy for all patients.
Enhancing patient safety through continuous temperature monitoring
Currently, the frequency of temperature collection in general hospital floors occurs at four-to-eight-hour intervals. Certainly, prodromal warning signs can happen in such a wide window. Even more concerning is that inaccurate or missed recordings are typical with manual observation- stretching this window even wider (Kellett). Indeed, the ongoing nursing crisis worsens such collection issues and emphasizes why simply increasing the number of manual measurements is not feasible.
Continuous temperature monitoring eliminates this window and transmits recordings via Blue-tooth in real time to the clinical workstation every few minutes. Additionally, nurses can easily read the transmitted temperatures, which are color-coded to indicate out-of-range recordings. A recent study reported that high-frequency temperature monitoring detected 89 percent of fevers earlier than intermittent measurements in cancer patients following treatment, which leaves them at increased risk of neutropenic fever (Flora). Moreover, in another study of immunocompromised pediatric patients, temperature checks every four hours often failed to detect fevers or were delayed compared to CTM (Sampson). In these situations, continuous temperature monitoring facilitated timely follow-up assessment and treatment in response to fevers compared to the current procedure of intermittent, manual measurements.
Making the most of temperature monitoring
CTM has another edge on manual monitoring: trend prediction. Temperature sampling at short intervals generates enough data for computational modeling or machine learning. Identifying patterns that precede fever could lengthen the window for healthcare workers to obtain additional testing, administer necessary treatments or signal the need for closer observation. For example, circadian modeling of temperature data derived from a wearable sensor revealed sustained deviations in baseline temperatures 3.5 hours before a fever occurred (Flora). Given that fever-related complications like sepsis and neutropenic fever are time-sensitive emergencies, this amount of lead time for clinical decision-making is an obvious advantage.
There is active interest in the circadian rhythm of various vital signs, temperature included, as disruption to this rhythmicity could signal deteriorating health (van Goor, Geneva). Body temperature is a convenient metric for observing circadian patterns, given its diurnal behavior. Thus, temperature patterns can provide clinically useful information regardless of concern for fever. A previous observation suggests that temperature patterns, rather than fever, could help diagnose sepsis earlier (Drewry). The potential for improved sepsis detection is considerable, as most preventable deaths result from delayed diagnosis or treatment (Rhee).
Ongoing efforts seek to understand the relationship between the incidence of patient decline requiring hospitalization and body temperature (Geneva). While the traditional interpretation of temperature is simply fever or no fever, the availability of CTM technology will unmask the actual value of this physiological parameter through temperature pattern identification.
Healthcare has ‘Digital Fever’
Continuous temperature monitoring benefits patients and providers by minimizing human-related errors, increasing patient safety, and supporting personalized care. CTM will foster a more comprehensive and fine-tuned approach to temperature monitoring that is impossible through manual collection. The COVID-19 pandemic recognized technology as the primary driver of next-generation healthcare. The digital push is now in full swing, with hospitals as a primary target. Many clinicians and patients look forward to seeing how advancing technology such as CTM can improve workflow and patient outcomes.