Abstract
BACKGROUND: Many patients experience a gradual decline in health before seeking hospital care, with subtle changes in vital signs such as increased heart rate or decreased mobility. Recognizing deviations from baseline vital signs can support clinical decision-making, especially admission decisions. Smart devices (ie, smartphones, smartwatches, and activity trackers) track health metrics like heart rate and step count, offering new opportunities to estimate illness severity and track deterioration early. OBJECTIVE: This study aimed to assess the feasibility of using heart rate and step count measurements from smart devices (ie, smartphones, smartwatches, and activity trackers) to enhance the evaluation of patients presenting with acute illness in emergency settings. METHODS: We conducted an international multicenter prospective observational study using the flash mob study design in 34 hospitals in the Netherlands (n=17), the United Kingdom (n=7), Denmark (n=9), and Switzerland (n=1) in May 2024. Researchers collaborated with patients to complete questionnaires upon an acute care (ie, emergency department, acute medical unit, same day emergency care) visit and extracted physiological data from their smart devices. RESULTS: Among patients with an acute care visit (n=1137), 40% (n=452) had a smart device with health data. These patients tended to be from a higher educational level and in relatively good health. Only half had retrievable heart rate or step count data, resulting in a usable data set for 20% (n=209) of the total study population. Analysis showed a significant increase in heart rate (P<.001) and a decrease in step count (P<.001) in the days preceding their hospital visit. Both heart rate (P=.04) and step count (P=.04) on the day before presentation were significantly associated with disposition. CONCLUSIONS: Our study demonstrates the feasibility of using a patient's personal smart device to monitor vital signs in the days leading up to an acute care visit. In a selected patient group, significant changes in heart rate and step count were observed prior to hospital presentation, suggesting that disposition may be predicted using data collected from the patient's own device. High-risk patient groups, who might benefit the most from digital health monitoring, are currently underrepresented among device users.