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The objective of this study is to explore the current state of research concerning the cost-effectiveness of wearable health technologies, excluding hearing aids, owing to extensive previous investigation. A systematic review was performed using PubMed, EMBASE/MEDLINE, Google Scholar, and Cumulated Index to Nursing and Allied Health Literature to search studies evaluating the cost-effectiveness of wearable health devices in terms of quality-adjusted life years and incremental cost-effectiveness ratio. The search was conducted on March 28, 2023, and the date of publication did not limit the search. The search yielded 10 studies eligible for inclusion. These studies, published between 2012 and 2023, spanned various locations globally. The studies used data from hypothetical cohorts, existing research, randomized controlled trials, and meta-analyses. They covered a diverse range of wearable technologies applied in different health care settings, including respiratory rate monitors, pedometers, fall-prediction devices, hospital-acquired pressure injury prevention monitors, seizure detection devices, heart rate monitors, insulin therapy sensors, and wearable cardioverter defibrillators. The time horizons in the cost-effectiveness analyses ranged from less than a year to a lifetime. The studies indicate that wearable technologies can increase quality-adjusted life years and be cost-effective and potentially cost-saving. However, the cost-effectiveness depends on various factors, such as the type of device, the health condition being addressed, the specific perspective of the health economic analysis, local cost and payment structure, and willingness-to-pay thresholds. The use of wearables in health care promises improving outcomes and resource allocation. However, more research is needed to fully understand the long-term benefits and to strengthen the evidence base for health care providers, policymakers, and patients.

Objective: To assess the feasibility and potential scalability of telemedicine-enabled ambulances for the prehospital evaluation of patients with suspected acute stroke symptoms. Patients and Methods: A pilot study of telemedicine-enabled ambulances for evaluating patients with suspected acute stroke symptoms en route at 2 tertiary academic comprehensive stroke centers from January 1, 2018, to February 5, 2024. Charts of included patients were reviewed for demographic data, vascular risk factors, final diagnosis, time from arrival to neuroimaging, door-to–needle and door-to-puncture times in patients eligible for acute treatment, and any reported technical challenges during audio-video consultations. Results: Forty-seven patients (mean age, 68.0 years; 62% men) were evaluated via telemedicine-enabled ambulances, of which 35 (74%) where for hospital-to-hospital transferred patients. Mean time from arrival to neuroimaging was 11.8 minutes. Twenty-nine patients (62%) were diagnosed with acute ischemic stroke, and the remainder were diagnosed with intracranial hemorrhage (n=13), seizure (n=2), brain mass (n=1), or other diagnoses (n=3). Four patients (9%) received intravenous thrombolysis with alteplase (mean door to needle, 30.3 minutes), and 15 patients (32%) underwent mechanical thrombectomy (mean door to puncture, 72 minutes). Technical challenges were reported in 15 of the 42 (36%) cases, of which 10 (67%) were related to poor internet connectivity. Conclusion: Telemedicine-enabled ambulances in emergency medical services systems are novel, feasible, and potentially scalable options for evaluating patients with suspected acute stroke in the prehospital setting. However, optimization of infrastructure, staffing models, and internet connectivity is necessary, and larger studies evaluating the clinical and cost effectiveness of this approach are needed before widespread implementation.

Objective: To determine the diagnostic accuracy of the initial telestroke consultation in a large academic hub-and-spoke telemedicine network. Patients and Methods: This retrospective study includes all patients evaluated for cerebral ischemia through video telestroke consultation in a large academic hub-and-spoke telemedicine network from January 1, 2019 to December 31, 2020. A detailed chart review was conducted to identify the initial suspected diagnosis and final diagnosis. Cerebral ischemia was defined as acute ischemic stroke and transient ischemic attack. All other diagnoses were defined as stroke mimics. Data were organized into continuous and categorical variables. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the curve (AUC), and likelihood ratio (LR+) for the telestroke-consultation diagnosis were calculated while using the final diagnosis as the gold standard diagnosis. Results: A total of 1043 patients met the inclusion criteria. The final diagnosis of cerebral ischemia was made in 63.5% of all patients (539 of the 1043 with acute ischemic stroke,123 of the 1043 with transient ischemic attack). Stroke mimic was diagnosed in 36.5% patients (381 of the 1043). The sensitivity and specificity of telestroke evaluation for diagnosis of cerebral ischemia were 97.1% and 81.4%, respectively. Positive predictive value was 90.1%, and negative predictive value was 94.2%. Overall diagnostic accuracy was 91.4%, with an LR+ of 5.21 and AUC of 0.89. Conclusion: This study highlights the high diagnostic accuracy of telestroke providers in diagnosing cerebral ischemia. Further research exploring the application of teleneurology in the nonstroke setting and other medical subspecialties is warranted.

Cerebrovascular disease (CeVD) is a leading cause of death and disability worldwide. Early detection of behavioral and physiologic changes associated with CeVD may be critical to improving patient outcomes. The growing prevalence of remote monitoring tools, from wearable devices to smartphone applications, which facilitate in situ observation of patients, holds promise for more timely recognition and possible prevention of stroke. The goal of this review was to examine and establish categories of innovation with digital sensors that monitor physiologic and behavioral variables in situ to augment the current CeVD screening and diagnostic processes. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist, a search strategy spanning multiple databases from January 2012 to September 30, 2022, was implemented, aggregating 729 articles, of which 51 (7.0%) met the inclusion criteria. The articles were divided into 2 categories on the basis of their focus: physiologic and behavioral. Physiologic articles were sorted into 1 of the following 6 subcategories according to the signal(s) monitored: motor function, heart rhythm, heart rate, kinematic analysis, physical activity, and blood pressure. Behavioral articles were sorted into the following 3 subcategories: mood, cognitive function, and fatigue. Most studies used a wearable accelerometer, photoplethysmography-enabled smartwatch, or smartphone-based sensors. This scoping review identified disparate methods and conclusions associated with the use of digital sensors for in situ physiologic and behavioral monitoring of patients with CeVD. Although most articles evaluated pilot validation and feasibility trials, the lack of randomized controlled trials was identified as a critical gap specific to this evolving research area.