Usability of Remote Assessment of Exercise Capacity for Pulmonary Telerehabilitation Program.

Pulmonary rehabilitation [PR] has been successfully carried out via telemedicine however initial patient assessment has been traditionally conducted in PR centers. The first step in PR is assessment of patient's exercise capacity which allows individualized prescription of safe and effective exercise program. With COVID-19 pandemics assessment of patients in PR centers has been limited resulting in significant reduction of patients undergoing life-saving PR. The goal of this pilot study was to introduce approaches for remote assessment of exercise capacity using videoconferencing platforms and provide initial usability assessment of this approach by conducing cognitive walkthrough testing. We developed a remote assessment system that supports comprehensive physical therapy assessment necessary for prescription of a personalized exercise program tailored to individual fitness level and limitations in gait and balance of the patient under evaluation. Usability was assessed by conducting cognitive walkthrough and system usability surveys. The usability inspection of the remote exercise assessment demonstrated overall high acceptance by all study participants. Our next steps in developing user-centered interface should include usability evaluation in different subgroups of patients with varying socio-economic background, different age groups, computer skills, literacy and numeracy.

Assessment of Patient Ambulation Profiles to Predict Hospital Readmission, Discharge Location, and Length of Stay in a Cardiac Surgery Progressive Care Unit.

Importance: Promoting patient mobility during hospitalization is associated with improved outcomes and reduced risk of hospitalization-associated functional decline. Therefore, accurate measurement of mobility with high-information content data may be key to improved risk prediction models, identification of at-risk patients, and the development of interventions to improve outcomes. Remote monitoring enables measurement of multiple ambulation metrics incorporating both distance and speed. Objective: To evaluate novel ambulation metrics in predicting 30-day readmission rates, discharge location, and length of stay using a real-time location system to continuously monitor the voluntary ambulations of postoperative cardiac surgery patients. Design, Setting, and Participants: This prognostic cohort study of the mobility of 100 patients after cardiac surgery in a progressive care unit at Johns Hopkins Hospital was performed using a real-time location system. Enrollment occurred between August 29, 2016, and April 4, 2018. Data analysis was performed from June 2018 to December 2019. Main Outcomes and Measures: Outcome measures included 30-day readmission, discharge location, and length of stay. Digital records of all voluntary ambulations were created where each ambulation consisted of multiple segments defined by distance and speed. Ambulation profiles consisted of 19 parameters derived from the digital ambulation records. Results: A total of 100 patients (81 men [81%]; mean [SD] age, 63.1 [11.6] years) were evaluated. Distance and speed were recorded for more than 14 000 segments in 840 voluntary ambulations, corresponding to a total of 127.8 km (79.4 miles) using a real-time location system. Patient ambulation profiles were predictive of 30-day readmission (sensitivity, 86.7%; specificity, 88.2%; C statistic, 0.925 [95% CI, 0.836-1.000]), discharge to acute rehabilitation (sensitivity, 84.6%; specificity, 86.4%; C statistic, 0.930 [95% CI, 0.855-1.000]), and length of stay (correlation coefficient, 0.927). Conclusions and Relevance: Remote monitoring provides a high-information content description of mobility, incorporating elements of step count (ambulation distance and related parameters), gait speed (ambulation speed and related parameters), frequency of ambulation, and changes in parameters on successive ambulations. Ambulation profiles incorporating multiple aspects of mobility enables accurate prediction of clinically relevant outcomes.

Using Big Data to Uncover Patient Determinants of Care Utilization Compliance in a Student Dental Clinic.

This study aims at assessing the relationship between social determinants of health (SDH) and dental care utilization compliance in a student dental clinic. Electronic dental records (EDR) were queried based on visit codes and evaluated using descriptive and inferential statistics, and binary logistic regression. Overall, characteristics of 16,474 visits were analyzed to identify potential predictors of appointment compliance. Factors affecting compliance with treatment plans prescribed at comprehensive care visits were identified in a cohort of 6,105 patients. Determinants of compliance with a comprehensive care visit following triage visits were analyzed in a cohort of 5491 patients. Results indicated that certain patient characteristics were associated with either increased or decreased compliance with dental care utilization. We concluded that EDR can be instrumental in identifying patterns of care utilization and determinants of patient compliance based on SDH.

Wearable Devices for Precision Medicine and Health State Monitoring.

Wearable technologies will play an important role in advancing precision medicine by enabling measurement of clinically-relevant parameters describing an individual's health state. The lifestyle and fitness markets have provided the driving force for the development of a broad range of wearable technologies that can be adapted for use in healthcare. Here we review existing technologies currently used for measurement of the four primary vital signs: temperature, heart rate, respiration rate, and blood pressure, along with physical activity, sweat, and emotion. We review the relevant physiology that defines the measurement needs and evaluate the different methods of signal transduction and measurement modalities for the use of wearables in healthcare.

Using a Real-Time Location System for Assessment of Patient Ambulation in a Hospital Setting.

OBJECTIVE: To assess the feasibility of using an infrared-based Real-Time Location System (RTLS) for measuring patient ambulation in a 2-minute walk test (2MWT) by comparing the distance walked and the Johns Hopkins Highest Level of Mobility (JH-HLM) score to clinician observation as a criterion standard. DESIGN: Criterion standard validation study. SETTING: Inpatient, university hospital. PARTICIPANTS: Patients (N=25) in an adult neuroscience/brain rescue unit. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: RTLS and clinician-reported ambulation distance in feet, and JH-HLM score on an 8-point ordinal scale. RESULTS: The RTLS ambulation distance for the 25 patients in the 2MWT was between 68 and 516ft. The mean difference between clinician-reported and RTLS ambulation distance was 8.4±11.7ft (2.7%±4.6%). The correlation between clinician-reported and RTLS ambulation distance was 97.9% (P<.01). The clinician-reported ambulation distance for 2 patients was +100ft and -99ft compared with the RTLS distance, implying clinician error in counting the number of laps (98ft). The correlation between the RTLS distance and clinician-reported distance excluding these 2 patients is 99.8% (P<.01). The accuracy of the RTLS for assessment of JH-HLM score for all 25 patients was 96%. The average patient speed obtained from RTLS data varied between 0.4 and 3.0mph. CONCLUSIONS: The RTLS is able to accurately measure patient ambulation and calculate JH-HLM for a 2MWT when compared with clinician observation as the criterion standard.

Introducing Contactless Blood Pressure Assessment Using a High Speed Video Camera.

Recent studies demonstrated that blood pressure (BP) can be estimated using pulse transit time (PTT). For PTT calculation, photoplethysmogram (PPG) is usually used to detect a time lag in pulse wave propagation which is correlated with BP. Until now, PTT and PPG were registered using a set of body-worn sensors. In this study a new methodology is introduced allowing contactless registration of PTT and PPG using high speed camera resulting in corresponding image-based PTT (iPTT) and image-based PPG (iPPG) generation. The iPTT value can be potentially utilized for blood pressure estimation however extent of correlation between iPTT and BP is unknown. The goal of this preliminary feasibility study was to introduce the methodology for contactless generation of iPPG and iPTT and to make initial estimation of the extent of correlation between iPTT and BP "in vivo." A short cycling exercise was used to generate BP changes in healthy adult volunteers in three consecutive visits. BP was measured by a verified BP monitor simultaneously with iPTT registration at three exercise points: rest, exercise peak, and recovery. iPPG was simultaneously registered at two body locations during the exercise using high speed camera at 420 frames per second. iPTT was calculated as a time lag between pulse waves obtained as two iPPG's registered from simultaneous recoding of head and palm areas. The average inter-person correlation between PTT and iPTT was 0.85 ± 0.08. The range of inter-person correlations between PTT and iPTT was from 0.70 to 0.95 (p < 0.05). The average inter-person coefficient of correlation between SBP and iPTT was -0.80 ± 0.12. The range of correlations between systolic BP and iPTT was from 0.632 to 0.960 with p < 0.05 for most of the participants. Preliminary data indicated that a high speed camera can be potentially utilized for unobtrusive contactless monitoring of abrupt blood pressure changes in a variety of settings. The initial prototype system was able to successfully generate approximation of pulse transit time and showed high intra-individual correlation between iPTT and BP. Further investigation of the proposed approach is warranted.