Use of Wearables in Hospitalized General Medicine Patients
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|ClinicalTrials.gov Identifier: NCT03646435|
Recruitment Status : Recruiting
First Posted : August 24, 2018
Last Update Posted : June 20, 2019
|Condition or disease||Intervention/treatment||Phase|
|Hospitalizations||Device: Fitbit Charge 2||Not Applicable|
Patients admitted to general internal medicine are admitted because they are sick and need monitoring that cannot be provided at home, need expedited testing and/or need treatments that are best administered in hospital. Currently, standard monitoring on the hospital ward consists of measuring vital signs typically twice a day. The rapid development, uptake of affordable wearables such as smartwatches and wearable devices that involve continuous measurement of vital measures may provide added information to the care of inpatients. To date, there have been limited studies on the use of wearables in hospitalized medical patients. The rationale for the study is to determine feasibility of using wearables in GIM patients and usefulness of the data that wearables provide.
The wearable chosen for this study will be the Fitbit Charge 2. The Fitbit will be worn by all patients who are recruited to participate in the study. It will be worn like a watch on a wrist and uses photoplethysmography (PPG) to detect periodic changes in blood flow beneath the sensor; thereby measuring changes in heart rate. Heart rate will be measured nearly continuously. Fitbit will also assess activity and will also assess sleep. Fitbit data will be transmitted via Bluetooth to a mobile app which then is uploaded to Fitbit servers. The Fitbit data will then be accessed via the Web. The data will be downloaded from Fitbit servers to a secure UHN server.
In an effort to reduce the risk of potential iatrogenic infection, the study team will use disinfectant wipes to thoroughly clean wearables between uses. Participants will be shown how to wear the band by a study investigator or research personnel.
At the end of the study for each participant, the investigators will ask the questions related to how useful they found the data. For each participant, the study team will provide summary of their data to nurses and physicians who were caring for them. The investigators hope to get 2 nurse surveys per patient (because of there being multiple shifts per patient) and to get 1 attending survey per patient.
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||50 participants|
|Intervention Model:||Single Group Assignment|
|Intervention Model Description:||This study model will involve a single cohort of about 50 GIM patients. All patients will be asked to wear the Fitbit Charge 2 for the duration of their stay in the hospital and the health information (heart rate, sleep, physical activity) collected from the wearable will be compared to the nurses' vital sign assessment for accuracy. There will be no other comparison group in this study.|
|Masking:||None (Open Label)|
|Masking Description:||After all the study participants are recruited, they will be assigned a study ID which investigators will use to anonymize data and track patient health data that is collected via the Fitbit.|
|Official Title:||Use of Fitbit Charge 2 in Hospitalized General Medicine Patients to Monitor Health Outcomes|
|Actual Study Start Date :||June 12, 2019|
|Estimated Primary Completion Date :||September 2019|
|Estimated Study Completion Date :||November 2019|
Experimental: Wearable device (Fitbit Charge 2)
The Fitbit Charge 2 is the wearable of interest for this pilot study. All 50 study participants will be requested to wear the electronic device for the duration of their stay in the hospital (maximum of 6 days). The Fitbit will passively collect health information of patients which will be tracked on mobile devices by the study investigators.
Device: Fitbit Charge 2
The Fitbit Charge 2 is the electronic wearable chosen for this pilot study. This particular Fitbit is capable of measuring patient heart rate, sleep and physical activity. The data collected will then be analyzed with respect to the outcomes of this study. To determine the accuracy of the Fitbit, data collected will be compared to the nurses' standard patient assessment (for HR and physical activity) and to patient responses on the Richards-Campbell Sleep Questionnaire (for sleep).
- Perceived usefulness of the wearable by patient [ Time Frame: 6 days ]Patients will be given a 'patient questionnaire' that is developed by the research team to provide feedback about their experience and how useful/feasible (if at all) they found the wearable to be in collecting their health information. The questionnaire is not adopted from any other source or the literature. There will be a mix of 10 questions (open-ended short answer or scale-based from 1-10) on the questionnaire. Higher scores will indicate that patients felt that their Fitbit data correlated well with their behaviour and nurses' vital sign assessment.
- Perceived usefulness of the wearable by nurses/physicians [ Time Frame: 6 days ]Nurses and physicians will be given a 'clinician questionnaire' which is also developed by the research team, to report how clinically useful they felt the Fitbit data was. There will be a mix of 6 questions (open-ended short answer or scale-based from 1-10) on the questionnaire. Higher scores on questionnaire indicate that nurses and physicians felt that the Fitbit data was mostly consistent with the nurses' assessment (which was conducted every 6 hours).
- Correlation between Fitbit HR and HR obtained by nurses [ Time Frame: 6 days ]Upon termination of the study, the minute-level HR data gathered from Fitbit will be compared to the HR data collected by nurses in the GIM ward (every 6 hours) to see how consistent and accurate both methods are. Ultimately, averaged data collected from both methods will be presented graphically and the correlation coefficient (r2) between the two types of data will be reported.
- Correlation between Fitbit sleep and sleep information gathered by patients [ Time Frame: 6 days ]Upon termination of the study, an analysis will be done to assess if there is a correlation between the sleep data gathered by the Fitbit and the sleep information obtained by patients (via the Richards-Campbell Sleep Questionnaire). All patients enrolled in the study will be required to fill out the RCSQ after the study concludes. This RCSQ uses a visual analog scale (0-100) to assess 5 features of sleep: sleep depth, latency, awakenings, percentage of time awake, and overall quality of sleep. Ultimately, all the individual feature scores will be aggregated to develop a final RCSQ score for each patient. Higher scores indicate that patient has a good sleep pattern. The RCSQ scores of patients will then be compared to the sleep data gathered by the Fitbit and a correlation coefficient (r2) between the two types of data will be reported.
- Correlation between Fitbit physical activity (number of steps taken) and activity information obtained by nurses [ Time Frame: 6 days ]The physical activity data gathered by the Fitbit (ie. number of steps taken every day by the patient) will be compared to the nurses' daily assessment of the patients which includes a Braden scale (for predicting pressure sore risk). The braden score consists of 6 categories: sensory perception, moisture, activity, mobility, nutrition and friction. The score ranges from 6-23 with lower scores indicating a higher risk. The Braden scores gathered by nurses for every patient in the study will be compared to each patient's Fitbit data to assess for accuracy and consistency. Ultimately, averaged data collected from both methods will be presented graphically and a correlation coefficient (r2) between the two types of data will be reported.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03646435
|Contact: Robert Wu, MD||416 340 firstname.lastname@example.org|
|Contact: Vikas Patel, BMSc||519 702 email@example.com|
|Toronto General Hospital||Recruiting|
|Toronto, Ontario, Canada, M5G 2C4|
|Contact: Robert Wu, MD 416 340 4567 firstname.lastname@example.org|
|Contact: Vikas Patel, BMSc 519 702 2570 email@example.com|
|Principal Investigator: Robert Wu, MD|
|Principal Investigator:||Robert Wu, MD||University Health Network, Toronto|