Use of Wearables in Hospitalized General Medicine Patients

Hospitalizations Clinical Trial

Official title:

Use of Fitbit Charge 2 in Hospitalized General Medicine Patients to Monitor Health Outcomes

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03646435
• Other study ID #: 18-5621
• Status: Completed
• Phase: N/A
• Start date: June 12, 2019
• Est. completion date: November 1, 2019

Study information

• Verified date: December 2019
• Source: University Health Network, Toronto
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This study will focus to determine the usefulness of continuous monitoring and the role it would play in improving inpatient management. The study is also conducted to collect patient's experiences regarding use of the wearable device for health monitoring. There will be no control or comparison group for this prospective cohort study. For each participant, the investigators will provide summary of their data to nurses and physicians who are directly involved in the patients' care. At the end of the study for each participant, the investigators will ask questions related to how useful they found the data. As a secondary endpoint for this study, the study team will also be evaluating the accuracy of the heart rate, sleep and activity data gathered from the wearable against the current gold standard used in hospitals (ie. information gathered by nurses or using sleep assessment patient questionnaires). The investigators predict that wearable devices will be well received among participants and that they can provide accurate information about patients on GIM.

Description:

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 50
• Est. completion date: November 1, 2019
• Est. primary completion date: October 5, 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• General internal medicine patients admitted to General Medicine Wards.

• Able to consent.

• Able to speak English.

• 18 years of age or older

Exclusion Criteria:

• Patients who are purely palliative "comfort measures only" where measuring vital signs would not be appropriate and will be excluded.

• To reduce the potential risk of transmitting nosocomial infections, patients under contact precautions for methicillin resistant Staphylococcus aureus (MRSA) and Clostridium difficile infections will also be excluded.

• We will also excluded patients at risk of vascular compromise of the arm on which the wearable device was to be placed, such as patients with upper extremity deep venous thrombosis, peripherally inserted central catheters, radial arterial lines, dialysis fistulas, and severe upper extremity trauma.

• We will exclude patients with significant cognitive impairment as patients will be required to complete daily surveys.

Related Conditions & MeSH terms

• Hospitalizations

Intervention

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).

Locations

Country	Name	City	State
Canada	Toronto General Hospital	Toronto	Ontario

Sponsors (1)

Lead Sponsor	Collaborator
University Health Network, Toronto

Country where clinical trial is conducted

Canada, 

References & Publications (8)

Abeles A, Kwasnicki RM, Pettengell C, Murphy J, Darzi A. The relationship between physical activity and post-operative length of hospital stay: A systematic review. Int J Surg. 2017 Aug;44:295-302. doi: 10.1016/j.ijsu.2017.06.085. Epub 2017 Jul 6. Review. — View Citation

Appelboom G, Camacho E, Abraham ME, Bruce SS, Dumont EL, Zacharia BE, D'Amico R, Slomian J, Reginster JY, Bruyère O, Connolly ES Jr. Smart wearable body sensors for patient self-assessment and monitoring. Arch Public Health. 2014 Aug 22;72(1):28. doi: 10.1186/2049-3258-72-28. eCollection 2014. — View Citation

Baldwin C, van Kessel G, Phillips A, Johnston K. Accelerometry Shows Inpatients With Acute Medical or Surgical Conditions Spend Little Time Upright and Are Highly Sedentary: Systematic Review. Phys Ther. 2017 Nov 1;97(11):1044-1065. doi: 10.1093/ptj/pzx076. Review. — View Citation

Helton MC, Gordon SH, Nunnery SL. The correlation between sleep deprivation and the intensive care unit syndrome. Heart Lung. 1980 May-Jun;9(3):464-8. — View Citation

Kroll RR, Boyd JG, Maslove DM. Accuracy of a Wrist-Worn Wearable Device for Monitoring Heart Rates in Hospital Inpatients: A Prospective Observational Study. J Med Internet Res. 2016 Sep 20;18(9):e253. doi: 10.2196/jmir.6025. — View Citation

Kroll RR, McKenzie ED, Boyd JG, Sheth P, Howes D, Wood M, Maslove DM; WEARable Information Technology for hospital INpatients (WEARIT-IN) study group. Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study. J Intensive Care. 2017 Nov 21;5:64. doi: 10.1186/s40560-017-0261-9. eCollection 2017. — View Citation

Pires GN, Bezerra AG, Tufik S, Andersen ML. Effects of acute sleep deprivation on state anxiety levels: a systematic review and meta-analysis. Sleep Med. 2016 Aug;24:109-118. doi: 10.1016/j.sleep.2016.07.019. Epub 2016 Aug 27. Review. — View Citation

Roehrs T, Hyde M, Blaisdell B, Greenwald M, Roth T. Sleep loss and REM sleep loss are hyperalgesic. Sleep. 2006 Feb;29(2):145-51. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Perceived usefulness of the wearable by patient	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.	6 days
Primary	Perceived usefulness of the wearable by nurses/physicians	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).	6 days
Secondary	Correlation between Fitbit HR and HR obtained by nurses	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.	6 days
Secondary	Correlation between Fitbit sleep and sleep information gathered by patients	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.	6 days
Secondary	Correlation between Fitbit physical activity (number of steps taken) and activity information obtained by nurses	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.	6 days