Testing Utility of Commercially Available Sleep Trackers for Physician-Patient Communication

January 3, 2019 updated by: Regenstrief Institute, Inc.

Testing Utility of Commercially Available Sleep Trackers for Physician-Patient Communication Around Sleep Experience, Habits, and Behaviors

Sleep related disorders are common in primary care practice. Sleep wear related data has not been utilized to improve sleep related communication between patients and providers. The study team is conducting a randomized study to improve physical-patient communication regarding sleep through a novel intervention based upon sleep wear and the Sleeplife® app.

Study Overview

Detailed Description

Based on a National US survey in 2012, 69% adults track at least one health indicator using either a tracking device or some other means. The main health indicators tracked were diet, weight, and exercise. Although not as extensive as the above health indicators, certain studies also looked at sleep indicators through the trackers to support validity of their use. Based on the study team's literature review, none of the studies looked at an intervention designed to utilize data-trackers-based data to improve physician-patient communication regarding sleep.

Commercially available and inexpensive exercise, fitness and sleep trackers are broadly available and consumer use is growing rapidly. Industry analysts estimate that over 30 million Americans have access to their sleep tracking data (e.g. Fitbit. Jawbone). Physicians seldom use patient-generated (i.e. subjective) sleep data (e.g. sleep diaries) and have been slow to integrate objective sleep data collected from commercial sleep trackers. Two commercial sleep trackers have been validated by independent testing. The National Sleep Foundation (NSF) has led recent efforts to establish normative data (i.e. appropriate ranges) for sleep duration and sleep quality. NSF, together with the Consumer Electronics Association (now Consumer Technology Association), has established a work-group involving over 40 sleep tracking technology companies which is working to standardize sleep tracking data collection and reporting. Finally, NSF has developed a tool ("SleepLife") that translates data retrieved from all commercially available sleep trackers into a personal sleep tracking record. This product has been tested rigorously for two years and publicly released in January 2016. These developments present the timely opportunity to test a new paradigm for patient and physician communication using objective patient data (sleep).

The study team will utilize a combination of observational and interventional study designs to achieve study objectives.

Study Type

Interventional

Enrollment (Anticipated)

200

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

Inclusion Criteria:

  1. 18 and older
  2. Have insomnia as identified by electronic record and/or a validated questionnaire
  3. Prescription medication for insomnia with International Classification of Disease (ICD) codes: 327.*, 780.5*, 347.*; icd-10's G47* and medications: Ambien (zolpidem), Belsomra (suvorexant), Butisol (butabarbital), Doral (quazepam), Edluar (zolpidem), Estazolam, Flurazepam, Halcion (triazolam), Hetlioz (tasimelteon), Intermezzo (zolpidem), Lunesta (eszopiclone), Restoril (temazepam), Rozerem (ramelteon), Seconal (secobarbital), Silenor (doxepin), Sonata (zaleplon), and Zolpimist (zolpidem)

3. English speaking 4. Consentable in-person 5. Have access to a telephone with smart phone capabilities. (iOS/Android)

Exclusion Criteria:

  1. Not English speaking
  2. Have ischemic or hemorrhagic cerebrovascular disease affecting collection of study outcomes (via ICD codes I6*, 43*)
  3. History of dementia (via ICD codes F0*, 290*)
  4. History of Bipolar/Schizophrenia/Depression (via ICD codes F2*, F31*, 296*, 295*)
  5. History of alcohol or substance abuse (via ICD codes F1*, 304*, 303*)
  6. Incarcerated/Long Term Care (LTC)
  7. Unable to complete study questionnaires due to hearing loss or blindness

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: SleepLife Application w/FitBit

Subject receives a FitBit. Subjects receive access to the SleepLife Application. Subjects receive training and assistance setting up use and access to the SleepLife Application.

Subject physicians will receive subject sleep data. Subject and physicians have the option of messaging each other through the SleepLife application.

Subjects receive a FitBit. Subjects receive access to the SleepLife Application. Subjects receive training and assistance setting up use and access to the SleepLife Application.

Subjects' physicians will receive subject sleep data. Subjects and physicians have the option of messaging each other through the SleepLife application.

Active Comparator: FitBit w/Minimal to No SleepLife App.

Subjects will receive a FitBit Subjects will be told about the SleepLife Application (but not be shown how to access it).

Subjects will receive no training with regard to how to access SleepLife Application.

Subjects' physicians will receive no subject sleep data.

Subjects will receive a FitBit. Subjects will be told about the SleepLife Application (but not be shown how to access it).

Subjects will receive no training with regard to how to access SleepLife Application.

Subjects' physicians will receive no subject sleep data.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of physicians using a commercially available sleep tracker assessed by the "Physician Satisfaction/Communication" questionnaire who saw an improvement in physician-patient dialogue regarding sleep and related behaviors and habits
Time Frame: Six Months
For patient-physician communications from the physicians' end, the team will collect all scores, ranging from 1 to 5, for all the "Communication" questions in the "Physician Satisfaction/Communication" questionnaire. The scores will be summed up as the total communication score from physician, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the physician is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. We will use linear regression model, and select relevant variables using Bayesian information criterion (BIC) in a step-wise manner. The SleepLife app will be pulling time-to-sleep (TST), amount of time in minutes to sleep, number of awakenings greater than 5 minutes, and sleep efficiency.
Six Months
Number of patient-physician communicationdialog assessed by using a commercially available sleep tracker assessed by the "Patient Satisfaction" questionnaire.
Time Frame: Six Months
For patient-physician communications from the patients' end, the team will collect all the scores, ranging from 1 to 5, for all the "Communication" questions in the "Patient Satisfaction" questionnaire. The scores will be summed up as the total communication score from the patients' end, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the patient is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. Considering the linear responses and the cluster design, the team will use generalized estimating equation (GEE) model with an identity link function, and the team will select relevant variables using QIC in a step-wise manner.
Six Months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of physician subjects with satisfaction with sleep counseling that improves when presented with objective patient sleep data.
Time Frame: Six Months
For physicians' satisfactory score, the team will collect all the scores, ranging from 1 to 5, for all the "GS" questions in the "Physician Satisfaction/Communication" questionnaire. The scores will be summed up as the total physicians' satisfaction score, and the total score will be treated as continuous response variable. Then a binary variable indicating whether the physician is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. The team will use linear regression model, and select relevant variables using BIC in a step-wise manner.
Six Months
Number of patients who feel that their communication with their physician has improved as a result of the program as measured by the "Patient Satisfaction" survey.
Time Frame: Six Months
For patients' satisfaction, the team will collect all scores, ranging from 1 to 5, for all the "General Satisfaction" questions in the "Patient Satisfaction" questionnaire. These scores will be summed up as the total patients' satisfaction score for the treatment and interaction with the physician, as a result of the program. Then a binary variable indicating whether the patient is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. Considering the linear responses and the cluster design, the team will use GEE model with an identity link function, and we will select relevant variables using QIC in a step-wise manner.
Six Months

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
To determine if data improves over time for measures related to total sleep time (TST) and satisfaction with sleep.
Time Frame: Six Months
the team will collect all the scores, ranging from 0 to 100, for all the "Sleep Outcomes" questions in the sleep outcome questionnaire. These scores will be summed up as the total patients' sleep outcomes. Then a binary variable indicating whether the patient is in the intervention (=1) or control (=0) arm will be treated as the main explanatory variable, a continuous variable regarding the time where the measurements are recorded, and the set of general demographic variables (age, race, gender, etc) will be used as covariates. Considering the linear responses and the cluster design, we will use GEE model with an identity link function, and we will select relevant variables using QIC in a step-wise manner.
Six Months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Babar Khan, MD, Regenstrief Institute, Inc.

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 10, 2018

Primary Completion (Anticipated)

December 31, 2018

Study Completion (Anticipated)

February 28, 2019

Study Registration Dates

First Submitted

May 3, 2018

First Submitted That Met QC Criteria

January 3, 2019

First Posted (Actual)

January 7, 2019

Study Record Updates

Last Update Posted (Actual)

January 7, 2019

Last Update Submitted That Met QC Criteria

January 3, 2019

Last Verified

January 1, 2019

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • Merck - 34

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

The Regenstrief research team will use Protected Health Information (PHI) to conduct this study. Data that does not identify the subject will be shared with Merck Sharp & Dohme Corp. and the National Sleep Foundation. At this time, that is only the study visit day.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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