Introduction: Sleep tracker data have not been utilized routinely in sleep-related disorders and their management. Sleep-related disorders are common in primary care practice and incorporating sleep tracker data may help in improving patient care. We conducted a pilot study to assess the feasibility of a sleep program using the Fitbit Charge 2™ device and SleepLife® application. The main aim of the study was to examine whether a program using a commercially available wearable sleep tracker device providing objective sleep data would improve communication in primary care settings between patients and their providers. Secondary aims included whether patient satisfaction with care would improve as result of the program.
Methods: A prospective, randomized, parallel group, observational pilot study was conducted in 20 primary care clinics in Indianapolis, IN from June 2018 to February 2019. Inclusion criteria included patients over the age of 18, have a diagnosis of insomnia identified by electronic medical record and/or a validated questionnaire, and were on a prescription sleep aid. The study was not specific to any sleep aid prescription, branded or generic, and was not designed to evaluate a drug or drug class. Each primary care clinic was randomized to either the SleepLife® intervention or the control arm. All patients were provided with a Fitbit Charge 2™ device. Only patients in the intervention arm were educated on how to use the SleepLife® application. Physicians in the intervention arm were set up with the SleepLife® portal on their computers.
Results: Forty-nine physicians and 75 patients were enrolled in the study. Patients had a mean age of 57 (SD 12.8) years and 61% were female. Mean age of physicians was 47 (SD 10.6) years. Patients showed high rates of involvement in the program with 83% completing all survey questions. Physician survey completion rate was 55%. Only one physician logged into the SleepLife portal to check their patients' sleep status. At the end of the 6-week intervention, patients' composite general satisfaction scores with sleep health management decreased significantly in the intervention arm when compared to controls (p = 0.03). Patients' satisfaction with communication also decreased significantly in the intervention group (p = 0.01). The sleep outcomes, which were calculated on the basis of study questionnaire answers, improved significantly in the intervention group as compared to the control group (p = 0.04). Physician communication satisfaction scores remained unchanged (p = 0.12).
Conclusions: SleepLife® and its related physician portal can facilitate physician-patient communication, and it captures patient sleep outcomes including behaviors and habits. Patients were highly engaged with the program, while physicians did not demonstrate engagement. The study design and questionnaires do not specifically address the reasons behind the decreased patient satisfaction with care and communication, but it was perceived to be a result of physician non-responsiveness. Sleep quality scores on the other hand showed an improvement among SleepLife® users, suggesting that patients may have implemented good sleep practices on their own. Given that it was a feasibility study, and the sample size was small, we were not able to make major inferences regarding the difference between sleep disorder types. Additionally, we excluded patients with a history of alcohol use, substance abuse, or depression because of concerns that they may affect sleep independently. To promote the growth of technology in primary care, further research incorporating results from this study and physician engagement techniques should be included.
Keywords: Communication; Primary care; Sleep; Smartphone app; Technology; Tracker.
© 2022. The Author(s).