The Re-Engineered Discharge for Diabetes Computer Adaptive Test (REDD-CAT): New patient-reported outcome measures that evaluate social determinants of health for persons with Type 2 Diabetes Mellitus

IntroductionType 2 diabetes is a global health priority. People with diabetes are more likely to experience mental health problems relative to people without diabetes. Diabetes guidelines recommend assessment of depression and diabetes distress during diabetes care. This systematic review will examine the effect of routinely assessing and addressing depression and diabetes distress using patient-reported outcome measures in improving outcomes among adults with type 2 diabetes.Methods and analysisMEDLINE, Embase, CINAHL Complete, PsycInfo, The Cochrane Library and Cochrane Central Register of Controlled Trials will be searched using a prespecified strategy using a prespecified Population, Intervention, Comparator, Outcomes, Setting and study design strategy. The date range of the search of all databases will be from inception to 3 August 2020. Randomised controlled trials, interrupted time-series studies, prospective and retrospective cohort studies, case–control studies and analytical cross-sectional studies published in peer-reviewed journals in the English language will be included. Two review authors will independently screen abstracts and full texts with disagreements resolved by a third reviewer, if required, using Covidence software. Two reviewers will undertake risk of bias assessment using checklists appropriate to study design. Data will be extracted using prespecified template. A narrative synthesis will be conducted, with a meta-analysis, if appropriate.Ethics and disseminationEthics approval is not required for this review of published studies. Presentation of results will follow the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidance. Findings will be disseminated via peer-reviewed publication and conference presentations.PROSPERO registration numberCRD42020200246.

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Validation of two generic patient-reported outcome measures in patients with type 2 diabetes

Health and Quality of Life Outcomes ◽

10.1186/1477-7525-5-47 ◽

2007 ◽

Vol 5 (1) ◽

Cited By ~ 41

Author(s):

Louis S Matza ◽

Kristina S Boye ◽

Nicole Yurgin

Keyword(s):

Type 2 Diabetes ◽

Outcome Measures ◽

Patient Reported Outcome Measures ◽

Patient Reported Outcome ◽

Patient Reported

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Patient-reported outcomes in type 2 diabetes mellitus: patients’ and primary care physicians’ perspectives in the Spanish health care system

Patient Preference and Adherence ◽

10.2147/ppa.s87005 ◽

2015 ◽

pp. 1413 ◽

Cited By ~ 1

Author(s):

Elena Labrador Barba ◽

Josep Franch Nadal ◽

Carmen Gomez Garcia ◽

Pilar Buil-Cosiales ◽

Jose Manuel Millaruelo ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Primary Care ◽

Health Care ◽

Type 2 Diabetes Mellitus ◽

Primary Care Physicians ◽

Patient Reported Outcomes ◽

Patient Reported ◽

Spanish Health

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Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes (Preprint)

10.2196/preprints.8122 ◽

2017 ◽

Author(s):

James Weatherall ◽

Yurek Paprocki ◽

Theresa M Meyer ◽

Ian Kudel ◽

Edward A Witt

Keyword(s):

Physical Activity ◽

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Pilot Study ◽

Patient Reported Outcomes ◽

Sleep Problems ◽

Health Data ◽

Patient Reported

BACKGROUND Few studies assessing the correlation between patient-reported outcomes and patient-generated health data from wearable devices exist. OBJECTIVE The aim of this study was to determine the direction and magnitude of associations between patient-generated health data (from the Fitbit Charge HR) and patient-reported outcomes for sleep patterns and physical activity in patients with type 2 diabetes mellitus (T2DM). METHODS This was a pilot study conducted with adults diagnosed with T2DM (n=86). All participants wore a Fitbit Charge HR for 14 consecutive days and completed internet-based surveys at 3 time points: day 1, day 7, and day 14. Patient-generated health data included minutes asleep and number of steps taken. Questionnaires assessed the number of days of exercise and nights of sleep problems per week. Means and SDs were calculated for all data, and Pearson correlations were used to examine associations between patient-reported outcomes and patient-generated health data. All respondents provided informed consent before participating. RESULTS The participants were predominantly middle-aged (mean 54.3, SD 13.3 years), white (80/86, 93%), and female (50/86, 58%). Use of oral T2DM medication correlated with the number of mean steps taken (r=.35, P=.001), whereas being unaware of the glycated hemoglobin level correlated with the number of minutes asleep (r=−.24, P=.04). On the basis of the Fitbit data, participants walked an average of 4955 steps and slept 6.7 hours per day. They self-reported an average of 2.0 days of exercise and 2.3 nights of sleep problems per week. The association between the number of days exercised and steps walked was strong (r=.60, P<.001), whereas the association between the number of troubled sleep nights and minutes asleep was weaker (r=.28, P=.02). CONCLUSIONS Fitbit and patient-reported data were positively associated for physical activity as well as sleep, with the former more strongly correlated than the latter. As extensive patient monitoring can guide clinical decisions regarding T2DM therapy, passive, objective data collection through wearables could potentially enhance patient care, resulting in better patient-reported outcomes.

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