Feasibility, usability and acceptance of weekly electronic patient-reported outcomes among patients receiving pelvic CT- or online MR-guided radiotherapy – A prospective pilot study

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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Pilot Study to Integrate Patient Reported Outcomes After Lung Cancer Operations Into The Society of Thoracic Surgeons Database

The Annals of Thoracic Surgery ◽

10.1016/j.athoracsur.2017.01.110 ◽

2017 ◽

Vol 104 (1) ◽

pp. 245-253 ◽

Cited By ~ 22

Author(s):

Onkar V. Khullar ◽

Mohammed H. Rajaei ◽

Seth D. Force ◽

Jose N. Binongo ◽

Yi Lasanajak ◽

...

Keyword(s):

Lung Cancer ◽

Pilot Study ◽

Patient Reported Outcomes ◽

Patient Reported

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Assessing disease experience across the life span for individuals with osteogenesis imperfecta: challenges and opportunities for patient-reported outcomes (PROs) measurement: a pilot study

Orphanet Journal of Rare Diseases ◽

10.1186/s13023-019-1004-x ◽

2019 ◽

Vol 14 (1) ◽

Cited By ~ 2

Author(s):

Laura L. Tosi ◽

◽

Marianne K. Floor ◽

Christina M. Dollar ◽

Austin P. Gillies ◽

...

Keyword(s):

Pilot Study ◽

Osteogenesis Imperfecta ◽

Life Span ◽

Patient Reported Outcomes ◽

Patient Reported ◽

Challenges And Opportunities ◽

Disease Experience

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Patient reported outcomes can improve performance status assessment: a pilot study

Journal of Patient-Reported Outcomes ◽

10.1186/s41687-019-0136-z ◽

2019 ◽

Vol 3 (1) ◽

Cited By ~ 6

Author(s):

Joan E. Broderick ◽

Marcella May ◽

Joseph E. Schwartz ◽

Ming Li ◽

Aaron Mejia ◽

...

Keyword(s):

Pilot Study ◽

Patient Reported Outcomes ◽

Performance Status ◽

Improve Performance ◽

Patient Reported ◽

Status Assessment

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Performance and psychometric properties of lupus impact tracker in assessing patient-reported outcomes in pediatric lupus: Report from a pilot study

Lupus ◽

10.1177/0961203320951264 ◽

2020 ◽

Vol 29 (13) ◽

pp. 1781-1789

Author(s):

Suhas K Ganguli ◽

Joyce S Hui-Yuen ◽

Meenakshi Jolly ◽

Jane Cerise ◽

Barbara Anne Eberhard

Keyword(s):

Systemic Lupus Erythematosus ◽

Pilot Study ◽

Disease Activity ◽

Lupus Erythematosus ◽

Patient Reported Outcomes ◽

Laboratory Data ◽

Damage Index ◽

Systemic Lupus ◽

Patient Reported ◽

The Mean

Objective To evaluate the reliability, validity, feasibility and psychometric performance of the Lupus Impact Tracker (LIT) as a patient reported outcome (PRO) measure tool in pediatric systemic lupus erythematosus (pSLE). Methods This is a prospective, observational, pilot study where patients aged between 12 and 25 years, fulfilling the 1997 ACR classification criteria for SLE, were enrolled. Over 3 consecutive, routine, clinical visits, the patients completed the LIT alongside the Patient-Reported Outcomes Measurement Information System-Short Forms (PROMIS-SFs), Childhood Health Assessment Questionnaire (CHAQ). Rheumatologists completed the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) and the Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC-ACR) Damage Index. Demographic, clinical and laboratory data were also collected. Results Of 46 patients enrolled, 38 patients completed 2 visits and 31 completed all 3 visits. Seventy-eight percent were female, 33% African American, 28% Asian, 15% Caucasian and 17% Hispanic. The mean (SD) age was 17.2 (2.7) years, with a mean (SD) disease duration of 4.6 (3.1) years. The mean (SD) SLEDAI-2K at enrollment was 3.54 (2.96). In the 38 patients who completed two or more visits, intra-class correlation coefficient and Cronbach alpha were calculated to be 0.70 and 0.91 respectively, signifying good reliability of LIT. The LIT showed positive correlation with CHAQ-Disability Index and majority of the PROMIS-SFs parameters. Construct validity was established against clinical disease activity (SLEDAI-2K). Conclusion The preliminary results indicate that the LIT is a reliable and valid instrument to capture PRO in p-SLE. Prospective validation with a larger, multicenter cohort is the next step.

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