Session Information
Session Type: ACR Poster Session A
Session Time: 9:00AM-11:00AM
Background/Purpose: Data capture of patient reported outcomes (PROs) is gradually shifting from data collection on paper in medical office to use of computer or mobile based technologies between doctor visits. Concerns have been raised that patients may have limited interest in contributing data over time, or that they may only record new data when there has been a change in their clinical status. We evaluated the patterns and factors associated with longitudinal PRO data capture among participants in the PCORI-funded Patient Powered Research Network for adult rheumatologic conditions, ArthritisPower.
Methods: Patients in the registry were asked to voluntarily complete PROs including the RAPID3 and 4 PROMIS instruments (pain interference, physical function, fatigue, and sleep disturbance) plus disease-specific information via a mobile application (App) on their smartphone or computer. We evaluated the average time assessment it took patients to record each of the instruments and the total number of unique days that patients recorded PROs. Given the newness of the registry (launched late 2015), longitudinal data was defined as contributing at least 2 sets of PROs on unique calendar days. We tested the hypothesis that patients would contribute longitudinal data only when at least one of their scores exceeded a minimally important difference (MID) of any of the 5 PROs examined (generally 2-3 units for PROMIS instruments; 3.6 units for RAPID3). Demographic factors associated with multiple PRO reports were identified using logistic regression among patients who had been enrolled in the registry for at least 3 months.
Results: At the time of analysis, ArthritisPower had recruited 2,103 patients, most (approximately 68%) had RA, and 20% provided their Twitter handle. Average (SD) age was 50 (12); 87% were women. The mean assessment time for each of the PROMIS instruments ranged from a low of 16 seconds (sleep disturbance) to a high of 105 seconds (RAPID3). The average score for pain interference was 64.3 (SD: 6.3), physical function 37.5 (6.5), sleep disturbance 59.3 (8.4), fatigue 64.2 (8.4), and RAPID3 15.7 (5.3). Of 1,946 patients who registered the Smartphone App more than 3 months prior to analysis, 20.6% never contributed any PRO information, 53.3% answered once, and 26.1% answered at least twice. Among patients with longitudinal data (>=2 assessments), the mean change score of PROs between pairwise PRO assessments was <1 point for all instruments (Table). Only 23.1% of patients contributing longitudinal data had a change greater than the MID in any of the 5 PRO measures. Patients with RA (OR: 1.54, 95% CI: 1.14-2.06), biologic use (2.12, 1.43-3.15), and those with Twitter accounts (1.40, 1.08-1.82) were more likely to contribute longitudinal PRO data in the absence of regular reminders.
Conclusion: Multiple factors were associated with patient willingness to contribute longitudinal PRO data. Importantly, some patients were willing to contribute longitudinal PRO data even without a change in their health state exceeding any MID and without physicians’ requests. Additional efforts are needed to engage patients to contribute PRO data over time, and to maximize patient engagement.
Tables: Mean change between 1st and 2nd visit among patients with longitudinal data | |||
Mean Change from 1st to 2nd Visit |
Absolute mean change from 1st to 2nd Visit |
% of patients exceeding change > MID |
|
PROMIS Physical function | -0.4 (3.8) | 2.7 (2.7) | 34.2% |
PROMIS Pain Interference | -0.4 (5.4) | 3.9 (3.6) | 52.3% |
PROMIS Sleep Disturbance | 0.2 (6.1) | 4.6 (4.0) | 56.0% |
PROMIS fatigue | -0.03 (6.6) | 4.8 (4.4) | 55.6% |
RAPID3 | 0.2 (3.8) | 2.8 (2.6) | 29.8% |
MID: Minimally important difference (3 points for PROMIS instruments and 3.6 for RAPID3) |
To cite this abstract in AMA style:
Yun H, Nowell WB, Willig J, Beaumont J, Johnson B, Ginsberg SD, Wiedmeyer C, Crow-Hercher R, Johnson BJ, Yang S, Curtis J. What Factors Relate to Patients Contributing Longitudinal Data Using Smartphone Technology? Findings from RA Patients Participating in Arthritispower Registry [abstract]. Arthritis Rheumatol. 2016; 68 (suppl 10). https://acrabstracts.org/abstract/what-factors-relate-to-patients-contributing-longitudinal-data-using-smartphone-technology-findings-from-ra-patients-participating-in-arthritispower-registry/. Accessed .« Back to 2016 ACR/ARHP Annual Meeting
ACR Meeting Abstracts - https://acrabstracts.org/abstract/what-factors-relate-to-patients-contributing-longitudinal-data-using-smartphone-technology-findings-from-ra-patients-participating-in-arthritispower-registry/