Predictors for response to electronic patient-reported outcomes in routine care in patients with rheumatoid arthritis: a retrospective cohort study
Tóm tắt
Routine collection of electronic patient-reported outcomes (ePROs) can improve clinical care. However, a low response rate may counteract the benefits. To optimize adoption, the aim of this study was to investigate which patient factors and/or timing of the invitation predicted response to ePROs sent prior to consultations in patients with rheumatoid arthritis. We performed a retrospective database study with clinical data collected as part of usual care from the electronic medical records at Reade Amsterdam. The dataset comprised the email invitations to complete the ePRO sent prior to consultation. Multiple patient factors and factors defining the timing of the invitation were investigated if they predicted response to the ePRO through a multivariable logistic generalized estimating equation analysis. In total, 17.070 ePRO invitations were sent to 3194 patients (mean age 60 (SD 14), 74% female), of which 40% was completed. Patients between 55 and 73 years (OR 1.39, 95%CI 1.09–1.77) and with higher social economic status (SES) (OR 1.51, 95%CI 1.22–1.88) had significantly higher odds for completing the ePRO, while patients living in an urban area had lower odds (OR 0.69, 95% CI 0.62–0.76). In year 4 after implementation, the OR was increased to 3.69 (95% CI 2.91–4.90). The implementation of ePROs in daily clinical practice needs improvement since 40% of the ePROs sent prior to consultations were completed. Patients that had higher odds to report the next ePRO were between the age of 55–73, had a higher socio-economic status, and were residents in a rural area. The adoption of reporting the PRO increased over time, but the timing of the prompt did not predict response. Additional research is needed to understand ePRO completion, especially for patients with lower socio-economic status.
Tài liệu tham khảo
Chen J, Ou L, Hollis SJ (2013) A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Health Serv Res 13:211. https://doi.org/10.1186/1472-6963-13-211
Seppen BF, Wiegel J, L’Ami MJ, Dos DuarteSantosRico S, Catarinella FS, Turkstra F, Boers M, Bos WH (2020) Feasibility of self-monitoring rheumatoid arthritis with a smartphone app: results of two mixed-methods pilot studies. JMIR Form Res. 4(9):e20165. https://doi.org/10.2196/20165
Seppen B, Wiegel J, Ter Wee MM, van Schaardenburg D, Roorda LD, Nurmohamed MT, Boers M, Bos WH (2022) Smartphone-assisted patient-initiated care versus usual care in patients with rheumatoid arthritis and low disease activity: a randomized controlled trial. Arthritis Rheumatol 74(11):1737–1745. https://doi.org/10.1002/art.42292
Schwartzberg L (2016) Electronic patient-reported outcomes: the time is ripe for integration into patient care and clinical research. Am Soc Clin Oncol Educ 35:e89-96. https://doi.org/10.1200/edbk_158749
Solomon DH, Rudin RS (2020) Digital health technologies: opportunities and challenges in rheumatology. Nat Rev Rheumatol 16(9):525–535. https://doi.org/10.1038/s41584-020-0461-x
Fautrel B, Alten R, Kirkham B, de la Torre I, Durand F, Barry J, Holzkaemper T, Fakhouri W, Taylor PC (2018) Call for action: how to improve use of patient-reported outcomes to guide clinical decision making in rheumatoid arthritis. Rheumatol Int 38(6):935–947. https://doi.org/10.1007/s00296-018-4005-5
Colls J, Lee YC, Xu C, Corrigan C, Lu F, Marquez-Grap G, Murray M, Suh DH, Solomon DH (2021) Patient adherence with a smartphone app for patient-reported outcomes in rheumatoid arthritis. Rheumatology 60(1):108–112. https://doi.org/10.1093/rheumatology/keaa202
Wiegel J, Seppen BF, Nurmohamed MT, Bos WH, Ter Wee MM (2022) Who stop telemonitoring disease activity and who adhere: a prospective cohort study of patients with inflammatory arthritis. BMC Rheumatol 6(1):73. https://doi.org/10.1186/s41927-022-00303-w
Sun EY, Alvarez C, Callahan LF, Sheikh SZ (2022) The disparities in patient portal use among patients with rheumatic and musculoskeletal diseases: retrospective cross-sectional study. J Med Internet Res 24(8):e38802. https://doi.org/10.2196/38802
Müskens WD, van RongenDartel SAA, Vogel C, Huis A, Adang EMM, van Riel P (2021) Telemedicine in the management of rheumatoid arthritis: maintaining disease control with less health-care utilization. Rheumatol Adv Pract. 5(1):rkaa079. https://doi.org/10.1093/rap/rkaa079
Renskers L, van RongenDartel SA, Huis AM, van Riel PL (2020) Patients’ experiences regarding self-monitoring of the disease course: an observational pilot study in patients with inflammatory rheumatic diseases at a rheumatology outpatient clinic in The Netherlands. BMJ Open 10(8):e033321. https://doi.org/10.1136/bmjopen-2019-033321
Bidargaddi N, Almirall D, Murphy S, Nahum-Shani I, Kovalcik M, Pituch T, Maaieh H, Strecher V (2018) To prompt or not to prompt? A microrandomized trial of time-varying push notifications to increase proximal engagement with a mobile health app. JMIR mHealth uHealth. 6(11):e10123. https://doi.org/10.2196/10123
MacPherson MM, Merry KJ, Locke SR, Jung ME (2019) Effects of mobile health prompts on self-monitoring and exercise behaviors following a diabetes prevention program: secondary analysis from a randomized controlled trial. JMIR mHealth uHealth. 7(9):e12956. https://doi.org/10.2196/12956
Pincus T, Castrejon I, Riad M, Obreja E, Lewis C, Krogh NS (2020) Reliability, feasibility, and patient acceptance of an electronic version of a multidimensional health assessment questionnaire for routine rheumatology care: validation and patient preference study. JMIR Form Res. 4(5):e15815. https://doi.org/10.2196/15815
Steenland K, Henley J, Calle E, Thun M (2004) Individual- and area-level socioeconomic status variables as predictors of mortality in a cohort of 179,383 persons. Am J Epidemiol 159(11):1047–1056. https://doi.org/10.1093/aje/kwh129
Ross EL, Jamison RN, Nicholls L, Perry BM, Nolen KD (2020) Clinical integration of a smartphone app for patients with chronic pain: retrospective analysis of predictors of benefits and patient engagement between clinic visits. J Med Internet Res 22(4):e16939. https://doi.org/10.2196/16939
Wiegel J, Seppen B, van der Leeden M, van der Esch M, de Vries R, Bos W (2021) Adherence to telemonitoring by electronic patient-reported outcome measures in patients with chronic diseases: a systematic review. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph181910161
Reiners F, Sturm J, Bouw LJW, Wouters EJM (2019) Sociodemographic factors influencing the use of eHealth in people with chronic diseases. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph16040645
Oinas-Kukkonen H, Harjumaa M (2009) Persuasive systems design: key issues, process model, and system features. Commun Assoc Inf Syst. https://doi.org/10.17705/1cais.0242
Han JH, Sunderland N, Kendall E, Gudes O, Henniker G (2010) Professional practice and innovation: chronic disease, geographic location and socioeconomic disadvantage as obstacles to equitable access to e-health. Health Inf Manag 39(2):30–36. https://doi.org/10.1177/183335831003900205
Neter E, Brainin E (2012) eHealth literacy: extending the digital divide to the realm of health information. J Med Internet Res 14(1):e19. https://doi.org/10.2196/jmir.1619
Nagler RH, Ramanadhan S, Minsky S, Viswanath K (2013) Recruitment and retention for community-based ehealth interventions with populations of low socioeconomic position: strategies and challenges. J Commun 63(1):201–220. https://doi.org/10.1111/jcom.12008
Bos WH, van Tubergen A, Vonkeman HE (2021) Telemedicine for patients with rheumatic and musculoskeletal diseases during the COVID-19 pandemic; a positive experience in the Netherlands. Rheumatol Int 41(3):565–573. https://doi.org/10.1007/s00296-020-04771-6
Seppen BF, Wiegel J, Nurmohamed MT et al (2023) Facilitators and barriers to adhere to monitoring disease activity with ePROs: a focus group study in patients with inflammatory arthritis. Rheumatol Int. https://doi.org/10.1007/s00296-022-05263-5
Krusche M, Klemm P, Grahammer M, Mucke J, Vossen D, Kleyer A, Sewerin P, Knitza J (2020) Acceptance, usage, and barriers of electronic patient-reported outcomes among german rheumatologists: survey study. JMIR mHealth uHealth. 8(7):e18117. https://doi.org/10.2196/18117