Patient-reported outcome measures collected via a web application versus a touchscreen in patients with Systemic Lupus Erythematosus
Authors
Pedersen, Julie Friis ; Høstgaard, Simone
Term
5. Term (Master thesis)
Education
Publication year
2021
Pages
17
Abstract
Baggrund: I Danmark har patienter med reumatologiske sygdomme siden 2006 udfyldt patientrapporterede målinger (PROM) på en touchskærm i ambulatoriet før hver konsultation. Med nye teknologier er der interesse for at indsamle PROM på egen smartphone eller tablet ("bring your own device", BYOD). Denne undersøgelse vurderer, om svar indsamlet via DANBIO’s webapp på en personlig enhed er sammenlignelige med svar fra den traditionelle touchskærm hos patienter med systemisk lupus erythematosus (SLE), en autoimmun sygdom. Formål: At sammenligne klinikkens touchskærm med en hjemmebrugt webapp med SLAQ globalt helbred (fra Systemic Lupus Activity Questionnaire) som primært udfald. Metode: Randomiseret, inden-for-person crossover-undersøgelse, hvor samme deltagere udfyldte PROM på begge enheder i tilfældig rækkefølge med en foruddefineret "washout"-periode imellem. Forskelle i PROM-scorer med 95% konfidensintervaller (KI) blev vurderet for lighed ud fra på forhånd fastsatte ækvivalensgrænser, og en Bland-Altman-analyse (standardmetode til at vurdere, hvor godt to måder at måle stemmer overens) blev brugt til at se grænser for overensstemmelse. Resultater: Der var ækvivalens for SLAQ globalt helbred med en gennemsnitlig forskel på -0,21, 95% KI (-0,64 til 0,23). Alle andre PROM var også ækvivalente, bortset fra VAS global (visuel analog skala for generelt helbred), hvor 95% KI på -1,45 til 6,80 overskred ækvivalensgrænsen på ±5. Forskellen lå dog inden for den minimale klinisk vigtige forskel (MCID) på ±10. 31 ud af 34 deltagere (91,2%) foretrak DANBIO-webappen. Konklusion: For første gang hos SLE-patienter er det vist, at PROM indsamlet på en webapp og på ambulatoriets touchskærm er sammenlignelige. Deltagerne foretrak webappen, og dens bredere implementering forventes at blive et nyttigt værktøj for patienter og sundhedsvæsen til mere individualiseret monitorering.
Background: In Denmark, patients with rheumatic diseases have completed patient-reported outcome measures (PROMs)—self-reported questionnaires about symptoms and health—on a clinic touchscreen before each visit since 2006. As technology advances, there is interest in collecting PROMs on personal devices (“bring your own device,” BYOD). This study examines whether answers collected via the national DANBIO web app on a smartphone or tablet match those from the traditional outpatient touchscreen in patients with systemic lupus erythematosus (SLE), an autoimmune disease. Objective: To compare the clinic touchscreen with a web app used at home, with the SLAQ global health score (from the Systemic Lupus Activity Questionnaire) as the primary outcome. Methods: Randomized within-participant crossover agreement study: the same participants completed PROMs on both devices in random order, with a predefined washout period. Differences in PROM scores with 95% confidence intervals (CI) were assessed for equivalence using prespecified margins, and a Bland–Altman analysis (a standard way to check how closely two measurement methods agree) was used to evaluate limits of agreement. Results: Equivalence was found for the SLAQ global health score, with a mean difference of -0.21, 95% CI (-0.64 to 0.23). All other PROMs were also equivalent except for VAS global (a visual analog scale of overall health), where the 95% CI of -1.45 to 6.80 exceeded the equivalence margin of ±5; however, the difference was within the minimal clinically important difference (MCID) of ±10. Thirty-one of 34 participants (91.2%) preferred the DANBIO web app. Conclusion: In SLE patients, PROMs collected via a web app were comparable to those collected on the clinic touchscreen. Participants strongly preferred the web app, and wider implementation is expected to support more individualized monitoring for patients and healthcare.
[This summary has been rewritten with the help of AI based on the project's original abstract]
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