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Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures

BACKGROUND: Remote patient-reported outcome measure (PROM) data capture can provide useful insights into research and clinical practice and deeper insights can be gained by administering assessments more frequently, for example, in ecological momentary assessment. However, frequent data collection c...

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Autores principales: Harrison, Conrad, Trickett, Ryan, Wormald, Justin, Dobbs, Thomas, Lis, Przemysław, Popov, Vesselin, Beard, David J, Rodrigues, Jeremy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540021/
https://www.ncbi.nlm.nih.gov/pubmed/37707947
http://dx.doi.org/10.2196/47179
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author Harrison, Conrad
Trickett, Ryan
Wormald, Justin
Dobbs, Thomas
Lis, Przemysław
Popov, Vesselin
Beard, David J
Rodrigues, Jeremy
author_facet Harrison, Conrad
Trickett, Ryan
Wormald, Justin
Dobbs, Thomas
Lis, Przemysław
Popov, Vesselin
Beard, David J
Rodrigues, Jeremy
author_sort Harrison, Conrad
collection PubMed
description BACKGROUND: Remote patient-reported outcome measure (PROM) data capture can provide useful insights into research and clinical practice and deeper insights can be gained by administering assessments more frequently, for example, in ecological momentary assessment. However, frequent data collection can be limited by the burden of multiple, lengthy questionnaires. This burden can be reduced with computerized adaptive testing (CAT) algorithms that select only the most relevant items from a PROM for an individual respondent. In this paper, we propose “ecological momentary computerized adaptive testing” (EMCAT): the use of CAT algorithms to reduce PROM response burden and facilitate high-frequency data capture via a smartphone app. We develop and pilot a smartphone app for performing EMCAT using a popular hand surgery PROM. OBJECTIVE: The aim of this study is to determine the feasibility of EMCAT as a system for remote PROM administration. METHODS: We built the EMCAT web app using Concerto, an open-source CAT platform maintained by the Psychometrics Centre, University of Cambridge, and hosted it on an Amazon Web Service cloud server. The platform is compatible with any questionnaire that has been parameterized with item response theory or Rasch measurement theory. For this study, the PROM we chose was the patient evaluation measure, which is commonly used in hand surgery. CAT algorithms were built using item response theory models derived from UK Hand Registry data. In the pilot study, we enrolled 40 patients with hand trauma or thumb-base arthritis, across 2 sites, between July 13, 2022, and September 14, 2022. We monitored their symptoms with the patient evaluation measure, via EMCAT, over a 12-week period. Patients were assessed thrice weekly, once daily, or thrice daily. We additionally administered full-length PROM assessments at 0, 6, and 12 weeks, and the User Engagement Scale at 12 weeks. RESULTS: The use of EMCAT significantly reduced the length of the PROM (median 2 vs 11 items) and the time taken to complete it (median 8.8 seconds vs 1 minute 14 seconds). Very similar scores were obtained when EMCAT was administered concurrently with the full-length PROM, with a mean error of <0.01 on a logit (z score) scale. The median response rate in the daily assessment group was 93%. The median perceived usability score of the User Engagement Scale was 4.0 (maximum possible score 5.0). CONCLUSIONS: EMCAT reduces the burden of PROM assessments, enabling acceptable high-frequency, remote PROM data capture. This has potential applications in both research and clinical practice. In research, EMCAT could be used to study temporal variations in symptom severity, for example, recovery trajectories after surgery. In clinical practice, EMCAT could be used to monitor patients remotely, prompting early intervention if a patient’s symptom trajectory causes clinical concern. TRIAL REGISTRATION: ISRCTN 19841416; https://www.isrctn.com/ISRCTN19841416
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spelling pubmed-105400212023-09-30 Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures Harrison, Conrad Trickett, Ryan Wormald, Justin Dobbs, Thomas Lis, Przemysław Popov, Vesselin Beard, David J Rodrigues, Jeremy J Med Internet Res Original Paper BACKGROUND: Remote patient-reported outcome measure (PROM) data capture can provide useful insights into research and clinical practice and deeper insights can be gained by administering assessments more frequently, for example, in ecological momentary assessment. However, frequent data collection can be limited by the burden of multiple, lengthy questionnaires. This burden can be reduced with computerized adaptive testing (CAT) algorithms that select only the most relevant items from a PROM for an individual respondent. In this paper, we propose “ecological momentary computerized adaptive testing” (EMCAT): the use of CAT algorithms to reduce PROM response burden and facilitate high-frequency data capture via a smartphone app. We develop and pilot a smartphone app for performing EMCAT using a popular hand surgery PROM. OBJECTIVE: The aim of this study is to determine the feasibility of EMCAT as a system for remote PROM administration. METHODS: We built the EMCAT web app using Concerto, an open-source CAT platform maintained by the Psychometrics Centre, University of Cambridge, and hosted it on an Amazon Web Service cloud server. The platform is compatible with any questionnaire that has been parameterized with item response theory or Rasch measurement theory. For this study, the PROM we chose was the patient evaluation measure, which is commonly used in hand surgery. CAT algorithms were built using item response theory models derived from UK Hand Registry data. In the pilot study, we enrolled 40 patients with hand trauma or thumb-base arthritis, across 2 sites, between July 13, 2022, and September 14, 2022. We monitored their symptoms with the patient evaluation measure, via EMCAT, over a 12-week period. Patients were assessed thrice weekly, once daily, or thrice daily. We additionally administered full-length PROM assessments at 0, 6, and 12 weeks, and the User Engagement Scale at 12 weeks. RESULTS: The use of EMCAT significantly reduced the length of the PROM (median 2 vs 11 items) and the time taken to complete it (median 8.8 seconds vs 1 minute 14 seconds). Very similar scores were obtained when EMCAT was administered concurrently with the full-length PROM, with a mean error of <0.01 on a logit (z score) scale. The median response rate in the daily assessment group was 93%. The median perceived usability score of the User Engagement Scale was 4.0 (maximum possible score 5.0). CONCLUSIONS: EMCAT reduces the burden of PROM assessments, enabling acceptable high-frequency, remote PROM data capture. This has potential applications in both research and clinical practice. In research, EMCAT could be used to study temporal variations in symptom severity, for example, recovery trajectories after surgery. In clinical practice, EMCAT could be used to monitor patients remotely, prompting early intervention if a patient’s symptom trajectory causes clinical concern. TRIAL REGISTRATION: ISRCTN 19841416; https://www.isrctn.com/ISRCTN19841416 JMIR Publications 2023-09-14 /pmc/articles/PMC10540021/ /pubmed/37707947 http://dx.doi.org/10.2196/47179 Text en ©Conrad Harrison, Ryan Trickett, Justin Wormald, Thomas Dobbs, Przemysław Lis, Vesselin Popov, David J Beard, Jeremy Rodrigues. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.09.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Harrison, Conrad
Trickett, Ryan
Wormald, Justin
Dobbs, Thomas
Lis, Przemysław
Popov, Vesselin
Beard, David J
Rodrigues, Jeremy
Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
title Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
title_full Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
title_fullStr Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
title_full_unstemmed Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
title_short Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
title_sort remote symptom monitoring with ecological momentary computerized adaptive testing: pilot cohort study of a platform for frequent, low-burden, and personalized patient-reported outcome measures
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540021/
https://www.ncbi.nlm.nih.gov/pubmed/37707947
http://dx.doi.org/10.2196/47179
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