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dc.contributor.authorAndrews, Jacob A.
dc.contributor.authorCraven, Michael P.
dc.contributor.authorLang, Alexandra
dc.contributor.authorGuo, Boliang
dc.contributor.authorMorriss, Richard K.
dc.contributor.authorHollis, Chris P.
dc.date.accessioned2022-08-02T10:30:33Z
dc.date.available2022-08-02T10:30:33Z
dc.date.issued2022
dc.identifier.citationAndrews, J. A., Craven, M. P., Lang, A., Guo, B., Morriss, R. K. & Hollis, C. P. (2022). Making remote measurement technology work in multiple sclerosis, epilepsy and depression: survey of healthcare professionals. BMC Medical Informatics and Decision Making, 22, pp.125.en_US
dc.identifier.other10.1186/s12911-022-01856-z
dc.identifier.urihttp://hdl.handle.net/20.500.12904/15671
dc.description© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.en_US
dc.description.abstractBACKGROUND: Epilepsy, multiple sclerosis (MS) and depression are long term, central nervous system disorders which have a significant impact on everyday life. Evaluating symptoms of these conditions is problematic and typically involves repeated visits to a clinic. Remote measurement technology (RMT), consisting of smartphone apps and wearables, may offer a way to improve upon existing methods of managing these conditions. The present study aimed to establish the practical requirements that would enable clinical integration of data from patients' RMT, according to healthcare professionals. METHODS: This paper reports findings from an online survey of 1006 healthcare professionals currently working in the care of people with epilepsy, MS or depression. The survey included questions on types of data considered useful, how often data should be collected, the value of RMT data, preferred methods of accessing the data, benefits and challenges to RMT implementation, impact of RMT data on clinical practice, and requirement for technical support. The survey was presented on the JISC online surveys platform. RESULTS: Among this sample of 1006 healthcare professionals, respondents were positive about the benefits of RMT, with 73.2% indicating their service would be likely or highly likely to benefit from the implementation of RMT in patient care plans. The data from patients' RMT devices should be made available to all nursing and medical team members and could be reviewed between consultations where flagged by the system. However, results suggest it is also likely that RMT data would be reviewed in preparation for and during a consultation with a patient. Time to review information is likely to be one of the greatest barriers to successful implementation of RMT in clinical practice. CONCLUSIONS: While further work would be required to quantify the benefits of RMT in clinical practice, the findings from this survey suggest that a wide array of clinical team members treating epilepsy, MS and depression would find benefit from RMT data in the care of their patients. Findings presented could inform the implementation of RMT and other digital interventions in the clinical management of a range of neurological and mental health conditions.
dc.description.urihttps://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-01856-zen_US
dc.language.isoenen_US
dc.subjectDepressionen_US
dc.subjectEpilepsyen_US
dc.subjectHealth personnelen_US
dc.subjectMultiple sclerosisen_US
dc.titleMaking remote measurement technology work in multiple sclerosis, epilepsy and depression: survey of healthcare professionalsen_US
dc.typeArticleen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
rioxxterms.versionNAen_US
rioxxterms.typeJournal Article/Reviewen_US
refterms.dateFOA2022-09-30T10:46:38Z
refterms.panelUnspecifieden_US
refterms.dateFirstOnline2022-05-07
html.description.abstractBACKGROUND: Epilepsy, multiple sclerosis (MS) and depression are long term, central nervous system disorders which have a significant impact on everyday life. Evaluating symptoms of these conditions is problematic and typically involves repeated visits to a clinic. Remote measurement technology (RMT), consisting of smartphone apps and wearables, may offer a way to improve upon existing methods of managing these conditions. The present study aimed to establish the practical requirements that would enable clinical integration of data from patients' RMT, according to healthcare professionals. METHODS: This paper reports findings from an online survey of 1006 healthcare professionals currently working in the care of people with epilepsy, MS or depression. The survey included questions on types of data considered useful, how often data should be collected, the value of RMT data, preferred methods of accessing the data, benefits and challenges to RMT implementation, impact of RMT data on clinical practice, and requirement for technical support. The survey was presented on the JISC online surveys platform. RESULTS: Among this sample of 1006 healthcare professionals, respondents were positive about the benefits of RMT, with 73.2% indicating their service would be likely or highly likely to benefit from the implementation of RMT in patient care plans. The data from patients' RMT devices should be made available to all nursing and medical team members and could be reviewed between consultations where flagged by the system. However, results suggest it is also likely that RMT data would be reviewed in preparation for and during a consultation with a patient. Time to review information is likely to be one of the greatest barriers to successful implementation of RMT in clinical practice. CONCLUSIONS: While further work would be required to quantify the benefits of RMT in clinical practice, the findings from this survey suggest that a wide array of clinical team members treating epilepsy, MS and depression would find benefit from RMT data in the care of their patients. Findings presented could inform the implementation of RMT and other digital interventions in the clinical management of a range of neurological and mental health conditions.en_US
rioxxterms.funder.project94a427429a5bcfef7dd04c33360d80cden_US


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