Khetrapal, P., Stafford, R., Ó Scanaill, P. et al. (15 more authors) (2022) Measuring patient compliance with remote monitoring following discharge from hospital after major surgery (DREAMPath): protocol for a prospective observational study. JMIR Research Protocols, 11 (4). e30638. ISSN 1929-0748
Abstract
Background:
The incidence of major surgery is on the rise globally, and more than 20% of patients are readmitted to hospital following discharge from hospital. During their hospital stay, patients are monitored for early detection of clinical deterioration, which includes regularly measuring physiological parameters such as blood pressure, heart rate, respiratory rate, temperature, and pulse oximetry. This monitoring ceases upon hospital discharge, as patients are deemed clinically stable. Monitoring after discharge is relevant to detect adverse events occurring in the home setting and can be made possible through the development of digital technologies and mobile networks. Smartwatches and other technological devices allow patients to self-measure physiological parameters in the home setting, and Bluetooth connectivity can facilitate the automatic collection and transfer of this data to a secure server with minimal input from the patient.
Objective:
This paper presents the protocol for the DREAMPath (Domiciliary Recovery After Medicalization Pathway) study, which aims to measure compliance with a multidevice remote monitoring kit after discharge from hospital following major surgery.
Methods:
DREAMPath is a single-center, prospective, observational, cohort study, comprising 30 patients undergoing major intracavity surgery. The primary outcome is to assess patient compliance with wearable and interactive smart technology in the first 30 days following discharge from hospital after major surgery. Secondary outcomes will explore the relation between unplanned health care events and physiological data collected in the study, as well as to explore a similar relationship with daily patient-reported outcome measures (Quality of Recovery–15 score). Secondary outcomes will be analyzed using appropriate regression methods. Cardiopulmonary exercise testing data will also be collected to assess correlations with wearable device data.
Results:
Recruitment was halted due to COVID-19 restrictions and will progress once research staff are back from redeployment. We expect that the study will be completed in the first quarter of 2022.
Conclusions:
Digital health solutions have been recently made possible due to technological advances, but urgency in rollout has been expedited due to COVID-19. The DREAMPath study will inform readers about the feasibility of remote monitoring for a patient group that is at an increased risk of acute deterioration.
Trial Registration:
ISRCTN Registry ISRCTN62293620; https://www.isrctn.com/ISRCTN62293620
International Registered Report Identifier (IRRID):
DERR1-10.2196/30638
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ©Pramit Khetrapal, Ronnie Stafford, Pádraig Ó Scanaill, Huriye Kocadag, Constantinos Timinis, Angela H L Chang, Adamos Hadjivasiliou, Yansong Liu, Olivia Gibbs, Eleanor Pickford, David Walker, Hilary Baker, Jacqueline Duncan, Melanie Tan, Norman Williams, James Catto, Ivana Drobnjak, John Kelly. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 06.04.2022. 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 JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included. |
Keywords: | digital health; telemonitoring; remote monitoring; telehealth; surgery; hospital; compliance; patient monitoring; wearable technology; smart devices |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Sheffield Teaching Hospitals |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 May 2022 14:40 |
Last Modified: | 03 May 2022 14:40 |
Status: | Published |
Publisher: | JMIR Publications |
Refereed: | Yes |
Identification Number: | 10.2196/30638 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186127 |