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      Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation

      research-article
      , BA, MSc, PhD 1 , , , PhD 1 , , PhD 1 , , MSci 1 , , HNC 2 , , MD 1 , , PhD 3 , , MBChB 4 , , MD 1 , 5 , , PhD 1 , , MBChB 3 , , BMedSci 3 , , PhD 6 , 7 , , PhD 1 , 3 , The ALPACA Study Team 3
      (Reviewer), (Reviewer), (Reviewer)
      JMIR Human Factors
      JMIR Publications
      surgery, shared decision-making, patient participation, mixed methods, surgery, real-time measurement, patient-reported measure, electronic data collection, usability, data collection, patient reported, satisfaction, mobile phone

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          Abstract

          Background

          Improving shared decision-making (SDM) for patients has become a health policy priority in many countries. Achieving high-quality SDM is particularly important for approximately 313 million surgical treatment decisions patients make globally every year. Large-scale monitoring of surgical patients’ experience of SDM in real time is needed to identify the failings of SDM before surgery is performed. We developed a novel approach to automating real-time data collection using an electronic measurement system to address this. Examining usability will facilitate its optimization and wider implementation to inform interventions aimed at improving SDM.

          Objective

          This study examined the usability of an electronic real-time measurement system to monitor surgical patients’ experience of SDM. We aimed to evaluate the metrics and indicators relevant to system effectiveness, system efficiency, and user satisfaction.

          Methods

          We performed a mixed methods usability evaluation using multiple participant cohorts. The measurement system was implemented in a large UK hospital to measure patients’ experience of SDM electronically before surgery using 2 validated measures (CollaboRATE and SDM-Q-9). Quantitative data (collected between April 1 and December 31, 2021) provided measurement system metrics to assess system effectiveness and efficiency. We included adult patients booked for urgent and elective surgery across 7 specialties and excluded patients without the capacity to consent for medical procedures, those without access to an internet-enabled device, and those undergoing emergency or endoscopic procedures. Additional groups of service users (group 1: public members who had not engaged with the system; group 2: a subset of patients who completed the measurement system) completed user-testing sessions and semistructured interviews to assess system effectiveness and user satisfaction. We conducted quantitative data analysis using descriptive statistics and calculated the task completion rate and survey response rate (system effectiveness) as well as the task completion time, task efficiency, and relative efficiency (system efficiency). Qualitative thematic analysis identified indicators of and barriers to good usability (user satisfaction).

          Results

          A total of 2254 completed surveys were returned to the measurement system. A total of 25 service users (group 1: n=9; group 2: n=16) participated in user-testing sessions and interviews. The task completion rate was high (169/171, 98.8%) and the survey response rate was good (2254/5794, 38.9%). The median task completion time was 3 (IQR 2-13) minutes, suggesting good system efficiency and effectiveness. The qualitative findings emphasized good user satisfaction. The identified themes suggested that the measurement system is acceptable, easy to use, and easy to access. Service users identified potential barriers and solutions to acceptability and ease of access.

          Conclusions

          A mixed methods evaluation of an electronic measurement system for automated, real-time monitoring of patients’ experience of SDM showed that usability among patients was high. Future pilot work will optimize the system for wider implementation to ultimately inform intervention development to improve SDM.

          International Registered Report Identifier (IRRID)

          RR2-10.1136/bmjopen-2023-079155

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          Using thematic analysis in psychology

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            Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

            Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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              A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance

              The UK Medical Research Council’s widely used guidance for developing and evaluating complex interventions has been replaced by a new framework, commissioned jointly by the Medical Research Council and the National Institute for Health Research, which takes account of recent developments in theory and methods and the need to maximise the efficiency, use, and impact of research.
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                Author and article information

                Contributors
                Journal
                JMIR Hum Factors
                JMIR Hum Factors
                JMIR Human Factors
                JMIR Human Factors
                JMIR Publications (Toronto, Canada )
                2292-9495
                2024
                10 April 2024
                : 11
                : e46698
                Affiliations
                [1 ] National Institute for Health and Care Research Bristol Biomedical Research Centre, Bristol Centre for Surgical Research Bristol Medical School: Population Health Sciences University of Bristol Bristol United Kingdom
                [2 ] Patient representative Bristol United Kingdom
                [3 ] North Bristol NHS Trust Bristol United Kingdom
                [4 ] Improvement Academy, Bradford Royal Infirmary Bradford Teaching Hospitals NHS Foundation Trust Bradford United Kingdom
                [5 ] University Hospitals Bristol and Weston NHS Foundation Trust Bristol United Kingdom
                [6 ] Leeds Unit of Complex Intervention Development (LUCID) Leeds Institute of Health Sciences, School of Medicine University of Leeds Leeds United Kingdom
                [7 ] The Research Centre for Patient Involvement (ResCenPI) Department of Public Health Aarhus University Central Denmark Region Denmark
                Author notes
                Corresponding Author: Christin Hoffmann c.hoffmann@ 123456bristol.ac.uk
                Author information
                https://orcid.org/0000-0002-6293-3813
                https://orcid.org/0000-0001-5477-2418
                https://orcid.org/0000-0002-6606-5427
                https://orcid.org/0000-0002-0423-5259
                https://orcid.org/0000-0002-3354-3330
                https://orcid.org/0009-0000-6390-4742
                https://orcid.org/0000-0002-6550-7481
                https://orcid.org/0000-0003-3635-6212
                https://orcid.org/0000-0002-6166-6055
                https://orcid.org/0000-0001-6882-9825
                https://orcid.org/0000-0001-6189-4720
                https://orcid.org/0000-0003-1978-5795
                https://orcid.org/0000-0002-2601-9258
                Article
                v11i1e46698
                10.2196/46698
                11043934
                38598276
                5b83c719-9726-4b9d-b674-5ebe4d2a53d9
                ©Christin Hoffmann, Kerry Avery, Rhiannon Macefield, Tadeáš Dvořák, Val Snelgrove, Jane Blazeby, Della Hopkins, Shireen Hickey, Ben Gibbison, Leila Rooshenas, Adam Williams, Jonathan Aning, Hilary L Bekker, Angus GK McNair, The ALPACA Study Team. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 10.04.2024.

                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 Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on https://humanfactors.jmir.org, as well as this copyright and license information must be included.

                History
                : 21 February 2023
                : 4 August 2023
                : 2 October 2023
                : 2 March 2024
                Categories
                Original Paper
                Original Paper

                surgery,shared decision-making,patient participation,mixed methods,real-time measurement,patient-reported measure,electronic data collection,usability,data collection,patient reported,satisfaction,mobile phone

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