scholarly journals A quality improvement (QI) project on improving trainee confidence in conducting remote psychiatric consultations at Pennine Care National Health Service (NHS) Foundation Trust in the United Kingdom (UK)

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S209-S210
Author(s):  
Rachel Moir ◽  
Roshelle Ramkisson ◽  
Seri Abraham ◽  
Shevonne Matheiken
Keyword(s):  
Real Time ◽  
Response Rates ◽  
Psychiatric Consultation ◽  
Time Data ◽  
Remote Consultation ◽  
Safe Patient Care ◽  
Pdsa Cycle ◽  
Real Time Data ◽  
The Uk ◽  
Remote Consultations

AimsWhen the coronavirus disease 2019 pandemic hit the UK, clinicians within Pennine Care NHS Foundation Trust (a five-borough mental health trust) were faced with the challenge of rapidly switching to a novel way of assessing patients remotely.The idea for a QI project on trainees’ experience with remote consultations was conceived in April 2020. We present our February 2021 results here.We aimed to improve trainee confidence in conducting remote psychiatric assessments by at least 40%, to ensure effective and safe patient care during their 6 months placement.MethodOur discovery process included surveying trainees in April 2020 to explore experiences with remote psychiatric consultations, a literature search of current UK guidance and a local audit. The audit reviewed documentation of consent to remote consultations, with reference to standards as per NHS England remote consultation guidance. Key change ideas included publication of an article, ‘Remote consultations – top tips for clinical practitioners’, video-simulated remote consultations and a session on remote consultations in the trainee induction.In the first ‘plan-do-study-act’ (PDSA) cycle, we presented key findings from the article in a video presentation, which was sent trust-wide. We measured confidence in conducting remote assessments pre- and post-presentation via a feedback survey. Unfortunately, response rates were low and in the second PDSA cycle we targeted a smaller cohort of trainees at the August 2020 induction, although encountered similar difficulties. In the third PDSA cycle, we collected real-time data using an interactive app at the February 2021 trainee induction, and measured pre- and post- confidence following a presentation and a video-simulated remote consultation.Result2/34 respondents had accessed previous remote psychiatric consultation training and12/35 had some telepsychiatry experience. Pre-induction trainee confidence results revealed: extremely uncomfortable (16%), not confident (31%), neutral (47%), confident (6%) and very confident (0%) and post-induction confidence was 0%, 22%, 52%, 26% and 0%, respectively.ConclusionOur project started during the first peak of the pandemic, which may be a reason for initial limited response rates. Our results suggest that the remote psychiatric consultation trainee induction session has shown some improvement in trainee confidence; the ‘confident’ cohort improved from 6% to 26%.Our next steps include collecting similar real-time data, mid-rotation and uploading video-simulated remote consultations to the Trust Intranet. We plan to complete the local audit cycle. We also plan to incorporate patient experience (from an ongoing systematic review) to inform a potential triage process post-pandemic, choosing between face-to-face versus remote consultations.

scholarly journals Developing a smartphone app with UK migrants for UK migrants: lessons learned from focus group work

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
R Burns ◽  
G C G Hugenholtz ◽  
V Kirkby ◽  
N Elsay ◽  
R W Aldridge
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Well Being ◽  
Lessons Learned ◽  
Migrant Population ◽  
Time Data ◽  
Longitudinal Data Collection ◽  
Real Time Data ◽  
The Uk ◽  
App Design

Abstract Background In 2018, 14% of people living in the UK were born abroad, yet we have a limited understanding of the broader determinants of their health. To address this knowledge gap, the Health on the MovE (HOME) smartphone application (app) study was conceived. Through app-based surveys, the study will examine how risk factors for health and well-being are distributed among migrants and how these vary over time since migration to the UK. There is a lack of research addressing the development of apps for longitudinal data collection in the general population - and we did not find any in migrant groups. Methods To better inform the design of the HOME app study, three workshops were held in 2018 and 2019, involving both migrants and App development experts. We used a semi-structured interview schedule focused on five themes: smartphones, apps and research, HOME app wireframe (screen-by-screen review of the app), types of surveys and survey schedules, resource section content, and participant engagement strategies. The participants were purposively sampled to reflect the migrant population arriving in the UK from non-EU countries. Results Migrants reported high smartphone use and were positive about the app design and app-based research. Concerns around privacy and data protection were highlighted and limits were suggested for the frequency of surveys and the number of questions used. Mental health was identified as a key topic for research. Participants requested the inclusion of resources concerning asylum claim procedures and immigrant and labour laws. Migrants advised that study recruitment material should clearly state the purpose and scope of the research and requested regular feedback on study outcomes. Conclusions The workshops provided important feedback and facilitated the co-production of the HOME app. Overall findings suggest that the study would be both acceptable to the migrant population and feasible for real-time data collection. Key messages The process identified potential barriers to the acceptability and feasibility of an app-based study for real-time data collection in the UK migrant population. Organising workshops with migrants allowed for an iterative process of co-production of the HOME app. Their critical comments resulted in subsequent changes to the app design and study methodology.

399-P: Nurse-Driven Intervention Using Real-Time Data to Improve Hypoglycemia Rates in a Respiratory Care Unit

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 399-P
Author(s):  
ANN MARIE HASSE ◽  
RIFKA SCHULMAN ◽  
TORI CALDER
Keyword(s):  
Real Time ◽  
Respiratory Care ◽  
Time Data ◽  
Real Time Data

MHA releases largest real‐time data from MH help‐seekers

2021 ◽  
Vol 31 (6) ◽  
pp. 7-7
Author(s):  
Valerie A. Canady
Keyword(s):  
Real Time ◽  
Time Data ◽  
Real Time Data

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

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