ABSTRACT
Background: Due to COVID-19, we saw an increased usage of digital platforms for healthcare delivery. However, its effect on internet postings for CF during 2021 is unknown. Methods: CF key phrases were identified by a CF MDT and entered in Google Alerts and tracked for 6 months in 2021. Alertswere also created for Asthma, COPD and Lung Fibrosis. Data recorded for each alert includes the date, title, URL, category, country of origin;if a discussion, like/share took place. Thiswas then compared against previous data collected (2015, 2019). Results: The number of CF alerts recorded decreased (2021:1846– 2015:2742) while the number of blocked alerts increased (2021:325– 2015:89). Almost half of the CF alerts originated from the USA. In 2021, News was the most common category (33.96%) followed by Financial/ Marketing (25.73%) and Medical (21.07%). The most common category for 2015 was News (58.35%) and Financial/Marketing in 2019 (35.2%). The majority of CF terms experienced an increase in quantity, specifically alerts relating to CF pathogens or changing condition expectations, such as Pseudomonas (2021:718, 2015:149), CFLD(2021:428, 2019:865, 2015:37), and CF Pregnancy (2021:91, 2015:5). For the comparative lung conditions, in 2015 Asthma was the most common alert (985) followed by CF, COPD, and Lung Fibrosis. In 2019 CF (605) was the most common. In 2021, the quantity of alerts decreased for all conditions, with CF (316) and Asthma (336) being of similar magnitude. Conclusion: The landscape for CF internet postings continues to evolve. CF is discussed frequently online, with the focus of these discussions changing to news items in 2021. The increased frequency of specific CF terms may reflect changing expectations (e.g Pregnancy). The number of blocked alerts continues to increase, potentially reflecting different global GDPR practices. Online non-EU healthcare resources need to factor this into their practice to avoid potential correct information loss for EU patients.
ABSTRACT
Due to the pandemic limitations caused by Covid-19, people need to work at home and carry on the meetings virtually. Virtual meeting tools start popularizing and thriving. Those tools allow users to see each other through screen and camera, chat through voice and text, and share content or ideas through screen share. However, screen sharing protein models through virtual meetings is not easy due to the difficulty of viewing protein 3D (Three Dimensional) structures from a 2D (Two Dimensional) screen. Moreover, interactions upon a protein are also limited. ProMVR is a tool the author developed to tackle the issue that protein designers may find limitations working in a traditional 2D or 3D environment and they may find it hard to communicate their ideas with other designers. Since ProMVR is a VR tool, it allows users to “jump into” a virtual environment, take a close look at protein models, and have intuitive interactions. © 2021 Copyright held by the owner/author(s).
ABSTRACT
Background: Medical professionals are aware that patients continue to use the internet as a medical information source. With the advent of government campaigns to increase awareness of data privacy and information sources, we investigate how the landscape of internet postings has changed for CF and how this could affect patients seeking online medical information. Methods: Key phrases relating to CF were identified by a CF multidisciplinary team and entered in Google Alerts with prospective tracking for 6 months in 2015. Alerts were also created for 3 non-orphan lung diseases (asthma, chronic obstructive pulmonary disease and lung fibrosis). These steps were repeated again in 2019 and the data compared. Results: In 2015, Asthma received the highest mean number of alerts per day (31.7), followed by CF (16.1), then COPD (14.6), and Lung Fibrosis (5.1). This changed in 2019 where CF was the highest with 19.5, followed by Asthma (11.5), COPD (10.3), and Lung Fibrosis (7.4). In both years, the USA generated (56%) the highest number of alerts for CF. There was an increased number of blocked articles in 2019 (540). In 2015, News (58%) was the most common category for CF alerts, but this changed to Financial/Marketing (35%) in 2019. In 2015 there was a small number of Social Media alerts recorded for all lung conditions;however, in 2019, there were none for the comparative lung conditions and only 3 for CF. Alert frequency for CF-related terms also increased in 2019. Conclusion: The landscape for internet postings for CF has changed. CF is now more commonly reported than other lung conditions and the ‘business of CF’ is now more frequently reported online while content from the general public has decreased (or is private). Medical professionals need to remain vigilant and increase awareness of information-dilution by monetary based media. A limitation of this study is that it predated the COVID-19 pandemic and it is suggested that future works revisit this at an appropriate time.
ABSTRACT
Background: Patients often contact the cystic fibrosis (CF) multidisciplinary team (MDT) via phone to express health-related concerns in between the standard quarterly review. This often requires a phone evaluation before organising an unscheduled appointment. These sporadic interactions heavily affect available resources. This strain on resources will be further impacted when considering that data from the European CF registry predicts that there will be a 75% increase in the adult CF population by 2025. Furthering this, CF services are increasingly more strained now during the global Covid-19 pandemic. Objective: This research first sets about to design and develop a Virtual Doctor system based on the expertise of a MDT through multiple consultations. Next, pilot data pertaining to user acceptance and experience with using this novel technology is gathered. We therefore aim to investigate if the use of such technology can be beneficial in a specific clinical setting. Method: The final collaborative-design of the Virtual Doctor comprises several technical features and is primarily a voice synthesis system allowing the patient to interact with natural language. The virtual doctor asks the patient questions regarding their health concerns and can collect real-time clinical metrics such as FEV1, oxygen saturation, temperature. The patients’ responses and metrics are then compared to baseline values calculating a score which stratifies a response time from the CF team. This information is then collated in a report and sent to the CF team for action. Future works: Initial stress testing of the technical performance is now complete. Supportive visual media to improve coaching of using clinical devices have now been implemented in preparation for patient pilot testing which is currently ongoing. It is anticipated that a virtual system such as the Virtual Doctor will become more accessible and acceptable to patients, especially during the Covid-19 pandemic.