Epworth Collection:
http://hdl.handle.net/11434/873
2024-03-28T14:15:13ZText mining and grounded theory for appraising the self-management compliance of diabetes mobile apps.
http://hdl.handle.net/11434/2061
Title: Text mining and grounded theory for appraising the self-management compliance of diabetes mobile apps.
Epworth Authors: Wickramasinghe, Nilmini
Abstract: Background: Understanding diabetes mobile apps functionality is fundamental to diabetes self-management because of the reliance of many patients with diabetes on these apps.
Objectives: The aim of this study is to perform a review of diabetes mobile apps to discover users’ sentiments and qualitatively examine the review comments to understand the perceptions of positive, neutral, and negative sentimental users of the apps.
Method: A total of 2678 user review comments obtained from the google play store were analysed from 47 diabetes mobile apps to understand user sentiments following clinical Self-management Indicators (SMIs) shown in previous research. Pearson correlation analysis was conducted to determine the association between the SMIs present in the apps’ and user review indicators such as rating score, user sentiment and the number of downloads. The users’ review comments were thematically screened using grounded theory to establish the themes to describe their perception of the apps.
Results: After evaluating SMIs such as weight tracking/BMI, sugar level monitoring, diet/Calories management, medication reminder, etc., 74.47% of the apps were found to have Sugar Level Monitoring(SLM) capabilities with 10.64% designed to track weight/BMI. There are 53.19% of the apps that can manage diet/calories and have data storage and security SMIs, however, less than 30% of them provide medication adherence, exercise management, doctor's appointment scheduling, and diabetes information repository. The number of the SMIs included in apps did not influence users’, but the value derived from the functionality of the apps.
Conclusions: Users are satisfied with the apps that are easy to use, setup, provide good analytics for blood sugar monitoring and have uncrowded graphical outputs and user interface. Proper data management and contemporary information about diabetes are among the identified challenges of the apps that were found to crash relentlessly on downloading, uploading, installing, and setup.2021-05-25T00:00:00ZA vision for leveraging digital twins to support the provision of personalised cancer care.
http://hdl.handle.net/11434/2060
Title: A vision for leveraging digital twins to support the provision of personalised cancer care.
Epworth Authors: Wickramasinghe, Nilmini; Vaughan, Stephen
Abstract: Exploring the opportunity for applying digital twins in the healthcare context is an emerging research area that has the potential to support more personalised care. A recognised aspect in cancer care is the need for more personalised treatment planning to complement the recent advances in precision medicine. In this article, we present a classification of digital twins into Grey Box, Surrogate and Black Box models using systems and mathematical modelling theory. We then explore one possible approach, namely a Black Box classification for incorporating the use of digital twins in the context of personalised uterine cancer care. This paper presents one of the first attempts to use digital twins in this capacity and represents an amalgamation of three key domains: clinical, digital health and computer science respectively.2021-03-01T00:00:00ZUsing community care coordination networks to minimize hospitalization of COVID-19 patients.
http://hdl.handle.net/11434/2053
Title: Using community care coordination networks to minimize hospitalization of COVID-19 patients.
Epworth Authors: Wickramasinghe, Nilmini
Abstract: Coronavirus surges have motivated hospitals around the globe to rapidly develop and deploy two key types of telemedicine/telehealth solutions: 1) to diagnose and manage COVID-19 patients at home as their symptoms emerge, avoiding hospitalization as much as possible, and 2) to discharge 'recovered' patients to homecare as rapidly as possible from the hospital, freeing as many critical care beds as possible for incoming patients. Since early 2019, hospitals in both large cities and small cities alike have reported multiple episodes of periodic overwhelming surges, and tele-homecare strategies have been part of their overload solution. In prior work, this team of researchers have demonstrated many Petri net simulation tools to model and design optimal community homecare hub to enable safer, more effective, and more efficient homecare. This paper leverages prior work to address COVID-19 patient care, and also expands the AI/Decision Support Layer to further illustrate care coordination needs in the emerging Accountable Care era.2021-03-01T00:00:00ZDeveloping personalised diabetic platform using a Design Science Research Methodology
http://hdl.handle.net/11434/2027
Title: Developing personalised diabetic platform using a Design Science Research Methodology
Epworth Authors: Wickramasinghe, N
Abstract: Diabetes Mellitus a prevalent chronic disease that affects people from all genders and ages, continues to grow exponentially with predictions of nearly 578 million people affected by 2030. Self-management, known to be an essential aspect of any care program can help patients with diabetics to control blood glucose and thereby reduce the impact and likely complications. However, self-management to date has included the development of digital health solutions have poor sustained uptake. This is primarily since such digital solutions have a poor fit with patient and clinician needs. In this paper we propose a digital platform for supporting patients with diabetes. The proposed platform is a work-in-progress research and has been co-designed and co-developed (jointly with patients and clinicians) based on design science principles and includes key aspects of task-technology fit information system theory for further evaluation.2021-01-05T00:00:00Z