scholarly journals Developing a Heart Transplantation Self-Management Support Mobile Health App in Taiwan: Qualitative Study

10.2196/18999 ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. e18999
Author(s):  
Yi-Wen Chen ◽  
Jeng Wei ◽  
Hwei-Ling Chen ◽  
Ching-Hui Cheng ◽  
I-Ching Hou
Keyword(s):  
Health Care ◽  
Heart Transplantation ◽  
Mobile Health ◽  
Health Professionals ◽  
Health Care Quality ◽  
Care Quality ◽  
Mobile App ◽  
Self Management ◽  
Semistructured Interview ◽  
Mhealth Apps

Background Heart transplantation (HTx) is the most effective treatment for end-stage heart failure patients. After transplantation, patients face physiological, psychological, social, and other health care problems. Mobile health (mHealth) apps can change the delivery of conventional health care to ubiquitous care and improve health care quality. However, a dearth of mHealth apps exists for patients with HTx worldwide, including in Taiwan. Objective The aim of this study was to investigate the information needed and to develop a preliminary framework for an mHealth app for post-HTx patients. Methods A qualitative approach with individual in-depth interviews was conducted at a heart center in the regional hospital of northern Taiwan from June to November 2017. Patients that had undergone HTx and their health professionals were recruited for purposeful sampling. A semistructured interview guideline was used for individual interviews and transcribed. Thematic analysis was used for data analysis. Results A total of 21 subjects, including 17 patients and 4 health professionals, were recruited for the study. The following five major themes were identified: reminding, querying, experience sharing, diet, and expert consulting. Minor themes included a desire to use the app with artificial intelligence and integration with professional management. Conclusions An intelligent mHealth app that addresses the five main themes and integrates the processes of using a mobile app could facilitate HTx self-management for Taiwanese patients.

scholarly journals Developing a Heart Transplantation Self-Management Support Mobile Health App in Taiwan: Qualitative Study (Preprint)

2020 ◽  
Author(s):  
Yi-Wen Chen ◽  
Jeng Wei ◽  
Hwei-Ling Chen ◽  
Ching-Hui Cheng ◽  
I-Ching Hou
Keyword(s):  
Health Care ◽  
Heart Transplantation ◽  
Mobile Health ◽  
Health Professionals ◽  
Health Care Quality ◽  
Care Quality ◽  
Mobile App ◽  
Self Management ◽  
Semistructured Interview ◽  
Mhealth Apps

BACKGROUND Heart transplantation (HTx) is the most effective treatment for end-stage heart failure patients. After transplantation, patients face physiological, psychological, social, and other health care problems. Mobile health (mHealth) apps can change the delivery of conventional health care to ubiquitous care and improve health care quality. However, a dearth of mHealth apps exists for patients with HTx worldwide, including in Taiwan. OBJECTIVE The aim of this study was to investigate the information needed and to develop a preliminary framework for an mHealth app for post-HTx patients. METHODS A qualitative approach with individual in-depth interviews was conducted at a heart center in the regional hospital of northern Taiwan from June to November 2017. Patients that had undergone HTx and their health professionals were recruited for purposeful sampling. A semistructured interview guideline was used for individual interviews and transcribed. Thematic analysis was used for data analysis. RESULTS A total of 21 subjects, including 17 patients and 4 health professionals, were recruited for the study. The following five major themes were identified: reminding, querying, experience sharing, diet, and expert consulting. Minor themes included a desire to use the app with artificial intelligence and integration with professional management. CONCLUSIONS An intelligent mHealth app that addresses the five main themes and integrates the processes of using a mobile app could facilitate HTx self-management for Taiwanese patients.

How Do We Align Health Services Research and Quality Improvement?

2020 ◽  
pp. 282-291
Author(s):  
Devika Das ◽  
Lalan Wilfong ◽  
Katherine Enright ◽  
Gabrielle Rocque
Keyword(s):  
Health Care ◽  
Quality Improvement ◽  
Health Services Research ◽  
Health Services ◽  
Health Care Quality ◽  
Care Delivery ◽  
Care Quality ◽  
Health Care Use ◽  
Semistructured Interview ◽  
Services Research

Quality improvement (QI) initiatives and health services research (HSR) are commonly used to target health care quality. These disciplines are increasingly important because of the movement toward value-based health care as alternative payment and care delivery models drive institutions and investigators to focus on reducing unnecessary health care use and improving care coordination. QI efforts frequently target medical error and/or efficiency of care through the Plan-Do-Study-Act methodology. Within the QI framework, strategies for data display (e.g., Pareto charts, run charts, histograms, scatter plots) are leveraged to identify opportunities for intervention and improvement. HSR is a multidisciplinary field of study that seeks to identify the most effective way to organize, deliver, and finance health care to maximize the quality and value of care at both the individual and population levels. HSR uses a diverse set of quantitative and qualitative methodologies, such as case-control studies, cohort studies, randomized control trials, and semistructured interview/focus group evaluations. This manuscript provides examples of methodologic approaches for QI and HSR, discusses potential challenges associated with concurrent quality efforts, and identifies strategies to successfully leverage the strengths of each discipline in care delivery.

Risk of Readmission for Diabetes Patients: A Machine Learning Approach

2019 ◽  
Author(s):  
K Sowjanya ◽  
Mou Dasgupta
Keyword(s):  
Machine Learning ◽  
Health Care ◽  
Mobile Application ◽  
Health Care Quality ◽  
Care Quality ◽  
Mobile App ◽  
Machine Learning Techniques ◽  
Diabetic Patients ◽  
Readmission Rates ◽  
The People

Diabetes mellitus generally referred to as diabetes is reaching epidemic proportions in India and all around the world. The degree of disease and destruction due to diabetes and complications connected with diabetes is enormous, and originated a significant health care burden on both households and society. Deficiency of knowledge about diabetes causes untimely death among the population at large. Thus, developing a technique that should spread awareness about diabetes may affect the people. In this book, a mobile/android application based solution to overcome the lack of awareness about diabetes has been presented. The application uses machine learning techniques to predict risk of readmission to the hospital in diabetics. At the same time, the system also provides knowledge about diabetes and some suggestions on the disease. A comparative analysis of four machine learning (ML) algorithms were performed. The Decision Tree (DT) classifier outperforms amongst the 4 ML algorithms. Hence, DT classifier is used to design the machinery for the mobile application for diabetes risk of readmission prediction using UCI dataset. Due to the lack of knowledge many people even don’t know that they have diabetes, this will lead to a serious problem, as duration of unknown disease increases the risks associated with it also increases. Hospital readmission is a high-priority health care quality measure and target for cost reduction. Reducing readmission rates of diabetic patients have the potential to greatly reduce health care costs while simultaneously improving care. In this book, a novel mobile application based solution for this problem is provided. This mobile app, MobDBRCal (Risk of Readmission in Diabetes) will act as an important tool that can help in predicting the chances of risk of readmission in diabetes and also provides knowledge about this chronic disease.

scholarly journals Barriers to and Facilitators of the Use of Mobile Health Apps From a Security Perspective: Mixed-Methods Study (Preprint)

2018 ◽  
Author(s):  
Leming Zhou ◽  
Jie Bao ◽  
Valerie Watzlaf ◽  
Bambang Parmanto
Keyword(s):  
Mobile Health ◽  
Health Management ◽  
Mobile App ◽  
Security And Privacy ◽  
Semistructured Interview ◽  
Privacy Concerns ◽  
Validated Questionnaire ◽  
Short Period ◽  
Study Participants ◽  
Mhealth Apps

BACKGROUND A large number of mobile health (mHealth) apps have been created to help users to manage their health or receive health care services. Many of these mHealth apps have proven to be helpful for maintaining or improving their users’ health. However, many people still choose not to use mHealth apps or only use them for a short period. One of the reasons behind this lack of use is the concern for their health information security and privacy. OBJECTIVE The goal of this study was to determine the relationship between users’ characteristics and their security and privacy concerns and to identify desired security features in mHealth apps, which could reduce these concerns. METHODS A questionnaire was designed and validated by the research team. This questionnaire was then used to determine mobile app users’ security and privacy concerns regarding personal health data in mHealth apps as well as the security features most users’ desire. A semistructured interview was used to identify barriers to and facilitators of adopting mHealth apps. RESULTS In total, 117 randomly selected study participants from a large pool took part in this study and provided responses to the validated questionnaire and the semistructured interview questions. The results indicate that most study participants did have concerns about their privacy when using mHealth apps. They also expressed their preferences regarding several security features in mHealth apps, such as regular password updates, remote wipe, user consent, and access control. An association between their demographic characteristics and their concerns and preferences in security and privacy was identified; however, in most cases, the differences among the different demographic groups were not statistically significant, except for a few very specific aspects. These study participants also indicated that the cost of apps and lack of security features in mHealth apps were barriers for adoption, whereas having free apps, strong but easy-to-use security features, and clear user protection privacy policies might encourage them to use mHealth apps in their health management. CONCLUSIONS This questionnaire and interview study verified the security and privacy concerns of mHealth app users, identified the desired security and privacy features, and determined specific barriers to and facilitators of users adopting mHealth apps. The results can be used to guide mHealth app developers to create apps that would be welcomed by users.

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