Smart Healthcare solutions in China and Europe, an international business perspective

The thesis is part of the Marie Curie Fellowship project addressing health related challenges with IoT solutions. The author tries to address the challenge for the implementation of telehealth solutions by finding out the demand of the telehealth solution in selected European economies and in China (chapter 1), analyzing the emerging business models for telehealth solution ecosystems in China (chapter 2), how to integrate telehealth solutions with institutional stakeholders (chapter 3) and why are elderly users willing to use telehealth solutions in China. Chapter 1 and chapter 2 form the theoretical background for empirical work in chapter 3 and chapter 4. The thesis addressed four research questions, namely “Which societal and social-economics unmet needs that Internet of Healthcare Things can help to resolve?”, “What are the business model innovation for tech companies in China for the smart health industry?”, “What are the facilitators and hurdles for implementing telehealth solutions”, “Are elderly users willing to use telehealth solutions in China?”. Both qualitative study and quantitative analysis has been made based on data collected by in depth interviews with stakeholders, focus group study work with urban and rural residents in China. The digital platform framework was used in chapter 2 as the theoretical framework where as the stakeholder power mapping framework was used in chapter 3. The discretion choice experiment was used in chapter 4 to design questionnaire study while ordered logit regression was used to analyze the data. Telehealth solutions have great potential to fill in the gap for lack of community healthcare and ensuring health continuity between home care setting, community healthcare and hospitals. There is strong demand for such solutions if they can prove the medical value in managing chronic disease by raising health awareness and lowering health risks by changing the patients’ lifestyle. Analyzing how to realize the value for preventive healthcare by proving the health-economic value of digital health solutions (telehealth solutions) is the focus of research. There remain hurdles to build trust for telehealth solutions and the use of AI in healthcare. Next step of research can also be extended to addressing such challenges by analyzing how to improve the transparency of algorithms by disclosing the data source, and how the algorithms were built. Further research can be done on data interoperability between the EHR systems and telehealth solutions. The medical value of telehealth solutions can improve if doctors could interpret data collected from telehealth solutions; furthermore, if doctors could make diagnosis and provide treatment, adjust healthcare management plans based on such data, telehealth solutions then can be included in insurance packages, making them more accessible

Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring

The functionality of the Internet is continually changing from the Internet of Computers (IoC) to the “Internet of Things (IoT)”. Most connected systems, called Cyber-Physical Systems (CPS), are formed from the integration of numerous features such as humans and the physical environment, smart objects, and embedded devices and infrastructure. There are a few critical problems, such as security risks and ethical issues that could affect the IoT and CPS. When every piece of data and device is connected and obtainable on the network, hackers can obtain it and utilise it for different scams. In medical healthcare IoT-CPS, everyday medical and physical data of a patient may be gathered through wearable sensors. This paper proposes an AI-enabled IoT-CPS which doctors can utilise to discover diseases in patients based on AI. AI was created to find a few disorders such as Diabetes, Heart disease and Gait disturbances. Each disease has various symptoms among patients or elderly. Dataset is retrieved from the Kaggle repository to execute AI-enabled IoT-CPS technology. For the classification, AI-enabled IoT-CPS Algorithm is used to discover diseases. The experimental results demonstrate that compared with existing algorithms, the proposed AI-enabled IoT-CPS algorithm detects patient diseases and fall events in elderly more efficiently in terms of Accuracy, Precision, Recall and F-measure

Machine Learning Enabled Vital Sign Monitoring System

Internet of Things (IoT)- based remote health monitoring systems have an enormous potential of becoming an integral part of the future medical system. In particular, these systems can play life-saving roles for treating or monitoring patients with critical health issues. On the other hand, it can also reduce pressure on the health-care system by reducing unnecessary hospital visits of patients. Any health care monitoring system must be free from erroneous data, which may arise because of instrument failure or communication errors. In this thesis, machine-learning techniques are implemented to detect reliability and accuracy of data obtained by the IoT-based remote health monitoring. A system is a set-up where vital health signs, namely, blood pressure, respiratory rate, and pulse rate, are collected by using Spire Stone and iHealth Sense devices. This data is then sent to the intermediate device and then to the cloud. In this system, it is assumed that the channel for transmission of data (vital signs) from users to cloud server is error-free. Afterward, the information is extracted from the cloud, and two machine learning techniques, i.e., Support Vector Machines and K-Nearest Neighbor are applied to compare their accuracy in distinguishing correct and erroneous data. The thesis undertakes two different approaches of erroneous data detection. In the first approach, an unsupervised classifier called Auto Encoder (AE) is used for labeling data by using the latent features. Then the labeled data from AE is used as ground truth for comparing the accuracy of supervised learning models. In the second approach, the raw data is labeled based on the correlation between various features. The accuracy comparison is performed between strongly correlated features and weakly correlated features. Finally, the accuracy comparison between two approaches is performed to check which method is performing better for detecting erroneous data for the given dataset

Enhancing pharmaceutical packaging through a technology ecosystem to facilitate the reuse of medicines and reduce medicinal waste

The idea of reusing dispensed medicines is appealing to the general public provided its benefits are illustrated, its risks minimized, and the logistics resolved. For example, medicine reuse could help reduce medicinal waste, protect the environment and improve public health. However, the associated technologies and legislation facilitating medicine reuse are generally not available. The availability of suitable technologies could arguably help shape stakeholders’ beliefs and in turn, uptake of a future medicine reuse scheme by tackling the risks and facilitating the practicalities. A literature survey is undertaken to lay down the groundwork for implementing technologies on and around pharmaceutical packaging in order to meet stakeholders’ previously expressed misgivings about medicine reuse (’stakeholder requirements’), and propose a novel ecosystem for, in effect, reusing returned medicines. Methods: A structured literature search examining the application of existing technologies on pharmaceutical packaging to enable medicine reuse was conducted and presented as a narrative review. Results: Reviewed technologies are classified according to different stakeholders’ requirements, and a novel ecosystem from a technology perspective is suggested as a solution to reusing medicines. Conclusion: Active sensing technologies applying to pharmaceutical packaging using printed electronics enlist medicines to be part of the Internet of Things network. Validating the quality and safety of returned medicines through this network seems to be the most effective way for reusing medicines and the correct application of technologies may be the key enabler

Exploring Security, Privacy, and Reliability Strategies to Enable the Adoption of IoT

The Internet of things (IoT) is a technology that will enable machine-to-machine communication and eventually set the stage for self-driving cars, smart cities, and remote care for patients. However, some barriers that organizations face prevent them from the adoption of IoT. The purpose of this qualitative exploratory case study was to explore strategies that organization information technology (IT) leaders use for security, privacy, and reliability to enable the adoption of IoT devices. The study population included organization IT leaders who had knowledge or perceptions of security, privacy, and reliability strategies to adopt IoT at an organization in the eastern region of the United States. The diffusion of innovations theory, developed by Rogers, was used as the conceptual framework for the study. The data collection process included interviews with organization IT leaders (n = 8) and company documents and procedures (n = 15). Coding from the interviews and member checking were triangulated with company documents to produce major themes. Through methodological triangulation, 4 major themes emerged during my analysis: securing IoT devices is critical for IoT adoption, separating private and confidential data from analytical data, focusing on customer satisfaction goes beyond reliability, and using IoT to retrofit products. The findings from this study may benefit organization IT leaders by enhancing their security, privacy, and reliability practices and better protect their organization\u27s data. Improved data security practices may contribute to social change by reducing risk in security and privacy vulnerabilities while also contributing to new knowledge and insights that may lead to new discoveries such as a cure for a disease

Digital Twin for Amyotrophic Lateral Sclerosis: a system for patient engagement

This chapter focuses on the context in which patients such as those with Amyotrophic Lateral Sclerosis (ALS) are placed and what possibilities information and communication technologies (ICTs) offer to keep them in touch with the world to reach Society 5.0. In particular, the authors intend to show how the healthcare sector can use digital twin (DT) through elements of augmented virtuality (AR) and building information modelling (BIM) to create interactive interfaces that can solve, in part, problems involving frail patients but at the same time allowing their monitoring. Interconnection is possible through a gamification approach. In addition, a solution that considers the user (patient) involvement and that aims at its increase through interaction with alternative places to their home so as to stimulate them to keep an active mind and the degree of fun in a limiting condition is proposed

Community management and policy on diabetes patients in coastal developed areas of China: an in-depth analysis of Shanghai model

Diabetes Mellitus is a chronicle disease with a projected growth and social, human and economic consequences that cannot be overlooked in a growing economy and progressively urbanized structure such as China. It is very much a matter of urgency and systemic policymaking. Its insidious nature and everlasting outcomes highlight the importance of preventive measures, focusing on all the contributive factors, such as nutrition, life style, monitoring, diagnosing, and prescription. Aware of this issue, the Chinese Government put forward a reform of the community health service targeting chronic diseases, such as diabetes, at an early stage. However, not all modes of managing the health infrastructure, namely the third tier healthcare system, have been articulated in the same manner and the nature of Chinese economy and society does not allow the direct importation of models in use abroad. Likewise, the primacy of prevention over treatment puts emphasis on the role community-based healthcare play and it should be targeted for a special focus in order to optimize its effectiveness, considering all the complex issues on healthcare of chronic non-infectious diseases. Therefore, with the aim of establishing the theoretic basis to analyze diabetes healthcare management systems this study mobilizes state of art literature from home and abroad, conducts several field studies with multiple stakeholders of the system. This is therefore a macro level study intended to structure knowledge so to depict, explore, understand and offer recommendations to the improvement of the overall community-based diabetes management system in a large coastal urban area in China. To understand the dynamics and possibilities for optimization of the community-based diabetes management the study focused on Shanghai and conducted a comparative empirical study to explore the benefit it brings for the overall purpose of upgrading the system. Likewise, the study endeavored to identify constrains and offer recommendations. Via a mixed methods approach, involving both qualitative techniques and data collection through interviewing key stakeholders (overall 51 interviews conducted) as well as a quantitative approach via a survey with 60 doctors, 60 nurses and 22 patients, and a collection of archival data from 400 patients the study does a comparative analysis to identify to which extent the Shanghai model is superior to the standard one. As an outcome, the study structures a system to improve the effectiveness of community-based diabetes management in China and generates a body of knowledge for future reference and consideration when studying macro-level healthcare systems with a focus on preventable chronic diseases.A Diabetes Mellitus é uma doença crónica com um crescimento estimado e consequências económicas, sociais e humanas que não podem ser negligenciadas numa economia crescente e estrutura progressivamente urbanizada como a China. Trata-se de um assunto com carácter de urgência e de formulação de políticas sistémicas. A sua natureza assintomática a par das consequências duradouras sublinham a importância das medidas preventivas focadas sobre todos os fatores tributários tais como a nutrição, o estilo de vida, a monitorização, diagnóstico e prescrição. Consciente deste problema, o Governo Chinês instituiu uma reforma dos serviços de saúde comunitários centrada nas doenças crónicas em fase inicial, tais como a diabetes. Contudo, nem todos os modos de gestão da infraestrutura de saúde, sobretudo o sistema de três níveis na saúde, tem sido articulado da mesma forma e a natureza da economia e da sociedade chinesas não permite a importação direta dos modelos utilizado internacionalmente. Do mesmo modo a primazia da prevenção sobre o tratamento enfatiza o papel que o sistema de saúde de base comunitária pode desempenhar e, por isso, deve ser alvo de estudo com um foco especial para otimizar a sua eficácia, considerando todos os problemas complexos que as doenças crónicas não infeciosas importam. Assim, com o objetivo de estabelecer as bases teóricas para analisar os sistemas de gestão de saúde, este estudo mobiliza o estado da arte da literatura chinesa e internacional, realiza vários estudos de campo junto de vários stakeholders do sistema. Trata-se de um estudo de nível macro que pretende estruturar o conhecimento de forma a descrever, explorar, compreender e oferecer recomendações conducentes à melhoria global do sistema de saúde comunitário numa grande área urbana costeira na China. Para compreender as dinâmicas e possibilidades de otimização do sistema de gestão de saúde de base comunitária, o estudo centra-se em Shangai e realiza uma análise empírica comparada para explorar as mais-valias que traz para o propósito geral de melhorar o sistema. Do mesmo modo, o estudo procura identificar constrangimentos e oferecer recomendações. Por via de uma abordagem metodológica híbrida, envolvendo quer a recolha de dados e técnicas qualitativas através de entrevistas junto de stakeholders-chave (um total de 51 entrevistas realizadas) bem como uma abordagem quantitativa por via de um inquérito por questionário junto de 60 médicos, 60 enfermeiros, e 22 pacientes, bem como a recolha de dados de arquivo relativos a 400 pacientes, o estudo procede a uma análise comparada para perceber em que medida o modelo de Shangai é superior ao padrão. Como resultado, o estudo estrutura um sistema destinado a melhorar a eficácia dos serviços de saúde de base comunitária na China, com um enfoque na diabetes, e produz um corpo de conhecimentos para referência futura para efeitos de estudos centrados no nível macro dos sistemas de saúde com um foco nas doenças crónicas evitáveis