The Ethical Implications of Personal Health Monitoring

Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes include privacy, autonomy, obtrusiveness and visibility, stigma and identity, medicalisation, social isolation, delivery of care, and safety and technological need. The issues around each of these are discussed. The system / lifeworld perspective of Habermas is applied to develop an understanding of the role of PHMs as mediators of communication between the institutional and the domestic environment. Furthermore, links are established between the ethical issues to demonstrate that the ethics of PHM involves a complex network of ethical interactions. The paper extends the discussion of the critical effect PHMs have on the patient’s identity and concludes that a holistic understanding of the ethical issues surrounding PHMs will help both researchers and practitioners in developing effective PHM implementations

On the Ethical Implications of Personal Health Monitoring

Recent years have seen an influx of medical technologies capable of remotely monitoring the health and behaviours of individuals to detect, manage and prevent health problems. Known collectively as personal health monitoring (PHM), these systems are intended to supplement medical care with health monitoring outside traditional care environments such as hospitals, ranging in complexity from mobile devices to complex networks of sensors measuring physiological parameters and behaviours. This research project assesses the potential ethical implications of PHM as an emerging medical technology, amenable to anticipatory action intended to prevent or mitigate problematic ethical issues in the future. PHM fundamentally changes how medical care can be delivered: patients can be monitored and consulted at a distance, eliminating opportunities for face-to-face actions and potentially undermining the importance of social, emotional and psychological aspects of medical care. The norms evident in this movement may clash with existing standards of ‘good’ medical practice from the perspective of patients, clinicians and institutions. By relating utilitarianism, virtue ethics and theories of surveillance to Habermas’ concept of colonisation of the lifeworld, a conceptual framework is created which can explain how PHM may be allowed to change medicine as a practice in an ethically problematic way. The framework relates the inhibition of virtuous behaviour among practitioners of medicine, understood as a moral practice, to the movement in medicine towards remote monitoring. To assess the explanatory power of the conceptual framework and expand its borders, a qualitative interview empirical study with potential users of PHM in England is carried out. Recognising that the inherent uncertainty of the future undermines the validity of empirical research, a novel epistemological framework based in Habermas’ discourse ethics is created to justify the empirical study. By developing Habermas’ concept of translation into a procedure for assessing the credibility of uncertain normative claims about the future, a novel methodology for empirical ethical assessment of emerging technologies is created and tested. Various methods of analysis are employed, including review of academic discourses, empirical and theoretical analyses of the moral potential of PHM. Recommendations are made concerning ethical issues in the deployment and design of PHM systems, analysis and application of PHM data, and the shortcomings of existing research and protection mechanisms in responding to potential ethical implications of the technology.he research described in this thesis was sponsored and funded by the Centre for Computing and Social Responsibility of De Montfort University, and was linked to the research carried out in FP7 research projects PHM-Ethics (GA 230602) and ETICA (Ethical Issues of Emerging ICT Applications, GA 230318)

Artificial Intelligence and Public Health: A Descriptive Review of Use Cases

The field of public health is critically important because it works to improve and safeguard the health of populations. The goal of public health is to improve the health and well-being of a population as a whole by focusing on issues such as disease prevention and lifestyle promotion. Those who work in public health have the important roles of educating populations, formulating policy, and responding to catastrophes and other emergencies. There are always emerging difficulties and opportunities in the field of public health, making the work of public health experts all the more important. AI has numerous applications that could greatly improve public health. AI is being used in many different ways to better health outcomes, such as in the detection and forecasting of disease outbreaks, the enhancement of patient diagnosis and treatment, the simplification of clinical trial processes, and the monitoring and enhancement of public health programs. However, there are also obstacles that must be overcome, such as protecting users' personal information, making sure AI models are accurate and fair, eliminating bias, and considering the ethical implications of using AI to public health

Self-Tracking, Social Media and Personal Health Records for Patient Empowered Self-Care

Objectives: This paper explores the range of self-tracking devices and social media platforms used by the self-tracking community, and examines the implications of widespread adoption of these tools for scientific progress in health informatics. Methods: A literature review was performed to investigate the use of social media and self-tracking technologies in the health sector. An environmental scan identified a range of products and services which were used to exemplify three levels of self-tracking: self-experi- mentation, social sharing of data and patient controlled electronic health records. Results: There appears to be an increase in the use of self-tracking tools, particularly in the health and fitness sector, but also used in the management of chronic diseases. Evidence of efficacy and effectiveness is limited to date, primarily due to the health and fitness focus of current solutions as opposed to their use in dis- ease management. Conclusions: Several key technologies are converging to produce a trend of increased personal health surveillance and monitoring, so- cial connectedness and sharing, and integration of regional and national health information systems. These trends are enabling new applications of scientific techniques, from personal experimentation to e-epidemiology, as data gathered by individuals are aggregated and shared across increasingly connected healthcare networks. These trends also raise significant new ethical and scientific issues that will need to be addressed, both by health informatics researchers and the communities of self-trackers themselves

Uncovering Bias in Personal Informatics

Personal informatics (PI) systems, powered by smartphones and wearables, enable people to lead healthier lifestyles by providing meaningful and actionable insights that break down barriers between users and their health information. Today, such systems are used by billions of users for monitoring not only physical activity and sleep but also vital signs and women's and heart health, among others. %Despite their widespread usage, the processing of particularly sensitive personal data, and their proximity to domains known to be susceptible to bias, such as healthcare, bias in PI has not been investigated systematically. Despite their widespread usage, the processing of sensitive PI data may suffer from biases, which may entail practical and ethical implications. In this work, we present the first comprehensive empirical and analytical study of bias in PI systems, including biases in raw data and in the entire machine learning life cycle. We use the most detailed framework to date for exploring the different sources of bias and find that biases exist both in the data generation and the model learning and implementation streams. According to our results, the most affected minority groups are users with health issues, such as diabetes, joint issues, and hypertension, and female users, whose data biases are propagated or even amplified by learning models, while intersectional biases can also be observed

A realisation of ethical concerns with smartphone personal health monitoring apps

The pervasiveness of smartphones has facilitated a new way in which owners of devices can monitor their health using applications (apps) that are installed on their smartphones. Smartphone personal health monitoring (SPHM) collects and stores health related data of the user either locally or in a third party storing mechanism. They are also capable of giving feedback to the user of the app in response to conditions are provided to the app therefore empowering the user to actively make decisions to adjust their lifestyle. Regardless of the benefits that this new innovative technology offers to its users, there are some ethical concerns to the user of SPHM apps. These ethical concerns are in some way connected to the features of SPHM apps. From a literature survey, this paper attempts to recognize ethical issues with personal health monitoring apps on smartphones, viewed in light of general ethics of ubiquitous computing. The paper argues that there are ethical concerns with the use of SPHM apps regardless of the benefits that the technology offers to users due to SPHM apps’ ubiquity leaving them open to known and emerging ethical concerns. The paper then propose a need further empirical research to validate the claim

Healthcare, lifestyle and well-being apps. Who am I sharing my data with and what for?

Today we can find healthcare, lifestyle and well-being applications – for smartphones, tablets, wearable devices - for a plethora of aspects: from monitoring pregnancy to checking on blood pressure. These apps are used in our everyday life and not only in medical settings. They hold the promise of enhancing, managing, predicting and improving our individual health and healthcare services. Anyone with a smartphone can share personal health related data with healthcare services and companies, as well as other organisations and individuals. While people use these applications social media companies harvest, archive and manage huge amounts of data –aka big data. These two issues – people sharing personal data and the harvest of these data – have serious implications for the way in which research on human subjects can be undertaken and for the ethical frameworks that regulate such research. Key concerns are privacy, anonymity and data management. This talk focuses on the ethical implications arising from the everyday life use of healthcare applications and the risks, challenges and threats of big data. It addresses three issues (1) collection, analysis and sharing of personalised social media data; (2) anonymity and (3) privacy in a context where people is encouraged to share their data

Designing the Health-related Internet of Things: Ethical Principles and Guidelines

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may be rapid. However, a host of ethical concerns are also raised that must be addressed. The inherent sensitivity of health-related data being generated and latent risks of Internet-enabled devices pose serious challenges. Users, already in a vulnerable position as patients, face a seemingly impossible task to retain control over their data due to the scale, scope and complexity of systems that create, aggregate, and analyse personal health data. In response, the H-IoT must be designed to be technologically robust and scientifically reliable, while also remaining ethically responsible, trustworthy, and respectful of user rights and interests. To assist developers of the H-IoT, this paper describes nine principles and nine guidelines for ethical design of H-IoT devices and data protocols