Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AI-assisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data.

Medication errors harm hospitalised patients and increase health care costs. Electronic Medication Management Systems (EMMS) have been shown to reduce medication errors. However, nurses do not always use EMMS as intended, largely because implementation of such patient safety strategies requires clinicians to change their existing practices, routines and behaviour. This study uses the Theoretical Domains Framework (TDF) to identify barriers and targeted interventions to enhance nurses’ appropriate use of EMMS in two Australian hospitals. This qualitative study draws on in-depth interviews with 19 acute care nurses who used EMMS. A convenience sampling approach was used. Nurses working on the study units (N = 6) in two hospitals were invited to participate if available during the data collection period. Interviews inductively explored nurses’ experiences of using EMMS (step 1). Data were analysed using the TDF to identify theory-derived barriers to nurses’ appropriate use of EMMS (step 2). Relevant behaviour change techniques (BCTs) were identified to overcome key barriers to using EMMS (step 3) followed by the identification of potential literature-informed targeted intervention strategies to operationalise the identified BCTs (step 4). Barriers to nurses’ use of EMMS in acute care were represented by nine domains of the TDF. Two closely linked domains emerged as major barriers to EMMS use: Environmental Context and Resources (availability and properties of computers on wheels (COWs); technology characteristics; specific contexts; competing demands and time pressure) and Social/Professional Role and Identity (conflict between using EMMS appropriately and executing behaviours critical to nurses’ professional role and identity). The study identified three potential BCTs to address the Environmental Context and Resources domain barrier: adding objects to the environment; restructuring the physical environment; and prompts and cues. Seven BCTs to address Social/Professional Role and Identity were identified: social process of encouragement; pressure or support; information about others’ approval; incompatible beliefs; identification of self as role model; framing/reframing; social comparison; and demonstration of behaviour. It proposes several targeted interventions to deliver these BCTs. The TDF provides a useful approach to identify barriers to nurses’ prescribed use of EMMS, and can inform the design of targeted theory-based interventions to improve EMMS implementation.

The health care quality improvement movement is a complex enterprise. Implementing clinical quality initiatives requires attitude and behaviour change on the part of clinicians, but this has proven to be difficult. In an attempt to solve this kind of behavioural challenge, the theoretical domains framework (TDF) has been developed. The TDF consists of 14 domains from psychological and organisational theory said to influence behaviour change. No systematic research has been conducted into the ways in which clinical quality initiatives map on to the domains of the framework. We therefore conducted a qualitative mapping experiment to determine to what extent, and in what ways, the TDF is relevant to the implementation of clinical quality interventions.

New technologies can help older persons age in place and support their caregivers. However, they need to be accepted by the end-users to do so. Technology acceptance models, such as TAM and UTAUT and their extensions, use factors like performance expectancy and effort expectancy to explain acceptance. Furthermore, they are based on quantitative methods. Our qualitative study investigates factors fostering and hindering acceptance among older persons and their caregivers for a variety of assistive technologies, including wearables, ambient sensors at home with and without cameras and social companion robots. The goal of this paper is twofold: On the one hand, it investigates the factors of technology acceptance models in a qualitative setting. On the other hand, it informs these models with aspects currently overlooked by them. The results reveal that performance expectancy and effort expectancy are relevant for acceptance. We also find that reliability, anxiety around technology and different social aspects have an influence on acceptance of assistive technology in aged care for all end-user groups. Our findings can be used to update current technology acceptance models and provide in-depth knowledge about the currently used factors.

"Sunshine" policy, aimed at making financial ties between health professionals and industry publicly transparent, has recently gone global. Given that transparency is not the sole means of managing conflict of interest, and is unlikely to be effective on its own, it is important to understand why disclosure has emerged as a predominant public policy solution, and what the effects of this focus on transparency might be. We used Carol Bacchi's problem-questioning approach to policy analysis to compare the Sunshine policies in three different jurisdictions, the United States, France and Australia. We found that transparency had emerged as a solution to several different problems including misuse of tax dollars, patient safety and public trust. Despite these differences in the origins of disclosure policies, all were underpinned by the questionable assumption that informed consumers could address conflicts of interest. We conclude that, while transparency reports have provided an unprecedented opportunity to understand the reach of industry within healthcare, policymakers should build upon these insights and begin to develop policy solutions that address systemic commercial influence.