How should artificial intelligence be used in Australian health care? Recommendations from a citizens' jury.

OBJECTIVE: To support a diverse sample of Australians to make recommendations about the use of artificial intelligence (AI) technology in health care. STUDY DESIGN: Citizens' jury, deliberating the question: "Under which circumstances, if any, should artificial intelligence be used in Australian health systems to detect or diagnose disease?" SETTING, PARTICIPANTS: Thirty Australian adults recruited by Sortition Foundation using random invitation and stratified selection to reflect population proportions by gender, age, ancestry, highest level of education, and residential location (state/territory; urban, regional, rural). The jury process took 18 days (16 March - 2 April 2023): fifteen days online and three days face-to-face in Sydney, where the jurors, both in small groups and together, were informed about and discussed the question, and developed recommendations with reasons. Jurors received extensive information: a printed handbook, online documents, and recorded presentations by four expert speakers. Jurors asked questions and received answers from the experts during the online period of the process, and during the first day of the face-to-face meeting. MAIN OUTCOME MEASURES: Jury recommendations, with reasons. RESULTS: The jurors recommended an overarching, independently governed charter and framework for health care AI. The other nine recommendation categories concerned balancing benefits and harms; fairness and bias; patients' rights and choices; clinical governance and training; technical governance and standards; data governance and use; open source software; AI evaluation and assessment; and education and communication. CONCLUSIONS: The deliberative process supported a nationally representative sample of citizens to construct recommendations about how AI in health care should be developed, used, and governed. Recommendations derived using such methods could guide clinicians, policy makers, AI researchers and developers, and health service users to develop approaches that ensure trustworthy and responsible use of this technology.

Community views on the secondary use of general practice data: Findings from a mixed-methods study.

INTRODUCTION: General practice data, particularly when combined with hospital and other health service data through data linkage, are increasingly being used for quality assurance, evaluation, health service planning and research. In this study, we explored community views on sharing general practice data for secondary purposes, including research, to establish what concerns and conditions need to be addressed in the process of developing a social licence to support such use. METHODS: We used a mixed-methods approach with focus groups (November-December 2021), followed by a cross-sectional survey (March-April 2022). RESULTS: The participants in this study strongly supported sharing general practice data with the clinicians responsible for their care, and where there were direct benefits for individual patients. Over 90% of survey participants (N = 2604) were willing to share their general practice information to directly support their health care, that is, for the primary purpose of collection. There was less support for sharing data for secondary purposes such as research and health service planning (36% and 45% respectively in broad agreement) or for linking general practice data to data in the education, social services and criminal justice systems (30%-36%). A substantial minority of participants were unsure or could not see how benefits would arise from sharing data for secondary purposes. Participants were concerned about the potential for privacy breaches, discrimination and data misuse and they wanted greater transparency and an opportunity to consent to data release. CONCLUSION: The findings of this study suggest that the public may be more concerned about sharing general practice data for secondary purposes than they are about sharing data collected in other settings. Sharing general practice data more broadly will require careful attention to patient and public concerns, including focusing on the factors that will sustain trust and legitimacy in general practice and GPs. PATIENT AND PUBLIC CONTRIBUTION: Members of the public were participants in the study. Data produced from their participation generated study findings. CLINICAL TRIAL REGISTRATION: Not applicable.

Views of general practice staff on sharing general practice data for research: a scoping review protocol.

OBJECTIVE: The objective of this scoping review is to understand the range and types of evidence in relation to the views of general practitioner and other general practice staff on sharing general practice data for research purposes. INTRODUCTION: The use of general practice data for research has the potential to drive transformative improvements in health care. The vast amount of patient data collected in general practice is valuable and provides researchers with data to conduct large-scale studies and generate evidence that can inform policy decisions, support the development of personalized medicine, and enhance patient outcomes. However, despite there being clear benefits to using general practice data for research, there are also potential harms, such as data misuse, loss of trust between the general practitioner and patient, and data breaches. INCLUSION CRITERIA: This scoping review will focus on the views of general practice staff, including general practitioners, practice nurses, and practice managers, about sharing general practice data for the purposes of research. This scoping review will exclude sources of evidence that are conducted outside of the general practice setting, and papers that report on public, patient, or community views on data sharing. METHODS: This scoping review will be conducted in accordance with JBI methodology for scoping reviews. A 3-step search strategy will be used to acquire both published and unpublished sources of evidence. Two independent reviewers will select sources of evidence in line with the inclusion and exclusion criteria. No limits on the date of the search or language will be applied. Data will be extracted and the results will be summarized descriptively and presented in a tabular format. REVIEW REGISTRATION: Open Science Framework https://osf.io/49yw5.

Ethical issues when conducting health research with military personnel: a scoping review protocol.

OBJECTIVE: The objective of this scoping review is to understand the scope and nature of evidence in relation to the ethical issues that arise when conducting health research with military personnel. INTRODUCTION: Ethical obligations in human research have been debated for centuries. Historically, research conducted with military personnel has led to ethical controversies regarding autonomy, harm, and informed consent. In particular, the power dynamics, hierarchical nature, and culture that are inherent in military structures may compromise the voluntary nature of research participation. INCLUSION CRITERIA: This scoping review will include all sources of evidence that identify ethical issues, such as autonomy, beneficence, non-maleficence, and justice, within health research with military personnel, including reservists. This review will exclude sources of evidence on health research conducted during combat or on new technologies for fighting in wars. METHODS: This scoping review will be conducted in accordance with the JBI methodology for scoping reviews. A 3-step search strategy will be used to obtain both published and unpublished sources of evidence. Two independent reviewers will screen sources of evidence against the inclusion and exclusion criteria. No limits on language will be applied; we will use Google Translate to translate sources of evidence in languages other than English. Sources of evidence published since 1964 will be included. Data will be extracted using a purpose-designed spreadsheet and the results will be summarized descriptively and presented in tabular format. REVIEW REGISTRATION: Open Science Framework https://osf.io/db85p.