The robot butler: How and why should we study predictive algorithms and artificial intelligence (AI) in healthcare?

Artificial intelligence (AI) and algorithms are heralded as significant solutions to the widening gap between the rising healthcare needs of ageing and multi-morbid populations and the scarcity of resources to provide such care. Objective: This article investigates how the PMHnet algorithm - an AI prognostication tool developed in Denmark to predict the one-year all-cause mortality risk for patients hospitalized with ischemic heart disease - was presented to cardiologists working in the hospital setting, and how they responded to this novel decision-support tool. Methods: Empirically, we draw upon ethnographic fieldwork in the Danish-led international research project, PM Heart, which since 2019 has developed the PMHnet algorithm and implemented the software into the electronic health record system in hospitals in Eastern Denmark (the Capital Region and Region Zealand). Results: Paying careful attention to the hopes and concerns of cardiologists who will have to embrace and adapt to algorithmic tools in their everyday work of diagnosing and treating patients, we identify three analytical themes meriting attention when AI is implemented in healthcare: 1) the re-negotiation of agency and autonomy in human-algorithm relations, 2) accountability in algorithmic prognostication and 3) the complex relationship between association and causation actualized by predictive algorithms. From these analytical themes, we elicit methodological questions to guide future ethnographic explorations of how AI and advanced algorithms are put to use in the healthcare system, with what implications, and for whom. Conclusion: We conclude that local, qualitative investigations of how algorithms are used, embraced and contested in everyday clinical practice are needed in order to understand their implications - good and bad, intended and unintended - for clinicians, patients and healthcare provision.

A systematic review finds a lack of consensus in methodological approaches in health inequality/inequity focused reviews.

OBJECTIVES: To critically review and analyze evidence synthesis articles using health inequality/inequity guidance to support their review. STUDY DESIGN AND SETTING: A comprehensive, systematic search of six social science databases (1990 to May 2022) and grey literature sources was undertaken. A narrative approach to synthesis was adopted, describing and categorizing the characteristics of included articles. A comparison of the existing methodological guides was also conducted, discussing the similarities and differences between them. RESULTS: From 205 identified reviews published between 2008 and 2022, 62 (30%) focusing on health inequality/inequity, met the criteria. The reviews were diverse in terms of methodology, populations, intervention level, and clinical areas. Only 19 (31%) reviews discussed the definition of inequality/inequity. Two methodological guides were identified: (i) the PROGRESS/Plus framework and (ii) the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Equity checklist. CONCLUSION: A critique on the methodological guides reaffirms a lack of clarity or guidance on how health inequality/inequity should be considered. The PROGRESS/Plus framework narrowly focuses on dimensions of health inequality/inequity but rarely considers the pathways and interactions of these dimensions and their effect on outcomes. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Equity checklist on the other hand provides guidance on report. A conceptual framework is needed to show the pathways and interactions of dimensions of health inequality/inequity.

Applying mixed methods to pilot feasibility studies to inform intervention trials.

BACKGROUND: Pilot feasibility studies serve a uniquely important role in preparing for larger scale intervention trials by examining the feasibility and acceptability of interventions and the methods used to test them. Mixed methods (collecting, analyzing, and integrating quantitative and qualitative data and results) can optimize what can be learned from pilot feasibility studies to prepare rigorous intervention trials. Despite increasing use of mixed method designs in intervention trials, there is limited guidance on how to apply these approaches to address pilot feasibility study goals. The purpose of this article is to offer methodological guidance for how investigators can plan to integrate quantitative and qualitative methods within pilot feasibility studies to comprehensively address key research questions. METHODS: We used an informal consensus-based process informed by key methodological resources and our team's complementary expertise as intervention researchers and mixed methodologists to develop guidance for applying mixed methods to optimize what can be learned from pilot feasibility studies. We developed this methodological guidance as faculty in the Mixed Methods Research Training Program (MMRTP) for the Health Sciences (R25MH104660) funded by the National Institutes of Health through the Office of Behavioral and Social Science Research. RESULTS: We provide the following guidance for applying mixed methods to optimize pilot feasibility studies: (1) identify feasibility domain(s) that will be examined using mixed methods, (2) align quantitative and qualitative data sources for the domain(s) selected for mixing methods, (3) determine the timing of the quantitative and qualitative data collection within the flow of the pilot study, (4) plan integrative analyses using joint displays to understand feasibility, and (5) prepare to draw meta-inferences about feasibility and implications for the future trial from the integrated data. CONCLUSIONS: By effectively integrating quantitative and qualitative data within pilot feasibility studies, investigators can harness the potential of mixed methods for developing comprehensive and nuanced understandings about feasibility. Our guidance can help researchers to consider the range of key decisions needed during intervention pilot feasibility testing to achieve a rigorous mixed methods approach generating enhanced insights to inform future intervention trials.

Scoping reviews: reinforcing and advancing the methodology and application.

Scoping reviews are an increasingly common approach to evidence synthesis with a growing suite of methodological guidance and resources to assist review authors with their planning, conduct and reporting. The latest guidance for scoping reviews includes the JBI methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Extension for Scoping Reviews. This paper provides readers with a brief update regarding ongoing work to enhance and improve the conduct and reporting of scoping reviews as well as information regarding the future steps in scoping review methods development. The purpose of this paper is to provide readers with a concise source of information regarding the difference between scoping reviews and other review types, the reasons for undertaking scoping reviews, and an update on methodological guidance for the conduct and reporting of scoping reviews.Despite available guidance, some publications use the term 'scoping review' without clear consideration of available reporting and methodological tools. Selection of the most appropriate review type for the stated research objectives or questions, standardised use of methodological approaches and terminology in scoping reviews, clarity and consistency of reporting and ensuring that the reporting and presentation of the results clearly addresses the review's objective(s) and question(s) are critical components for improving the rigour of scoping reviews.Rigourous, high-quality scoping reviews should clearly follow up to date methodological guidance and reporting criteria. Stakeholder engagement is one area where further work could occur to enhance integration of consultation with the results of evidence syntheses and to support effective knowledge translation. Scoping review methodology is evolving as a policy and decision-making tool. Ensuring the integrity of scoping reviews by adherence to up-to-date reporting standards is integral to supporting well-informed decision-making.