Background Health care can broadly be divided into two domains: clinical health services and complex health services (ie, nonclinical health services, eg, health policy and health regulation). Artificial intelligence (AI) is transforming both of these areas. Currently, humans are leaders, managers, and decision makers in complex health services. However, with the rise of AI, the time has come to ask whether humans will continue to have meaningful decision-making roles in this domain. Further, rationality has long dominated this space. What role will intuition play? Objective The aim is to establish a protocol of protocols to be used in the proposed research, which aims to explore whether humans will continue in meaningful decision-making roles in complex health services in an AI-driven future. Methods This paper describes a set of protocols for the proposed research, which is designed as a 4-step project across two phases. This paper describes the protocols for each step. The first step is a scoping review to identify and map human attributes that influence decision-making in complex health services. The research question focuses on the attributes that influence human decision-making in this context as reported in the literature. The second step is a scoping review to identify and map AI attributes that influence decision-making in complex health services. The research question focuses on attributes that influence AI decision-making in this context as reported in the literature. The third step is a comparative analysis: a narrative comparison followed by a mathematical comparison of the two sets of attributes—human and AI. This analysis will investigate whether humans have one or more unique attributes that could influence decision-making for the better. The fourth step is a simulation of a nonclinical environment in health regulation and policy into which virtual human and AI decision makers (agents) are introduced. The virtual human and AI will be based on the human and AI attributes identified in the scoping reviews. The simulation will explore, observe, and document how humans interact with AI, and whether humans are likely to compete, cooperate, or converge with AI. Results The results will be presented in tabular form, visually intuitive formats, and—in the case of the simulation—multimedia formats. Conclusions This paper provides a road map for the proposed research. It also provides an example of a protocol of protocols for methods used in complex health research. While there are established guidelines for a priori protocols for scoping reviews, there is a paucity of guidance on establishing a protocol of protocols. This paper takes the first step toward building a scaffolding for future guidelines in this regard. International Registered Report Identifier (IRRID) PRR1-10.2196/42353

BACKGROUND Humans currently dominate decision-making in both clinical health services and complex health services such as health policy and health regulation. Many of the assumptions inherent in health service models today are underpinned by Expected Utility Theory (Ramsey, 1926), a prominent theory in the field of economics that is rooted in rationality. Such rational, evidence-based metrics currently dominate the culture of decision-making in health policy and regulation. However, as the Covid-19 pandemic has shown, rational metrics alone may not suffice in making better policy and regulatory decisions – intuition is equally valuable. Nevertheless, rationality may well be entrenched and may influence the lexicon of our thinking about decision-making. Therefore, this scoping review has real-world, practical value, as it highlights the counter narrative of decision-making that is underpinned by the uniquely human attribute of intuition. This may have ramifications for decision-making in complex health services today. It may also point to the importance of incorporating both intuitive and rational attributes in programming and training artificial intelligence for the healthcare of the future. OBJECTIVE The aim is to map the attributes that influence human decision-making in complex health services. METHODS This scoping review was designed to answer the following research question: What attributes have been reported in the literature that influence human decision-making in complex health services? It provides a clear, reproducible methodology and is reported in accordance with the framework and recommendations by Peters et al. (2015). As the topic of interest merits broad review to scope and understand literature from a holistic viewpoint, a scoping review of literature was appropriate here. A database search within three search systems identified 140 potential records. Inclusion and exclusion criteria were developed. Based on these criteria, four articles were deemed relevant. Four additional articles were added through citation tracking. RESULTS The results of this review highlight key themes that underline the complex and nuanced nature of human decision-making. The results suggest that rationality may be entrenched, and may influence the lexicon of our thinking about decision-making. The results also highlight the counter narrative of decision-making that is underpinned by the uniquely human attribute of intuition. The review, itself, takes a rational approach, and the methods used were suited to this. CONCLUSIONS This scoping review identifies and maps attributes that influence human decision-making in complex health services. The review itself has taken a rational approach, and the methods used were suited to this. However, there may be scope to take a more intuitive approach. The results of this review indicate that human decision-making is both complex and nuanced. Rationality has been so entrenched that it has influenced the lexicon of our thinking about decision-making. This review has highlighted the counter narrative of decision-making that is underpinned by the uniquely human attribute of intuition. INTERNATIONAL REGISTERED REPORT RR2-10.2196/42353

Humans currently dominate decision-making in both clinical health services and complex health services such as health policy and health regulation. This scoping review identifies and maps attributes that influence human decision-making in complex health services. A systematic search identified 140 potential articles. Inclusion and exclusion criteria were developed. Based on these criteria, four articles were deemed relevant. Four additional articles were added through citation tracking. The results of this review highlight key themes that underline the complex and nuanced nature of human decision-making. The results suggest that rationality may be entrenched, and may influence the lexicon of our thinking about decision-making. The results also highlight the counter narrative of decision-making that is underpinned by the uniquely human attribute of intuition. The review, itself, takes a rational approach, and the methods used were suited to this.

Nanomedicine contributes to cancer therapeutics in several ways, harnessing some of the remarkable properties of nanomaterials to target tumor cells with increasing specificity. Nano-scale therapeutic strategies enable the simultaneous transport of hydrophilic and hydrophobic drugs across physical and physiological barriers like the blood-brain barrier. Alternative routes of drug administration, such as the intranasal route, have become viable, with more promising therapies for highly lethal tumors like glioblastomas. Cancer nanomedicine allows increased solubility and bioavailability of anti-cancer drugs, reducing their toxicity. Multi-drug delivery systems such as dendrimers, noble metal nanoparticle drug delivery systems, nanoparticle-based theranostics, and nano-biomarkers may well bring about a sea change in cancer therapeutics. This review presents an overview of the scope of cancer nanomedicine, including immunotherapy for cancer.

BACKGROUND Health care can broadly be divided into two domains: clinical health services and complex health services, i.e., non-clinical health services such as health policy and health regulation. Artificial Intelligence (AI) is transforming both these areas. Currently, humans are leaders, managers, and decision makers in complex health services. However, with the rise of AI, the time has come to ask whether humans will continue to have meaningful decision-making roles in this domain. OBJECTIVE The objective is to establish a protocol of protocols to be used in the proposed research, which aims to explore whether humans will continue in meaningful decision-making roles in complex health services in an AI-driven future. METHODS The proposed research is designed as a four-step project, divided into two phases. In keeping with this design, the overarching protocol encompasses (i) the protocol for a scoping review that aims to identify and map human attributes that influence decision-making in complex health services; (ii) the protocol for a scoping review that aims to identify and map AI attributes that influence decision-making in this context; (iii) the protocol for a comparative analysis of human and AI attributes identified in the reviews; and (iv) the protocol for a simulation that tests the likelihood of humans competing, cooperating, or converging with AI in order to continue in meaningful decision-making roles in this context. RESULTS The results will be presented in tabular form, as well as visually intuitive formats. CONCLUSIONS This paper provides a roadmap for the proposed research. It also provides an example of a protocol of protocols for methods used in complex health research. While there are established guidelines for a priori protocols for scoping reviews, there is a paucity of guidance on establishing a protocol of protocols. This paper takes the first step towards building a scaffolding for future guidelines in this regard. CLINICALTRIAL This protocol of protocols has not been registered.