Collaborative Intelligence to catalyze the digital transformation of healthcare

Abstract

Collaborative intelligence reflects the promise and limits of leveraging artificial intelligence (AI) technologies in clinical care. It involves the use of advanced analytics and computing power with an understanding that humans bear responsibility for the accuracy, completeness and any inherent bias found in the training data. Clinicians benefit from using this technology to address increased complexity and information overload, support continuous care and optimized resource allocation, and to enact efforts to eradicate disparities in health care access and quality. This requires active clinician engagement with the technology, a general understanding of how the machine produced its insight, the limitations of the algorithms, and the need to screen datasets for bias. Importantly, by interacting, the clinician and the analytics will create trust based on the clinician’s critical thinking skills leveraged to discern value of machine outputs within clinical context. Utilization of collaborative intelligence should be staged with the level of understanding and evidence. It is particularly well suited to low-complexity non-urgent care and to identifying individuals at rising risk within a population. Clinician involvement in algorithm development and the amassing of evidence to support safety and efficacy will propel adoption. Utilization of collaborative intelligence represents the natural progression of health care innovation, and if thoughtfully constructed and equitably deployed, holds the promise to decrease clinician burden and improve access to care.

Use of Artificial Intelligence tools in supporting decision-making in hospital management

“…The lack of understanding about AI models emerges as a complicating element for trust in its use and full comprehension of its functionalities and practical advantages [30,40] . This situation, while not exclusive to health institutions and managers, becomes critical due to the impact it could have on the decision to adopt it as a tool to support organizational and even clinical management, due to the indirect effects of management mechanisms on health structures [41][42][43] . The ethical concerns expressed by managers are evident and expected [17] .…”

“…Moreover, the vision of leadership is conditioned by the perception of existing technology and thus, it is imperative that healthcare organization leaders understand the capabilities, potential, and new digital trends [32] . Collaborative intelligence, which integrates human perception and analysis with AI's computational power, emerges as an essential strategy to overcome some of the barriers mentioned [43] . In this way, it will be possible to take into account the need for active involvement of managers in AI development, ensuring that technology not only supports but also amplifies analytical capacity, creating more responsive and efficient health systems [38,43,48,49] .…”

“…Collaborative intelligence, which integrates human perception and analysis with AI's computational power, emerges as an essential strategy to overcome some of the barriers mentioned [43] . In this way, it will be possible to take into account the need for active involvement of managers in AI development, ensuring that technology not only supports but also amplifies analytical capacity, creating more responsive and efficient health systems [38,43,48,49] .…”