TECHNOLOGY INNOVATION IN HEALTHCARE
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TECHNOLOGY INNOVATION IN HEALTHCARE


Universities should produce new generations of doctors and nurses who are capable of understanding and capable of using information technologies as well as expressing their clinical needs in a way that is comprehensible to IT professionals. At the same time, IT professionals should delve more deeply into the processes of diagnosis, therapy, and care. Not to approach them with an engineering mindset, but by putting themselves in the shoes of healthcare workers [and patients]. If we envision the hospital of the future, where artificial intelligence and the web will be used extensively for decision support, predictive analysis tools, and process and production optimization solutions, we can understand why it is necessary to break down the barriers that separate healthcare professionals from technology and the market, and how the role of the Chief Information Officer in healthcare organizations will need to change significantly. [freely adapted from the article* by Paolo Colli Franzone ].

In order for technologies to work synergistically, we must ensure that people know how to collaborate and learn that, even in very complex and multifaceted organizations. This topic encompasses various issues, including cultural, soft skills, educational and training, and technological aspects. It is not the usual story of teamwork or gathering together - It is a cultural issue - maybe I should write "deep skills".

Today and even more so in the future, (hyper)specialization is essential. However, on its own, it is not fully effective and risks becoming a source of frustration. To project into the future, that is, to innovate, it is equally essential to open as many other mental channels as possible with which nature has endowed us, such as 'forma mentis', dialogic, peripheral, or lateral thinking, or whatever you prefer to call that which allows us to develop and consolidate the aptitude and ability to grasp the meaning of what lies outside of us and our specific skills.

Culture is essentially the ability to navigate and 'orient' oneself in the face of what happens, who we meet, and the new. It is the desire and ability to 'absorb without being absorbed.' Education and training do not equate to culture. The amount of data and overall knowledge is increasing at an ever-faster rate. While it has never been possible to know everything, now the horizon of what we can aspire to master is narrowing ever more rapidly. To understand and communicate, to collaborate, it is necessary to keep an open mind to new things and diversity. This is the only true commitment to inclusion. We must increasingly develop ectopic roots that project and grow towards different perspectives and other people. To those who believe that specialization is the fundamental ingredient for innovation, I respond, no. The fundamental ingredient is the drive (the tropism), the attitude, and the ability to generate new connections between different 'things,' such as people, ideas, technologies, languages, and scenarios. Here, the concept and practice of imagination also come into play. Interestingly, the growth of the nervous system, as well as learning and imagination functions, are interwoven with the growth of new, unpredictable neural connections.

Finally, and no less importantly, I would like to point out that the extensive use of artificial intelligence, machine learning, and the web is very useful for obtaining decision support. However, decisions cannot be entrusted even to the most advanced technological tools. The support they can provide will become increasingly functional for our purposes, but it can never replace the decision-making function, which is inherently human. This is where the topic of Decision Science comes into play.

* https://tinyurl.com/2jxrcczw


Giovanni Righini

Professor at Università degliStudi di Milano

4 个月

I completely agree, Antonio. From an ICT viewpoint, many insist on the role of data, especially "big data". On the contrary, from a mathematical perspective, innovation is triggered by reasoning on models, consists of conceiving new and better models and is accumulated in models themselves. By model, I mean the mathematical model of a decision problem. This really makes decision-making inherently human and advocates the development of Decision Science, as you point out.

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