According to Forbes, the healthcare industry may be “the sector most affected by the enormous changes of the fourth industrial revolution”.
With the continuous development of technology and the increasing importance of data, new professions are emerging that require specific skills for data analysis (statistics, data visualisation, clustering, classification, etc.), the use of artificial intelligence (machine learning, deep learning, robotics, computer vision, natural language processing, etc.) but also for the proper application of regulations to digital solutions and their fair, transparent and safe use.
Among the most in-demand professions are data scientists, bioinformaticians, experts in artificial intelligence, virtual and augmented reality, robotics technicians, materials scientists etc.
Not just new jobs
The digital transformation, however, will not be limited to the introduction of new professionals able to better manage the introduction of advanced technologies and artificial intelligence systems, but will also involve all traditional professions.
The process, in fact, is progressively changing the content and mode of service delivery in all healthcare professions through the automation of processes, the remoteisation of activities, the introduction of sensors for real-time monitoring, and the development of software and devices to assist patients and healthcare workers.
To accommodate this very near future – some of which is already present – doctors will have to learn to familiarise themselves with telemedicine and remote communication systems, surgeons will have to master robotic equipment, nurses will have to get used to managing patients wearing electronic sensors and interacting with IoT monitoring systems, etc.
In addition, health professionals will have to learn how to collaborate with experts in new emerging professions. These figures have specific skills in data analysis, genomics, artificial intelligence, automation and robotics, but in order to apply them to the healthcare context they will have to work in parallel with clinicians.
The work will be increasingly co-operative and cross-functional: data scientists will collaborate with clinicians to develop artificial intelligence models (e.g. with oncologists and researchers to create predictive models of tumours), biomedical engineers will work with orthopaedists and physiotherapists to design new prostheses and devices for musculoskeletal rehabilitation, software developers will work alongside clinicians to develop devices and apps for remote diagnostics and monitoring of patients.
…but without contact
Working patterns are also set to change by integrating new modes such as teleworking, coworking and flexible working environments. This certainly has many positive aspects but also brings with it several grey areas.
According to a report by the International labour organisation, flexible working hours have an extremely positive impact on the productivity and well-being of employees and offer women a greater chance of remaining active in the labour market after childbirth.
However, the ability to work from anywhere and at any time can lead to social and professional isolation and can lead to a kind of ‘dependency’ that eliminates the boundary with private life.
Jobs at risk?
A particularly sensitive aspect concerns the impact that new technologies may replace human operators in performing certain tasks.
Job losses are certainly a real possibility, but the rapid growth of technology has actually opened the way for endless job opportunities.
Ashok K Harnal, The Economic Times
A 2021 study in the medical field suggests that the introduction of artificial intelligence systems has varying effects depending on the job roles occupied.
For example, the results show that the salaries and employment levels of doctors and surgeons both increased after the introduction of ‘Watson for healthcare’ (IBM’s AI system dedicated to healthcare) in 2013, while no significant effect was found for secretaries and administrative assistants .
The main technology-related professions in pharma
Data scientist: a professional who analyses large amounts of data collected from clinical trials, experiments and other sources to obtain useful information on drug performance and patient needs.
Artificial intelligence expert: a professional who develops and uses machine learning and artificial intelligence algorithms to improve drug discovery, drug safety assessment and personalisation of treatments.
Robotics and automation expert: a professional who uses robotic technologies to automate the drug development and manufacturing process, from compound synthesis to distribution.
Materials scientist: a professional who develops new materials for medical devices, such as sensors, pumps, implants and prostheses, to improve their safety, durability and functionality.
Pharmaceutical technologist: a professional who uses information technology to monitor the production of drugs, ensuring that they are produced safely and comply with regulations.
Augmented and virtual reality expert: a professional who uses augmented and virtual reality to improve the effectiveness of treatments, the training of healthcare professionals, and patients’ understanding of their conditions.