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Refining the profile of the health workers of the future: the feedback of the European Medical Association members

By Guglielmo M. Trovato MD, the European Medical Association (EMA)

The profile of the health workers of the future is a inclusive debate on the core competences required in the emerging models of care, on the gaps in the current educational and profession pathways, and on the policy changes necessary to support health workers in the transformation of care.

The HFE paper includes also some policy recommendations addressed to the European Policymakers. The development of skills focused to interdisciplinary teamwork, person-centric communication, digital competences and flexibility to different settings, facilities and resource availability and models of care is warranted. Analyzing the feedback contributed by the European Medical Association Members, we detected few topics which deserves a further focus in inter-related subset, and among them:

  1. The increase of quality and effectiveness of medical practice in limited resources contexts. This calls for an explicit support to the achievement of skills and sustainable tools – such as diagnostic ultrasound and point of care lab – suitable for timely diagnosis in the perspective of
      • more effective secondary prevention
      • reducing the costs of redundant or delayed diagnostic procedures
      • timely emergency interventions.
  1. The growth of digital infrastructures for health care education and lifelong education and training should follow a sustainability cascade of priorities:
      • development of e-learning professional competences. These must be tailored for delivering high impact courses effective for promoting and guaranteeing the wished behavior and practice changes of the greater number of attendees;
      • capability of managing data collection and protection;
      • expertise in running diagnostic, monitoring and treatment response information to optimize care pathways;
      • awareness of the availability of advanced artificial intelligence (AI) supports for e-medicine and for the use of innovative device, materials, drug, procedures. Such comprehensive work-ups, diagnostic and therapeutic should be suitable to be engineered in processes of reliability and clinical risk management.

These issues, encompassing the features of evidence-based-medicine and of innovative big-data management, should include knowledge and skills in stat-math domains (basic computational statistics) for better assessing reliability of information available. Such competence, since can be acquired by basic interactive web-based courses, should be more explicitly endorsed by academic, research and professional organization. The current trend, calling for a greater psychological and social disposition of practicing medical doctors, may favor anti-science and misleading non-conventional medicine credence and approaches, which are actual threats for the health of individuals and populations.

A recent survey of the European Medical Association reported that Health Professionals do not trust strongly in the realistic benefits of using e-learning courses for teaching digital skills pertinent for medical practice. Actually, this is contradictory with the extremely wide and agile use of video tutorials, also among MDs. Most tutorials are freely accessed, for solving setbacks and snags in the use of several apps and in many basic physical rehabilitation maneuvers or tricks.

There seems to be a natural refractoriness of doctors for the use of mathematical or statistical tools. This contrasts with the use of machinery with high technological content. Even more, despite the mandatory nature of statistical courses in the curricula of the Schools of Medicine, basic knowledge and ability to choose and use appropriate statistical tools for data management seemingly remain the heritage of a few physicians, if particularly interested in research. For this reason, the forthcoming BioS course in bioinformatics and computational biology, whose architecture includes computational statistics, is particularly worthy of use. The BioS Project is an action funded by Erasmus Plus and the European Commission.

Computational statistics, or statistical computing, is the interface between statistics and computer science. Even if this sector is developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education, unmet needs and conspicuous gaps are evident. As in traditional statistics the goal is to transform raw data into knowledge: however, the focus lies on computer intensive statistical methods, such as cases with very large sample size and non-homogeneous data sets. A wide audience of MDs and health professionals can be trained for using online stats and med calculators, as in some School of Medicine was and is already done.

We recall below by an abridged index some of relevant posted information regarding how we can face with some specific statistical approach. The aim is to encourage learning by doing computational statistics,  still in pills, but already suitable to be translated into practice.

Lesson 1 – Introduction October 8th , 2013

Lesson 2 Which Statistics Test Should I Use? October 15th , 2013


G. Trovato EMA

Guglielmo Trovato 

EMA– European Medical Association