Healthcare is constantly changing as big data analytics and advanced technologies such as artificial intelligence are now being applied to healthcare. These high-tech changes have the potential to transform patient care. In response to these changes, an international team of scientists has published a perspective paper describing the competencies of data scientist clinicians and addressing challenges in training these healthcare professionals. Their prospective report was published in the journal Health Data Science on August 8, 2022
A data scientist clinician combines in-depth clinical knowledge with data science skills. These healthcare professionals are well equipped to identify the healthcare challenges that accompany the growing digital transformation. They are able to conduct meaningful research, communicate well across disciplines, and provide shared critical interpretations. With their interdisciplinary knowledge, these data scientist clinicians will play a critical role in guiding the approvals of innovative technologies and the creation of digital health policy.
“In the age of digital health, data scientist clinicians are extremely important because they have a deep understanding of both data science and the humanistic nature of medicine and are ready to identify clinically important questions,” said Luxia Zhang, professor at National Institute of Health Data Science, Peking University.
In their perspective paper, the researchers explore the core competencies that a data scientist clinician should possess, emphasizing that these individuals must be able to closely bridge medicine and data science to work effectively and enable data-driven healthcare discoveries .
“The core competencies of a data scientist clinician should include a fundamental understanding of health data, training in epidemiology, statistics, bioinformatics, and computer science, combined with an understanding of continuous healthcare improvement frameworks, socio-technical system challenges, and advanced skills in interdisciplinary communication and collaboration,” said Dr. Mai Wang of the National Institute of Health Data Science, Peking University. Researchers believe that with a strong understanding of healthcare and the ability to identify knowledge gaps in medical practice, data scientist clinicians will play a critical role in data research projects.
In addition to exploring the core competencies a data scientist clinician needs, the researchers also explored the training these healthcare professionals need. This learning is challenging due to the increased complexity of data and the rapid development of analytical techniques. As an added challenge, data science is not part of conventional medical training. While some medical schools are beginning to modify their curricula, in general, integrated formal training programs for clinician-data scientists are scarce globally.
Researchers see teamwork as key to this process. “To address learning challenges, senior clinical faculty and data scientists must form a close partnership and work together to design learning frameworks with flexibility and frequent updating to adapt to different application scenarios,” Wang said.
Looking to the future, the researchers emphasize that clinical data specialists are key members of the patient health care team. Clinicians need training in data science skills. At the same time, data scientists with deep technical skills are needed so that key clinical questions are formed and prioritized.
“Data scientist clinicians are critically important because they possess a deep understanding of both the science and the humanistic nature of medicine and are poised to identify clinically important questions that, if addressed, can make medical advances and provide excellence in patient care,” said Zhang.
“The next step is to form a training framework and design curricula that focus on the core competencies required of data scientist clinicians. And this needs to be constantly updated to adapt to new developments,” Zhang said.
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Fulin Wang et al, Clinical Data Specialists – Preparing for the Future of Medicine in a Digital World, Health Data Science (2022). DOI: 10.34133/2022/9832564
Provided by Health Data Science
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