According to Jithin K. Sreedharan, respiratory therapists see value in lung ultrasonography (LUS) and artificial intelligence (AI), but many lack training in those tools.
Sreedharan is an assistant professor and the head of the U of M’s department of respiratory therapy. He studies how respiratory therapists learn and use new clinical tools. Sreedharan’s work spans respiratory care, LUS, AI and the design of healthcare education programs.
In a study of 256 respiratory therapists, Sreedharan and his colleagues found that 18.1 per cent used LUS in practice, while 43 per cent had never received training. A second study involving 514 respiratory therapists in 22 countries found a positive attitude toward the tool alongside gaps in formal training, he shared.
According to Sreedharan, LUS can help trained clinicians assess conditions including fluid around the lungs and areas of collapsed lung. It can also provide information while patients are on mechanical ventilation or being taken off it, Sreedharan explained.
For respiratory therapists, the appeal includes being able to assess patients at the bedside. However, his research points to a question for educators asking them how to teach the skill and assess whether graduates can use it competently.
Sreedharan said the findings from his research informed a change at Prince Sultan Military College of Health Sciences, where LUS was added to the final year of a respiratory care bachelor’s program through structured training involving multiple disciplines.
In another survey of 448 respiratory therapists about the knowledge and perception of AI involvement in practice, 51 per cent believed AI would play an important role in the profession’s future, but 28 per cent reported some knowledge of it and 8.5 per cent had practical experience, Sreedharan said. Fifty-nine per cent supported teaching AI fundamentals in respiratory care programs.
Sreedharan said AI could have uses in areas such as medical imaging, patient monitoring and predicting when a patient’s condition might worsen. He cautioned that its use in patient care requires clinical validation, protection of patient data, attention to bias and clear professional oversight.
“The important point is that I see AI as an augmentation of respiratory therapists’ clinical expertise rather than a replacement for professional judgment,” he said.
He is now developing a framework for adding AI, simulation and other technologies to healthcare programs. The project examines what institutions need before introducing a tool, including equipment, faculty training and access for students. The proposed framework moves from assessing readiness to adding technology to courses and evaluating how well it works.
Sreedharan’s interest in education grew out of his clinical work in critical and emergency care. He said that experience led him to consider how training affects the decisions healthcare workers make.
“When I transitioned into academia and began developing and leading Allied Health programs across different countries, my research questions naturally expanded from ‘How do we improve clinical practice?’ to ‘How do we better prepare the people who deliver that care?’” he said.
One of his works also examines how students build research skills during clinical training and how programs assess clinical competence. He is developing an assessment framework that draws on direct observation, simulation, portfolios and feedback from multiple sources. He plans to test it with students, clinical supervisors and faculty at multiple sites.
For students, Sreedharan advised them to see research as part of respiratory therapy practice, whether they pursue clinical care, education or leadership.
“Research does not have to begin with a complicated idea,” he said. “Ask simple but important questions: Why do we do this? Is there a better way? What evidence is missing? How could this improve a patient’s care?”
