Misdiagnosing cases can be dramatically reduced through AI application. Source: Shutterstock

Misdiagnosing cases can be dramatically reduced through AI application. Source: Shutterstock

Experts believe that AI can enhance the clinical decision support system

ONE OF the most critical issues affecting medical professionals and healthcare organizations alike is the misdiagnosing of patients.

In the healthcare industry, diagnostic errors are not only costly but also deadly and can severely tarnish the reputation of an institution.

According to a recent study, diagnosing errors contribute directly to higher mortality and longer hospital stay – especially among emergency room (ER) patients.

The clinical decision support system (CDSS) is among advances that reduce human errors and help provide better care.

This is not to say that the expertise of healthcare professionals is flawed, but mistakes are sometimes unavoidable and CDSS has helped improved clinical decisions.

While CDSS is important, it is not exactly groundbreaking technology. This is why medical experts John Halamka and Paul Cerrato, who specialize in the adoption of medical health records, wrote a book Reinventing Clinical Decision Support: Data Analytics, Artificial Intelligence, and Diagnostic Reasoning.

The experts believe that CDSS should be integrated with artificial intelligence (AI) to help the system look past the archaic “most diseases have a single cause” theory.

Medicine is constantly evolving

As a field, medicine is becoming more complex every day and can overwhelm the human mind. Having said that, there is also an urgent need to meet the increasing demand for quality healthcare services.

There is only so much that limited systems and the human mind can do, but AI can drastically change this through automated symptoms analysis, predictive analytics, and precise treatment suggestions.

A precision-based approach to medical diagnostics and patient care is a solution that healthcare providers can no longer afford to ignore.

“Algorithms that take advantage of machine learning, neural networks and a variety of other types of artificial intelligence (AI) can help address many of the shortcomings of human intelligence,” said the experts.

Obviously, challenges and shortcomings are to be expected.

Issues such as the explainability of AI in producing decisions may cause skepticism among healthcare providers and professionals. There is also a mixed result in how AI integration impact patients’ outcome. Fortunately, these issues are easy to solve through data improvement and better training.

The experts did make it a point to stress that embracing digital innovation will not undermine the skills of trained healthcare professionals.

True enough, in their words: “Little doubt that a competent physician who uses all the tools that AI has to offer will soon replace the competent physician who ignores these tools.”