Project Algo
If you've spent any time working in healthcare or have had to use it, you're likely aware of the challenges clinicians face in the health & fitness industry. Year over year, the demands on clinicians seem to have increased—not only in patient volume but also in complexity. This could partly be attributed to the growing recognition of exercise's positive effects on various conditions by other healthcare professionals but there may be other reasons.
I believe it is mainly the result of health & fitness clinicians assuming greater responsibilities within healthcare. This is not just about taking on more administrative work or secondary duties but rather an expansion of their scope of practice. Year over year, I've felt a widening in the average clinician's scope of practice, with seemingly more conditions to treat and manage, increasing uncertainty, and posing more challenges for delivering effective care.
From my perspective, today's primary challenge is that most clinicians have, knowingly or unknowingly, become first-line practitioners, now requiring a working knowledge that extends beyond common musculoskeletal issues. An increasing number of patients attend clinics without seeing a GP, placing the entirety of the patient's health responsibility on the treating clinician.
In the past, the solution for treating patients with complaints outside of common musculoskeletal issues was to attend seminars and develop protocols for effective care. However, this method has become impractical as we've moved from managing a few conditions to many, especially when protocols change and become more nuanced each year. It can drive a sane person into madness trying to stay updated with the relevant changes in each protocol.
The only practical solution to this issue is to incorporate and integrate computer algorithms into patient care. Before you shake your head, consider that you might already be thinking through an algorithmic process when deciphering a patient's condition and determining the most suitable treatment. Of course, the intention is not to replace the clinician but to offer guidance on differentials, highlight relevant information, and outline a suitable treatment pathway.
In the past, the solution for treating patients with complaints outside of common musculoskeletal issues was to attend seminars and develop protocols for effective care. However, this method has become impractical as we've moved from managing a few conditions to many, especially when protocols change and become more nuanced each year. It can drive a sane person into madness trying to stay updated with the relevant changes in each protocol.
The only practical solution to this issue is to incorporate and integrate computer algorithms into patient care. Before you shake your head, consider that you might already be thinking through an algorithmic process when deciphering a patient's condition and determining the most suitable treatment. Of course, the intention is not to replace the clinician but to offer guidance on differentials, highlight relevant information, and outline a suitable treatment pathway.
By integrating algorithms into the diagnostic process with the potential to suggest suitable treatment pathways, we can streamline patient care, enabling clinicians to devote more attention to the nuanced aspects of care that necessitate a human touch—empathy, understanding, and personalized attention.
My ultimate vision involves seamlessly incorporating these algorithms into electronic medical records to enhance the clinical practice. This idea has stayed at the back of my head for some time, born out of the hope that someone with a deeper knowledge of computer programming would recognize its potential and bring it to fruition. Unfortunately, so far, no one has taken up the challenge to develop this concept to the extent that it markedly influences clinical practice.
