Treatment is bringing AI to the the next generation of healthcare professionals, supporting medical and nursing schools, who use its Global Library of Medicine to enhance future clinical skills of their students.Supplied
As a Canadian company using AI to positively disrupt the healthcare sector, Treatment welcomed the recent news of a federal government plan to include a $2.4-billion fund in the upcoming budget intended to help sectors like health and agriculture develop artificial intelligence (AI) adoption strategies.
The global AI healthcare market, valued at $11-billion in 2021, is projected to be worth $187-billion by 2030.
“This will have a positive impact on costs and cost allocation for our healthcare organizations and governing bodies,” says Dr. Essam Hamza, Chief Executive Officer of Treatment.
If qualified, the fund could help expedite several Treatment initiatives, such as the Global Library of Medicine (GLM), created to provide the highest level of qualified clinical support to healthcare professionals, ensuring enhanced diagnostic accuracy and transparency.
The Library was developed with input from hundreds of healthcare professionals from around the world and utilizes proprietary algorithms. Though still growing, it currently comprises 1,000 of the most common clinically seen illnesses and over 10,000 symptoms.
To underscore the accuracy of its platform, a non-medical student using Treatment’s medical diagnostic software for the Objective Structured Clinical Examination (OSCE), taken at medical, nursing and other professional healthcare schools, achieved a remarkable 92-per-cent success rate.
Passing the OSCE – a mandatory annual exam that tests a student’s diagnostic aptitude – is a national requirement for graduation in 57 countries worldwide, including the U.S., Canada and U.K.
The diagnostic software has operated with such accuracy, that the company has partnered with both the Mayo Clinic and the University of Minnesota, and is being used both to train medical students, and to help make quick, accurate diagnoses in hospitals.
Treatment provides solutions for medical education and clinical information support. Its’ Medical Education Suite (MES) provides case-based clinical decision-making testing, grading and remedial action support for the next generation of healthcare professionals. That includes:
- Streamlining administrative duties such as automated history taking and chart note creation — helping eliminate 15-30% of healthcare spending that goes towards administrative waste.¹
- Offering recommendations and double-checking work and treatment, by providing an explanation of every step and likelihood associated with various symptoms.
- Recommending appropriate tests and physical exams to support the accuracy of a diagnosis.
“We are extremely excited with the power and accuracy of our AI medical diagnostic engine and the faith medical schools have in utilizing it, for testing and training the medical professionals of tomorrow,” says Dr. Hamza. “This underlying software is also the foundation of new products we are planning to launch in the healthcare marketplace later this year, in our mission to dramatically disrupt how healthcare is delivered worldwide.”
With the challenges facing healthcare systems and professionals today, including burnout and staff shortages, the GLM aims to help mitigate many menial tasks such as history taking, chart notes and billing to allow for professionals to spend more quality time with patients.
Separately, the National Institute of Health (NIH) in the U.S., is funding Treatment to help develop an artificial intelligence approach for collecting information about family medical history that is culturally sensitive and appropriate for African-American families.
Current methods used by clinicians to collect family medical histories often do not satisfactorily capture important information from blended families or non-traditional relationships commonly found in racial or ethnic minority communities.
In collaboration with Minneapolis-based Rush River Research, Treatment is using its proprietary AI capabilities to change how family health is collected and recorded to address existing disparities.
The company held multiple focus groups with African-American doctors and community members to help develop and prototype culturally sensitive approaches to collecting information about family health.
Treatment and Rush River Research have recently submitted an expanded Phase 2 grant proposal to the NIH to extend the work. The goal of the proposal is to move the prototype into a commercial solution which will promote adoption and integration into electronic health records and apps.
“Old data approaches inevitably reflect old biases,” says Dr. Kevin Peterson, MD, MPH and Chief Medical Officer. “Treatment confronts issues of historical bias by reinventing how data about families is collected and stored to reflect the realities of modern life.”
Meanwhile, Treatment has also partnered with aiXplain, the industry’s first no-code/low-code integrated AI development platform.to enable greater access to GLM by contributing to aiXplain’s ever-growing dynamic AI marketplace.
Treatment and aiXplain also intend to explore mutually beneficial international opportunities through the partnership. Both parties have a shared interest in the future to provide the GLM in multiple languages.
The collaboration also allows aiXplain and Treatment to work closely on testing and development of further new mutual joint commercial applications and/or solutions. The intent of this collaboration is to promote the development, installation, testing, validation and commercialization of one or more novel solutions that further the goals of both companies and proactively impact the health care market globally.
For more information about Treatment.com AI’s products and services, please visit info@treatment.com
Advertising feature provided by Treatment. The Globe and Mail’s editorial department was not involved.