OpenEvidence’s Meteoric Rise Is Huge For Doctors

What caught my attention is What's particularly noteworthy is InnovationHealthcareOpenEvidence’s Meteoric Rise Is Huge For DoctorsByDr

Sai Balasubramanian, M, in this volatile climate. , Contributor

Forbes contributors publish independent expert analyses and insights

Sai writes healthcare, innovation and nology

This analysis suggests that company’s goal is straightforward and incredibly ambitious: to collate the entire corpus of medical knowledge and re developments in a way that is easily accessible to physicians and thereby, imve health outcomes

Furthermore, The service is aiming to vide a similar “touch and feel” as other generative AI services such as Chat GPT or Google’s Gemini—except, its target audience is primarily doctors

Medical science is a rapidly evolving field with a perpetually expanding sea of knowledge, especially as re and development across the fields of disease, therapeutics and human sciences continue to grow

In fact, as Sequoia Capital notes, “a new PubMed article [which is often the flagship resource for peer-reviewed science studies] is published every three minutes, and medical knowledge doubles every 73 days,” meaning that there are always opportunities to learn and explore new ways to treat

Furthermore, Using a chatbot interface, physicians can query millions of studies to understand the re, trends and diagnostic tools available for a given condition or situation; according to the company, the service is already being used by more than 40% of physicians in the United States across 10,000 hospitals and medical centers

The value of this type of nology is increasingly being recognized

The models for OpenAI’s ChatGPT (GPT 4, given the current landscape. 1 and o3) have displayed incredible efficacy in taking command of medical knowledge; in May, the company published its work with HealthBench, posing a rubric for model performance in healthcare and also indicating that GPT’s models performed at par or even better than standard physician evaluations

In contrast, Even Google’s Gemini family of models has made significant gress in this space; its MedLM suite, for example, is a highly tuned model that can aid the entire healthcare workflow, ranging from answering medical questions to deciphering unstructured health data (noteworthy indeed), in today's financial world

However, Why is all of this important

On the other hand, Meanwhile, There are a few different reasons, in today's market environment

In contrast, First and foremost, this nology is aiming to democratize medical knowledge in a way that is easy to access

Furthermore, it comes at a time when the healthcare system, and its respective workforce, is facing unprecedented headwinds, given current economic conditions

Studies have repeatedly indicated that physician burnout and attrition are incredibly concerning blems for health systems and organizations of all sizes; physicians simply do not have the bandwidth to fulfill all of their patient care duties in addition to the increasingly prevalent administrative, compliance and regulatory burdens placed on them

This also means that there is less time for fessional development and continuing education

MORE FOR YOU These nologies can serve as a major advantage to the physician workflow as they vide an opportunity to easily query, fact-check and understand the science that is involved with a condition

Furthermore, Carry this even further with tools such as OpenEvidence DeepConsult, which gives physicians access to PhD-level AI agents that can conduct medical re, or Gemini’s foundation models that can rapidly decipher medical images, or even AI scribing nology that can rapidly generate patient-physician encounter notes, and soon, hours can be d from a physician’s daily workflow (this bears monitoring)

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