Digital Pharmacist Digest - 💻 EHR education in university, GPT4 in healthcare, and more

Hiya 👋

We’re back with another edition of the digital pharmacist digest!

Here are this week's links that are worth your time.

Thanks for reading,
Kevin

📖What I'm reading

🩺💻 Health informatics - Navigating the electronic health record in university education: helping health care professionals of the future prepare for 21st century practice

"Despite the EHR’s importance, relatively little attention is paid to how to best use this valuable resource in many healthcare professional (HCP) undergraduate curricula or postgraduate training programmes... Learning how to interpret and enter data into the EHR are essential skills, and navigating poorly developed EHRs can be a cause of work-related stress and burnout...Tomorrow’s HCPs need to know how to write in the EHR in a way that will benefit their colleagues and be medicolegally sound and will also now need to cater for a patient audience. This will also apply to hospital discharge letters, letters between specialties and comments added to test results."

🩺💻 Health informatics and 🤖 Artificial Intelligence - Microsoft Research head Peter Lee on the applications of GPT-4 in medicine and life sciences

Examples of medical use cases for GPT4 are described in the article:

• Healthcare documentation

• Medical diagnosis

• Data interoperability

• Research papers

• Biomedical studies
  

💊Patient Safety - Why Hospitals Still Make Serious Medical Errors—and How They Are Trying to Reduce Them

Patient harm from health care is persistent despite decades of effort to address problems that degrade care. This article discusses the potential that improved technology use has in reducing medication errors, falls, surgical errors, and high-risk hospital-acquired infections.

👨‍💻 Product management - Disruptive Technologies

We are constantly asking ourselves: “how can we use this new technology to solve problems for our customers, that we have never been able to solve before?”

"I used to stress about figuring out the impact of new technologies as fast as possible because I felt the clock ticking. But now I’ve learned that it’s really not possible to truly predict the impact of disruptive technologies. We can predict a few first-order effects, but the really interesting impacts are usually second or third order effects. And I think this has never been more true than with AI."

In Benedict Evans’ latest analysis he said: “There’s an old saying that when we get a new tool, we begin by making it fit the old way of working, and then we change the way we work to fit the new tool.”