What medical staff hate most isn't overtime. It's writing reports
Originally written in Chinese. Translated with AI, reviewed by Gary. Read the Chinese original →
One more takeaway from the CommonWealth Economic Forum:
As Taiwan becomes a super-aged society, its healthcare system faces unprecedented challenges. In a recent talk, 程文俊, chair of the decision committee at the Chang Gung Medical Foundation, pointed out that the population over 65 grows every year and diseases of old age such as cancer keep rising. That raises the bar for healthcare: in future it must focus more on integrated care and precise treatment for elderly patients.
At the same time, as ageing accelerates, long-term care and palliative care matter more and more. Chang Gung has put a lot of effort into this area, for example by opening a retirement village and launching end-of-life services for seniors, giving them all-round support.
How can AI empower healthcare?
In his talk, 程文俊 named a major challenge facing healthcare today: staff shortages. Applying artificial intelligence (AI) can offer a way through.
He gave a very interesting example:
Writing medical reports is one of the biggest headaches for many medical staff, yet reports are essential. Only with accurate patient records can doctors plan precise treatment.
It turns out that what many medical staff hate most isn't overtime, or even treating patients. It's that most of their time goes into "writing reports".
Bringing in AI can help medical staff generate and manage reports automatically, reducing the time and energy spent on repetitive work, which raises efficiency and lowers staff turnover.
From healthcare to managing a team
In a startup's early days, the team is small, communication is fairly simple, and progress is easy to track. But as the team grows, tracking projects and goals gets much more complicated, and reports matter more and more.
Riding the AI wave doesn't necessarily mean building complex large models. Using the AI technology we already have well can speed up our work and lighten the load.
For example, use AI tools to generate reports, organise data or streamline communication. As long as we make good use of what's already available, we can each go further in our own fields.