In statistics, if one has a sample size that is large enough, one can make an estimation with a certain degree of accuracy.
When I was a student, a sample of a few thousand cases was already considered quite remarkable.
With the advent of artificial intelligence and big data technology, crunching enormous data has become feasible.
By analyzing the data, we can establish links among seemingly disparate and irrelevant information and predict what’s going to happen.
Colorectal cancer, for example, has been the leading cause of death in urban areas for years, and there has been no consensus about its causes.
But by analyzing data on colorectal cancer involving more than 100 million people from six countries and regions, the Chinese University of Hong Kong (CUHK) was able to establish that the incidence of colorectal cancer among younger age groups has been on the rise. Research also suggested the risk factors might stem from unhealthy lifestyles in the cities.
Given this trend, the Hong Kong government has regularized the subsidized screening program since last year and has extended it to residents in the 50-75 age bracket in phases, from 61-70 previously.
The program aims to identify high-risk groups and patients without obvious symptoms. In the long run, it would help reduce medical costs and the social burden.
Will the combination of technology and medical science be able to predict other diseases? Are there other things we can do?
These are the questions the government should ask when planning the allocation of medical resources.
Having so much data at its fingertips, the government should be able to build a better Hong Kong by processing and harnessing it in different fields.
This article appeared in the Hong Kong Economic Journal on Jan 11
Translation by Julie Zhu
[Chinese version 中文版]
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