Paris Hospitals: Big Data in Healthcare
23 July 2021
How hospitals in Paris are using Big Data in practice
At four of the hospitals which make up the Assistance Publique-Hôpitaux de Paris (AP-HP), data from internal and external sources – including 10 years’ worth of hospital admissions records– has been crunched to come up with day- and hour-level predictions of the number of patients expected through the doors.
The system allows doctors, nurses and hospital administration staff to forecast visit and admission rates for the next 15 days. This means extra staff can be drafted in when high numbers of visitors are expected, leading to reduced waiting times for patients and better quality of care.
The technical details
The system is built on the open source Trusted Analytics Platform (TAP) – which was chosen for the task due to its capacity for ingesting and crunching large amounts of data. As well as the hospital’s internal data, several external datasets such as weather, public holidays and flu patterns were tapped.The result is a web browser-based interface designed to be used by staff who are untrained in data science.
The core of the analytics work involves using time series analysis techniques – looking for ways in which patterns in the data can be used to predict the admission rates at different times. Machine learning is employed to determine which algorithms provide the best indicator of future trends, when they are fed data from the past.
Lessons learned will undoubtedly prove valuable for the group’s next Big Data project – building a data warehouse to store all of its clinical data in a form that can be interrogated by common techniques such as Python or R algorithms.
Ideas and insights you can steal
With the cost of providing healthcare increasing at more than the rate of GDP in every developed country, smart, intelligent systems like AP-HP’s are likely to play an important part in the future of healthcare. By more accurately predicting the demand for services, waste can be cut, and patient care can become more efficient.
Reducing waste and increasing efficiency is something that most companies in most industries can aspire to – from predicting customer numbers in order to plan staffing, to predicting the popularity of products and services at various times of the year, and many more applications. Predictive modelling can help you do all this and more.
You can read more about how organisations are using Big Data to drive success in Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results.
Related Articles
The 10 Tech Trends That Will Transform Our World
What makes the fourth industrial revolution so different from previous industrial revolutions is the convergence and interaction between multiple technology trends at once. In thi[...]
How Any Business Can Build Data Skills
Anyone interested in how businesses can start making better use of the explosion of data that's available for capture, analysis, and insights, has probably heard about the data skills crisis.[...]
How To Build A Business Data Infrastructure
In the information age, data is one of a company’s most valuable assets. Businesses that distinguish themselves in how they work with data are leading the field.[...]
How Do You Prioritize Data Projects?
Every business could come up with hundreds (or thousands) of potential data projects. How do you prioritize?[...]
9 Steps You Can Take to Help Save the Planet
Caring for our natural world is everyone’s responsibility. The good news is that taking action to reduce your impact doesn’t have to be difficult or expensive[...]
The 5 Biggest Cloud Computing Trends In 2022
During 2020 and 2021, cloud computing exploded as work went virtual and businesses adapted to the global pandemic by focusing[...]
Stay up-to-date
- Get updates straight to your inbox
- Join my 1 million newsletter subscribers
- Never miss any new content
Social Media