Podcast: Meet our Researchers

Chris Paton

Dr Chris Paton studies the use of open-source Electronic Health Records (EHR) software, online learning and mobile technology to improve healthcare delivery in low-resource settings.

Current projects include a survey of EHR systems in use in Kenya, a simulation of Health IT infrastructure, and a mobile game for training healthcare professionals to deal with emergencies.

Global health informatics

Learning health system

In a learning health system, health care providers use electronic health records to identify problems, implement local solutions and check if the solutions are effective.

Health informatics, or the use of IT in healthcare, needs to find innovative solutions for low income settings, such as the use of open-source softwares and mobile technology. This approach has been used to deliver training to rural healthcare workers in Kenya.

Translational Medicine

From Bench to Bedside

Ultimately, medical research must translate into improved treatments for patients. At the Nuffield Department of Medicine, our researchers collaborate to develop better health care, improved quality of life, and enhanced preventative measures for all patients. Our findings in the laboratory are translated into changes in clinical practice, from bench to bedside.

Chris Paton: Global health informatics

Q: How can informatics help us understand global health issues?

Chris Paton: Health informatics is about the use of IT in healthcare. In high income settings like the UK and the US, we have been using IT in hospitals and clinics for quite a long time now. Our research is looking at the use of IT in healthcare in low resource settings, such as Kenya.

In high resource settings, although we have had the technology in place for quite a long time, we are now starting to use the data that is stored in the systems as part of what is called a learning health system: we analyse the data that is stored in electronic health records systems to for example, identify any problems with care, then implement new solutions to address the issues and then look in the same data source to see whether the solutions have been effective. Our research is about how we can apply that same process of the learning health system in a low resource setting.

Q: What are some of the issues in low income settings that your approach has identified?

CP: We have been looking at doing a survey across Kenya, which is where our research is based, of what IT systems they are currently using and what they are planning to use. Some of the issues that we've found have been things like intermittent electricity and problems with broadband connectivity.  But we have also found some quite innovative solutions to those issues. Instead of investing a lot of money in creating new broadband connections or electricity supplies, we are seeing doctors and researchers using mobile technology which has long battery lives and can connect to the internet over the mobile phone network, leap frogging over the current systems that we have in high income settings.

Q: Can you give us an example of a solution which has been generated in this way?

CP: One of our projects is about training rural healthcare workers on how to manage new-born babies and children. Traditionally, they would have had face-to-face training and our research groups have done a lot of face-to-face training of healthcare workers in Kenya and across Africa. But we think that if we can use mobile technology to deliver the training - delivering the same type of training but through a mobile device - then we can reach far more people at much lower costs than traditional face-to-face training.

Q: What are the most important lines of research that have emerged in the last 5-10 years?

CP: One interesting area of research is the growth of open-source software in healthcare. Over a number of years there have been different research groups that have developed their own software for things like looking at the HIV epidemic across Africa. These research groups are now coming together and saying: we are trying to solve the same problem, how can we combine our resources and develop software together.

One of the interesting aspects (for example, a project called OpenMRS which has been used in HIV clinics) is that although it has been developed for a specific purpose, because it is open-source it can be taken up by other groups and developed further. We are now seeing that kind of software put into hospitals and larger clinics, used not just for HIV but for other areas. We think this kind of software might be of use in building the learning health system idea that we are looking at.

Q: Why does your line of work matter and why should we fund it?

CP: We think the learning health system idea has huge potential, especially in low resource settings. Despite recent progress there are still many problems in maternal care and early childhood care which has resulted in many millions of babies dying prematurely, when compared to other countries. We think that if we can implement this idea of a continuously learning system, where doctors and hospital administrators can look at the date they are collecting and implement local solutions based on the problems that they have identified, that could have a big impact on how healthcare is delivered.

Q: How does your research fit into translational medicine within the department?

CP: We think that global healthcare informatics is at a really critical stage at the moment. The IT systems are only just going into low resource settings, whereas they have been in use in high income settings for many years now. You might have read about some of the issues about expense and difficulty of putting in IT systems in healthcare. We hope that by translating the research that has been done internationally to low resource settings, they can avoid some of those mistakes.

On the other side we are seeing new innovative solutions such as the mobile health solution being used in Kenya, solving problems that are costing high income countries quite a lot of money at the moment and can be implemented affordably and using relatively simple technology. So we could translate some of the research from low resource settings back into the high income world.