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Medicine Interview Hot Topics: Digitisation of Healthcare Data & AI in Healthcare
As healthcare advances, previous staples of the doctor’s working life become part of their memory. Gone is the notebook - replaced with electronic medical records (EMR). As medical data is written and stored, it becomes increasingly pertinent to ask, who should have that data? Should it be combined to aid learning and AI? Is it better in the hands of local healthcare providers or as a public resource?
The Current Situation
As it stands, each individual healthcare organisation has its own data infrastructure, which supports its own needs - with little thought given to the bigger picture. Data is stored in-organisation, using rules and formats for that organisation. The ability to maintain care across organisations is severely constrained. Individual organisations will typically have bought their own EMR systems, which are locked by the provider of that system. Whilst countries with unified healthcare are likely to have a single system that all doctors are used to, no matter the practice, the US therefore has numerous different systems. This doesn’t fit with the increasing push to provide cheaper, more efficient healthcare, and the desire to allow a true continuity of care between hospitals, practices and areas. It seems that aggregating data between different areas of healthcare will benefit each organisation, individual patients, and allow the use of AI.
What Should Change?
As the capability of AI has exploded in recent years, it becomes more possible to use aggregated healthcare data to train models that will automate diagnosis, target resources and recommend treatments, using a depth of knowledge that would otherwise be impossible to achieve. This would be a great benefit as an adjunct to the doctor’s clinical judgement. However, as well as the correct AI systems, we would need the correct data infrastructure to allow this process to begin. It would require the sharing of information between practices, an understanding of the local population, and a guarantee that the algorithm will perform to the same level through different cohorts - meaning that if the patient data lacks one type of patient on which to train the AI, this must be known and understood. Likewise, re-calibration would have to continue after the AI had already been implemented.
As it stands, the average clinician is unsatisfied with their EMR. They struggle to enter basic data, finding that the system makes simple tasks complicated. There is no communication between one system and another. It therefore is apparent that we cannot expect the average doctor to wholeheartedly embrace the chance to use AI and aggregated data in their practice.
However, we can encourage them to consider who owns healthcare data, and who should have the right to use it. The public needs to trust that the government will use their data for the right reasons, and doctors having an interest in, and understanding of, data protection and the use of data is crucial if people are to believe that their healthcare data is being used for their best interests.
If the US government mandated that each healthcare had to store their clinical data in a secure cloud, would this be of benefit? We must question the huge security risks associated with such a move, and balance them against the potential upside of the ability to aggregate and study this data in a manner never achievable before.
If we are to realise the potential of AI to revolutionise healthcare, we must resolve the issue of who owns data, and the government must invest in data infrastructure. With more investment in data infrastructure, and side-by-side investment in EMR systems, doctors could have access to a patient system that not only functions well for them, but provides massive benefit to them, or their colleagues, when conducting research.
Potential questions which may be asked in the interview
- What do you think about digitisation of healthcare in the US?
- What are some of the issues around digitisation of healthcare in the US?
- Who owns healthcare data in the US?
- What is an EMR?
- What would the benefits of aggregating healthcare data in the US be?
- What are the risks of aggregating healthcare data?
- How might you convince a traditional family doctor to subscribe to a new EMR system that will aggregate his data with that of many others?
- In the future, how would you describe data aggregation and AI to a patient curious about what happens to their healthcare data?
- What do you think the impact of AI will be on healthcare?
How to answer questions on AI in healthcare
Remember that you don’t need to know a great deal about this topic - having a basic understanding is sufficient - but you can stand out through knowing about it. If you are considering talking about public health or research you should especially consider the roles of digitisation, aggregation of data, and the use of AI.