The rise of artificial intelligence (AI) in recent years has reshaped industries across the board – and the world of clinical indemnity is no exception.
As the healthcare landscape has become an increasingly complex place to navigate, many insurance providers are now turning to AI to improve their services, enhance their risk assessment and harness their pricing models.
Here at THEMIS, we have already used AI for many years, incorporating the technology into our services to provide more precise and tailored indemnity coverage for medical professionals. But why have we done this? And how exactly do we use AI for this purpose?
In this article, we will answer both of these questions and more, exploring the broader impact of AI on clinical indemnity, before taking a deeper look at how we currently use the technology within our services.
How does AI benefit clinical indemnity?
After decades of research, hype and untapped potential, AI has finally exploded in recent years and is now redefining data-led processes across all industries1.
In combination with machine learning – a form of AI that uses algorithms to continuously learn as it becomes exposed to more and more data – the scope for using AI within clinical indemnity is unparalleled, offering a number of key benefits. These include:
- Improved patient diagnoses – AI-powered diagnostic tools can enhance the speed, accuracy and reliability of medical diagnoses2. As a result, this reduces the likelihood of misdiagnoses, limiting any of the associated liability risks for healthcare providers, such as dealing with damaging claims of medical negligence or malpractice.
- More accurate risk assessments – from newly qualified doctors to highly skilled surgeons, AI allows insurance providers to understand the nuances of sub-specialities throughout the medical landscape. Having this level of precision then allows insurers to tailor coverage and the associated premium to the specific challenges faced by each type of medical professional, helping ensure their policies are fit for purpose.
- Enhanced record keeping – AI can be used to help healthcare professionals maintain accurate and comprehensive patient records. Being able to document and refer to patient data in this way can then make a huge difference during any cases of negligence or malpractice.
- Dynamic data-driven pricing – AI’s ability to continuously analyse incoming data allows real-time adjustments to be made to premium rates. Through this functionality, pricing systems can then be honed to ensure cover aligns with the evolving landscape of clinical risks. It can also help address any potential issues of over or underpricing, enabling all medical disciplines to receive fair pricing that is driven by tailored data.
- Automated admin – AI can help streamline administrative tasks, reducing the administrative burden on healthcare professionals. This can then not only reduce the likelihood of errors resulting from administrative oversights but can also free up more time for healthcare professionals to focus on what they do best: looking after their patients.
- Improved risk management – mutually beneficial to corporate indemnity providers and healthcare professionals, AI can identify risks within specific medical disciplines and recommend actionable preventative measures. Being able to address emerging risks in this way then promotes best practice within healthcare, resulting in a safer environment for patients. It also reduces the likelihood of potentially damaging claims being made.
The risks of AI in clinical indemnity
While AI may offer a number of benefits to the clinical indemnity landscape, as an emerging and constantly changing piece of technology, incorporating it into pre-existing processes also brings with it several areas of controversy and concern.
As AI systems become increasingly involved in clinical decision-making processes, questions will soon start to appear over who is liable should an error or adverse outcome come about.
In order to overcome this, a recent review has highlighted the need to create a more balanced liability system, stating that current frameworks are “inadequate to encourage safe clinical implementation and disruptive innovation of AI”3.
To do this effectively, the review recommends that alterations first need to be made to the standard of care, insurance, indemnification and regulatory processes. That way, AI and machine learning can then be implemented within clinical care a lot more safely.
Patient data privacy & security
Because of AI’s reliance on analysing large quantities of patient data, concerns have also recently been raised over issues like data privacy and security. As such, this has made complying with data protection regulations even more important, in order to avoid future data breaches.
Research into this area has also raised concerns that the slow-paced nature of regulatory changes could affect the integration of AI within clinical practice.
In a study published back in 2021, researchers analysed the challenges involved in protecting patient health information while embracing the rise of AI technology4. They concluded their findings by stating: “We are currently in a familiar situation in which regulation and oversight risk falling behind the technologies they govern.”
They also highlighted an increased need for regulation to embrace “increasingly sophisticated methods of data anonymisation” in order to protect patient data safely. However, these methods could take some time to create, build and implement.
How we implement AI at THEMIS
Here at THEMIS, we currently utilise the power of AI within two key areas of clinical indemnity: underwriting and pricing models.
Let’s take a closer look at both of these areas individually.
With access to the world’s largest known data set for medical malpractice claims and risk data, our AI is able to continually detect and respond to emerging risks, enabling our underwriters to adapt and respond to evolving risk criteria.
This not only allows effective risk management during the initial underwriting stage, but it also has a huge proactive benefit in encouraging best practice. This can then ensure we continue to provide reliable coverage to healthcare professionals, in a way that mitigates any potential risks.
Say, for instance, our AI identifies a new litigation risk in the standard consent procedure for wherever a scalpel incision is made – something that affects hundreds of thousands of procedures each year.
We can then recommend changes to the consent forms used during these procedures, improving patient awareness and care while – at the same time – reducing a clinician’s potential exposure to the risk involved.
As a result, this can then lower the price of premiums and offer several overarching benefits to the rest of the healthcare industry, especially in terms of avoiding any potentially damaging claims.
Learning from our data, our pricing engine can accurately predict where claims are likely to occur, how much they will cost to defend and how often they will occur.
Because of this, we can consider the exact costs associated with potential claims for specific types of medical professionals. This enables us to offer premiums that are dynamically priced in real-time and able to automatically respond to any sudden changes in risk.
Having these invaluable insights allows us to analyse and undertake risk selection in much more finite detail – something which we can then reflect in our pricing.
Accurate pricing can make private practice more profitable for current privately practising clinicians and more accessible to those, often younger clinicians, looking to enter into private practice.
It can also help ensure certain medical disciplines are not over- or underpriced – as has been seen to be the case within obstetrics and gynaecology over recent years5.
THEMIS: AI-driven clinical indemnity experts
Our team at THEMIS are well aware of the strength of AI and understands how revolutionary it has been within the world of clinical indemnity.
By harnessing the power of AI, we are able to better safeguard the professional and personal reputations of thousands of doctors, nurses and surgeons, offering clear and reliable coverage that you can trust.
We are committed to staying at the forefront of this technology and are continuously looking for new ways to improve and harness the use of AI in our services.