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RegTech in Healthcare: Opportunities and Challenges

For many, Regulation Technology is perceived as a branch of financial technology. In this light, while FinTechs are helping players improve their customer propositions while bolstering the efficiency of their operations, RegTech enables financial institutions to radically improve the way they run their compliance processes. While this is true, the potential of RegTech goes far beyond financial services.

While the UK's Financial Conduct Authority (FCA) define RegTech as: "a subset of fintech", RegTech is in fact any technology that improves the way businesses manage their compliance obligations. Therefore, while RegTech has seen most application in financial services due to the increase in the cost of compliance and the penalties for compliance failures, in reality, RegTech can be applied to any regulated industry. Limiting RegTech's application solely to financial services highlights the focus on the present but ignores the great potential in other industries: telecoms, petrol & gas, insurance, fishing, freight and what we in this article will be focussing on, healthcare. What these industries all have in common is the weight of regulation that bares down on them and therefore presents fertile ground for RegTech solutions.

Even before the coronavirus hit, hospitals in developed countries have been widely overstretched in terms of their administrative obligations. The UK's NHS for example spends roughly 8-10% of its £100 billion budget on administration. Anyone who has received treatment in the UK will still note the reliance on paper and pen notes that doctors and nurses pass between each other. This type of information flow is symptomatic of large bureaucracies, and whether you have worked in healthcare, financial services, government agencies or any other large bureaucracy, you will no doubt understand, if not bemoan, this inefficiency. The problem with healthcare however, without wanting to sound melodramatic, is that this extra burden costs lives, with between 5% to 50% of all medical errors in primary care are administrative errors according to the WHO.

Not only is this potentially costly to lives, but it is potentially costly full stop. A report by the American Hospital Association found that an average-sized community hospital with 161 beds spends USD 7.6 million on administration that supports compliance with federal regulations, with that figure rising to USD 9 million for hospitals with intensive care. To put that into perspective, that's a regulatory burden of USD 1,200 per patient admittance. The regulatory cost has a significant opportunity cost, the compliance budget could ultimately be spent on better medical instruments or more staff for example, and ultimately detracts from the care a patient receives.

Not only is there a significant financial opportunity cost but compliance administration also presents a significant waste of time from a care-giving perspective. Adhering to regulation is of course crucial, but ultimately, doctors and nurses are caregivers, not administrators. Regulation adherence is currently drawn from the time and commitment of staff that could otherwise be dedicated where it is needed most, patient treatment. Effective adherence to regulation would allow for the execution of compliance without being to the detriment of patient care and technology could be one way of alleviating such issues.

With healthcare being a highly regulated industry and the time, cost and error-prone nature of the current compliance process, healthcare is ripe for RegTech innovation. The automation of processes could significantly increase the efficiency and effectiveness of healthcare services, along with healthy bottom-line advantages. Furthermore, similarly with financial regulation, that of healthcare is constantly evolving. Several RegTechs already automate the internalisation of regulatory change in the financial services industry and there's no reason why the same technology couldn't be applied to the healthcare industry.

The finance industry has been making significant strides in AI by applying Natural Language Processing (NLP) and machine learning technology to compliance. This manifested due to the increase in regulatory volume and complexity and calls for data-driven, efficient solutions - a similar patter emerging in healthcare. NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. NLP, when used in conjunction with machine learning, can 'read' documents to identify the who and what. This includes extracting metadata (which identifies important elements of a regulation helping to determine its relevance and whether a response is required), identifying 'who' factors (e.g. to whom the document is addressed, by whom and the key actors) and understanding content (identifying the requirements and determining to who and what they apply to).

This technology has the effect of dramatically increasing efficiency and streamlining the compliance process. Such technologies allow compliance professionals to interpret, understand, internalise and react to regulatory changes in a fraction of the time it would take to do it manually. Therefore reducing the number of compliance staff necessary and freeing up budget for healthcare staff or updated medical equipment or reallocating such staff to focus on more complex regulatory challenges.

Employing automation technology reduces the level of human intervention required which reduces interpretation variability increasing standardisation which increases productivity and cost efficiency. Robotic process automation, for compliance, can also automatically access multiple information systems and compile records increasing the efficiency of regulatory audits and inquiries.

The core functions of the technologies - reading, interpreting, understanding and automating - have direct applications in healthcare, just as they do in finance. Whereas in finance it is used to combat fraud and terrorist financing, a goal may be to prevent unauthorised access to private medical information. The context may differ, but the function remains the same.

However, although this is true, it is an oversimplification. A highly regulated industry is a complex industry. Most RegTech solutions are tailored to the industry and company that seek them. Just like the general skills of a compliance officer are similar between industries, the specific knowledge is not as easily as transferable. This also does not consider the value of experience in an industry, which is an underappreciated string to the compliance officer's bow. These differences often manifest in frustration between RegTech solution providers and their clients. Namely, the RegTech lacks an understanding of the idiosyncrasies of the industry and thus the challenges that require overcoming.

These issues are also apparent in technology transfers. There are some fields, such as data protection, that require small changes inter-industry. Whereas others, such regulatory change management, require bigger adjustments. Then there are fields which are simply entirely incompatible. Therefore there is often a steep learning curve for RegTechs to overcome when applying a solution in a different industry, notably healthcare. For solution providers, it is therefore essential to identify precisely the opportunities that exist before a move into a new industry.

However, with an apprehension of inter-industry differences, automated compliance functions like NLP and machine learning occupy a critical intersection of technology advancement in the healthcare industry. For regulatory and medical professionals alike, attention to these issues and openness to innovation has the potential to enhance compliance and productivity and ultimately help save lives.


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