There are a lot of areas that these technologies can permeate, especially when it comes to the analysis and manipulation of vast amounts of personal, and private, medical data. However, not all sectors of the medical sphere have moved over to more efficient ways, leaving a disparity across the field.

While surgeons are using robotics to perform tiny operations, the National Health Service, in the UK, has only from the beginning of 2019 been banned from using Fax technology. It is astounding that such obsolete technology was still being used just last year for the distribution of data and communication with patients.

In the United States, there is a huge problem with medical debt, not only in the expense of procedures in the country but in the actual invoicing and dispersing of data between doctors and hospitals, through to the insurance companies and eventually onto the patients who have to pay.

Seeking collections

Part of the American medical debt problem, which stands at a staggering $76 billion, affecting nearly 43 million citizens, is the confusion when it comes to the collection of the money from the individuals.

Many times, patients are unaware of what they owe as health data is not centralised and spread around different organisations. It can lead to patients falling unwittingly into debt, leaving medical institutions out of pocket as well as insurance companies stuck as confused intermediates in the middle.

Levon Brutyan, CEO of Collectly, a company that is utilizing Artificial intelligence and looking into blockchain to try and organise and centralise healthcare debt data, explains the problems being faced in healthcare debt collecting.

“The fact that health data is not centralised and spread around different organisations is a huge issue in healthcare and impacts on healthcare debt in a massive way,” said Brutyan. “It creates additional overheads for both insurance companies and providers, and in turn, patients. The ultimate result is that a lot of bills go unpaid and a lot of people unwittingly slip into debt.”

“It is hard to assess the exact numbers but let me give you an example. US healthcare debt currently stands at a staggering $76 billion. Some of this is because patients don’t know what they are paying for and when they are supposed to pay.”

Brutyan believes this is a significant problem, but one that can be solved by leveraging advanced technology, like AI, to analysis and disseminate the data, and potentially blockchain as well to store it.

“What we have seen, in terms of the numbers, after working with more than 60,000 patients in a month we have collected more than $12 million of unpaid invoices for 2,500 providers. This has increased the collection rate on patient bills from an industry average of 8-12 percent, depending on the type of practice, to 50-75 percent. At its heart, this is the result of centralised and distributing data in a timely and efficient manner.”

Technologically clarifying

This lack of clarity from healthcare debt data may be causing a backlog of collected fees which impacts healthcare professionals, but it also hits back at patients who are unwise to the level of debt they are in before it is too late.

The need for more precise data can surely help in streamlining the process as it would be all too easy to say the massive debt problem is only because of  the expense of procedure. Confusion between insurers and medical practitioners often leads to ambiguous and convoluted bills and that is further impacted by a lack of technical understanding from patients.

“The problem is more that patients don’t know how much they will end up paying for the bill,” adds Brutyan. “The second biggest problem is in the fact that whenever patients receive bills, these bills are so unclear that patients don’t understand them. Thus, the use of AI to learn about health plans and provide instant answers on questions that patients have about their bills helps tremendously.”

“By fusing all major medical billing software, and creating data-driven, patient billing software that keeps patients in the loop, patients understand what they owe, why they owe, why their insurance company didn’t cover the costs, and how they can settle the balance with the provider.”

The use of AI to analyse and disseminate clear and understandable data allows for patients to receive only the facts that they need, with clear patterned reasoning as to why a particular figure is a figure, and leave the patient with one path to paying their debt.

Technology of this level is intended to streamline and cause high levels of efficiency for today’s society, but even with advancements like this tackling outdated and convoluted data, there is more that can be done with other technologies.

Enter blockchain

When it comes to data and how it can be utilized and understood better, blockchain is becoming more and more essential, especially in combination with other emerging technologies such as AI and the Internet of Things.

A lot of billing data for healthcare practices contains private and personal information, so not only does the introduction of blockchain into the fold help keep this data secure, as well as only available to the parties that need to view it.

Blockchain can become a storage of this data that becomes available to the AI mechanism, but without allowing the AI to take on information that it does not need, ensuring the privacy. However, it can also do more in a system like this, explains Brutyan.

“Potentially, a combination of an AI platform like our and blockchain could empower patients with more profound insight. They could gain a unique understanding of real healthcare costs alongside full control of who has access to patient data and more importantly the precise services they were provided with, the exact costs, what the reimbursement from insurance companies was, and what is the ‘real’ balance.

“The healthcare industry is drowning in patient medical records and complex billing processes. Adoption and implementation of blockchains and AI can enable the industry to come together to determine what levels of collaboration can be used.

“A common database of health information, payment records, healthcare services and insurance policies would mean less admin time and more time spent on services. The entire billing chain would be completely transparent down to the tiniest detail and accessible to all relevant parties.”

Use cases

With blockchain and AI technology entering a much more experimental stage in important sectors like healthcare, it is probably pertinent to tackle some of the more minor, but hugely significant, aspects of it. The fact that AI and Blockchain can help with medical research and other facets of healthcare is exciting, but probably a long way off.

However, the simple fact of analysing, storing and organising data on those emerging technologies to present it directly and effectively to patients to slow the rot that is medical debt appears to be an achievable and valiant goal.