The U.S. healthcare system faces major challenges in the present; it has to prepare for even bigger ones that will arrive in the near future. An aging population, growing numbers of chronic diseases induced by modern lifestyle choices, pollution and other factors, along with doctor shortages and lack of other critical staff are all part of the large picture affecting the medical picture. Perhaps the most difficult obstacle to overcome consists of the huge amount of paperwork involved with patient care and its related costs.
Reasons for that are numerous, the main one being the number of different participants in the system and all their data. Patients, doctors, hospitals, clinics, insurance companies and banks, all take part in receiving or giving healthcare, and in paying for it.
The large amount of documentation needed to ensure patient safety, while also meeting all sorts of rules and regulations, has an equally big cost. Administrative U.S. healthcare spending is roughly three times what it is in other developed countries, and is a major reason the U.S. spends twice as much on healthcare.
Administrative and operational inefficiencies account for nearly $1 trillion each year, roughly one third of the U.S. healthcare system’s total costs.
Dealing with all parts of this expensive mess could prove to be too much for people, since some health clinics already employ more clerks than care providers. This is absurd, considering the main purpose of healthcare institutions should be to take care of people’s health, not papers.
The numbers are actually crushing any hope of changing the system soon. For every $1 billion in revenue, the healthcare system employs the equivalent of 770 full-time people to settle the bills. What do they do? They not only issue bills, they also fix mistakes, answer patient questions, send patient information to insurers in order to have treatments approved, deal with insurer payment denials, and much more. On top of that, doctors also have to spend time dealing with red tape, instead of seeing more patients. Here is where employing AI solutions come in, such as Notable’s wearable doctor’s assistant, for instance.
AI might be the answer not only to helping doctors and finding new treatments, but also to reduce and make manageable some of the healthcare system’s administrative tasks.
“A number of recent studies have found that [health care] administrative costs [in the U.S.] continue to rise and or remain higher than other countries,” says Pamela Hepp, an expert in data security, health care regulation, and digital health records at Buchanan, Ingersoll & Rooney. “There is always room for improving efficiencies in the delivery of care and AI has some promise in that regard.”
Solutions have to be found for the healthcare system, and soon, because its productivity has been constantly declining since World War II, and especially in the past decade. Healthcare productivity cannot be compared to that of any other industry, since its operational abilities mean the difference between life and death for many people. The math is simple: when healthcare costs more, people can afford less and less treatment. Add to that overall administrative costs that also burden communities, resulting in healthcare facilities that are both fewer in number and more under-equipped. This is one reason why falling life expectancy in America is becoming obvious.
The need for change within the healthcare system has become stringent. The reason the present state of facts is negatively influencing productivity in the system is that six out of every 10 people who work in the medical field never actually see patients. Doctors, nurses and other people in the system who do see patients, spend only 27% of their time working directly with them; the remaining time being used to tackle huge administrative tasks.
This is where AI-powered tools would come in handy. Healthcare systems tend to be slow to adopt new solutions, as seen with the introduction of electronic health records (EHRs).
However, if EHRs demand high costs and difficult overall system integration, AI solutions can make this process more focused and easier to handle. Some of the areas in which healthcare could use AI on a larger scale are the same ones in which pioneers in the field have already tried and succeeded.
Some of these are as basic as bed assignments in hospitals, better documentation done in less time and better detection of fraud related to healthcare insurance.
Assigning beds to patients in a large hospital can quickly become a nightmare. Large numbers of staff are needed to deal with the problem. Determining which beds are available at any given time in the various hospital departments, so patients don’t have to wait too long before being admitted in case of emergency, or even when they simply need a certain type of care is a complicated process.
Well, AI has the power to change all that, and Johns Hopkins has already proved it.
The system they introduced two years ago combines available data about patients and bed availability to predict when and why blockages may appear in the future and make useful suggestions about how to avoid them. In this way staff can even find solutions days before beds are needed.
As a result of this new method for bed assignments, Johns Hopkins can now assign beds 30% faster. This creates a very useful and desirable ripple effect: unnecessary waiting time in recovery rooms for surgery patients has been reduced by 80%, while the time emergency room patients have to wait in order to be admitted is decreased by 20%. Due to increased efficiency in assigning beds, the hospital can accept 60% more transfer patients.
Another way AI can make a difference is by helping with analysis and validation of health records. The task is so huge, that on average 60 people are assigned to this task, a quarter of these staff people are doctors and nurses, who are unable to provide actual health care during that time.
An AI-powered tool developed in cooperation with electronic health record vendor Cerner Corporation proves to be a game changer. The AI tool created by Nuance Communications helps doctors comply with federal guidelines, while saving time and money.
AI also comes in handy when it comes to preventing or discovering fraud within the system. The National Health Care Anti-fraud Association (NHCAA) estimates that 3% of all healthcare spending, or $60 billion is wasted due to fraud.
Of course, AI won’t completely eliminate fraud, but what it can do is to facilitate claim identification when a review is needed, preventing more inadequate claims from slipping through the cracks of the system. Startup Fraudscope, for instance, has already saved insurers more than $1 billion by using machine learning algorithms to identify potentially fraudulent claims before payments were made.
There many ways to use technology to optimize the healthcare system, be those focused on caregiving or lessening the administrative burden. Players in the healthcare industry choosing to accept some ‘intelligent’ help will eventually make the difference between industry leaders and the rest.