The US spends an almost unimaginable amount of money each year on healthcare. Spending in the US reached $4.3 trillion in 2021. At $12,914 per capita, this is a greater expenditure than any other developed nation. If US healthcare spending was a country, it would represent the fourth-highest GDP in the world, ahead of Germany, the United Kingdom, and India.
Sadly, not all this money is spent well. Around one in four dollars ($1 trillion) is wasted.
The US healthcare system can simply no longer afford this – especially long term. In 2020, 17% of Americans were aged 65+, but this is set to rise to 22% by 2050. An aging population will come with increased costs. For example, cancer will cost $25.2 trillion globally over the next 30 years. The US and China will bear the highest economic burden.
The US healthcare industry urgently needs to plug the leaks. While some costs come from inefficiencies within the system itself, patients also bear some responsibility. Here, we will look at three of the biggest causes of healthcare wastage and explain how AI technology can help solve the problems.
Healthcare is a highly fragmented, complex ecosystem of funding sources and practitioners. Sources such as Medicaid, employer insurance, and private insurance must interact with hospitals, pharmacies, and practitioners to find solutions. Insurers supply multiple tiers of coverage that must be interpreted and processed to pay claims. Friction and complexity exist in each and every link along the chain from treatment to payment.
Administrative costs are a major cause of excess medical spending. The US spends about 8% on administrative costs compared to the 1-3% that the top 10 other highest-income countries spend.
AI can streamline the inefficiencies in healthcare admin. Insurers should use automated, conversational AI that patients can interact with when they need to make a claim. Patients could use digital channels, such as text, to provide the information needed, responding from wherever they are, and whenever it is, when it’s convenient for them. That information could be appended seamlessly to their medical records.
If automation can reduce some of the waste that would otherwise be spent in human hours going through fragmented service and claim details, then AI can tackle one of the biggest causes of spending waste.
Rising drug costs
With an average cost of $1,300 per person per year, prescription costs are higher in the US than they are anywhere else in the world. For new drugs, the costs are even more painful, with a median of more than $222,000 for a year supply – putting those treatments beyond the reach of most Americans.
While drug manufacturers continue to increase prices each year, this is not the only cause behind out-of-control prices. Some of the blame here is down to the public. Missed prevention costs $310bn and overuse costs $451bn in healthcare waste.
By centralizing medical data and using AI to make sense of it, healthcare businesses would be able to see what prescription a patient is on and how far through it they should be at any given time. Businesses could regularly reach out to patients to check on their progress with their prescription using conversational AI. This will chip away at the cost of overuse, while encouraging patients to take a more preventative approach to serious illness.
Each missed appointment costs an average of $200. Though this doesn’t seem like a substantial cost, it quickly adds up when there are 750 million missed appointments per year. The loss of $150bn in this way is inexcusable.
The reasons why Americans miss their appointments are varied, but most can be tackled at least in part by AI. Thirty-four per cent of Americans say they do not like visiting the doctor due to expensive payments. Forty per cent of Americans say they fear the medical bills that could come with a serious illness. Thirty-two per cent fear the illness itself.
The second biggest reason is misdiagnosis. Thirty per cent lack trust due to being misdiagnosed in the past.
The third main reason comes down to timing. One in five say they can’t get time off work. Appointments can even be missed due to a patient’s hatred of Mondays. A study in the UK found scheduling medical appointments later in the week increased attendance by more than 10%.
AI can tackle each of these issues. Businesses could communicate a range of likely costs in advance of an appointment, preventing nasty surprises and putting the patient in control. They could also present them with payment plan options if they are unable to pay in full.
Machine learning is also helping improve diagnosis accuracy, and this increases patient confidence when used in conjunction with a human practitioner.
As for arranging a time to visit, AI could record a patient’s preferences and match them with the level of care they need at a time that works best.
Machine intervention has also been proven to reduce the likelihood of missing appointments due to simple human error. After a Veterans Affairs hospital in Texas introduced automated reminders ahead of appointments, the no show-rate decreased by 7%.
The amount of wasted money in the US healthcare system is unsustainable. It’s hard to imagine many operations wasting a quarter of their annual spend and remaining viable. Thankfully, there is a solution. AI has the potential to help healthcare businesses make sense of their data and enable their staff to make quick and efficient solutions by giving them access.
Whether it’s administrative inefficiencies, rising medicine costs, or missed appointments, AI can be used to tackle the biggest threats to healthcare businesses while improving service levels for customers.
We are seeing this trend across multiple industries and there is no reason payers and providers alike can’t benefit too. It’s time to get serious about tackling wasted resources in healthcare by employing AI solutions that can help these essential operations thrive long-term.