How AI is making healthcare cheaper for Americans
Machine learning has an incredible ability to interpret and find meaning in huge sets of data, faster and more effectively than the human brain. This means that industries choosing to implement AI in the coming decade are going to see fundamental shifts in how they function, and the healthcare industry is no exception.
The U.S. healthcare industry is somewhat infamous for its sky-high costs. In 2013, 56 million people struggled to pay health care related costs, despite many of those people having health insurance. The United States struggles to maintain an effective health care system that is accessible for all of its citizens, and a lot of this comes from the burden of excessive administration costs. Turning to machine learning to lighten some of this burden is a clear next step for health industry experts and intelligence developers alike.
At QuartzClinical, we took the leap in 2013 of incorporating artificial intelligence into the foundational structure of our software system, and we have since seen tremendous results amongst our clients (is there a link we can add here Sapan?) We use this artificial intelligence algorithm to analyze millions of clinical, financial, and supply chain data points, and to come up with innovative solutions for our clients that reduce healthcare costs, especially administrative costs. This blog post discusses 5 specific ways that the artificial intelligence adopted by Quartz can cut administrative costs of healthcare in the US, a solution that may end up relieving the financial burden of healthcare for many American families.
- Decrease patient stayOne of the biggest expenses for hospitals, and something that bogs down the administrative efforts of the hospital, is patients that stay in the hospital longer than they need to. Machine learning efforts can find patterns in patient admission and discharge history to determine what categories of patients tend to overstay in hospitals, helping medical staff determine which individual patients can shorten their stays. Quartz clinical’s AI technology uses algorithms that allow hospitals to maximize the efficiency of their patient stays, and at the same time, make sure that nobody is discharged before they need to be.
- Foreseeing readmissionPart of decreasing patient stay means making sure that you know what patients are at risk of readmission. Otherwise, decreasing patient stays can have dangerous consequences. The same AI algorithms that help us to decrease patient stay are able to locate high risk patients, and make sure that they stay under a doctor’s care for a sufficient amount of time. At the same time, these calculations help to decrease the overall mortality rate of the patients, both inside and outside of the hospital, by finding patterns in past data of what kind of patients die in the hospital or shortly thereafter, and how to prevent it from happening again. In general, machine learning allows healthcare professionals to learn from past mistakes and successes in a way that combines all of the billions of data points available, and this leads to smarter, more informed decisions across the board.
- Identify Cost SavingsDecreasing patient stays is one way that all hospital’s try to cut costs. A massive way that artificial intelligence decreases administrative costs is by identifying areas of cost savings. These could be fixed costs, such as the cost of hospital supplies and variable costs, such as the cost of a patient stay and varying costs of treatment. Machine learning algorithms can assess where the hospitals are overspending, even on something as benign as disposable gloves, or overpaying for restocking items before it is necessary, and help allocate resources and arrange processes in the most efficient and effective way possible.
- Improve population health management
Population health management is a complex field that deals a lot with drawing general conclusions based on large subsets of data. This strategy of finding patterns in order to establish best practices is what machine learning excels at the most. With the help of AI, the options are endless in terms of determining the best course of action for national health care plans, widespread services, and accessible care. Quartz is at the forefront of collecting data that will make healthcare as efficient as possible in the U.S., and this means better managed, more affordable care for everybody.
- Discovery and researchDiscovery and medical research are fields that benefit greatly from “unsupervised learning” a subset of machine learning that allows machines to explore and come up with new, never before seen solutions and ideas for drugs, treatments, and cures. Quartz prides itself on being a leader in medical development, with ambitious goals to create the solutions that will end global suffering and reduce the amount of Americans affected by incurable or chronic diseases.
As with any new technology, there are questions that remain unanswered when it comes to what possible repercussions there might be when artificial intelligence collides with the care of real human beings, and when machines start to take over managing and implementing the systems that we use to manage, track, and make sense of the health of our population.
Perhaps the question that most immediately comes to mind is: Who is paying for this research, and if/when AI does reduce administrative costs in healthcare, who will reap the benefits? Will it be the taxpayer? The hospitals? AI consulting agencies?
The line between where machines’ efficiency ends and we need to return to instinct driven, empathetic human logic and reason is another perpetual question with any sort of research and development involving AI. When AI makes its way into the healthcare industry in any way, there are ethical decisions to be considered. What if someone is deemed to be an excessive burden on the hospital based on machine learning algorithms? Will they be turned away? Will their insurance premiums skyrocket? Is sorting individuals based on their administrative cost really the direction we want to go in as a country?
Answering these questions will require proper government involvement and a system of checks and balances on AI consulting firms, pharmaceutical companies, and hospitals that are benefiting from this AI technology. Despite these uncertainties, one positive aspect of using AI to facilitate administrative tasks in the healthcare industry is that it does not venture into the debate regarding if or when “robots” will replace doctors and begin interacting with the patients themselves. Using machine learning to find patterns and trends that will make our current healthcare administrative system more effective and more intelligent is something that most people can agree on: handing our administrative software over to a robot poses less ethical concern than handing over a scalpel in the operating room. While these questions of how far we will let artificial intelligence go are important and worth considering, it is interesting to consider that at least machines can be used to improve our lives and systems without taking our role within those systems and rendering humans obsolete.
Artificial intelligence is a broad area of study with a lot of different applications, but perhaps the most important way we will learn to use artificial intelligence is in making the world a healthier, more prosperous place, and decreasing administrative costs is the first step in making this a realistic option for the United States.