Healthcare contains too many manual processes — which leaves too many opportunities for human error!
While electronic medical records (EMR) are a step in the right direction, the real transformation in healthcare has arrived in the form of powerfully intelligent machines capable of winnowing out and eliminating ever more inefficiencies with every cycle.
Artificial intelligence (AI) and machine learning will eventually revolutionize every facet of healthcare. Machine learning algorithms have already been used to identify skin cancer and diagnose diabetic retinopathy in retinal images. Yet it lends itself to some processes better than others; specifically, those that a) are reproducible or standardized; and b) possess large image datasets.
The greatest value to be extracted will come from processing prior authorizations. “The biggest value proposition for AI is not the machine’s ability to make critical healthcare decisions, but it’s the ability to take administrative processes off the plate of humans who have more important things to do,” said Infinx VP of Product Navaneeth Nair. “The most valuable systems are those that help people make better decisions and actions while learning continuously.”
Data Drives Machine Learning
Machine learning requires a certain amount of data to generate a practical algorithm. The more available the data, the smarter the machine. When decision-making is more predictive, it improves outcomes. As a result, organizations with the most extensive data sets produce the most effective machine learning tools.
In terms of prior authorization determinations and RCM, few organizations possess Infinx’s extensive knowledge base of payer policies, and guidelines or the vast knowledge of rules learned using advanced machine learning techniques employed on a vast repository of payer authorization outcomes.
The proprietary engine in Infinx’s Prior Authorization Software automatically determines in real-time if a prior authorization is required or not, saving healthcare providers valuable time, resources and money when scheduling procedures. “Our solution is the direct result of two primary factors: extensive operational experience with the national payers on prior authorization and cutting-edge machine learning,” said Nair. “This results in an ever-smarter, more efficient product. The engine also has the capability to be integrated to any EMR or practice management system through an API which would offer real-time results at scheduling.”
AI continuously learns and improves from these data and interactions to provide humans with an ever more accurate portrait of the process. Ultimately, its job is to enable intelligent decisions by applying both human and machine learning including natural language processing and understanding.
“The healthcare industry is swimming in data. We are up to our eyeballs in it. As a result, the value proposition with the most potential is a tool that can take that data, make sense of it, and present it in a way that allows humans to make the best possible decision,” said Nair. “It is important to point out that machines do not make the decision. The outcome is still very much a product of human determination.”
Nair and the team at Infinx are focused on further applying the rapidly developing AI algorithms to healthcare payment collections. Nair leads product vision and execution of a new generation of healthcare products designed to increase revenue capture and enhance patient satisfaction for providers at Infinx.
“It will have significant implications on prior authorization and revenue cycle management (RCM) processes,” said Nair. “What we are seeing now is only the beginning.”
Seeking an Automated Prior Authorization Vendor
Fragmented RCM processes added more than $500 billion in U.S. healthcare costs in 2018 alone, according to a recent McKinsey report. The rapidly growing healthcare market is variable, uncertain, and prone to disruption. To prepare for the tectonic industry shift, it’s important to reallocate capital and resources toward future business models through investments in machine learning, artificial intelligence, advanced analytics, or digital to significantly lower costs.
In addition, a reorientation from delivery-centric models to consumer-centric ones should receive priority over traditional approaches. In short, the winners in the healthcare industry will empower patients to not just own their health data but using AI to generate actionable insights from data in real-time to drive engagement and outcomes.
Yet AI is not an in-house project for hospitals and health systems. Why? It simply is not a core competency. Plus, attracting talent can be difficult. AI talent does not necessarily view hospitals or health systems as career hotspots. Instead, providers should seek vendors like Infinx who already have the capability and talent to solve for 100 percent of prior authorization.
Infinx Healthcare provides innovative and scalable patient access and RCM solutions for healthcare providers, hospitals, imaging centers, and laboratories. Combining intelligent, cloud-based software driven by artificial intelligence and automation, with exception handling by certified prior authorization and billing specialists, Infinx helps clients preserve and capture more revenue, enabling them to shift focus from burdensome administrative details to billable patient care.
Schedule a demo today and learn how Infinx can maximize your revenue in your payment lifecycle.