How AI Solutions Help Clinics Deliver Better Care & improve Operations
AI is a crucial tool for healthcare providers today, from revenue cycle management and patient engagement to operational efficiencies for existing workflows. In this post, you’ll know how AI improves healthcare delivery, increases net patient revenue (NPR) for providers, and more.
The healthcare industry is facing growing challenges, from staffing shortage to cost pressures, as well the transition from a service- and fee-based model to an outcome- and value-based model.
Hospitals are becoming decentralized, with home healthcare and telehealth care on the rise. Patients have been turned into consumers, faced with the proliferation of high-deductible plans, and need up-front visibility and transparency into the price.
But new healthcare AI solutions are helping healthcare providers close those gaps and transform how healthcare is delivered, says Kaushik Roy, VP, AI product management at Change Healthcare.
“From an operational standpoint, the industry has been looking at AI for some time,” Roy says. “Interest is growing now because companies have become more successful at developing and evolving models, and more crucial as more data becomes available.”
Here’s a look at some of the ways AI has met the challenges on both the operational and consumerization side of the healthcare delivery system.
NLP offering relief for staffing issues and increasing patient engagement. Natural language processing (NPL) and conversational AI have become sophisticated enough to be leveraged on the front line, as the first point of patient contact. Voice and chat bots are rolling out on patient phone lines, clinic apps and websites, helping lift some of the burden of staff.
Healthcare organizations that have implemented the technology have seen a 21% reduction in average handle time, Roy says. And containment rate, which refers to whether a bot is able to handle a call or if it needs to be passed to a human, have gone as high as 60%, Roy says.
Improving billing and coding efficiency. Whether it’s creating codes, predicting the claims or speeding up denials processing, AI and robotic process automation (RPA), are offering tremendous gains. Vendors report that up to 10% of claims get denied on first submission, and 65% of those never get reworked — perhaps because correcting and resubmitting a claim comes at a cost of $31.50. AI models can predict the probability of a denial before the claim is submitted — and Roy says organizations have reduced errors by up to 50% in claims before they’re submitted, improving the chances of appeal.
Reducing case manager burdens. Admin is a significant part of the behind-the-scenes work in a healthcare organization. Automation and AI was designed to handle those kinds of repetitive jobs that require accuracy and speed. Roy says that they’ve seen organizations realize a reduction in medical necessity review by 75% for case managers, when an AI solution is deployed.
Integrating AI into workflows: Where to start
Many healthcare organizations, whatever their size, have already been implementing AI solutions in their processes, particularly when it comes to the administrative burden. But scaling that investment is challenging. And those organizations that haven’t already begun their AI journey are starting to recognize the benefits, and understand that it’s time to leap into the fray. The best way to start is to work with vendors and systems integrators, Roy says.
“It’s more than just having a model and training the model with data,” he explains. “AI requires an integrated, end-to-end solution, as well as continuous learning. Vendors have the experience and expertise that smaller clinics, in particular, can benefit from.”
He also advises organizations to start small — first, ensuring that you have the data that you need. And secondly, look to the low-hanging fruit for operational gains. Target the easiest-to-tackle operational use cases first and build some competencies around that, whether it’s clinical content extraction or work prioritization — the areas that augment day-to-day functions. And once you have established that competency, build on that.
To learn more about the ways that AI is improving operational efficiency for healthcare organizations now, a look at how some organizations are implementing the technology in the real world and a glimpse into the future of healthcare AI, don’t miss the event post on here.