Healthcare Jobs That Can Be Improved by AI

Healthcare jobs are crucial to a functioning society. They exist in an industry where digital innovation regularly happens. According to Deloitte Center for Health Solutions’ top 10 healthcare innovations, artificial intelligence (AI) was listed as one of the key ways healthcare can provide “more for less – more value, better outcomes, greater convenience, access and simplicity.” Today, healthcare jobs — where the shortage of applicants is reaching a crisis level in many parts of the country — are in a prime position to be influenced by cutting edge technologies like AI.

You can make a strong argument that nearly all healthcare professionals are already affected by AI, in one way or another, simply by the growing adoption of AI in the healthcare setting.

That includes physicians and surgeons as well as healthcare management and administration professionals. From the best-paying healthcare jobs to entry-level roles, almost everyone is already interacting with AI technologies in some form.

Let’s take a closer look at a few jobs in healthcare where AI could play an especially important and positive role.

Nurses

Nurses play key roles in carrying out treatment plans, working with patients, and so much more. Hospitals and health systems couldn’t function effectively without them.

The lack of available nurses is a serious issue across the world of healthcare and unfortunately, a severe shortage of nurses has impacted the healthcare industry. A recent survey conducted by Wolters Kluwer and UKG, and shared by Fierce Healthcare, found 92% of nurse leaders expect the nurse shortage to worsen through 2022 and well into 2023.

Thankfully, AI can help.

A group of nurses walks down a corridor inside of a hospital

Automating Utilization Management Supports Nurses

The purpose of utilization review (the process) is to ensure that the patient’s “five rights” are observed – that the patient receives the right services at the right time, delivered by the right provider in the right setting for the right cost. The actions a hospital takes to this end can be referred to as utilization management. AI-driven utilization management software, such as XSOLIS’ CORTEX.UR solution, assures we are meeting these five patient rights.

Nurses can receive actionable patient data in real-time, and then act on it appropriately, through the automation of key, time-consuming aspects of utilization review. With the use of AI, nurses can risk-stratify the cases that need their attention the most. Further, AI supports case review by packaging and presenting all relevant patient information clearly and concisely to support medical necessity documentation required by payers.

All of this adds up to a more informed and efficient approach to utilization review. Unfortunately, there isn’t one simple solution to attract more nurses to the case management profession or to your organization. However, AI offers a clear path to making nurses more efficient in their daily duties while reducing the administrative burden placed on them.

Managers and Administrators

Professionals in healthcare management jobs may realize the broadest benefits from AI, even as it transforms the way they go about their daily duties.

Administrator jobs in healthcare focus on a wide range of business functions and processes. Nearly all can be improved through forecasting, analysis, and many other forms of automation provided by the right type of AI-driven software.

In terms of AI and utilization management specifically, organizations can realize these three key benefits through automation:

  • More efficient payer communication: AI makes it simple for payer reviewers to access escalated cases and leverage analytics in decision-making. AI-driven solutions allow providers to streamline what they’re sending to payers – as opposed to overwhelming them with too much data – resulting in clearer, shared views, to expedite decisions and increase first-touch determinations.
  • Revenue opportunity: It’s great to apply AI to identify inpatient conversions. But when a provider is over-inflated with their observation rate, they’re still missing revenue. Best-in-class solutions therefore present a revenue opportunity for managers and administrators, particularly when paired with clinical experts that can help right-size observation rates according to what works for each, unique organization, or customer. Once AI is applied to stratify risk to revenue opportunity, you can further recognize and prevent denials and medical necessity denials as well.
  • Cost savings: AI can substantially reduce time spent on administrative tasks related to claims and denials by automating previously manual tasks. AI, when combined with Machine Learning, can also accurately classify a case as outpatient or inpatient – this is presented to XSOLIS customers via our Care Level Score (CLS). The CLS is centered in evidence-based medicine and removes manual work with a 99%+ degree of accuracy. Both of those processes save your organization time and money.

AI Making Healthcare Jobs More Effective

XSOLIS supplies its partners with AI software solutions proven to address unique clinical and administrative needs in the healthcare industry.

We bridge gaps between payers and providers, between hospitals and their providers, and between managerial and administrative roles and their nursing staff. Is your organization missing out on revenue opportunities due to breakdowns in communication among any of these groups?

Learn how XSOLIS can help.

michelle-w-2022

Michelle Wyatt, DNP, MSN, RN, CMS, is Senior Director, Clinical Best Practices at XSOLIS and has over 20 years’ experience in healthcare, most recently serving as Director of Case Management and Utilization Review at HCA Healthcare. Prior, she was Director of Utilization Management at Vanderbilt University Medical Center and received her Doctorate of Nursing Practice, Nursing Administration, from Vanderbilt University School of Nursing. She began her career in utilization review performing care management reviews for Universal Care of TN and currently oversees the XSOLIS clinical teams that lead customer implementation.