Quantcast
Select Page

By MCG Health

Even before the COVID-19 pandemic, many case managers across the nation were facing challenges around:

  • High patient volumes
  • Balancing workload across understaffed teams
  • Timely completion of medical necessity documentation

Adding an additional layer of complexity, most health systems work with many different payers, and each with its own unique policies and timelines for claim resolution. With so many variables to consider when prioritizing work, more case management professionals are turning to assistive artificial intelligence (AI) and machine learning to help optimize the efficiency of utilization reviews (UR). A major hospital system in northeastern Florida is one such success story in leveraging new AI technology to improve case management practices.


Successful Use of Machine Learning to Assist Case Managers

As a non-profit health system comprised of five hospitals including a tertiary care pediatric hospital, four free-standing emergency departments, and an integrated ACO (accountable care organization), this hospital receives approximately 290,000 emergency room visits and approximately 65,000 admissions. The hospital’s Utilization Management and Clinical Documentation Integrity department was seeking ways to improve their abilities to optimize case prioritization and assign appropriate levels of care. In 2020, they adopted an AI-powered solution, Indicia for Effective Focus from MCG Health, to help them achieve their goals.

Since its implementation in 2020, the machine learning software has helped this hospital Utilization Management team capture more conversion opportunities, prioritize work consistently, and improve the efficiency of their reviews. After just a few months of use, the case management team started to see successful return on investment (ROI).

As they compared data from 2019, 2020, and the beginning months of 2021, this hospital saw:

  • A decrease in their Observation rate (year over year) and an increase in their Inpatient conversion rate toward the beginning of 2021.
  • Condition Code 44, which is done exclusively on the hospital system’s Medicare population, has seen a steady decline in application since the implementation of Indicia for Effective Focus – another sign that appropriate admissions are being determined upfront.
  • The hospital calculated that about 10% of the reduction in Observation Care rate has been attributed to the use of the Indicia solution, and over a 5-month period, their team appropriately increased inpatient admissions by 680 cases (with 68 of those conversions attributed to Indicia for Effective Focus).

This was a direct result of the tool prompting staff early enough after admission to examine the appropriateness of the status. In financial terms, this amounted to $558,000 in additional hospital revenue in the first 5 months of using the program. As the team tracked conversion opportunities in the first two months of 2021, they calculated an additional $264,000 of increased revenue attributable to the use of the tool. The results have allowed the hospital not to overutilize or underutilize available resources and act as better advocates for their patients.

By giving their UR nurses a way to prioritize their workload and removing redundant clerical tasks, the hospital’s case management team can focus their time and energy on critical patient needs and more complex projects. This has helped optimize existing staff resources without having to hire additional nurses at a time when recruiting healthcare professionals has become challenging.

You can learn more about this success story by reading the case study or watching the on-demand webinar.

Does your organization use AI? If so, has it helped?