The aging population is creating an unprecedented demand for healthcare services while the available healthcare workforce is declining. Meanwhile, the healthcare system continues to rely heavily on manual processes which have to date been powered by people. After a patient visit, a healthcare provider typically requires a full administration team to manage data across various systems, just to receive reimbursement from the insurance providers, Medicaid, or patients for the services provided.
This process is highly inefficient, and this workload is going to worsen as demand increases.
According to the Centers for Medicare & Medicaid Services, annual growth in national health spending is expected to average 5.1% from 2021-2030, reaching nearly $6.8 trillion by 2030.
U.S. healthcare spending reached $4.5 trillion in 2022. The 2023 CAQH Index estimates that 22% — or $89 billion — of U.S. health provider expenditures go toward administrative expenses.
Continually adding headcount in an attempt to keep up with growing demand will increase the pressure on already slim operating margins. The challenges of replacing employees as older workers retire while dealing with unprecedented levels of attrition due to burnout and other factors are only going to intensify.
This situation creates a perfect storm, making staffing a painful issue for many healthcare providers.
The most effective way to address this issue is by leveraging technology, specifically with fully human-capable AI-powered agents.
Here’s why.
AI agents can be trained faster than humans
Companies specializing in automation, who have heavily invested in proprietary training processes, teams, and technology, can train fully human-capable AI agents in as quickly as 30 days.
This is significantly quicker than the average training time for humans, which can take 4-6 months to reach full productivity. Furthermore, once trained, human workers do not have perfect recall and require continuous oversight and re-training.
Once an AI agent is trained for a specific role, there’s no need for additional training or hiring for that role in the future. This is far more efficient than the costly cycle of recruiting, onboarding, training, and retraining personnel.
AI agents are infinitely scalable
Unlike humans, AI agents don’t have a limit to the workload they can take on. Healthcare providers often face fragmented workflows in their administrative work. Interacting with various insurance organizations, plans, processes, and forms can be overwhelming. While handling individual processes or documents may be manageable, remembering all different procedures or continuously referring to operating guidelines can be inefficient and error-prone. These errors lead to denied claims, impacting revenue and payment timelines.
AI agents, however, don’t have these limitations. They can be trained on organization-specific protocols and recall all details with perfect precision with boundless scope.
AI agents can do repetitive work without errors and improve employee retention
If you’re grappling with the rising demands in healthcare, you might believe that your only solution is to employ additional people for your revenue cycle management (RCM) team. However, this approach might exacerbate the problem, leading to increased costs and decreased profits.
Humans aren’t well-suited to performing repetitive tasks for extended periods. Such work can lead to cognitive burnout, low engagement, and high turnover rates. Turnover in RCM departments is in the 11-40% range, far higher than the 3.8% national average.
But with AI agents, there’s no subjectivity, fatigue, or confusion. The technology does exactly what it was designed to do every single time. This makes your training significantly more efficient and the automated tasks error-free, allowing your organization to benefit from perfect precision. This, in turn, enables you to reallocate resources to other areas, such as enhancing the patient experience.
The bottom line is that manual, human-powered, approaches for RCM are unsustainable as the talent pool is shrinking and healthcare demand continues to soar. Why would you continue allocating more resources to something that’s very inefficient and will only worsen?
The good news is that you don’t have to. It’s time to lean into AI and allow your people to focus on what they do best, which is helping patients.
About Dan Parsons
Dan Parsons, as the co-founder and Chief Product Officer at Thoughtful, stands at the forefront of AI innovations in healthcare. His visionary leadership has supported Thoughtful’s mission to fix the U.S. healthcare system – they’ll achieve this by accelerating the adoption of fully human capable AI agents across the system, starting with revenue cycle management teams.