Account intelligence guided agents drive AR gains
Modern practice management systems contain a trove of information for generating higher reimbursements from the flow of claims.
Unfortunately, little of that information is available to an agent following up on billed accounts.
The industry seems to attribute poor reimbursement to inflexible systems and weak skills. Although we sympathize with our clients’ staff. Beyond obvious targets like high-dollar accounts and accounts approaching timely filing limits, system queues provide little differentiation to increase cash flow. We don’t, unfortunately, always work on the most promising accounts.
And the PMS provides little guidance on what tactics successfully resolved similar accounts, leaving staff mired in long comments fields and reaching deeply into their own experience for clues on a promising approach. Newer agents are left awash in ineffective tactics like the Refer to Manager button or "change something reasonable and hit the Resubmit button."
Our agents feel like lab rats tagging a bar to dispense a pellet, and trying to figure out what to do with that undifferentiated account before the next account flies down the chute. We’ve found this to be an ineffective strategy for lowering AR and terribly demotivating to our staff.
Managers and team leaders at Vee Technologies tackled the need for a more effective AR process Their solution started with account prioritization and scaled by mapping accounts to scenarios that guide agents through high probability solutions.
We imprinted an account priority model and process scenarios on our Process Management Information System. Vee Technologies built the ProMIS platform to scale clients' production transaction processes.
Setting account priority is akin to emergency triage. With good intelligence, some accounts need immediate attention to have a chance of getting paid. We can ignore others as likely to be paid without further attention.
The key insight for setting account priority came from history-driven inventory categories. We’ve examined the effects of payer liquidity rates, denial reasons, physician specialties, and billing errors on the timeliness of reimbursement.
With a client’s aged trial balance and 837s/835s, we accumulate a production history to forecast results and adjust model parameters. We create virtual queues of target accounts to implement daily priorities.
Our process managers carefully craft root cause error categories into ProMIS solution scenarios. Each scenario leads the agent through a research path using discriminating questions, decision trees, payer clarifications, and recommended actions to get reimbursed with the fewest touches.
ProMIS serves the agent as a coach through each account encounter to offer high-probability paths for a successful transaction. Agents increase skills through micro-events, as they’re offered data to support resolution.
Following the ProMIS priority algorithm, agents address accounts each day that are most likely to need intervention to increase payment results. Working process scenarios at scale, we experience a 20% increase in monthly reimbursements from working the right accounts with the right scenarios at the right time. While continually improving our agents’ skills and experience, these gains have been driven primarily by inventory priority control.
From process scenarios and accumulated history data, ProMIS feeds a dashboard to help our managers and clients deeply understand account inventory and control resource priorities.
Experience in managing root causes of payment failures led us to reengineer the entire concept of a dashboard.
On the management dashboard, need meets function. It's designed to provoke questions and unearth insights. Our managers and clients use it to understand inventory factors like account age, financial categories, error categories, payer dynamics and scenario volumes.
By drilling down from categories, to sub-categories, and to account details, a manager builds an intuitive feel for the account inventory, how it's changing, and results driven by current priority strategies.
Our dashboard highlights inventory structure in graphic dimensions like:
Drilling down in each graph gives insights on structure and causes. For instance, drilling into AR by Age shows Financial Classes for that age. Following a Financial Class shows the Denial Categories. Under each Denial Category, the Payer Inventory for that denial is exposed. Ultimately the detail for individual accounts can be accessed.
With insights from quickly exploring different data paths, our managers develop intuition for the inventory and prospective improvement actions. The dashboard becomes indispensible to production reviews by focusing attention on the largest opportunities.
For a client’s inventory, the dashboard highlights impending problems and helps them explore optimization strategies. Critically, we find that solid performance data measures the effect of recent decisions and helps formalize initiatives for continuing improvement.
For any mix of resources, Vee Technologies clients enjoy better control of billing inventory and higher reimbursements from our ProMIS.
A special 'thank you' to my engineering friends and colleagues who researched and delivered this innovation, and without whom I wouldn’t fully appreciate the extraordinary outcomes we create every day for our precious clients:
Account intelligence guided agents drive AR gains