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Automation Creates 24/7 Referral-Acceptance Capabilities for James River Home Health

Automation Creates 24/7 Referral-Acceptance Capabilities for James River Home Health

James River Home Health (JRHH) was poised for expansion, but they needed a better way to manage their patient-referral intake process. In the competitive home health industry, agencies that respond to patient referrals the quickest have the best opportunity for landing the new clients. While JRHH received daily referrals, their existing manual process for capturing new referrals was time-consuming and inefficient. Knowing that their expansion depended on landing as many strong referrals as possible, JRHH sought a competitive edge. They reached out to UDig for help building an intelligent automation solution.

How We Went from Ideas to Impact

  • The Idea

    A manual patient referral-review process that was burdensome and didn’t enable them to capture patient referrals after hours or on weekends.

  • The Process

    Intelligent automation built around JRHH’s unique decision logic for when to accept and decline incoming patient referrals that could work around the clock.

  • The Impact

    A 24/7 automated decision-making system that is 77% faster and accounts for 75% of referral decisions.

  • “UDig enabled us to take our intake process to the next level. Their intelligent automation solution not only helps us make decisions more quickly and accurately, it’s become an essential tool in meeting our expansion goals.”
    David GriffithDirector Of Health Applications Strategy & Innovation, James River Home Health

The Idea

A Time-Intensive, Disjointed Process

Every day, JRHH receives up to 30 or more home-health patient referrals from healthcare organizations looking for an agency to continue care for a new patient. The referrals can come in at any time, including after hours and on weekends. To manage the incoming patient referrals, a team of at least six employees manually reviewed whether their company was a good fit for the referred patient. The patient-referral intake process could take five minutes per referral, which pulled employees away from other responsibilities.  

Additional challenges existed:  

  • Delays in reviews: Referrals that came after-hours and over the weekends had to wait until the next business day to be addressed. This delay often resulted in lost revenue when referrals went to competitors. 
  • Referral reviews were slow to process: As employees reviewed referrals to verify whether a client was a good fit, the manual process slowed down how efficiently the company could accept new patients. 
  • Criteria changes required manual updates: When the criteria for accepting referrals would change or evolve, employees had to manually communicate these elements to teammates. As a result, they had to not only remember what changes existed but also make sure everyone knew of these updates. This process led to inevitable gaps in up-to-date criteria when approving or denying referrals.  

These ongoing demands meant that JRHH was missing out on essential revenue across their referral-review process — and impacting their ability to expand.

The Process

Intelligent Automation That Streamlines the Process

To help JRHH meet their expansion goals, we knew that intelligent automation was a good fit. They needed a system that could work around the clock and streamline the amount of time employees would spend managing reviews. Rather than take five minutes on each referral, the company aimed to accept or decline a referral within two minutes. By doing so, they could be among the first agencies responding to the referral while giving their employees more time to work on other tasks.  

To meet their needs, we collaborated with JRHH in the following process: 

1.   Discover which elements were primed for automation.  

In this step, we worked closely with their team to understand their referral-review criteria. We identified the various elements of their business logic that they needed to incorporate into the automated decision-making process. We also addressed challenges their team was facing in working efficiently and making the best decisions on their reviews. 

2.   Design for their decisioning logic. 

Through an iterative process, we worked with JRHH to build the logic the automated system must use when identifying whether a referral is a good fit. We also knew these rules had to be flexible and scalable. For each decisioning logic, we created a list of every data point the system must analyze in order to know if JRHH should accept or decline the referral. We ensured that the solution seamlessly fit into their existing business process and could generate the reports they needed. 

3.   Develop their solution.  

Once JRHH approved their design, we developed the end-to-end automation using unattended bots within UiPath. We used an agile methodology to bring the design to life, which enabled us to address any changes to the patient-referral intake process solution in real time.  

4.   Test the automation before launch.  

We knew that JRHH needed to hit the ground running, so testing the automation was a critical element of our process. We worked closely with JRHH to plan and conduct test cycles that allowed our team to provide system support and fix any bugs before they became an issue. 

The Impact

A 24/7 Decision-Making System

Today, JRHH is able to move through their referral process with speed and efficiency. What once was manually laborious is now an automated system that captures leads 77% faster. And rather than only make decisions during business hours, they can capture which referrals to take throughout all hours of the day — increasing their revenue. Further, intelligent automation is able to make decisions on 75% of referrals, leaving only a quarter of referrals requiring manual review. This system frees up their employees to support other responsibilities. As JRHH begins expanding their market territories, they have a flexible, intelligent tool that can evolve with them. They now can more effectively meet their revenue goals and maximize what’s possible for their future.

  • How We Did It
    Business Process AnalysisRobotic Process Automation Solution Architecture
  • Tech Stack
    AllscriptsMicrosoft ExcelMicrosoft OutlooknaviHealthUiPath

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