This is the second in a series of four articles highlighting the key pillars of RCM success and the technology healthcare outsourcers need to achieve revenue recovery excellence.

Use data to drive decisions—seems as if it goes without saying. But inadequate data analytics and inefficient workflows that prevent the front-, middle- and back-end of the revenue cycle from working together to communicate and resolve issues is a prevailing challenge for those managing the revenue cycle continuum.

At the root of this challenge is the management of multiple data sources and vendor solutions. This creates a disjointed environment that not only makes it difficult for your account representatives to navigate these various systems—increasing reliance on manual processes and slowing the speed to payment—but it also prevents you from getting the holistic view of the actionable data you need to identify gaps in your revenue cycle.

It Starts with a Centralized, Reliable Data Environment

A strong, reliable data environment—one that provides that holistic view of the revenue cycle continuum—is key to allowing you to proactively identify areas where you need to optimize workflow processes and achieve a new level of overall organizational transparency. Look for a solution with these components:

Centralized Workflow Platform

Using a centralized platform allows providers to create a seamless workflow environment through system agnostic bi-directional integration. This simplifies data navigation and eliminates slowdowns with aggregation of patient, payer, and account level data under a single platform.

Dynamic Scoring and Advanced Segmentation

A dynamic scoring model uses Artificial Intelligence (AI) and Machine Learning (ML) technologies to leverage historical data coupled with alternative data sources (spending behavior, social media activity, online presence, etc.) while evaluating staff behaviors. This ongoing process provides a more holistic view of patient behavior than that of a credit score-based static method. A dynamic score that updates weekly can breathe new life into patient portfolios and increase the value of accounts providers might not be working.

The dynamic scoring model helps uncover insightful patterns in patient data, allowing you to incorporate advanced segmentation strategies into your workflow so that your account representatives connect with patients at the best time, with the most productive methods.

• Propensity to Pay (P2P) – AI-driven, dynamic P2P segmentation strategies prioritize accounts to drive the highest probability of payment.
• Best Time to Call – Makes the most out of opportunities to contact patients by understanding the most likely time for successful outreach.

Easily Digestible Visualization of KPI’s

A technology solution with embedded analytics helps you integrate actionable insights into existing processes so you can make better decisions. Easily digestible views of performance and results for end users and supervisors across business lines provides visibility into the behaviors and trends needed to understand and make business decisions that will further organizational growth.

• Activities and Productivity – Account volume, worked, types of work conducted, call summaries
• Payer Follow-Up Metrics – Claims per payer call, average hold times, talk time
• Patient Pay Follow-Up Metrics – Payment arrangements and activities, total collections

Make sure you don’t miss out on the next article in this blog series where we’ll take a closer look at the technology outsourcing organizations need to accelerate financial results. Sign up to receive the latest Healthcare News notifications from Finvi.