Friday, March 29, 2024
HomeHealthcareUse comprehensive consumer data to improve healthcare collection

Use comprehensive consumer data to improve healthcare collection


Even before the COVID-19 outbreak, collecting was difficult. The bottom line of providers is already tight, and the trend of high deductibles continues, making patients bear greater medical expenses.

The highly volatile but continuously improving employment environment is of no avail, and some patients’ ability to pay has not kept up with their growing financial responsibilities. Many people have new health plans, lapsed insurance, or focus on other debts, which makes collections more difficult to predict.The provider may also believe that the change in payer’s policy has not made it easier to make up for the income lost by the pandemic, and some losses Two full working days per week Complete prior authorization.No wonder almost One in five suppliers They completely reformed their patient collection strategy last year.

Now, one year after the pandemic’s impact on income, the three main trends in this area continue: Increase in patient balances and an accelerated shift to innovative payment experiences that are shifting to digital participation as the first choice for paper or “over the counter” payments Choose,” and recognize that compassion is a key factor in solving this challenge.

Avoid new pitfalls in patient collection

The preferred strategy for improving patient collection before the pandemic may simply include providing more patient payment options, doing more work to check for missing coverage, or focusing efforts on patients most likely to pay. These are wise choices, but if implemented improperly, they are more like band-aids than cures. Some disadvantages include:

  1. Models that rely on historical payment data cannot show the full picture

Providers know that focusing collection efforts on patients who are most likely to pay is the most effective method. However, it may not be reliable to determine the patient’s ability to pay only based on historical payment data.

Experian Health’s research shows that when the collection model only relies on historical data, about 50% of accounts will eventually operate without data at all. The new account is assigned to the “very likely to pay” section, regardless of whether this reflects their actual situation. The cost of this model is four times that of using Experian Health’s collection optimization manager, which can predict the patient’s ability to pay by using multiple data sources, even if there is no historical payment.

A collection based on limited data will require more resources to process more accounts, but this will ultimately be the same as a collection based on multiple data sources.

  1. Beware of artificial claims about artificial intelligence

In order to simplify work processes and avoid wasting staff time due to inefficient processes, many vendors are turning to automated patient collection solutions. artificial intelligence It is an exciting prospect in the healthcare sector, but not all solutions are as they seem.

Matt Baltzer, Product Director of Experian Health, said:

“Many collection tools claim to actually use artificial intelligence when using basic automation based on incomplete data. Since the quality of the output depends on the input data, the insights these tools produce will be severely limited.”

In order to solve the challenges of the collection workflow, providers need an end-to-end strategy that integrates multiple high-quality data sources, intelligent analysis, and a learning and adaptive response platform to prioritize patients and interact with them in a way that makes collection easier They communicate.

  1. Cash payment and price transparency can be part of the solution, but not all

One way to eliminate the bumpy income cycle is to provide discounts for cash-paying patients. It saves management costs and guarantees that at least part of the bill is paid. Although this is meaningful for minor illnesses, the management and treatment costs of chronic diseases and major medical incidents are still high. Flexible collection strategies need to be fully operational, addressing the many treatments, procedures, and care plans that suppliers provide and manage every day.

Requirements for improving collections after COVID-19

The cohesive integration model that providers need has the following key elements:

  • Comprehensive analysis of multiple data sources

Optimal set modeling Use different data sources to make more reliable predictions of patients’ ability to pay. Combining credit data, behavioral modeling, and socio-economic insights can help providers better understand the financial status of patients and quickly and accurately group them accordingly.

  • Provide convenience and clarity for patients and staff

An automated workflow with an easy-to-use interface will make it easier for staff to collect and eliminate time-consuming manual tasks. At the same time, it’s more fluid, More targeted collection process This means that staff can interact with patients on the basis of accurate information, reducing (and less stressful) phone calls and emails.

  • Advanced data analysis and automation reduce errors and rejections

In-depth data analysis enables suppliers to quickly screen and segment patients to help prioritize accounts by probability of payment, thereby achieving higher collection rates.A tool such as Collection optimization manager The performance of collections will be evaluated in real time to help providers predict patient payments and avoid bad debts.

  • Expert consulting support, keeping up with industry trends

As the payment landscape continues to change, having an expert to help navigate the changes and advise on industry trends is an important asset. The Experian Health team is ready to help providers monitor and improve collections through industry insights and best practice strategies.

Understand how Collection optimization manager It can help your organization avoid patient collection pitfalls and reduce income loss after a pandemic.



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