Self Payment Collection
Driving dollars through data: An innovative way to improve self-debt collections
Determining propensity to pay with an account segmentation approach allows providers to effectively focus efforts on accounts most likely to deliver maximum returns.
September 20, 2023
2:22 pm
Sponsored by Cognizant
Recent industry trends indicate the challenge of self-pay collections within the revenue cycle management (RCM) space will continue to rise, driven primarily by the increasing number of consumers opting for high deductible health plans.
Effective collections strategies require additional expertise to focus efforts where there is a higher return on investment. It’s time-consuming to chase collections and difficult to decide when to consider writing off an amount as bad debt. Poor decisions can lead to patient friction and hurt satisfaction scores. Yet aging receivables also represent revenue that providers need to improve cash flows and overall patient care.
This white paper will discuss why providers should leverage an account scoring and segmentation approach to proficiently determine the propensity to pay for outstanding self-pay accounts. Readers will review examples of how a data model with a foundation in artificial intelligence and machine learning can deliver multivariate analyses of account data and identify and categorize accounts effectively, allowing providers to direct their resources towards accounts ranked as having the highest propensity to pay.
Additionally, the white paper will detail the most common account segmentation errors to avoid and conclude with a case study. The case study will deliver insights into how a provider successfully utilized an account scoring and segmentation methodology to increase their collection rate by 25% in a single fiscal year as compared to the same period in the prior year.
This white paper explores the benefits of utilizing a data model to implement account segmentation for outstanding self-pay accounts. Readers will:
- Gain an understanding of why an account scoring and segmentation model with a foundation in artificial intelligence and machine learning should be used to determine propensity to pay for outstanding self-pay account
- Review common account segmentation mistakes to avoid
- Read a case study on how a large provider successfully used account scoring and segmentation to improve collections
