Introduction
Revenue cycle management refers to a process applied in the healthcare systems that helps monitor patients’ revenue from their first appointment to their last balance payment. In many places, it is a usual part of the healthcare administration department (Gapenski & Pink, 2007).
The revenue cycle is defined as every administrative and clinical function contributing to capturing, managing, and collecting patient service revenue (Reiter & Song, 2021). Among revenue cycle management metrics, others are more important than others. The paper evaluates four metrics and explains why the Dates of Service Outstanding is the most important.
Dates of Service Outstanding (DSO)
Dates of Service Outstanding refers to a metric determining the time elapsed since an individual visited a hospital and the date a healthcare provider is paid. It tracks the revenue cycle’s efficiency and identifies any delay or bottleneck that may be affecting the ability of the provider to receive payment on time (Harahap et al., 2022).
A low DSO would suggest that the professional is getting paid quickly after rendering the service, whereas a high DOS would show a delay in the revenue cycle (Harahap et al., 2022). This metric is the most important as it measures the effectiveness of an organization’s credit and collection policies.
Net Percentage Collection
Net Percentage Collection is a metric measuring the percentage of total charges for a patient’s procedure or visit that a specific healthcare provider collects as payment. It tracks the overall efficiency of the revenue cycle and identifies any area where a provider may be losing revenue.
NPC is computed by dividing the total amount collected by the amount charged and multiplying by one hundred to express the outcome as a percentage (Harahap et al., 2022). A low NPC shows that the provider is collecting a low percentage of their charges, whereas a high NPC suggests that they are getting a high percentage.
Accounts Receivable Over 90 Days
Accounts Receivable Over 90 Days is a metric that determines the amount of money a healthcare provider expects from the patients for services rendered more than ninety days ago. According to Gilreath et al. (2019), it is responsible for monitoring the revenue cycle’s efficiency and noting existing bottlenecks that may influence a healthcare provider’s ability to get paid.
A high AR90 shows that the professional has a large sum of unpaid claims that are over ninety days old. In most instances, this suggests that delays in the revenue cycle prevent the provider from being paid in a timely manner (Harahap et al., 2022). Delays in submitting and processing claims or patient reimbursement issues can result in high AR90.
Bad Debt Percentage
Bad Debt Percentage (BDP) is a metric that determines the percentage of total charges for a payer’s procedure or visit that a healthcare provider may fail to collect as payment. According to Sivashanker et al. (2020), BDP monitors the efficiency of the revenue cycle and notes where a provider may lose revenue due to unpaid bills.
On the one hand, a high BDP shows that a healthcare provider is losing a tremendous amount of revenue due to unpaid bills (Harahap et al., 2022). On the other hand, a low BDP suggests that the provider is collecting the majority of their charges and experiencing significant losses caused by bad debt.
Conclusion
In conclusion, the paper has summarized four metrics of revenue cycle management and described Dates of Service Outstanding as the most important. It helps to determine the time that has passed since a person visits a hospital and the date a provider receives payment (Gapenski & Pink, 2007). Other metrics discussed include Net Percentage Collection, Accounts Receivable Over 90 Days, and Bad Debt Percentage.
References
Gapenski, L. C., & Pink, G. H. (2007). Understanding healthcare financial management. (7th ed.). Health Administration Press.
Gilreath, M., Morris, S., & Brill, J. V. (2019). Physician practice management and private equity: market forces drive change. Clinical Gastroenterology and Hepatology, 17(10), 1924-1928. Web.
Harahap, R. U., Agintha, N. D., Muda, I., & Nasution, F. N. (2022). Accounting information system related to the revenue cycle in healthcare and pharmaceutical sector. Journal of Pharmaceutical Negative Results, 4108-4113. Web.
Reiter, K. L., & Song, P. H. (2021). Gapenski’s healthcare finance: an introduction to accounting and financial management. (7th ed.). Health Administration Press.
Sivashanker, K., Duong, T., Resnick, A., & Eappen, S. (2020). Health care equity: From fragmentation to transformation. NEJM Catalyst Innovations in Care Delivery, 1(5), 1-8. Web.