“ACL has enabled us to take control of our data and gain a deeper understanding of trends in Managed Care Organization plan payments. As CHS Audit Services gained more experience with ACL’s software, the project completion time dropped by 50 percent, even as its scope continued to expand. This three-year Managed Care Payment project has been so successful, the Variance Summary Report was nicknamed ‘the treasure map’.”
Linda B. Franklin, Senior Auditor, Colorado Office of the State Auditor
Carolinas HealthCare System (CHS) is one of the largest health care providers in the southeastern United States, with a wide range of medical facilities and a large physician practice network. The Audit Services Department needed an automated method to analyse variances between expected and actual Managed Care Organization (MCO) payments for physician services. Using ACL software, CHS conducted a three-year Managed Care Payment project that identified approximately £1,370,000 in potential underpayments. ACL has given CHS unprecedented monitoring capabilities and has vastly streamlined a lengthy, labor-intensive data analysis process.
Carolinas HealthCare System has over 17,000 employees, 15 acute care facilities, nine nursing centers and senior care facilities, four behavioral health centers, an air ambulance service, and a network of more than 70 physician practices. Carolinas HealthCare is a not-for-profit, self-supporting public organisation.
CHS’ Audit Services Department started using ACL technology in late 2000, and has gradually expanded its role throughout the organisation. For the Managed Care Payment project, CHS auditors created a single relational database and wrote test scripts to address detailed technical challenges.
The CHS physician practice network, which includes over 70 practices, needed to compare MCO payments to the physicians’ charges for service. This was considered a stop-gap measure while CHS identified, tested, and implemented a viable commercial software application for contract management that could interface with their current billing system.
CHS had attempted data variance analyses with spreadsheet software. However, due to the complexity of the contracts and technical limitations, they met with little success. They found that only small samples of patient charges and MCO payments could be manually matched on a line-by-line basis. In many cases, they were unable to complete their analysis within the allowed time period in order to claim any errors and request additional reimbursement. CHS management felt that significant reimbursement opportunities likely existed, but lacked tools quick and powerful enough to verify their suspicions.
The Variance Summary Report enabled management to identify trends in MCO plan payments and create a strategy for pursuing additional reimbursements.
ACL allowed CHS auditors to combine three separate databases: fee schedules and MCO reimbursement rates; patient charges as shown on claims submitted to MCOs for reimbursement; and MCO insurance company payments posted to patient accounts. The audit team could then create a single relational database sorted by payer plan and calculate variances between MCO insurance company payments and expected payments in accordance with contractual terms. To date, the potential reimbursement recovery total for the three-year project is approximately £1,370,000 – a significant recapture rate that is growing each year.
Once the CHS team consolidated all MCO payments posted for claims on specific payer plans, ACL’s automated data analysis capabilities allowed in-house variance analysis rather than relying on contracted services – an estimated direct cost savings of about £306,500. This process also freed internal staff from conducting time-intensive manual analyses, and improved productivity and efficiency throughout the Patient Accounting department.
When CHS selected and implemented their new physician network patient accounting contract management system, ACL was used to independently monitor its effectiveness and accuracy.
The CHS audit team used ACL’s powerful software analytics to: