Case Study
Client Profile
A large multi-site clinic with 100 providers, averaging 850 patient visits per day. The clinic currently manually spot checks ~5% of clinical notes for clinical accuracy and compliance with coding requirements. As a result, the staff spends a significant amount of time on administrative tasks, and the clinic experiences regular coding errors leading to denied claims.
Challenges
High denial rate: The clinic has an average denial rate of 12%, often due to inaccuracies in clinical notes and coding errors.
High administrative workload: The clinic’s staff spends approximately 115 hours per month on clinical note reviews.
Delayed reimbursement: The average time to reimbursement is around 30 days.
Compliance concerns: The clinic’s management is worried about potential compliance issues resulting from inaccuracies in clinical notes.
New provider ramp-up: The clinic’s management is concerned that new providers are ramping up too slowly because QA flags documentation errors around 60 days after patient encounter.
Solution
The clinic implemented Brellium to streamline their clinical note review process and improve the accuracy of clinical notes. Brellium, leveraging advanced AI technology, automatically audits and flags errors in clinical notes and suggests potential corrections.
Results
Reduced administrative time: With Brellium's automated reviewing, the time spent on chart reviews dropped from 115 hours per week to less than 3 hours per week.
Lowered denial rate: Due to improved accuracy in clinical notes, the denial rate fell from 12% to 9%.
Accelerated reimbursement: The cleaner and more accurate notes sped up the claims process, reducing the time to reimbursement from 30 days to 25 days.
Enhanced compliance: The increased accuracy of clinical notes led to improved compliance, reducing the clinic’s risk of non-compliance penalties.
New providers ramping up quicker: feedback lag on improving clinical documentation is now delivered to providers in real-time, reduced from a 60 day lag.
Financial Impact
Reduced denials: The 3% reduction in denials led to an additional $51,000 per month in revenue, or $612,000 per year.
Saved administrative time: With 115 hours saved per week and assuming a staff cost of $45/hour, the clinic saves $5,100 per week or $61,200 per year.
Faster reimbursement: The 5-day acceleration in reimbursement improved the clinic’s cash flow and could be estimated to lead to an additional $14,000 in annual interest revenue.
The 1990’s alternative: Reaching these metrics by hiring manual auditors would require an additional $102,000 per month in salary costs vs. $51,000 in savings, making it financially not feasible. Brellium is the clear best option.
The total financial impact is estimated to be around $630,000 per year, a significant increase in the clinic’s bottom line.
Additional Benefits
In addition to the direct financial benefits, the clinic also experienced several indirect benefits:
Improved quality of care: With faster new provider ramp up and better clinical quality control, the clinic provides a better standard of care for patients.
Improved patient satisfaction: With fewer billing errors, patient satisfaction improved.
Increased capacity: The time saved on administrative tasks allowed the clinic to take on more patients, thereby increasing revenue.
Reduced stress: With Brellium taking over burdensome administrative tasks, the clinic’s staff reported reduced stress levels and improved job satisfaction.
Direct quote from QA Specialist: “Thank you so much for helping me with this overwhelming process.”
Conclusion
Brellium transformed the clinic’s RCM process, reducing administrative time, lowering denial rates, accelerating reimbursement, and enhancing compliance. The result was a direct financial benefit of $630,000 per year and several additional indirect benefits. The clinic’s management was delighted with Brellium's performance and plans to continue its use in the foreseeable future.
Assumptions: Staff cost is based on an estimated average. Denial rate, reimbursement rate, and interest calculations are hypothetical for this case study. Results may vary depending on the specific clinical operations and circumstances.
