Revenue excellence in healthcare through rapid, innovative ML-powered revenue capture
The healthcare industry faces staff shortages, increased labor costs, and inflation on top of pre-pandemic healthcare affordability and access issues. This accelerating crisis presents an opportunity to reshape the business with data and automation to deliver outstanding care while improving the bottom line.
With the massive growth of digital data, using a rule-based approach coupled with manual audits to flag revenue leaks has proven inadequate. With revenue leakage being a widespread challenge across the healthcare industry, innovative, cutting-edge solutions are needed to recover the billions of dollars typically lost yearly. ML can look across staggering amounts of data, analyze patterns and look at outliers to deliver extraordinary insights.
State-of-the-art technology today allows scanning the entire revenue cycle, covering administrative and clinical operations that capture and manage patient services revenue. As a result, they navigate the complexities of billings, coding mistakes, insurance claims, payer denials, and the collection process.
RevCaptureAi is a sophisticated machine learning solution to identify, predict and capture missed charges. RevCaptureAi analyzes data from disparate hospital and physician systems to uncover anomalies and draw insights to maximize revenue capture. It helps achieve operational excellence by identifying potential sources of the leaks and then fine-tuning the processes to avoid such leaks in the future.
ML models learn continuously with more and more data and user interaction, leading to higher revenue excellence. The ML solution is easy to deploy and can be implemented on-premises or hosted as a service while supporting leading EHR or EMR software. Results are typically seen in 6-8 weeks. The model prioritizes predictions for revenue realization using payer contract data and historical payments data. Every dollar invested in the solution typically yields 8X in return.
One of the largest health systems with over $4 billion in net revenue relied on an inefficient, resource-intensive rules-based system revenue cycle system. The low revenue opportunity findings with high false positives and high resource cost led to millions of dollars in lost net revenue due to missed charges and coding errors.
ElectrifAi’s RevCaptureAi streamlined the charge reconciliation process and identified potential areas of opportunity. It employed predictive analytics to identify complex charging patterns and locate missed charges at the account level for both hospital and professional accounts.
It automated integration with a variety of EMR systems in different regions. In addition, it leveraged feedback models to learn from auditors’ responses and further enhance the predictions.
The solution identified $40m+ confirmed missed charges annually. It analyzed all 100% outpatient accounts through automated pre-bill and post-bill processes. Additionally, it spotted top departments with systemic gaps in charge capture, e.g., Injection/Infusions, EKG, surgery, implants & medical devices.
ElectrifAi: US’ leading ML solutions provider
ElectrifAi is one of the US’ leading ML solutions providers, with an extensive library of pre-built ML solutions enabling our clients to capture tangible benefits quickly. We work with the C-suite to understand and solve business problems through data and machine learning in diverse industries such as Higher Ed, BFSI, Life Sciences, Hospitality, Retail, Chemicals, Oil & Gas, Telecom, Insurance, etc. The insights generated by our ML solutions, such as HigherEdAi, SpendAi, ContractAi, HospitalityAi, RevCaptureAi, and InspectionAi, have helped our clients realize savings in 6-8 weeks.
Our solution does not require investment in a new platform, infrastructure, or data science team. Instead, we leverage the data existing in your system to power the ML models to deliver business outcomes.
We are the last-mile solution that sits on the top to solve specific business problems and bring about savings. Contact us to learn more!