The healthcare claims denial and rejection process is a significant administrative burden and source of loss to various healthcare providers and payers as well.
We have helped healthcare enterprises to lower the burden of rework by automating the identification of Claims prone to denial by reason, source, cause and other deciding factors.
The various classification and self-learning modules based on Machine Learning (ML) are utilized to fully automate identification of such claims prone to rejection or denial with high accuracy, investigate the reasons for claims denial and recommend methods to engineer features using Reject Reason Codes with high Information Gain.
Capturing Benefits requirements is a tedious but important process and it is also time consuming as it involves multiple phases of iterations of capturing the details.
e-Zest has worked with Pharmacy Benefits Managers to facilitate streamlining of the Benefit requirement capture process by leveraging intelligent web tools that reduce the timeline required to configure Benefits, include features to track each change and revise history for iterations made by each client individually.
Clinical requirements can be further classified into various requirement categories, typically known as “Drug Lists”, “Formulary” and “Utilization Management" requirements. These requirements are complex and their categorization is a tedious process.
e-Zest has worked on solutions that standardize the process of Clinical Requirement gathering in Pharmacy Benefits Management systems, to handle and facilitate better management of clinical requirements for all lines of business – Medicare, Medicaid, Commercial and Exchange. Some of the components e-Zest has worked on include building a web interface for reviewing and approving the clinical requirements that are passed as an automated process to downstream systems responsible for making coding and testing activities.
Defect predictions and analytics leverages historical defect data to predict and analyze the probability of defects while configuring benefit systems.
e-Zest brings years of experience in leveraging ML and AI techniques to streamline the process of defect triaging.
We have extensively worked on algorithms that can classify high probability defects and recommend correction, hence ensuring less burden on large sets of claims data.
Over the years, e-Zest has developed expertise in a number of domains within the healthcare sector, especially those involving Pharmacy Benefit Managers (PBMs).
We have developed solutions that have helped healthcare facilities such as PBMs by providing cost benefit analysis while onboarding new carriers.
Well visualized dashboards enable the PBMs to gain insightful and intrinsic views to the carrier being onboarded into the system, through efficient cost and benefit analysis such as Prescription Drug or Over The Counter Drug, Avg. Claim Cost, Average. Client Amount Due and so on.
Investigators and regulatory agencies are increasingly using claims data to identify quality improvement initiatives.
e-Zest has proven expertise in developing solutions for pharmacy benefits Surveillance that help ensure a member isn’t being inadvertently charged.
A key feature is an integrated dashboard view of all the key findings or learnings revealed by the Surveillance team, which can by used for its internal audits as well as to derive better insights on the current business trends.
e-Zest is a leading digital innovation partner for enterprises and technology companies that utilizes emerging technologies for creating engaging customers experiences. Being a customer-focused and technology-driven company, it always helps clients in crafting holistic business value for their software development efforts. It offers software development and consulting services for cloud computing, enterprise mobility, big data and analytics, user experience and digital commerce.