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AIE Technology Solutions, Inc.
AIE TS offers custom software design builds for the healthcare industry and has also created in-house solutions including a telehealth platform, telecom solution, client branded data storage, and Aegisio which is in the pipeline to leverage AI/ML in streamlining the revenue cycle. Our recent custom builds include RPM software and file conversion software.
We are on a mission deliver financially viable solutions for the healthcare industry leveraging cutting edge technology in support of best practice patient experience.
Type of Organization
Startup - Newly established businesses, investable
Size of Organization
Organization Mailing Address
8 The Green STE #6766
Dover, DE 19901
Aegisio integrates AI & Machine Learning to facilitate a streamlined revenue cycle. This reduces human errors, escalates the payment timelines and reduces risk associated with fraud/abuse. The administrative back-end, cost to collect, and unpredictable cash flow creates difficulty in the planning and execution of patient care. Our solution bridges this gap through automation that is consistently learning and adjusting based upon payer behaviors.
Our use of AI and machine learning to intelligently process claims, denials, and insurance payment issues will be handled automatically. Our machine learning system will be continuous learning based on payer responses, user actions, and other relevant actions on claims. This information can be aggregated and utilized to process claims for other healthcare organizations to reduce errors amongst varying groups. This will decrease the cost to collect, allow for more accurate timely claims submission, as well as automated rework of the most common denials without human intervention. With staff no longer burdened by these time consuming and mundane tasks, the human capital contributions can be shifted to support higher-level functions. Additionally, by removing the excess administrative and cost to collect costs, healthcare organizations will be able to reallocate resources towards improving patient care. Lastly, leveraging this solution will provide an avenue to mitigate risk associated with fraud/abuse as the solution provides automation.
The revenue cycle process has been stagnant since its inception. The healthcare industry is constantly evolving, yet the revenue cycle process and the manner in which the process is executed has been left virtually unchanged. This is because the primary focus of businesses in the healthcare software industry has been on electronic medical record systems, leaving the need to innovate the associated revenue cycle process neglected. Our product seeks to reimagine the revenue cycle construct by utilizing artificial intelligence and machine learning.
Our product will streamline this neglected process by reducing manual labor and errors. The best systems such as Epic, Cerner, and Meditech rely upon rules that are manually inputted by the users to aid in the circumvention of human error. There are thousands of rules based on a myriad of factors that must be continually maintained and updated. These products are not available to the majority of small to mid-level healthcare organizations due to their high costs and continued maintenance expenses.
Our market is twofold and encompasses both facilities and provider practices. Facilities (i.e. hospitals) bill on a UB-04 claim form for institutional care whereas outpatient and professional services are rendered on a CMS 1500. The revenue cycle flow for both segments of billing is very similar and allows for the technology to be leveraged for customers of both billing types.
Category of Innovation
Health IT - Health IT refers to the “pipes” or “infrastructure” that technological systems are built upon and that digital health solutions may use to provide information or other necessities. Ex. Electronic medical records (EMRs)
Intended End User
Provider - Individuals or organizations responsible for providing care to patients (e.g. doctors, nurses, hospital/clinic administrators, etc.)
Problem (i.e. barrier, issue, complication, etc.) being solved for the end user
Aegisio will profoundly impact the healthcare industry by reducing the administrative burden associated with the cost to collect. Presently, revenue cycle management companies are charging an average commission rate of 2-8% depending on the complexity and volume of the associated billing.
Idea/solution to the problem, if applicable
With the inclusion of Aegisio's machine learning algorithms, the metric can feasibly be cut in half. This will allow struggling rural healthcare facilities to continue operations and urban physician practices to thrive.
Level of adoption (i.e. list of customers/users, testimonials, etc.), if applicable
We have crafted a partnership which will provide a pathway to data to train the algorithms for swiftly bringing the product to market.
Impact (i.e. measurable outcomes), if applicable
Our solution is still being developed.
List of Funding Sources (if applicable)
We are in the review stage of an SBIR grant application.