TEAM INNOVATIONS

LikeME

Historically, clinical trials did not always recruit participants who represented the individuals most affected by a particular disease, condition, or behavior. Often, these clinical trials relied almost exclusively on White male study participants. This shortcoming has created gaps in our understanding of diseases and conditions, preventive factors, and treatment effectiveness across populations. These gaps in knowledge can impede the quality of health care decision making, ability to counsel people on ways to reduce their risk, optimal treatment responses, and even the development of more effective medications or interventions. LikeMe offers an assessment on the similarity between a patient and the clinical trial cohort. LikeMe users will input their demographic information; then they can input a drug/therapy name to see if it has been tested with persons like them. LikeMe empowers patients to participate knowledgably with their provider in treatment planning and reduces the risk of prescribing treatments that have unknown outcomes for certain population segments.

Project Innovators: Manian CSB, Suzanne Beaumont, Joseph Kitchen, Dan Metz, Yulia Kuznetsova

Enterprise Monitoring Team 

Blue Cross NC has several old applications, like Care Radius and Amisys. We are currently monitoring them for the total transactions/good/bad transactions. It was long perceived that automation of some jobs like controlM and bot automation could cause a user experience issue if all happened at the same time. However, there is no real data to prove this assumption. We used mathematics and analytics for the good/bad/total transactions for the above apps at specific times, and found the analytics prove the assumptions are correct. The statistical analysis allows the automatic correlation and insight of data sets we could not see before. The benefit of this project allows the business to rearrange these auto jobs to minimize impact.

Project Innovators: Hui Wang, Bobby Dodson, Mitch Weiner

Team Docs 

This project builds out a centralized documentation system with benefits including:

• More Efficient Operations: Having all the important files in a single space will make work much easier to complete.

• Reduce Data Loss from Human Error: There will be a decrease in data loss due to human error. From employees who may accidentally lose files or delete important information. 

• Improved Security: A centralized documentation systems provide much greater security.

• Better Compliance: A centralized documentation systems allow for practice of better compliance with security regulations.

Project Innovator: Collins Afanwi

FTS Olympians 

File Transfer Services require a repository of vendor contact information to maintain healthy relationships and data flows with our partners. Much of the team's data is collected during the initial stages of the data flow's lifecycle, leading to an abundance of outdated contact information existing in our environment. Previously, the new contacts were being stored in an excel spreadsheet. As vendors changed names, people left their previous roles, or new people were hired, this spreadsheet became cumbersome. Our team needed an easily accessible and maintainable solution to be more proactive in responding to these changes.This tool fills the need for an accessible and maintainable repository of vendor contacts. Users easily access and edit the contact information for vendors in a windowed application in only a few clicks. Many teams could benefit from a flavor of this application as it is highly customizable.

Project Innovators: Emily Moran, Alaina Randolph, Paul Pham, Tynia Barrow

Team SAGE 

Blue Cross NC is unintentionally denying previously paid claims causing manual work, provider abrasion, and late payment interest (LPI).​ Automated adjustments, such as corrected claims, do not run through all Facets Workflow rules. This causes many claims to process incorrectly, often denying in error, resulting in the need for subsequent manual adjustments and LPI.​ We analyzed all Facets corrected claims that had subsequent manual adjustments generating LPI. We used this data to estimate potential LPI savings. We also looked at the entire universe of corrected claims to estimate the volume impact of turning on workflow rules for corrected claims. ​

Project Innovators: Aaron Terry, Bethany Freeland, Goutham Gunasekaran, James Smith​, Jay Hill​, Kyle Sabbe​, Latonya Carrington​, Michael Hieronymus, Nelson Bassett​, Niraj Kumar, Rohini Mandge, Sonal Mittal​, Terry Kroliczak

Medicaid Minds 

Heavy manual work in needed to process Medicaid claims in Facets. This has impacted MTM scores, turnaround times, impact to other LOB claims processing, unnecessary Late Payment Interests and has caused financial impacts. Medicaid claims are already paid to the provider by Managed Care Organizations (MCOs). Later, MCOs submit the claims to Blue Cross NC (if the member has a plan/ contract with us). Blue Cross NC adjudicates Medicaid claims differently compared to a normal claim. The fact that these claims are already paid by MCO plays a significant role in adjudication. We price the claim as a normal claim and later compare the MCO paid amount and reimburse the lesser of two. It is because of this comparison, we adjudicate Medicaid claims twice. However, the automation process which does this was equipped to handle only claims from NC DHHS. Since 2022, we have added 6 more MCOs and this has caused automation process for the new MCO claims and pay wrongly to DHHS. In addition, a mix of manual errors, configuration issues, provider data set up issues, gaps in predecessor/ successor processes of automation process has caused severe manual workaround for teams like Facets production support IT, claims operations, CCFE, PDM, etc. This has inspired us to bundle up all problems and come up with solutions for the betterment of Medicaid claims processing in Facets.

Project Innovators: Stephane LeBlanc, Mithunkumar Athinarayanan, Marilyn Thayer, Heather Sammons, Wendy Scarlett

Consistency is Key 

In an era where automation can be done on most things, we seem to be doing many things in an ad-hoc manner. Using tools that we already own, we want to create a new pipeline using templates that will allow our development community to push content faster (i.e. with less manual work by multiple teams). This pattern will also allow us to remediate vulnerabilities quicker and our build/deploy pattern becomes more consistent across development teams.

Project Innovators: Robert Harvey, Gordon Flood, Justin Stroda

Team Force

Many enterprises struggle with effectively retrieving and accessing the vast amount of information and knowledge available within their organization. Traditional methods of searching and retrieving information can be time-consuming, inefficient, and often result in incomplete or irrelevant results. This creates challenges for employees who need quick and accurate access to critical information to make informed decisions and perform their tasks efficiently. To address this problem, we developed an AI (Artificial Intelligence) tool called ACAI (Advanced Cognitive Assistant for Information). ACAI aims to provide a modern and efficient solution for querying enterprise knowledge. It leverages advanced cognitive technologies to understand and interpret complex queries, intelligently search, and analyze vast amounts of structured and unstructured data, and present relevant and accurate information to users in a user-friendly manner. By acting as a cognitive assistant, ACAI seeks to streamline the process of retrieving enterprise knowledge, saving time, and improving productivity for employees across the organization.

Project Innovators: Srikanth Karre, Sai Kiran Kadari, Vijaya Chowdari, Subhash Payal