Healthcare
Featured Solutions
Patient Jarvis Webpage Elevator Pitch Transforming Pharma Decision-making with Patient Jarvis
As the collection of claims data grows exponentially, patient analytics has emerged the focal point of commercial analytics in the pharmaceutical landscape.
Claims data offers granular insights into patient behavior, physician characteristics, and market trends for Pharma companies. However, its complexity and higher time to insight hinder quick decision-making.
Patient Jarvis, combining innovative technology and extensive understanding of pharma knowledge, not only speeds up insights but also provides advanced AI support, empowering swift decision-making.
- Whitebox solution
Transform your system with our seamless white-box solution, seamlessly integrated to become your proprietary masterpiece.
- Standardized claims data
- Experience 40% to 60% boost in bandwidth alongside unparalleled code reusability, all tailored to perfection.
- Lesser L&D time across teams as single training will suffice for claims data.
- Automated DE pipeline
- Empower your process with our end-to-end automated pipeline, orchestrating data seamlessly from ingestion to consumption, maximizing speed and quality at every turn.
- JarviSQL
- JarviSQL empowers various teams in your pharmaceutical company by expediting ad-hoc analyses through efficient SQL coding, leveraging generative AI-driven capabilities.
- Efficient KPI tracking
- Customizable DQ report for all the claims data in clients’ environment.
- Quicker Time to Insight with KPI dashboards covering E2E patient journey reducing redundant KPIs by 25% – 30%.
- SQL workbench
- SQL workbench will enable the strategy & insights team to do firsthand deep dives.
Patient Jarvis is precision-engineered to tackle the unique challenges faced by different roles within pharmaceutical companies. With a steadfast commitment to streamlining patient analytics for all, it empowers better decision-making across the industry.
With an innovative analytical framework applied on external data, payers can enhance the performance of existing rating modifiers to inform additional risk. Health insurers can leverage new signals from consumer data to predict claims experience to deliver an improved risk assessment process. These new signals include factors indicating buying behavior patterns, socio economic and financial statuses and health interests.
The enhanced rating modifier can help payers create an R-squared lift of up to 15%.
This lift is over and above claims experience typically informed by internal risk factors that payers already assess—such as age, gender, and location.
A few external indicators of additional risk informed by claims experience can include data on economic stability, usage of mobile phones, prime time television usage, smoking, community engagements, derogatory records, and dwelling status.
It’s time for payers to experience a better way to identify anomalous claims. The common process to identify anomalies is business-rules-driven, manual intensive, applied in a post-pay scenario and focuses mainly on known patterns, thus solving the problem partially.
Applying advanced analytics and looking for opportunities beyond overpaid dollars, such as better utilization management, plan design changes and network optimization, helps detect hundreds of unknown anomalies.
Payers can use the new analytical framework to drive up to $50M additional impact within the first year of operationalization — by increasingly focusing on unknown anomalies.
Get better results by:
- Applying predictive analytics and AI to better prioritize claims for SIU review
- Automating the entire anomaly identification process
- Creating a visual solution suite to help identify anomalies, track alerts, and measure the impact of interventions
- Delivering significant impact in both post-pay and pre-pay scenarios
The significant ROI in initial year/s enables payers to self-fund a suite of more advanced AI-driven scalable solutions to keep identifying and tracking anomalies, and improving recoveries from the flagged claims.
Our Thinking
Intelligent process automation: Driving accelerated decision making in healthcare
How can healthcare orgs leverage public datasets and AI to understand member’s health?
Case Studies
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4 min. ReadMaking sure the price is right
A healthcare giant faced exactly the challenge to manage a complex portfolio of products, with a variety of different contract terms that dictate pricing and rebates. Find how Fractal helped them get 90% reduction in time spent on deal creation and approval.
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5 min. readHealthy experiences? It’s all in the detail
A Top 5 health insurance payer redefined its marketing strategy by delivering personalized experiences relevant to their member needs leading to 21% improvement in ROI
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4 min. readFractal Health Triage enables personalized and coordinated care to payer’s Medicare members
Learn how Health Triage enabled personalized care at scale for a Fortune 100 health plan by getting a deeper understanding of members’ care needs and driving the right healthcare interventions.
The big picture A Fortune 100 health plan faced challenges with disjoint clinical care plans targeted to its members. This fragmented approach, delivered by different internal teams, resulted in costly and reactive...
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3 min. readReduce high costs of care associated with avoidable ER visits
A payer identifies opportunities to redirect avoidable ER visits, saving $10MM in cost reductions
The Big Picture The high cost of maintenance and limited availability of Emergency Rooms (ER) facilities are under intense scrutiny by payers, the government, providers and employers. According to the Centers for...
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3 min. readPharmaceutical uses behavioral science informed design to reduce prescription attrition
A patch-based dopamine agonist used to treat Parkinson’s Disease was facing a steep attrition rate of 50%. A new behavioral understanding led to significant changes in treatment outcomes.
The Big Picture As a manufacturer of a patch-based dopamine agonist used to treat Parkinson’s Disease, a major global pharmaceutical was facing a steep attrition rate of 50%, post two months of prescription uptake....
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3 min. readImprove collectability of the self-pay portion of medical expenses
Analytics helps a leading provider network identify patient segments to collect $20MM from unpaid invoices
The Big Picture Escalating healthcare costs have forced employees with employer-provided insurance to bear a higher portion of self-payment costs such as co-pay, coinsurance, deductible and out-of-pocket expenses....
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3 min. readDevelop prediction framework to address high attrition
A pharmacy distributor identifies $45MM opportunity to boost customer retention by predicting attrition
The Big Picture Wholesale drug distributors have experienced strong competition and consolidation leaving only a few surviving entities to service most of the US market. A leading distributor of drugs to long-term care...
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2 min. readImprove medication adherence to lower health costs and improve patient outcomes
Better problem solving and machine-learning helps healthcare payer save $5MM from reducing medication non-adherence
The Big Picture Non-adherence of medication is one of the most critical problems when treating patients with chronic conditions. Patients who do not follow the prescribed drug regimen are more likely to suffer poor...
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2 min. readLeverage external data to improve pricing and underwriting decisions
A payer better predicts claims experience with external data, supplemental to internal claims data.
The Big Picture A leading health insurer believed it could better predict claims experiences using external data, as supplement to internal claims data. The organization wanted to leverage the predicted claims...
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3 min. readImprove claims anomaly identification and tracking
A payer identifies $5M+ in potential savings in first year of powering claims anomaly identification with analytics
The Big Picture A top 5 US payer wanted to improve its ability to identify and track claims anomalies. Its existing process was business rules-driven, significantly manual, applied only in a post pay scenario and lacked...
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3 min. readBiotech firm uses data to unlock $100M opportunity to improve revenue.
Advanced analytics predicts decline in drug prescriptions to engage physicians and drive sales
The Big Picture: A leading pharmaceutical company was facing a decline in the sales volume of its flagship drug, which usually accounts for over $5 Billion of its annual sales. Less than 30 percent of physicians...
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3 min. readTop 5 US health payer identifies $45M in overpaid claims
Unsupervised learning methods helped recover claims payments and contain costs from fraud, waste, and abuse
The Big Picture: The US healthcare system loses more than $200 billion every year in fraud, waste, and abuse-nearly 10 percent of annual healthcare spending. The Government Accountability Office (GAO) has deemed...
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2 min. readBuilding a Gen-AI Tagging (GAIT) platform powered by AWS for a leading pharma company
Background and objective In response to the evolving landscape of content management, our client, a leading pharmaceutical company, faced a critical challenge in managing unstructured data files, particularly their...
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0 min. readCustomer Interaction Insights automates agent call monitoring for a large healthcare payor
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2 min. readShriners Children’s Hospital empowers physicians by mining clinical notes using Azure OpenAI
Background Shriners Children’s Hospital, a leading US-based pediatric care facility, faced critical challenges accessing historical clinical notes and manual processes, hindering patient care. In...
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