Patient analytics

Unlocking actionable insights and enabling better commercial decisions by combining patient interaction and journey with AI/ML-driven analytics.

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Combine real-world data, therapeutic expertise, and AI/ML-driven analytics

The value of patient analytics is driven by both an increasing need for more granular insights along the patient journey and an increasing supply of real-world data. AI/ML-powered analytics can help identify patient behaviors and patterns, drivers and barriers of these behaviors to influence and inform key decisions, both commercial and medical.

Equipped with deep insights and AI/ML-recommended actions, companies can achieve patient analytics excellence to transform the lives of people by ensuring the right treatment for the patients, at the right time.

Leverage Axtria’s patient analytics capabilities that bring together a deep domain/therapeutic experience, understanding of structured and unstructured patient-level data, and data science techniques to reveal unexpected relationships.

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Integrating information from diverse sources for mapping the comprehensive patient journey and more…

Axtria brings an extensive knowledge of data sources and a depth of experience in analytics. Our approach addresses these issues using statistical techniques and triangulation across multiple data sources.

RWE Data

Electronic medical records (EMR)
Longitudinal prescription data (LRx)
Medical claims data
Hospital and lab data
Oncology data (SEER)

Traditional Sources

Medical team expertise
Chart audits
Product sales
Quant surveys
Patient focus groups
Desk research
KOL interviews
Disease state reports

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Axtria’s solution offerings

Patient journey

Derive insights related to patient diagnosis, treatment, health outcomes, and their associated costs to inform decisions and actions.

Patient finder

Find the right patients at the right time (prior to switch or discontinuation to take corrective actions, showing characteristics similar to other patients with a relevant confirmed diagnosis, are currently on a first-line therapy and will probabilistically move to a second line therapy after three months, etc.)

Patient-centered customer segmentation

Drive payer and provider segmentation to identify high-value opportunities to guide ‘where to play’ and ‘how to win’ decisions, to focus on high-value segments.

AI/ML-driven analytics

Identify complex patterns in data and deliver greater insights (improving drug adherence using ML-based interventions (message alerts and targeted/relevant content), treatment pathway recommendations using predictive models, etc.)

Flow models

Capture key dynamics in diagnosis, treatment, and management-role played by providers at each stage, leverage and leakage points, choice of regimen at each line of therapy, etc.

Patient data BI

Self-service access that cuts through the complexity of patient-level data, with the ability to create intuitive visualizations that deliver engaging and timely insights.

Market sizing

Market sizing and evaluation in various product situations, such as products with multi-indications, used for specific populations, requiring a diagnostic test, etc.

HEOR

Facilitates cost and benefit tradeoffs and establish outcomes evidence.

Clinical trials

Supports trials via data-based patient recruitments, site selection, and cohort studies.

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Overcoming barriers to patient adherence

Poor drug adherence is associated with adverse health outcomes, higher healthcare costs, and lost brand revenues. Patient adherence to a therapy was a persistent problem in a rare cardiovascular condition which has no cure. Although the treatment improves symptoms, decreases healthcare costs, significantly slows progression, and reduces the risk of early death, about 45% of patients discontinue drug usage in less than 90 days of prescription.

To overcome the barriers to patient adherence, Axtria deployed various steps and designed machine learning algorithms. This helped to identify patient risk adherence, implementation of algorithms for continuous scoring, and impact analysis to estimate the impact of the patient intervention program.

Download Case Study / $15 million incremental revenue with AI/ML-enabled patient adherence

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Customer success stories

Case Study

Automated Email Campaigns Support The Patient Assistance Journey For Enhanced Treatment Outcomes

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Case Study

Patient Flow Analysis For A Global Oncology Leader

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Case Study

Enabling 95% Patient Adherence With Rapid Patient Data Analytics

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Patient Analytics

Patient analytics

Combine real-world data, therapeutic expertise, and AI/ML-driven analytics