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Patient analytics

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


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.

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

Axtria’s solution offerings

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