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Thought Leadership

Perspectives on Health Informatics

Thought leadership at the intersection of clinical medicine, data science, and healthcare technology from the Acumenus team.

Data Architecture 12 min read New

From Raw Data to Clinical Wisdom

The Healthcare Data Pipeline

Sanjay M. Udoshi MD | Mar 1, 2025

Healthcare organizations generate staggering volumes of data every day. But data alone doesn't save lives. This article walks through the six stages of the healthcare data pipeline — a comprehensive framework for converting raw clinical and business data into knowledge and practice that improves patient outcomes.

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Clinical History 8 min read

The Enduring Legacy of Sir William Osler

Sanjay M. Udoshi MD | Dec 22, 2023

Sir William Osler, often regarded as the father of modern medicine, established principles of clinical practice that continue to resonate over a century later. His emphasis on bedside teaching, systematic observation, and the humanistic approach to patient care laid the groundwork for evidence-based medicine.

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AI & Healthcare 9 min read

Don't Believe The Hype

First-gen AI in healthcare will create more clutter, not clarity

Sanjay M. Udoshi MD | Dec 17, 2023

The current wave of AI hype in healthcare threatens to obscure the very real challenges of clinical data management and decision support. Without rigorous validation, standardized data infrastructure, and clinical workflow integration, AI risks becoming another source of alert fatigue.

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Data Science 8 min read

Improving Healthcare Outcomes with Data Science

Sanjay M. Udoshi MD | Dec 14, 2023

Data science methodologies offer healthcare organizations powerful tools for improving patient outcomes. The key lies not in the sophistication of the algorithms but in the quality and standardization of the underlying data.

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Analytics 9 min read

Knowledge Generation Through Advanced Analytics and Decision Support

Sanjay M. Udoshi MD | Dec 13, 2023

The transformation of raw clinical data into actionable knowledge requires more than dashboards and reports. It demands a systematic approach to analytics that begins with data standardization and culminates in decision support tools that integrate into clinical workflows.

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We welcome opportunities to co-author, present, and partner on research at the intersection of clinical informatics and data science.

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