Big Data: The Ultimate Medical Textbook


There is little doubt that data will drive both the delivery and improvement of healthcare in the future.  “Big data” refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. It is intentionally subjective and is expected to grow over time. A  study from the McKinsey Global Institute estimated that big data has$300 billion of potential added value to the US healthcare system.  Examples of this may be seen with Kaiser Permanente’s of clinical and cost data leading to the discovery of adverse cardiovascular outcomes from Vioxx and the Italian Medicines Agency which collects and analyzes clinical effectiveness and cost of approved medications over time, after conditional reimbursement is granted.

The report goes on to discuss the USA’s four main disjointed sources of healthcare data: pharmaceutical R & D data from clinical trials, claims and cost data from providers and payers, consumer data from purchases of health-related items, and clinical data from EHRs.  It goes on to identify five ‘levers’ (related to the development and delivery of care) of potential cost savings from big data: clinical operations (which in turn has 5 levers-comparative-effectiveness research, clinical decision support systems, transparency about medical data, Advanced analytics applied to patient profiles and remote patient monitoring),  payment/pricing (consisting of automated systems and health economics and outcome research), research and development in the PMP sector (includes predictive modeling, statistical tools to improve clinical design, analysis of clinical trial data, personalized medicine via genomics, and analysis of disease patterns), new business models (aggregating clinical records and claims data, and online communities), and public health.

Big Data creates value in demonstrating transparency, enabling experimentation, identifying population-specific needs, supporting human decision support with automated algorithms, and promoting new business models and technologies.

Patient-derived data is garnered from multiple sources.  Clinical records, claims analysis, and direct remote patient monitoring.  It is digestible both on a micro and hugely macro level, with benefits derived from multiple observational levels. Big data are then used to benefit people who are not yet perhaps affected by a given illness.  It is the ultimate textbook of medicine.  William Osler said “Medicine is learned by the bedside and not in the classroom.” Patient-derived Big Data is the textbook of the future. Patients through their data will tell us what is best for them on an individual and population level, true personalized medicine.


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About davidleescher

David Lee Scher, MD is Founder and Director at DLS HEALTHCARE CONSULTING, LLC, which specializes in advising digital health technology companies, their partners, investors, and clients. As a cardiac electrophysiologist and pioneer adopter of remote patient monitoring, he understood early on the challenges that the culture and landscape of healthcare present to the development and adoption of digital technologies. He is a well-respected thought leader in mobile and other digital health technologies. Scher lectures worldwide on relevant industry topics including the role of tech in Pharma, patient advocacy, standards for development and adoption, and impact on patients and healthcare systems from clinical, risk management, operational and marketing standpoints. He is a Clinical Associate Professor of Medicine at Penn State College of Medicine.
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