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Healthcare conglomeration to access Big Data and lower costs

Posted in Artificial Intelligence - Breakthroughs in Theories and Technologies, Big Data, BioTechnology - Venture Creation, Clinical & Translational, Clinical Diagnostics, Computational Biology/Systems and Bioinformatics, Diagnostics and Lab Tests, Digital HealthCare – biotech & internet joint ventures, Drug Toxicity, Electronic Health Record, HealthCare IT, Healthcare Reform, Intelligent Information Systems, Technology Advance Assessment of, tagged , on January 13, 2016| Leave a Comment »

Healthcare conglomeration to access Big Data and lower costs, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Healthcare conglomeration to access Big Data and lower costs

Curator: Larry H. Bernstein, MD, FCAP 

 

 

UPDATED on 3/17/2019

https://www.medpagetoday.com/cardiology/prevention/78202?xid=nl_mpt_SRCardiology_2019-02-25&eun=g99985d0r&utm_source=Sailthru&utm_medium=email&utm_campaign=CardioUpdate_022519&utm_term=NL_Spec_Cardiology_Update_Active

Medicare Advantage plans may be driving up quality of care in terms of preventive treatment for coronary artery disease patients, but that has had little impact on outcomes compared with fee-for-service Medicare, researchers reported in JAMA Cardiology.

 

The expected benefits are not as easily realized as anticipated.   The problem of access to data sources is not as difficult as the content needed for evaluation.

 

Healthcare Big Data Drives a New Round of Collaborations between Hospitals, Health Systems, and Care Management Companies

DARK DAILY   DARK DAILY info@darkreport.com

 

January 13, 2016

Recently-announced partnerships want to use big data to improve patient outcomes and lower costs; clinical laboratory test data will have a major role in these efforts

In the race to use healthcare big data to improve patient outcomes, several companies are using acquisitions and joint ventures to beef up and gain access to bigger pools of data. Pathologists and clinical laboratory managers have an interest in this trend, because medical laboratory test data will be a large proportion of the information that resides in these huge healthcare databases.

For health systems that want to be players in the healthcare big data market, one strategy is to do arisk-sharing venture with third-party care-management companies. This allows the health systems to leverage their extensive amounts of patient data while benefiting from the expertise of their venture partners.

Cardinal Health Acquires 71% Interest in naviHealth

One company that wants to work with hospitals and health systems in these types of arrangements is Cardinal Health. It recently acquired a 71% interest in Nashville-based naviHealth. This company partners with health plans, health systems, physicians, and post-acute providers to manage the entire continuum of post-acute care (PAC), according to a news release on the naviHealth website. NaviHealth’s business model involves sharing the financial risk with its clients and leveraging big data to predict best outcomes and lower costs.

“We created an economic model to take on the entire post-acute-care episode,” declared naviHealth CEO and President Clay Richards in a company news release. “It’s leveraging the technology and analytics to create individual care protocols.”

Click here to see image

“The most basic, and the most important, thing is … they [Cardinal Health] share the same core values as we do, which is to be on the right side of healthcare,” naviHealth CEO Clay Richards told The Tennessean. “It’s about how you deliver better outcomes for patients with lower costs: How do you solve the problems [with growing costs]? That’s what we and Cardinal define as being on the right side of healthcare.” (Caption and image copyright: The Tennessean.)

Provider Investments Signal Continuation of Trend

Cardinal Health intends to combine its ability to reduce costs while providing effective care with naviHealth’s evidence-based, personalized post-acute-care plans. This is one approach to harness the power of big data to improve patient care. One goal is focus this expertise on post-acute care, which is one of Medicare’s quality measures.

Patients and their families often are unsure of what to expect after being discharged. And, according to an article published in Kaiser Health News, a 2013 Institutes of Medicine (IOM) report noted a link between the quality of post-acute care and healthcare spending following the discharge of Medicare patients.

However, maximizing the use of healthcare big data requires the participation of multiple stakeholders. Information scientists, hospital administrators, software developers, insurers, clinicians, and patients themselves must all perform a role in order for big data to reach its full potential. No single sector will be able to bring the benefits of big data to fruition; rather collaboration and partnerships will be necessary.

Other Collaborations and Alliances Target Healthcare Big Data

Two other organizations engaged in a similar collaboration are the Mayo Clinic andOptum360, a revenue management services company that focuses on simplifying and streamlining the revenue cycle process. In a press release, the companies announced that they were partnering to “develop new revenue management services capabilities aimed at improving patient experiences and satisfaction while reducing administrative costs for healthcare providers.” (See Dark Daily, “When It Comes to Mining Healthcare Big Data, Including Medical Laboratory Test Results, Optum Labs Is the Company to Watch,” December 14, 2015.)

In order to accomplish this, Mayo will have to share its revenue cycle management (RCM) data with Optum360, which will use the data to devise improved revenue cycle processes and systems.

“What we’re trying to find out, if we can, is what does healthcare cost, and what of that spend really adds value to a patient’s outcome over time, especially with these high-impact diseases,” stated Mayo Clinic President and CEO John Noseworthy, MD, in a story published by the Star Tribune. He was referencing another big data project Mayo is engaged in with UnitedHealth Group. “Ultimately, we as a country have to figure this out, so people can have access to high-quality care and it doesn’t bankrupt them or the country.”

Click here to see image

Mayo Clinic President and CEO John Noseworthy, MD, believes big data may be the key to transforming healthcare costs by informing clinical decision-making and altering patient outcomes. (Photo copyright: Mayo Clinic.)

Another interesting healthcare big data partnership is the Pittsburgh Health Data Alliance (The Alliance). It involves a collaboration between Carnegie Mellon University (CMU), the University of Pittsburgh (PITT), and the University of Pittsburgh Medical Center (UPMC). The aim of The Alliance is to take raw data from wearable devices, insurance records, medical appointments, as well as other common sources, and develop ways to improve the health of individuals and the wider community.

The common thread among all these collaborative efforts is a desire to improve outcomes while reducing costs. This is the promise of healthcare big data. And no matter which direction the effort takes, clinical laboratories, which generate a vast amount of critical health data, are in a good position to play important roles involving the contribution of lab test data and identifying ways to use healthcare big data projects to improve patient care.
—Dava Stewart

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Atul Butte

Posted in Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Computational Biology/Systems and Bioinformatics, Curation, Developmental biology, Diabetes Mellitus, Drug Toxicity, tagged , on October 17, 2015| Leave a Comment »

Atul Butte, MD, PhD

Larry H Bernstein, MD, FCAP, Curator

LPBI

Introduction to the Butte Lab

https://buttelab.stanford.edu/

The long-term research goal of the Butte Lab is to solve problems relevant to genomic medicine by developing new methodologies intranslational bioinformatics.

First, we have developed bioinformatics methods to take genomic, genetic, phenotypic, and RNAi data from multiple sources and phenotypes and reason over these data. An example of this was in our work in cancer drug discovery published in the Proceedings of the National Academy of Science (2000), on type 2 diabetes mellitus published in the Proceedings of the National Academy of Science (2003), on fat cell formation published in Nature Cell Biology (2005), on obesity in Bioinformatics (2007), and in transplantation published in Proceedings of the National Academy of Science (2009). Second, we have developed tools to automatically index and find genomic data sets based on the phenotypic and contextual details of each experiment. Our work on automatic annotations of the data in the NCBI Gene Expression Omnibuswas published in Nature Biotechnology (2006), our work in re-mapping microarray data was published in Nature Methods (2007), and our work in deconvolution of whole blood expression was published in Nature Methods (2010). Third, we have been developing some novel methods in comparing clinical data from electronic health record systems with gene expression data, as described in Science (2008),using genetic measurements, as described in PLoS Genetics (2010), and using gene-expression data, as described in Molecular Systems Biology (2009), and described in PLoS Computational Biology (2010), and described in the New York Times and International Herald Tribune.

The Butte Lab is in the Stanford Department of Pediatrics in the Stanford University School of Medicine, and is a core faculty laboratory in the Biomedical Informatics Training Program at Stanford University. The Butte Lab also serves as the Center for Pediatric Bioinformatics atLucile Packard Children’s Hospital. The Butte Lab is also affiliated with the Stanford Center for Biomedical Informatics Research (formally Stanford Medical Informatics or SMI).

Background

Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children’s Hospital Boston, then received his PhD from Harvard Medical School and MIT.   Dr. Butte has authored nearly 200 publications, with research repeatedly featured in Wired Magazine, the New York Times, and the Wall Street Journal.  Dr. Butte is also the principal investigator of ImmPort,  the archival and dissemination repository for clinical and molecular datasets funded by the National Institute of Allergy and Infectious Diseases.  In 2013, Dr. Butte was recognized by the White House as an Open Science Champion of Change for promoting science through publicly available data.  Other recent awards include the 2014 E. Mead Johnson Award for Research in Pediatrics, 2013 induction into the American Society for Clinical Investigation, the 2012 FierceBiotech IT “Top 10 Biotech Techies”, and the 2011 National Human Genome Research Institute Genomic Advance of the Month.  Dr. Butte is also a founder of three investor-backed data-driven companies: Personalis, providing clinical interpretation of whole genome sequences, Carmenta, discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data.

Experience

Founder and Scientific Advisor

NuMedii, Inc.

January 2011 – Present (4 years 10 months)Palo Alto, CA

Founder and Scientific Advisor

Personalis, Inc.

August 2011 – Present (4 years 3 months)Palo Alto, CA

Personalis™: Founded by global leaders in human genome interpretation

Co-founder and Co-chair of the Scientific Advisory Board

Carmenta Bioscience

November 2012 – Present (3 years)Palo Alto, CA

Scientific Advisor

Geisinger Health System

2011 – Present (4 years)Danville, Pennsylvania

UCSF Taps Atul Butte to Lead Big Data Center

https://buttelab.stanford.edu/people/abutte

By Kristen Bole on January 15, 2015

Photo by Susan Merrell

UC San Francisco has recruited a world-renowned expert in medical technology, Atul Butte, MD, PhD, to lead the new UCSF Institute for Computational Health Sciences, which will serve as a cornerstone of the university’s efforts to harness the power of “big data,” to lead to faster and more effective cures for patients worldwide.

A noted expert in pediatrics and medical informatics at Stanford University, Butte brings the rare combination of deep knowledge in medicine and biomedical research, and technological fluency to lead in the new realm of computational health. The appointment will be effective April 1.

The institute is a core element of UCSF’s campuswide efforts in what is known as precision medicine – a growing field that aims to take advantage of new advances in computer technology to mine the immense amounts of data being generated by biomedical research and clinical care, including vast new understanding of human genetics.

“Atul is a visionary leader working at the intersection of the technological and life sciences,” said UCSF Chancellor Sam Hawgood, MBBS. “The convergence of these disciplines will revolutionize how we envision wellness and medicine in the future. Under Atul’s leadership, our new Institute of Computational Health Sciences will position UCSF at the forefront of this revolution in health.”

Keith Yamamoto, PhD, vice chancellor for Research, announced Atul Butte’s appointment at the UCSF Informatics and Digital Health Conference on Jan. 15. Photo by Susan Merrell

In addition to his role at UCSF, Butte also has been named executive director of clinical informatics for UC Health Sciences and Services, in which he will assist UC Senior Vice President John Stobo, MD, and other UC Health leaders in the ongoing development and implementation of a UC-wide data warehouse and analytic platform.

This type of platform and data warehouse ultimately could enable researchers to tap into the vast amount of clinical data being generated by the five medical centers in the University of California system to help advance basic research in disease, better understand which therapeutic approaches are most effective and improve care across the UC system.

Butte is currently chief of the Division of Systems Medicine and associate professor of pediatrics at Stanford University and Lucile Packard Children’s Hospital, where he has been a faculty member for the past decade. Trained in both computer science and medicine at Brown University, Butte previously worked as a software engineer at Apple Inc. and Microsoft Corp., and received his PhD in Health Sciences and Technology from Harvard Medical School and the Massachusetts Institute of Technology. He is also a founder of several Bay Area biotech startup companies.

Butte’s research laboratory, which is funded by grants from the National Institutes of Health and March of Dimes, focuses on building and applying computational tools to convert hundreds of trillions of points of molecular, clinical and epidemiological data collected by researchers worldwide over the past decade, now commonly known as “big data,” into new diagnostics, therapeutics and insights into both rare and common diseases.

That is the crux of precision medicine, in which UCSF has played a key role, including co-chairing the committee that authored the definitive white paper on the subject for the National Academy of Science in 2011.

The institute Butte will lead is one of the core elements of UCSF’s precision medicine platform, which provides a single, overarching strategic vision for the campus going forward. That vision brings together the knowledge gained across the continuum of biomedical research and care, from basic researchers to translational scientists, clinical practitioners and social and behavioral scientists in all four of its schools – dentistry, medicine, nursing and pharmacy – and to patients and the community.

“If we could access and integrate the enormous amount of data imbedded in that continuum, we could potentially change the ways we understand life processes, imagine therapeutics and cure and avoid disease,” said Keith Yamamoto, PhD, UCSF vice chancellor of research and a national leader in bioscience research. “If we just aggregate the data, we’d have just a pile of data. The challenge is to devise ways to analyze it, mine it and make sense of it.”

The institute, which launched under interim directors Neil Risch, PhD, and Michael Fischbach, PhD, with seed funding from the Chancellor’s office so it could co-recruit its first faculty members with other UCSF departments, will serve as a campus hub for computer scientists and for researchers who use big data and computation as critical tools in biomedical research and practice, while also serving as an educational center to train future leaders in the field.

“The idea is to build a fully inclusive institute that reflects and harnesses what’s happening in all of the schools at UCSF,” Butte said. “Of course we hope that we will be successful in making discoveries and developing diagnostics and therapeutics, which we will disseminate through publications. But we also intend to take these discoveries out of the laboratories through licensing and starting companies, when we need to.

“We especially want to take advantage of the entrepreneur spirit growing in Mission Bay,” Butte continued. “If we want to change the world of medicine, we have to bring those discoveries into the marketplace and closer to patients.”

Watch Atul Butte’s talk on big data at TEDMED 2012.

Butte has authored nearly 200 publications and delivered hundreds of invited presentations in personalized and systems medicine, biomedical informatics, and molecular diabetes, including 20 at the National Institutes of Health or NIH-related meetings and TEDMED.

http://www.youtube.com/watch%3Fv%3DrCl6YK-xLXA

http://www.youtube.com/watch%3Fv%3DLSk6UMpxbmY

His awards include the 2014 E. Mead Johnson Award from the Society for Pediatric Research, 2013 National Academy of Sciences Kavli Frontiers Fellowship and 2013 Champion of Change in Open Science awarded by the White House. He was inducted into the American Society of Clinical Investigation (ASCI) in 2013, the Society for Pediatric Research (SPR) in 2011 and American College of Informatics in 2009. He received numerous early-career awards, including the 2010 Society for Pediatric Research Young Investigator Award and the 2006 Howard Hughes Medical Institute Early Career Award, among others. Butte also co-authored one of the first books on microarray genomic analysis titled “Microarrays for an Integrative Genomics” published by MIT Press.

Butte’s compensation includes a base salary of $147,300, in accordance with his academic rank and program unit, for which he will be eligible for the UC Retirement Plan and other standard UC benefits. He also is eligible for an additional $332,700 in negotiated salary, which will be supported through philanthropic sources and extramural grants.

UCSF is the nation’s leading university exclusively focused on health. Now celebrating the 150th anniversary of its founding as a medical college, UCSF is dedicated to transforming health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It includes top-ranked graduate schools of dentistry, medicine, nursing and pharmacy; a graduate division with world-renowned programs in the biological sciences, a preeminent biomedical research enterprise and top-tier hospitals, UCSF Medical Center and UCSF Benioff Children’s Hospitals.

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