What big tech companies aren't saying about HHS data rules

Hospitals and doctors are pitted against patient data advocates in a strident debate over HHS plans to facilitate data sharing with software companies. But the biggest tech players — Google, Facebook, Amazon and others — have largely remained on the sidelines.

Health care professional groups have flooded HHS with comments on upcoming data sharing rules, expressing worry that developers could sell patient data for advertising and marketing purposes. They are urging HHS to add privacy provisions before finalizing the rules, which would force providers, vendors and insurers to adopt common standards so patients can share their information with apps they choose.

The full Politico article can be viewed at this link.  

Trump's next health care move: Giving Silicon Valley your medical data

The Trump administration's push to give patients more control over their health records could turn over a massive trove of very personal data to giant tech companies, app designers and data brokers.

If proposed policy changes go through, patients would be able to download their health records on to their smartphones and direct it to apps of their choice. But there’s a major privacy pitfall: As soon as those records leave the software system of the doctor or hospital, they are no longer protected by HIPAA, the landmark medical privacy law.

That’s where Google and Apple step in to hoover up the data. The tech giants have lobbied the administration to require access. That might allow for unprecedented convenience, letting patients more easily share data for a second opinion or enabling a researcher to find participants for a clinical trial. But it also opens up a Wild West of data sharing on the most intimate health care details for millions of Americans.

The full Politico article can be viewed at this link.  

The State of Patient Matching in America Survey Report

Patient matching and identification remain a top priority when it comes to lowering costs, enhancing clinical decision-making, improving patient safety and fostering care coordination— all critical components of value-based care. The purpose of this survey is to provide an upto-date assessment of the patient matching challenges and opportunities both providers and HIEs face, as well as their attitudes toward possible patient identification solutions

The full report can be downloaded below.

Correctly linking patient data across EHR systems remains a significant challenge for health systems, hospitals, offices, and any facility where patients receive care. Health Information Exchanges (HIE) also face challenges with patient matching. Duplicate or mismatched records result in privacy and safety risks, claim denials, redundant medical tests and procedures, and analytical reporting errors.

Presenter:

Vince Vitali

Vice President of Strategy, Nextgate

Vincent Vitali is a veteran healthcare IT leader with more than three decades of experience driving digital transformation as part of a passion to improve clinical, financial and operational efficiencies. He joined NextGate in September 2019 as Vice President of Strategy and Business Development to identify growth opportunities, increase market penetration, forecast trends and foster relationships with industry stakeholders.​ Vitali has dedicated his career to the advancement of healthcare IT, specializing in application integration, business intelligence (BI) and analytics, and population health management. Before joining NextGate, he was the Vice President and Chief Information Officer at Norwegian American Hospital in Chicago. Prior to joining Norwegian in 2018, he spent three years as CIO at RML Specialty Hospital, three years at Chicago’s LaRabida Children’s Hospital, and three years as Vice President and CIO at BroMenn Healthcare in Normal, IL.

Dr. Shaun Grannis

Vice President for Data and Analytics at the Regenstrief Institute

Dr. Shaun Grannis, MD, MS, FAAFP, FACMI is Vice President for Data and Analytics at the Regenstrief Institute, Professor of Family Medicine, and holds the Sam Regenstrief Chair for Biomedical Informatics at the Indiana University School of Medicine. He has provided technical and policy guidance to many organizations including the Department of Health and Human Service’s National Committee for Vital and Health Statistics (NCVHS), the World Health Organization, UNAIDS, the Pew Charitable Trusts and the Centers for Disease Control. Globally, Dr. Grannis collaborates with several developing countries to guide country-wide Health IT architecture, including establishing Rwanda’s first HIE-related MPI. His recent analyses in conjunction with the Pew Charitable Trusts showed that standardizing matching variables demonstrably improves matching accuracy. In addition to identity management, Dr. Grannis’ current work focuses on applying machine learning, natural language (NLP), and phenotyping methods to improve discovery, decision making, case identification and population health measurements.​

Join eHI as our webinar panelists discuss our 2019 national survey, The State of Patient Matching in America. We will dive into:
• The biggest contributors to duplicate medical records
• The biggest barriers to improving patient matching rates
• How potential mismatches are addressed
• The government's role in patient matching

Scaling Blockchains to Support Electronic Health Records for Hospital Systems

Electronic Health Records (EHRs) have improved many aspects of healthcare and allowed for easier patient management for medical providers. Blockchains have been proposed as a promising solution for supporting Electronic Health Records (EHRs), but have also been linked to scalability concerns about supporting real-world healthcare systems. This paper quantifies the scalability issues and bottlenecks related to current blockchains and puts into perspective the limitations blockchains have with supporting healthcare systems. Particularly we show that well known blockchains such as Bitcoin, Ethereum, and IOTA cannot support transactions of a large scale hospital system such as the University of Kentucky HealthCare system and leave over 7.5M unsealed transactions per day. We then discuss how bottlenecks of blockchains can be relieved with sidechains, enabling well-known blockchains to support even larger hospital systems of over 30M transactions per day. We then introduce the Patient-Healthchain architecture to provide future direction on how scaling blockchains for EHR systems with sidechains can be achieved.

The full article can be downloaded below.  

Nine Experts On The Trends That Changed Healthtech In The Last Decade, And The Innovations To Expect By 2030

As we enter 2020, it seems like a good moment to reflect on how technology has reshaped the way we think about, and deliver, healthcare in the last 10 years, and to look forward to the innovations that might transform our sector in the decade ahead. 

I asked some of my peers to share their views on the biggest developments in digital health during the 2010s, and their predictions for what the 2020s will bring.

The full Forbes article can be viewed at this link.  

The economy of connecting

Right now, patients don’t know their own strength. But as they wake up to their emerging role as keepers of their own healthcare data, the economic clout that comes with ownership will hand them a controlling stake in the new business models that are set to disrupt traditional financing across the sector.

Forecasts give a strong indication of the potential scale of that role – and the reasons why technology startups, insurers, providers and researchers are gearing up for the age of value-based health, in which patients will trade their data as currency, investing in their own care outcomes and the tools that will help to identify and realise them.

The full Healthcare IT News article can be viewed at this link.  

 The Rise of the Data-Driven Physician

Since its inception, the Stanford Medicine Health Trends Report has examined the most consequential developments and technologies that are changing health care delivery. Our 2020 report describes a health care sector that is undergoing seismic shifts, fueled by a maturing digital health market, new health laws that accelerate data sharing, and regulatory traction for artificial intelligence in medicine.

The full report can be downloaded below.  

On the Digital Health Conundrum (Part I)

For a decade, digital health has been the supposed savior of the healthcare system, coming to drive healthcare into a data-first, low-cost industry worthy of the 21st century. Investors have poured over $30b into digital health since 2011 but what material change can we point to in health care costs or the experience of the average patient? Are there companies that qualify as major disruptors? To me, the answer is no. I call this the Digital Health Conundrum.

The full Medium article can be viewed at this link.