FHIR Fever Is Catching On In Healthcare

It's been almost two decades since the nonprofit Health Level Seven International (HL7) created the FHIR standard, now on its fourth release. The forces of government regulation, consumer demand, competition and the journey to value-based care are creating new pressure on the healthcare industry to embrace interoperability, a Deloitte report says, with FHIR emerging as the common language. Open standards to link diagnostic, clinical health and certain administrative data can reduce medical errors, eliminate opportunities for fraud and bring down the data siloes that account for so much waste.

The full Forbes article can be viewed at this link.  

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.  

Why health care AI can’t replace medicine’s human component

The AMA deliberately uses the term augmented intelligence (AI)—rather than the more common term “artificial intelligence”—when referring to machine-learning computer algorithms that hold the potential to produce dramatic breakthroughs for health care research, population health risk-stratification and diagnostic support.

And there’s a good reason for that.

“In health care, machines are not acting alone but rather in concert and in careful guidance with humans, i.e., us—physicians,” said AMA Board of Trustees Chair Jesse M. Ehrenfeld, MD, MPH. “There is and will continue to be a human component to medicine, which cannot be replaced. AI is best optimized when it is designed to leverage human intelligence.”

The full AMA article can be viewed at this link.  

Predictions for Telehealth in 2020: Will This be the Takeoff Year?

In order to place predictions for telehealth in proper perspective, consider that like all new industries, telehealth is characterized by disparate ideas developed by different people, often for the same medical specialty and/or medicine-related activity. Over time, these ideas must coalesce to provide growth and economies of scale. This occurs at multiple levels. One need only look at the history of banking and finance for an analogous situation that is highlighted by innovation, mergers, and integration. In healthcare, the overall experience with an array of disparate health information exchanges has been less than satisfactory for most observers. While the trend towards consolidation has begun in the telehealth arena, it is at an early stage. With this in mind, our invited experts looked into the future from their shared and unique perspectives to offer their view on the next big thing(s) in telehealth in 2020.​

The full article can be downloaded below.  

We’re kidding -- there are no dummies here! But HIPAA is complicated, and not well-understood. Learn about the basics of our primary federal health privacy law – including who is covered, what data is covered, and how the law and its regulations work in practice.

Presenter:

Alice B. Leiter​:

Vice President and Senior Counsel, eHealth Initiative

Alice is a health regulatory lawyer with a specialty in health information privacy law and policy. She previously worked as a Senior Associate at the law firm Hogan Lovells, where she worked with clients on Medicare and Medicaid pricing and reimbursement. Alice spent several years as policy counsel at two different non-profit organizations, the National Partnership for Women & Families and the Center for Democracy & Technology. She currently sits on the DC HIE Policy Board, as well as the boards of Beauvoir School, Educare DC, and DC Greens, the latter of which she chairs. She received her B.A. in human biology from Stanford University and her J.D. from the Georgetown University Law Center. Alice and her husband, Michael, live in Washington, D.C. with their four children.​

Artificial Intelligence Is Not Ready For The Intricacies Of Radiology​

Radiology is one of the most essential fields in clinical medicine. Experts in this field are specialists in deciphering and diagnosing disease based on various imaging modalities, ranging from ultrasound, magnetic resonance imaging (MRI), computerized tomography (CT), and x-rays. Studies have shown that the use of radiology in clinical practice has exponentially grown over the years: at the Mayo Clinic, between the years 1999 to 2010, use of CT scans increased by 68%, MRI use increased by 85%, and overall use of imaging modalities for diagnostic purposes increased by 75%, all numbers that have likely continued to rise, and indicate the sheer demand and growth of this robust field.

A unique proposal that has become prominent over the last few years to help alleviate this increased demand is the introduction of artificial intelligence (AI) technology into this field. Simply put, the premise of AI as an addition to the practice of radiology is straightforward, and has been envisioned in two main ways: 1) a system that can be programmed with pre-defined criteria and algorithms by expert radiologists, which can then be applied to new, straightforward clinical situations, or 2) deep learning methods, where the AI system relies on complex machine learning and uses neural-type networks to learn patterns via large volumes of data and previous encounters; this can then be used to interpret even the most complicated and abstract images.

However, while much of the theoretical basis for AI in the practice of radiology is extremely exciting, the reality is that the field has not yet fully embraced it. The most significant issue is that the technology simply isn’t ready, as many of the existing systems have not yet been matured to compute and manage larger data sets or work in more general practice and patient settings, and thus, are not able to perform as promised. Other issues exist on the ethical aspects of AI. Given the sheer volume of data required to both train and perfect these systems, as well as the immense data collection that these systems will engage in once fully mainstream, key stakeholders are raising fair concerns and the call for strict ethical standards to be put into place, simultaneous to the technological development of these systems.

The full Forbes article can be viewed at this link.  

Precision global health for real-time action

Precision global health, augmented with artificial intelligence, has the potential to address transnational problems (eg, outbreaks of emerging infectious diseases, diabetes, addictions, ageing, or mental health) and deliver targeted and effective interventions through integrated approaches which combine life sciences, social sciences, and data sciences with public support. More than half the global population are connected to the Internet, mainly through mobile phones, and several countries in sub-Saharan Africa are leading the annual growth of active mobile social users with over 17% in 2018. Thus, the role of local populations and civil society is more important than ever, to identify challenges and work together to address some of the most pressing global health issues and sustainable development.

The full commentary can be downloaded below.  

AI: Pharma's Perfect Medicine

AI appears set to be the thing that separates the next generation of business success stories and market dropouts. It has revolutionized the transportation industry by bringing the science fiction dream of autonomous cars into reality, as driverless taxis have already been tested and deployed in the U.S.

Further indicators of its importance come from finance companies like Goldman Sachs, JPMorgan and Morgan Stanley — all of which have aggressively expanded their data and tech teams over the past year — looking to deploy AI projects that will give them the competitive edge against their rivals. The application of this technology ranges from the mundane to the absurd, seemingly with no sector able to escape its influence — and the pharma industry is no different.

The full Forbes article can be viewed at this link.