BOSTON, March 10, 2020 - Orion Health has developed the first comprehensive pandemic outbreak monitoring platform to alleviate demand on health systems and reduce the risk of further spread of the COVID-19 virus. The Orion Health software that supports this will be offered at no cost to existing and future customers.

As the number of confirmed COVID-19 cases grow globally, especially in those countries currently in the community outbreak phase of the disease, there will be a need for more people to receive support at home. Read the full press release at the link below. 

Trump rules let patients download health records to their phones

The Trump administration on Monday unveiled its plan to make it easier for patients to download their own health and insurance records to their smartphones — an effort that's triggered privacy concerns from some of the biggest health care trade groups and intense lobbying from the tech industry.

The rules force insurers and hospitals to make patients' information easily shareable using common data standards. Trump health officials on Monday framed the rules as a way to give patients — instead of health care providers, health records companies and insurers — control over health data.

The full Politico article can be viewed at this link.  

A Nod To The Past Can Help Define Healthcare's Future

In 1970, healthcare spending represented 6.9% of U.S. GDP. Last year, findings from Centers for Medicare & Medicaid Services showed healthcare spending in the U.S. was expected to reach $3.8 trillion, representing 17.8% of GDP. It’s a sobering figure, and one that is only expected to rise during the coming years. Managing this spending is central not only for the health of the industry, but also for the U.S. economy.

For decades, the healthcare industry operated on a fee-for-service model. Costs soared in large part due to inefficiencies in the supply chain and care delivery related to this volume-based model. As a result, the U.S. is known for spending much more on healthcare than other countries, while delivering lower quality outcomes than many other developed countries.

Moving to a value-based care model could fundamentally shift how the healthcare industry conducts business. The industry would no longer support reimbursement based on volume, but instead, on value. Value in healthcare has been defined as "the outcomes that matter to patients and the costs to achieve those outcomes."

The full Forbes article can be viewed at this link.  

Diet, nutrition, and cancer risk: what do we know and what is the way forward?

Scientists have suspected for decades that nutrition has an important influence on the risk of developing cancer. Epidemiological studies as early as the 1960s showed that cancer rates varied widely between populations and that cancer rates in migrants moving from low to high risk countries could rise to equal or sometimes exceed the rates in the host population. These observations implied the existence of important environmental causes of cancer, and other studies showed strong correlations between many types of cancer and dietary factors; for example, countries with high intakes of meat had high rates of colorectal cancer. Furthermore, experiments in animals showed that cancer rates could be altered by manipulating diet, with compelling evidence that restricting energy intake causes a general reduction in cancer development. 

Cancer is predicted to be the leading cause of death in every country of the world by the end of this century. Although dietary factors are thought to be important in determining the risk of developing cancer, establishing the exact effects of diet on cancer risk has proved challenging. Here we describe the relatively few dietary factors that clearly influence risk of cancers along the digestive tract (from top to bottom) and of other common types of cancer, as well as challenges for future research.

The full article can be downloaded below.  

Why you’re more likely to see a physician assistant than a doctor

Dr. Aziz Nazha, the oncologist in charge of the Cleveland Clinic’s Center for Clinical Artificial Intelligence, has a controversial opinion about what kind of training the next generation of doctors should undergo. “Physicians of the future should know how to program,” he said, “but I know I won’t win that battle.”

The fact that there are even discussions about whether coding should be a requirement of medical school is just one of the many changes at hand for the millions of clinicians who make up the U.S. health care workforce.

Not only are there predicted shortages of nurses and physicians that are expected to worsen over the next decade, industry attempts to shift from a fee-for-service reimbursement model to a value-based system have called for more efficient clinicians and better care for patients.

At the same time, hospitals are increasingly turning to artificial intelligence tools like chatbots and digital scribes and machine-learning models that aim to predict readmission rates and examine mammograms for breast cancer. (Even the tech giants are starting to dabble in health care. Apple Inc. is trying to improve nursing workflow, while Alphabet Inc.’s Google is testing whether digital voice assistants can reduce the amount of time doctors spend entering patient information into the electronic health record.)

All of these trends are influencing how care is delivered and by what kind of clinician. In the exam room of the future — which may be your living room — the doctor may ask about your feelings or know how to code, a physician assistant may be virtual or human, and a nurse may be assisted by a robot.

The full MarketWatch article can be viewed at this link.  

AI was supposed to save health care. What if it makes it more expensive?

Last year, Mount Sinai Hospital switched on an artificial intelligence program to search the hospital’s records for evidence of malnourished patients in its wards. The numbers it turned up were eye-popping: 20 percent more cases were diagnosed than in the previous year.

Around the same time, Barbara Murphy, chief of the renowned health system’s department of medicine, was helping to develop another AI program, to predict whether diabetic patients are at near-term risk of kidney disease and to help prioritize specialist visits for those who are. One of the early findings, according to Murphy: “We probably need some more nephrologists.”

As hospital systems around the country unleash machine learning algorithms — computer models that function like millions of unblinking eyes inspecting patient records — such findings are becoming more common. The algorithms, deployed in hospitals over the past couple of years, are often designed to help locate the sickest patients, but in some cases, they also provide more opportunities to bill.

The full Politico article can be viewed at this link.  

Six Healthcare Trends To Watch For 2020

As we begin the new decade, I'd like to talk about six major healthcare industry trends that I'm most excited about in 2020.

1. AI-Powered Tools To Increase Efficiency
2. Using The Cloud To Break Down Silos And Move Data Faster
3. Ensuring Patient Consent In The Big Data Era
4. Virtual Solutions For Busy Medical Professionals
5. Demystifying Healthcare Data For Patients
6. Home-Based Healthcare

The full Forbes article can be viewed at this link.  

'Fixing health care' is a disservice to society

We all know — and the presidential candidates keep reminding us at every debate and in the run-up to Super Tuesday — that our health care system is struggling to provide Americans with affordable care. While we broadly agree that health care needs to be fixed, the conversation on “how” is headed down the wrong path. Instead of looking for solutions to patch up the current system, we should think anew for higher efficiencies, lower costs and, most importantly, better outcomes.  

We should start by asking how we use existing and emerging technologies to invent a preventive, proactive, predictive, and personalized self-care system that delivers tenfold cost-effectiveness enhancements. How do we seize the new economics of a tech-enabled national health care system? Many of the tools needed to affect this transformation are now available; others are rapidly evolving. Health care policymakers need to focus on cultivating and rapidly incorporating a new tech-enabled paradigm of health management while phasing out the old.  

The full opinion piece from The Hill can be viewed at this link.  

Implications of artificial intelligence for medical education

Although digital health has occasioned huge changes for medicine, the issues it provokes have yet to be integrated into teaching and learning across the medical education continuum. This question is all the more pressing given that the rise of artificial intelligence (AI) systems, discussed here as a specific example of healthcare’s digitalisation, are associated with a fundamental paradigm shift in teaching. Whereas 20th-century medical education models relied on experimental results evolving into a recognised standard that then informed textbook teaching, today this sequencing no longer holds. The speed at which new health AI technologies are developing, being introduced into clinical practice, and being used by patients requires equipping doctors to deal appropriately with experimental techniques that have not yet become part of a generally accepted body of knowledge. Agile teaching and educated guesswork about which treatments will benefit patients the most are crucial for enabling physicians to lead the introduction of such technologies without simply being forced to react to them.

The full comment can be downloaded below.  

Nurturing the digital baby: Open innovation for development and optimization

The primary aim around developing and optimizing an electronic health record is to improve patient care and population health. The objective of this study is to design and evaluate an action research approach for the optimization of the design of a summary page artefact within an electronic health record for newborn healthcare. An action research approach was chosen for its participatory democratic process for developing practical knowledge and solutions. Collaborative workshops lead by an independent graphic facilitator with a ‘bottom up’ approach, involving self-selected motivated members from multidisciplinary healthcare teams, were designed and conducted. To evaluate this approach, insights were drawn from behavioural and design science paradigms to demonstrate that knowledge and understanding of the design problem and its solution were acquired in building the optimized summary page artefact. Information system development for healthcare requires consideration not just of what we do but how and why we do things. Our analysis demonstrates that action design research represents an agile and lean approach for successful optimization and implementation of information system development in healthcare.

The full article can be viewed at this link.