Industry Watch – Jan/Feb 2019

Jan. 30, 2019
Recent news from around the world of health IT

Policy & Value-Based Care

CMS Finalizes Overhaul of Medicare ACO Program

The Centers for Medicare & Medicaid Services (CMS) recently published a final rule that makes sweeping changes to the Medicare Shared Savings (MSSP) accountable care organization (ACO) program, with the goal to push Medicare ACOs more quickly into two-sided risk models.

Referred to as “Pathways to Success,” the Trump Administration’s overhaul of Medicare’s ACO program will redesign the program’s participation options by removing the traditional three tracks in the MSSP model and replacing them with two tracks that eligible ACOs would enter into for an agreement period of no less than five years: the BASIC track, which would allow eligible ACOs to begin under a one-sided model and incrementally phase in higher levels of risk; and the ENHANCED track, which is based on the program’s existing Track 3, providing additional tools and flexibility for ACOs that take on the highest level of risk and potential rewards. At the highest level, BASIC ACOs would qualify as an Advanced Alternative Payment Model (APM) under the Quality Payment Program.

The MSSP program launched in 2012 and currently over 10.4 million beneficiaries in fee-for-service Medicare, of the 38 million total fee-for-service beneficiaries, receive care from providers participating in a Medicare ACO, according to CMS.

According to CMS, data on ACO performance shows that over time ACOs taking accountability for costs perform better than those that do not. As a result of the changes, CMS estimates projected savings to Medicare totaling $2.9 billion over ten years.

The Pathways to Success program redesign reduces the amount of time that an ACO can remain in the program without taking accountability for healthcare spending from six years to two years for new ACOs and three years for new “low revenue” (physician-led) ACOs, including some rural ACOs.

As part of the final rule, CMS also finalized a higher initial shared savings rate of 40 percent for one-sided risk ACOs, after initially proposing to cut potential shared savings in half—from 50 percent to 25 percent for one-sided risk ACOs. The shared savings rate for two-sided risk ACOs will remain at 50 percent under this final rule.


CISO-Led Initiative Targets Third-Party Risk

An industry-wide effort, led by healthcare chief information security officers (CISOs), to establish a standardized method to assess the risk management posture of third-party suppliers is gaining momentum and support from healthcare security leaders.

A group of CISOs from several healthcare organizations established the Provider Third-Party Risk Management (TPRM) Initiative back in August with the aim of improving risk management for providers and efficiencies for third parties.

The founding member organizations for the Provider TPRM Council include Allegheny Health Network, Cleveland Clinic, University of Rochester Medical Center, UPMC, Vanderbilt University Medical Center and Wellforce/Tufts University. Working with HITRUST and PwC, the Council aims to bring uniformity and consistency to the process while also reducing the burden on providers and third parties.

According to founding participants of the Provider TPRM Council, the initiative and its growing number of participants are adopting a consistent approach that address the issues affecting information security-related risks in their organization’s supply chain and safeguarding patient safety and information.

One of the goals of the initiative is to address the inefficiencies found in the third-party supply chain ecosystem. By reducing the multiple audits and questionnaires, the financial savings will allow business partners to invest in substantive risk reduction efforts and not redundant assessments.

Digital Health

FDA Commissioner Outlines Next Steps for Pre-Cert Digital Health Pilot Program

The U.S. Food and Drug Administration (FDA) has drafted a regulatory framework to test new approaches for the review of digital health device applications.

The purpose of FDA’s Software Pre-Cert pilot is to leverage customer input to develop a program that can help reduce the time and cost of market entry for software developers that FDA determines reliably manufacture high-quality, safe and effective digital health devices while providing appropriate patient safeguards, the agency said at the time.

More recently, FDA Commissioner Scott Gottlieb, M.D., announced that based on the Pre-Cert pilot, the FDA has drafted a regulatory framework. “Our goal in piloting the Pre-Cert Program was to support the development of new technologies that are frequently updated, as well as to learn from software developers about the unique nature of their products,” Gottlieb stated. “Our aim has been to develop a Pre-Cert program that would allow developers who have been assessed by the FDA for meeting specific excellence principles—known as an ‘Excellence Appraisal’—to participate in a more tailored premarket submission process appropriate for their specific type of digital device.”

Commentary—Don’t Get Left Behind: Important Steps to Take in Healthcare’s Transformation

We are at the onset of a healthcare transformation, and the catalyst is hidden in the data

By Florian Quarre, Chief Digital Officer, Ciox

Across the healthcare continuum, organizations are looking at health data as the catalyst set to power advances toward ambitious, digital and data-driven futures. For care providers, the future could include better care and qualitative outcomes by improved diagnosis and historical insights at a population level. For health insurance companies, better data and analysis means more accurate risk adjustment and improved population health measures. For universities and other life science organizations, better data means faster, tailored cures, and world-changing breakthroughs.

And that’s just the beginning.

Much in the way of health data may soon be generated and shared by patients themselves. From wearable health technology to diagnosis-giving mobile apps, users increasingly expect access to their own health information, and are looking for new and innovative ways to deploy that data.

Leading health information companies are beginning to look more like technology companies as they unlock once siloed health data sets and gain critical intelligence for payers, providers and life science organizations. It’s a simple effort on the surface, with endless complexity in execution—create more analysis-ready electronic medical records (EMRs). The first step—and this is exactly how organizations can stay ahead of impending transformations in healthcare—is to ensure that interoperable, liquid datasets are being generated and shared throughout healthcare organizations.

Today, most of the data created by patient/provider exchanges exists in the form of EMRs aggregated and housed at one of the many EMR companies that populate the health information management industry. The records are, by virtue of the countless record-keeping standards in provider offices, functionally illiquid. Some are PDFs of pen and paper notes, many are simply faxed pieces of paper in a file. When a change agent with groundbreaking technology attempts to access broad, population-sized data sets, they first must meet the challenge of bringing structure to the data. There’s also a high degree of variability between coding styles.

These advances are only now becoming a reality. Utilizing AI (artificial intelligence)—specifically computer vision, natural language processing and machine learning—health data companies on the cutting edge are creating standardized, unified smart charts housed in large, searchable data vaults to create longitudinal patient records that are at once interoperable and executable.  These newly fashioned electronic medical records are the kinds of data inputs that doctors need to gain complete visit-specific patient overviews, or that insurance companies need to get big picture analytics running on their populations, or that universities can use to run longitudinal population-based studies. They are scalable. They are complete.

In turn, these are the datasets that future AI models can really sink their teeth into. A future AI health agent could, for instance, provide automated medical diagnosis from a series of symptoms, spot behavioral traits suggesting depression, or identify if an individual is at risk for cardiovascular disease. One day soon, AI health agents could be deployed onto a blockchain-driven network to seek out patterns that look like cancer on a unified set of health records, or to highlight how an under-publicized treatment protocol might just be a cure to a target patient’s cohort.

Aggregating liquid datasets makes it easier to find others with similar diseases or patterns, and to identify which treatment methodologies are working for patient populations across the world.

The beauty in the systems that are here today—like health information companies driving AI and machine learning to create better and more liquid smart charts, and those coming soon, like AI-powered health agents crawling the blockchain in search of red flags—is that all of it will create a flywheel effect of data and intelligence. While at first it may be hard to see each industry revolution through, as each silo falls and each revolution of the wheel passes, it builds momentum and makes the next revolution that much easier to achieve.

We are at the onset of a healthcare transformation, and the catalyst is hidden in the data. Every organization in healthcare should future-proof itself today by ensuring the data it creates, the data it utilizes, and the data it shares are smart, interoperable and executable. They are liquid. Because when the day in the near future comes that the tipping point is reached, the dust will settle on major, sweeping changes in how healthcare is delivered, and the biggest players in the healthcare industry will be those who understand how to mine the gold inside their data.

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