Health Law Advisor

Announced in the Consolidated Appropriations Act of 2021, Rural Emergency Hospitals (REHs) will be a new type of Medicare provider starting January 1, 2023.  REHs are meant to help address the stressed health care system of rural providers by providing an option to closure for distressed critical access hospitals (CAHs) and small rural hospitals.

Existing CAHs and rural hospitals with fewer than 50 beds will be eligible to convert to an REH.  CMS is streamlining this process so that this conversion to be an REH can be accomplished through a change of information on an existing Medicare 855A enrollment rather than through a new provider application, which carries potentially significant delays and potential gaps in payment.  REHs are designed to provide primarily emergency department, observation, and outpatient services.  Because REHs will not provide inpatient care, an area that often creates a significant financial and operational burden on CAHs and small rural hospitals, REHs will allow locally-delivered healthcare to continue to be furnished by existing providers.

The motivation for this month’s post was my frustration with the techniques for searching the FDA’s 510(k) database.  Here I’m not talking about just using the search feature that FDA provides online. Instead, I have downloaded all of the data from that database and created my own search engine, but there are still inherent limitations in what the data contain and how they are structured.  For one, if you want to submit a premarket notification for an over-the-counter product, it really isn’t easy to find predicates that are specifically cleared for over-the-counter without a lot of manual work.

To see if I could find an easier way, I decided to use the database FDA maintains for unique device identifiers, called the Global Unique Device Identification Database (GUDID).  You can search that database using the so-called AccessGUDID through an FDA link that takes you to the NIH where the database is stored. That site only allows for pretty simple search, so for what I needed to do, I downloaded the entire database so I could work directly on the data myself.

While the UDI database is enormous at this juncture (over 3 million products), what I found left me with questions about just how comprehensive and complete the data are.  At the same time, it seems like a good way to supplement the information that can be gleaned from the 510(k) database.

In September of this year, New York City Councilwoman Julie Menin announced her plan to introduce a series of bills that would create further price transparency requirements for hospitals, with noncompliance resulting in high financial penalties.

The bill package would create an office of hospital accountability that would inform the public as to how much hospitals are charging for various services via a price transparency information portal, where hospitals would be required to provide certain key pricing information to the public. Currently, such pricing data is not typically available for public access, and patients typically have little knowledge regarding how much they will be charged for services.

It has been four years since Congress enacted the Eliminating Kickbacks in Recovery Act (“EKRA”), codified at 18 U.S.C. § 220. EKRA initially targeted patient brokering and kickback schemes within the addiction treatment and recovery spaces. However, since EKRA was expansively drafted to also apply to clinical laboratories (it applies to improper referrals for any “service”, regardless of the payor), public as well as private insurance plans and even self-pay patients fall within the reach of the statute.

Building on attempts in recent years to strengthen the Department of Justice’s (DOJ’s) white collar criminal enforcement, on September 15, 2022, Deputy Attorney General Lisa Monaco announced revisions to DOJ’s corporate criminal enforcement policies. The new policies, and those that are in development, further attempt to put pressure on companies to implement effective compliance policies and to self-report if there are problems. Notably, the new DOJ policies set forth changes to existing DOJ policies through a “combination of carrots and sticks – with a mix of incentives and deterrence,” with the goal of “giving general counsels and chief compliance officers the tools they need to make a business case for responsible corporate behavior” through seven key areas:

Over the spring and summer, I did a series of posts on extracting quality information from FDA enforcement initiatives like warning letters, recalls, and inspections.  But obviously FDA enforcement actions are not the only potential sources of quality data that FDA maintains.  FDA has what is now a massive data set on Medical Device Reports (or “MDRs”) that can be mined for quality data.  Medical device companies can, in effect, learn from the experiences of their competitors about what types of things can go wrong with medical devices.

The problem, of course, is that the interesting data in MDRs is in what a data scientist would call unstructured data, in this case English language text describing a product problem, where the information or insights cannot be easily extracted given the sheer volume of the reports.  In calendar year 2021, for example, FDA received almost 2 million MDRs.  It just isn’t feasible for a human to read all of them.

That’s where a form of machine learning, natural language processing, or more specifically topic modeling, comes in.  I used topic modeling last November for a post about major trends over the course of a decade in MDRs.  Now I want to show how the same topic modeling can be used to find more specific experiences with specific types of medical devices to inform quality improvement.

In this episode of the Diagnosing Health Care Podcast:  While the COVID-19 pandemic seems to be moving into our rearview mirror, government investigations and enforcement actions targeting COVID-19-related fraud are just starting to heat up.

What can businesses do to prevent or mitigate potential civil and criminal charges in this area?

The California Consumer Privacy Act (CCPA) and the California Privacy Rights Act (CPRA) gives consumers increasingly more control over their personal information when collected by businesses subject to the law. We have previously discussed the compliance requirements of these data privacy laws on organizations doing business in California.[1] Significantly, CCPA/CPRA defines the term “consumer” to mean any California resident; which from a business perspective, such a broad definition encompasses not only the business’s individual customers, but also its employees, job-applicants or even business-to-business (B2B) contacts.  With the moratoriums currently in place for B2B and employee/applicant data sunsetting on January 1, 2023 and not likely to be extended, and the prospect for federal data privacy legislation with wide preemptive effect of state law looking less likely, businesses should be actively preparing to meet these expanded statutory obligations.

A private equity client asked us recently to assess a rumor that FDA was on the warpath in enforcing the 510(k) requirement on medical devices from a particular region.  Such a government initiative would significantly deter investments in the companies doing the importing.  Turns out, the agency was not.  The FDA’s recent activities in the region were well within their historical norms.

But the project got us thinking, what does the agency’s enormous database on import actions tell us about the agency’s enforcement priorities more generally?  There are literally thousands of ways to slice and dice the import data set for insights, but we picked just one as an example.  We wanted to assess, globally, over the last 20 years, in which therapeutic areas has FDA been enforcing the 510(k) requirement most often?

From the Diagnosing Health Care Podcast:  How have complaints of information blocking been submitted to the Office of the National Coordinator (ONC), and by whom? What does government enforcement action really look like?

In this episode of our special series on interoperability, hear from ONC attorneys Cassie Weaver and Rachel Nelson.