RAND researchers estimated the effects that four proposed out-of-network payment limits for hospital care—125 percent of Medicare payments (a strict limit), 200 percent of Medicare payments (a moderate limit), state average payment by private plans (a moderate limit), and 80 percent of average billed charges (a loose limit)—would have on negotiated in-network prices and total payments for hospital care. These four scenarios reflect the variation in base measure (traditional Medicare, market price, and charges) and payment generosity among existing policy proposals.
Competitor’s Veto: State Certificate of Need Laws Violate State Prohibitions on Monopolies | Regulatory Transparency ProjectMarch 10, 2020
CON laws, after all, violate a host of constitutional provisions, including the anti-monopoly clauses found in several state constitutions. Enabling existing providers to use the law to bar others from entering an industry or offering a service is the very definition of a government-created monopoly. Few state courts have so far directly addressed whether CON laws violate state anti-monopoly clauses, but several have noted that they are inherently anticompetitive. Although this paper discusses how CON laws are designed to function in precisely the way prohibited by state constitutions.
When a provider doesn’t submit an MPRA for a Medicaid-covered pregnant patient in Baltimore, her child is five times more likely to die before birth or in the first year of life than babies whose providers submit the form, according to an analysis by the Baltimore City Health Department.
The legal argument against certificate of need is quite simple: The North Carolina Constitution bans monopolies, and the CON law effectively creates and preserves a monopoly by making it difficult or outright impossible for competitors to open a business.“
The effect of the MRI-CON requirement is to prevent [Singh] from acquiring a fixed MRI scanner to provide safe, quality, affordable MRI scans to patients who need them, solely because incumbent providers got there first,” the lawsuit on Singh’s behalf alleges. “Therefore, the MRI-CON requirement, both on its face and as applied, grants certain health care providers a monopoly in violation… of the North Carolina Constitution.”
Singh’s lawyers also argue the law violates their client’s equal protection rights and his right to earn a living as guaranteed by the state Constitution.
Prices for Medical Services Vary Within Hospitals, But Vary More Across Them by Nathan Wilson, Ted Rosenbaum, Matthew Panhans :: SSRNJanuary 2, 2019
Using commercial claims for 2012-2013 from Colorado’s All-Payer Claims Database, we examine how medical service prices vary for five hospital-based procedures and the complexity adjusted inpatient price. We find that prices vary substantially in multiple dimensions. Our analysis indicates that there is significant price variation across payers for the same service in the same hospital. If prices converged to the lowest rate each hospital receives, commercial expenditures would fall by 10-20%. The share of overall price variation accounted for by hospitals variation tends to be even more substantial. For four out of six prices, we find that differences associated just with hospitals’ metropolitan areas account for over 45% of the total variation. We observe substantial residual variation (17-50%) after accounting for factors specific to a given payer or provider.
Predictive analytics and “big data” are emerging as important new tools for diagnosing and treating patients. But as data collection becomes more pervasive, and as machine learning and analytical methods become more sophisticated, the companies that traffic in health-related big data will face competitive pressures to make more aggressive claims regarding what their programs can predict. Already, patients, practitioners, and payors are inundated with claims that software programs, “apps,” and other forms of predictive analytics can help solve some of the health care system’s most pressing problems. This article considers the evidence and substantiation that we should require of these claims, focusing on “health” claims, or claims to diagnose, treat, or manage diseases or other medical conditions. The problem is that three very different paradigms might apply, depending on whether we cast predictive analytics as akin to medical products, medical practice, or merely as medical information. Because big data methods are so opaque, its claims may be uniquely difficult to substantiate, requiring a new paradigm. This article offers a new framework that considers intended users and appropriate evidentiary baselines.
This article examines the possible constructs behind the announcement by Amazon, Berkshire Hathaway, and JPMorgan Chase & Co., that they are jointly building a new healthcare entity for their employees. The article provides context by discussing and comparing the healthcare ambitions of the three largest information technology companies and argues that various forms of hybrid entities will increase their footprint in healthcare data and delivery. The core of the article is a thought experiment about the nature of what the article terms “Prime Health.” That analysis is based initially on observations about Amazon’s existing culture and business model of Amazon. Thereafter the article examines both what Prime Health could and should be, arguing that it will go beyond the pedestrian model of a very large self-funded group insurance plan, will disintermediate traditional healthcare insurers, and attempt to bring consumers and healthcare providers together into some type of online marketplace; an updated, privatized version of managed competition. The final parts of the article deal with the regulatory environment that hybrid healthcare generally and Prime Health in particular will face. The analysis includes federal device and data protection laws, some idiosyncratic state laws, and a brief discussion of the problems inherent in the limited regulation of hybrid healthcare entities.