Google’s semi-secret deal with Ascension is testing the limits of HIPAA as society grapples with the future impact of machine learning and artificial intelligence.
Glenn Cohen points out that HIPAA may not be keeping up with our methods of consent by patients and society on the ways personal data is used. Is prior consent, particularly consent from vulnerable patients seeking care, a good way to regulate secret commercial deals with their caregivers? The answer to a question is strongly influenced by how you ask the questions.
Here’s a short review of this current and related scandals. It also links to a recent deal between Mayo and Google, also semi-secret. A scholarly investigative journalism report of the Google AI scandal with London NHS Foundation Trust in 2016 might be summarized as: the core issue is not consent; it is a conflict of interest at the very foundation of the information governance process. The foxes are guarding the patient data henhouse. When the secrecy of a deal is broken, a scandal ensues.
The parts of the Google-Ascension deal that are secret are likely designed to misdirect attention away from the intellectual property value of the business relationship.
Say the word “shortage” to a healthcare professional and chances are the first thing that will come to mind is drug shortages. With good reason, too – there are more than 100 drugs currently at risk or not readily available for U.S. hospitals, according to the Food and Drug Administration’s (FDA) drug shortage list.
Shortages don’t just apply to drugs, however, and as 2019 has shown, healthcare providers must become more focused on shortages of the medical device variety. The shutdown of multiple medical device sterilization facilities in 2019 is poised to jeopardize the availability of devices that are critical to routine patient care. On Nov. 6, the FDA is hosting a panel to hear from stakeholders, including hospital epidemiologists and healthcare supply chain experts, on the risks associated with facility shutdowns and potential action steps.
The industry as a whole is in need of meaningful solutions. As taxpayers, patients and key stakeholders in healthcare, we must collaborate to eliminate interruptions to our healthcare supply chain. For those invested in improving healthcare from the inside, this means working across competitive boundaries and borrowing best practices from sister industries as we work to identify the root cause of these issues and provide meaningful and preventative solutions.
The Oct. 22 announcement starts with: “U.S. Sens. Mark R. Warner (D-VA), Josh Hawley (R-MO) and Richard Blumenthal (D-CT) will introduce the Augmenting Compatibility and Competition by Enabling Service Switching (ACCESS) Act, bipartisan legislation that will encourage market-based competition to dominant social media platforms by requiring the largest companies to make user data portable – and their services interoperable – with other platforms, and to allow users to designate a trusted third-party service to manage their privacy and account settings, if they so choose.”
Although the scope of this bill is limited to the largest of the data brokers (messaging, multimedia sharing, and social networking) that currently mediate between us as individuals, it contains groundbreaking provisions for delegation by users that is a road map to privacy regulations in general for the 21st Century.
The bill’s Section 5: Delegation describes a new right for us as data subjects at the mercy of the institutions we are effectively forced to use. This is the right to choose and delegate authority to a third-party agent that can manage interactions with the institutions on our behalf. The third-party agent can be anyone we choose subject to their registration with the Federal Trade Commission. This right to digital representation by an entity of our choice with access to the full range of our direct control capabilities is unprecedented, as far as I know.
In a previous post, I described how some features of the Affordable
Care Act, despite the best intentions, have made it harder or even impossible
for many plans to compete against dominant players in the individual and small
employer markets. This has undermined aspects of the ACA designed to improve
competition, like the insurance exchanges, and exacerbated a long
term trend toward consolidation and reduced choice, and there is evidence it
is resulting in higher costs. I focused on the ACA’s risk adjustment program
and its impact on the small group market where the damage has been greatest.
The goal of risk adjustment is commendable: to create
stability and fairness by removing the ability of plans to profit by “cherry
picking” healthier enrollees, so that plans instead compete on innovative
services, disease management, administrative efficiency, and customer support.
But in the attempt to find stability, the playing field was tilted in favor of
plans with long-tenured enrollment and sophisticated operations to identify all
scorable health risks. The next generation of risk adjustment should truly even
out the playing field by retaining the current program’s elimination of an
incentive to avoid the sick, while also eliminating its bias towards incumbency
and other unintended effects.
One important distinction concerns when to use risk
adjustment to balance out differences that arise from consumer preferences. For
example, high deductible plans tend to attract healthier enrollees, and without
risk adjustment these plans would become even cheaper than they already are,
while more comprehensive plans that attract sicker members would get
disproportionately more expensive, setting off a race to the bottom that pushes
more and more people into the plans that have the least benefits, while the
sickest stay behind in more generous plans whose premium cost spirals upward. Using
risk adjustment to counteract this effect has been widely beneficial in the
individual market, along with other features like community rating and
However, in other cases where risk levels between plans differ
due to consumer preferences it may not be helpful. For example, it has been
documented that older and sicker members have a greater aversion to change (changing
plans to something less familiar) and to constraints intended to lower cost
even if they do not undermine benefit levels or quality of care, like narrow networks.
These aversions tend to make newer plans and small network plans score as
healthier. Risk adjustment would then force those plans to pay a penalty that in
turn forces enrollees in the plans to pay for the preferences of others.
It is not wise for Democrats to spend all their energy
debating Single Payer health care solutions.
None of their single player
plans has much chance to pass in 2020, especially under the limited
reconciliation process. In the words of Ezra Klein, “If Democrats don’t have a
plan for the filibuster, they don’t really have a plan for ambitious health
Yet while we debate Single Payer – or, even if it somehow
passed, wait for it to be installed — millions of persons are still hurting
under our current system.
We can help these people now!
Here are six practical programs to create a better ACA.
Taken all together they should not cost more than $50
billion a year. This is a tiny fraction of the new taxes that would be needed
for full single payer. This is at least negotiable, especially if Democrats can
take the White House and the Senate.
With each passing year, the Affordable Care Act becomes
further entrenched in the American health care system. There are dreams on both
the far left and far right to repeal and replace it with something they see as
better, but the reality is that the ACA is a remarkable achievement which will
likely outlast the political lifetimes of those opposing it. Future
improvements are more likely to tweak the ACA than to start over from scratch.
A critical part of making the ACA work is for it to support
healthy, competitive and fair health insurance markets, since it relies on them
to provide health care benefits and improve access to care. This is
particularly true for insurance purchased by individuals and small employers,
where the ACA’s mandates on benefits, premiums and market structure have the
most impact. One policy affecting this dynamic that deserves closer attention
is risk adjustment, which made real improvements in the fairness of these
markets, but has come in for accusations that it has undermined competition.
Risk adjustment in the ACA works by compensating plans with
sicker than average members using payments from plans with healthier members.
The goal is to remove an insurer’s ability to gain an unfair advantage by
simply enrolling healthier people (who cost less). Risk adjustment leads insurers
to focus on managing their members’ health and appropriate services, rather
than on avoiding the unhealthy. The program has succeeded enormously in bringing
insurers to embrace enrolling and retaining those with serious health
This is something to celebrate, and we should not go back to
the old days in which individuals or small groups would be turned down for
health insurance or charged much higher prices because they had a history of
health issues. However, the program has also had an undesired effect in many states:
it further tilted the playing field in favor of market dominant incumbents.
Medicare Payment Advisory Commission (MedPAC) and other proponents of the
Hospital Readmissions Reduction Program (HRRP) justified their support for the
HRRP with the claim that research had already demonstrated how hospitals could
reduce readmissions for all Medicare fee-for-service patients, not just
for groups of carefully selected patients. In this three-part series, I am
reviewing the evidence for that claim.
We saw in Part I and Part II that the research MedPAC cited in its 2007 report to Congress (the report Congress relied on in authorizing the HRRP) contained no studies supporting that claim. We saw that the few studies MedPAC relied on that claimed to examine a successful intervention studied interventions administered to carefully selected patient populations. These populations were severely limited by two methods: The patients had to be discharged with one of a handful of diagnoses (heart failure, for example); and the patients had to have characteristics that raised the probability the intervention would work (for example, patients had to agree to a home visit, not be admitted from a nursing home, and be able to consent to the intervention).
In this final installment, I review the research cited by the Yale New Haven Health Services Corporation (hereafter the “Yale group”) in their 2011 report to CMS in which they recommended that CMS apply readmission penalties to all Medicare patients regardless of diagnosis and regardless of the patient’s interest in or ability to respond to the intervention. MedPAC at least limited its recommendation (a) to patients discharged with one of seven conditions/procedures and (b) to patients readmitted with diagnoses “related to” the index admission. The Yale group threw even those modest restrictions out the window.
The Yale group recommended what they called a “hospital-wide (all-condition) readmission measure.” Under this measure, penalties would apply to all patients regardless of the condition for which they were admitted and regardless of whether the readmission was related to the index admission (with the exception of planned admissions). “Any readmission is eligible to be counted as an outcome except those that are considered planned,” they stated. (p. 10)  The National Quality Forum (NQF) adopted the Yale group’s recommendation almost verbatim shortly after the Yale group presented their recommendation to CMS.
In their 2007 report, MedPAC offered these examples of related and unrelated readmissions: “Admission for angina following discharge for PTCA [angioplasty]” would be an example of a related readmission, whereas “[a]dmission for appendectomy following discharge for pneumonia” would not. (p. 109) Congress also endorsed the “related” requirement (see Section 3025 of the Affordable Care Act, the section that authorized CMS to establish the HRRP). But the Yale group dispensed with the “related” requirement with an astonishing excuse: They said they just couldn’t find a way to measure “relatedness.” “[T]here is no reliable way to determine whether a readmission is related to the previous hospitalization …,” they declared. (p. 17) Rather than conclude their “hospital-wide” readmission measure was a bad idea, they plowed ahead on the basis of this rationalization: “Our guiding principle for defining the eligible population was that the measure should capture as many unplanned readmissions as possible across a maximum number of acute care hospitals.” (p. 17) Thus, to take one of MedPAC’s examples of an unrelated admission, the Yale group decided hospitals should be punished for an admission for an appendectomy within 30 days after discharge for pneumonia. 
Robust exchange of health information is absolutely critical to improving health care quality and lowering costs. In the last few months, government leaders at the US Department of Health and Human Services (HHS) have advanced ambitious policies to make interoperability a reality. Overall, this is a great thing. However, there are places where DC regulators need help from the frontlines to understand what will really work.
As California’s largest nonprofit health data network, Manifest MedEx has submitted comments and met with policymakers several times over the last few months to discuss these policies. We’ve weighed in with Administrator Seema Verma and National Coordinator Dr. Don Rucker. We’ve shared the progress and concerns of our network of over 400 California health organizations including hospitals, health plans, nurses, physicians and public health teams.
With the comment periods now closed, here’s a high-level look at what lies ahead:
CMS is leading on interoperability (good). Big new proposals from the Centers for Medicare and Medicaid Services (CMS) will set tough parameters for sharing health information. With a good prognosis to roll out in final form around HIMSS 2020, we’re excited to see requirements that health plans give patients access to their claims records via a standard set of APIs, so patients can connect their data to apps of their choosing. In addition, hospitals will be required to send admit, discharge, transfer (ADT) notifications on patients to community providers, a massive move to make transitions from hospital to home safe and seamless for patients across the country. Studies show that readmissions to the hospital are reduced as much as 20% when patients are seen by a doctor within the first week after a hospitalization. Often the blocker is not knowing a patient was discharged. CMS is putting some serious muscle behind getting information moving and is using their leverage as a payer to create new economic reasons to share. We love it.
notion that hospitals can reduce readmissions, and that punishing them for
“excess” readmissions will get them to do that, became conventional wisdom
during the 2000s on the basis of very little evidence. The Medicare Payment
Advisory Commission (MedPAC) urged Congress to enact the Hospital Readmissions
Reduction Program (HRRP) beginning in 2007, and in 2010 Congress did so. State
Medicaid programs and private insurers quickly adopted similar programs.
The rapid adoption of readmission-penalty programs without evidence confirming they can work has created widespread concern that these programs are inducing hospitals to increase utilization of emergency rooms and observation units to reduce readmissions within 30 days of discharge (the measure adopted by the Centers for Medicare and Medicaid Services [CMS] in its final rule on the HRRP), and this in turn may be harming sicker patients. Determining whether hospitals are gaming the HRRP and other readmission-penalty schemes by diverting patients to ERs and observation units (and perhaps by other means) should be a high priority for policy-makers. 
Part I of this series I proposed to address the question of whether hospitals
are gaming the HRRP by asking (a) does research exist describing methods by
which hospitals can reduce readmissions under the HRRP and, in the event the
answer is yes, (b) does that research demonstrate that those methods cost no
more than hospitals save. If the answer to the first question is no, that would
lend credence to the argument that the HRRP and other readmission-penalty
schemes are contributing to rising rates of emergency visits and observation
stays. If the answer to second question is also no, that would lend even more
credence to the argument that hospitals are gaming the HRRP.
In Part I, I noted that proponents of readmission penalties, including MedPAC and the Yale New Haven Health Services Corporation (hereafter the “Yale group”), have claimed or implied that hospitals have no excuse for not reducing readmission rates because research has already revealed numerous methods of reducing readmissions without gaming. I also noted many experts disagree, and quoted a 2019 statement by the Agency for Healthcare Research and Quality that “there is no consensus” on what it is hospitals are supposed to do to reduce readmissions.
this article, I review the research MedPAC cited in its June 2007 report to
Congress, the report that the authors of the Affordable Care Act (ACA) cited in
Section 3025 (the section that instructed CMS to establish the HRRP). In Part
III of this series I will review the studies cited by the Yale group in their
2011 report to CMS recommending the algorithm by which CMS calculates “excess”
readmissions under the HRRP. We will see that the research these two groups
relied upon did not justify support for the HRRP, and did not describe
interventions hospitals could use to reduce readmissions as the HRRP defines
“readmission.” The few studies cited by these groups that did describe an
intervention that could reduce readmissions:
The notion that hospital readmission rates are a “quality” measure reached the status of conventional wisdom by the late 2000s. In their 2007 and 2008 reports to Congress, the Medicare Payment Advisory Commission (MedPAC) recommended that Congress authorize a program that would punish hospitals for “excess readmissions” of Medicare fee-for-service (FFS) enrollees. In 2010, Congress accepted MedPAC’s recommendation and, in Section 3025 of the Affordable Care Act (ACA) (p. 328), ordered the Centers for Medicare and Medicaid Services (CMS) to start the Hospital Readmissions Reduction Program (HRRP). Section 3025 instructed CMS to target heart failure (HF) and other diseases MedPAC listed in their 2007 report.  State Medicaid programs and the insurance industry followed suit.
Today, twelve years after MedPAC recommended the HRRP and seven years after CMS implemented it, it is still not clear how hospitals are supposed to reduce the readmissions targeted by the HRRP, which are all unplanned readmissions that follow discharges within 30 days of patients diagnosed with HF and five other conditions. It is not even clear that hospitals have reduced return visits to hospitals within 30 days of discharge. The ten highly respected organizations that participated in CMS’s first “accountable care organization” (ACO) demonstration, the Physician Group Practice (PGP) Demonstration (which ran from 2005 to 2010), were unable to reduce readmissions (see Table 9.3 p. 147 of the final evaluation) The research consistently shows, however, that at some point in the 2000s many hospitals began to cut 30-day readmissions of Medicare FFS patients. But research also suggests that this decline in readmissions was achieved in part by diverting patients to emergency rooms and observation units, and that the rising rate of ER visits and observation stays may be putting sicker patients at risk  Responses like this to incentives imposed by regulators, employers, etc. are often called “unintended consequences” and “gaming.”
To determine whether hospitals
are gaming the HRRP, it would help to know, first of all, whether it’s possible
for hospitals to reduce readmissions, as the HRRP defines them, without gaming.
If there are few or no proven methods of reducing readmissions by improving
quality of care (as opposed to gaming), it is reasonable to assume the HRRP has
induced gaming. If, on the other hand, (a) proven interventions exist that reduce
readmissions as the HRRP defines them, and (b) those interventions cost less
than, or no more than, the savings hospitals would reap from the intervention
(in the form of avoided penalties or shared savings), then we should expect much
less gaming. (As long as risk-adjustment of readmission rates remains crude, we
cannot expect gaming to disappear completely even if both conditions are met.)