A class action legal ruling this month, on a case originally filed in 2014, found that UnitedHealthCare’s (UHC) mental health subsidiary, United Behavioral Health (UBH), established internal policies that discriminated against patients with behavioral health or substance abuse conditions. While an appeal is expected, patients with legitimate claims were systematically denied coverage, and employer/union purchasers who had paid for coverage for their employees and their family members received diminished or no value for their investments.
Central to the plaintiff’s argument was the fact that UBH developed its own clinical guidelines and ignored generally accepted standards of care. In the 106 page ruling, Judge Joseph C. Spero of the US District Court in Northern California wrote, “In every version of the Guidelines in the class period, and at every level of care that is at issue in this case, there is an excessive emphasis on addressing acute symptoms and stabilizing crises while ignoring the effective treatment of members’ underlying conditions.” He concluded that the emphasis was “pervasive and result[ed] in a significantly narrower scope of coverage than is consistent with generally accepted standards of care.” Judge Spero found that UBH’s cost-cutting focus “tainted the process, causing UBH to make decisions about Guidelines based as much or more on its own bottom line as on the interests of the plan members, to whom it owes a fiduciary duty.”
In a statement to FierceHealthcare, UnitedHealth said it “looks forward to demonstrating in the next phase of this case how our members received appropriate care…We remain committed to providing our members with access to the right care for the treatment of mental health conditions and substance use disorders.”
It is important to be clear about what transpired here. Based on evidence, a subsidiary of UnitedHealthCare, America’s second-largest health care firm, has been found in a court of law to have intentionally denied the coverage of thousands of patients filing claims. The organization justified the restrictions in coverage using internal guidelines tilted to favor financial performance rather than accepted standards of care. In other words, UBH’s leaders (as well as those at UHC) knowingly defrauded their customers and devised a mechanism to rationalize their scheme. In his ruling, Judge Spero described testimony by UHC representatives as “evasive — and even deceptive.”
Jeanette Brown had lost twenty pounds, and she was worried.
“I’m not trying,” she told me at her regular diabetes visit as I pored over her lab results. What I saw sent a chill down my spine:
A normal weight, diet controlled diabetic for many years, her glycosylated hemoglobin had jumped from 6.9 to 9.3 in three months while losing that much weight.
That is exactly what happened to my mother some years ago, before she was diagnosed with the pancreatic cancer that took her life in less than two years.
Jeanette had a normal physical exam and all her bloodwork except for the sugar numbers was fine. Her review of systems was quite unremarkable as well, maybe a little fatigue.
“When people lose this much weight without trying, we usually do tests to rule out cancer, even if there’s no specific symptom to suggest that,” I explained. “In your case, being a former smoker, we need to check your lungs with a CT scan, and because of your Hepatitis C, even though your liver ultrasounds have been normal, we need a CT of your abdomen.”
The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have proposed final rules on interoperability, data blocking and other activities as part of implementing the 21st Century Cures Act. In this series, we will explore the ideas behind the rules, why they are necessary and the expected impact. Given that these are complex and controversial topics open to interpretation, we invite readers to respond with their own ideas, corrections and opinions. You can find Part 1 of the series here.
In 2016, Congress enacted the 21st Century Cures Act with specific goals to “advance interoperability and support the access, exchange and use of electronic health information.” The purpose was to spur innovation and competition in health IT while ensuring patients and providers have ready access to the information and applications they need.
The free flow of data and the ability for applications to connect and exchange it “without special effort” are central to and supported by a combination of rules proposed by ONC and CMS. These rules address both technical requirements and expected behaviors. In this article, we look at specific technical and behavioral requirements for interoperability. Future articles will examine data blocking and other behavioral issues.
Compatible “Plugs and Sockets”
The proposed rules explicitly mandate the adoption and use of application programming interface (API) technology (or a successor) for a simple reason: APIs have achieved powerful, scalable and efficient interoperability across much of the digital economy. Put simply, APIs provide compatible “plugs and sockets” that make it easy for different applications to connect, exchange data and collaborate. They are an essential foundation for building the next generation of health IT applications. (Note: readers who want to go deeper into APIs can do so at the API Learning Center).
APIs are versatile and flexible. This makes them powerful but can also lead to wide variations in how they work. Therefore, ONC is proposing that certified health IT applications use a specific API based on the Fast Healthcare Interoperability Resources (FHIR) specification. FHIR is a consensus standard developed and maintained by the standards development organization (SDO) Health Level–7 (HL7). Mandating the use of the FHIR standard API helps to ensure a foundational compatibility and basic interoperability. This gives API technology suppliers (like EHR vendors) a clear set of standards to follow in order to fulfill the API requirement. It also ensures “consumers” of that API (like hospitals and health IT developers), have consistency when integrating applications.
Today on Health in 2 Point 00, Jess and I power through a whopping six questions. In this episode, Jess asks me about the merger between Cambia Health Solutions and Blue Cross NC, Alex Azar getting grilled by Rep. Joe Kennedy on Medicaid work requirements, Omada Health adding connected blood pressure and glucose monitors, 23andMe’s new Type 2 Diabetes predisposition test, and raises by Akili Interactive and MAP Health Management. —Matthew Holt
Those that advocate for change in healthcare most often make their case based on the unsustainable cost or poor quality care that is sadly the norm. A 2018 article in Bloomberg highlights this fact by reporting on global healthcare efficiency, a composite marker of cost and life expectancy. Not remarkably, the United States ranks 54th globally, down four spots from 2017 and sandwiched neatly between Azerbaijan and Bulgaria. Unarguably, the US is a leader in medical education, technology, and research. Sadly, our leadership in these areas only makes our failure to provide cost-effective, quality care that much more shameful. For the well-off, the prospect of excellent accessible care is bright, but, as the Bloomberg article points out, as a nation our rank is rank. Anecdotally, I can report that as a physician I am called upon with some regularity to intervene on the behalf of family and friends to get a timely appointment or explain a test or study that their doctor was too busy to explain, and so even for the relatively well-off, care can be difficult and deficient.
The cost of care frequently takes center stage in arguments advocating change. The recognition that health care costs are driving unsupportable deficits and limiting expenditures in other vital areas is very compelling. Therefore, lowering the cost of care would seem to be an area in which there would be swift consensus. However, solutions to rein in costs fail to address the essential truth that most of us define cost subjectively. Arguments about the cost of care divide rather than unify as the discussion becomes more about cost shifting than controlling overall cost. Further, dollars spent on healthcare are spent somewhere, and there are many who profit handsomely from the system as it is and work aggressively sowing division to maintain the status quo.
Poor quality and access are additional lines of argument employed to win support for change. These arguments fail due to a lack of a commonly accepted definitions of quality and access to care. Remedies addressing quality and access issues are frequently presented as population level solutions. Unfortunately, these proposals do not engage a populace that cares first and foremost about their access to their doctor. The forces opposed to change readily employ counterarguments to population-based solutions by applying often false, but effective, narratives that population-based solutions are an infringement on a person’s fundamental freedoms. In that counterargument is the key to improving healthcare.
With a stated intent of bringing social justice and financial relief to hundreds of thousands of patients undergoing coronary angioplasty in the country every year, the Government of India capped the sale price of coronary stents in Feb 2017. Stent prices fell by as much as 80% with this populist move, seen as anti-trade within the industry circles. It is tempting for a practising interventional cardiologist to look at two years of this government control on medical device prices in a market economy.
Before price-capping, angioplasty patients were indeed getting a raw deal. There was no uniformity in price among stents of similar class/generation made by different manufacturers. The cost of the only bioabsorbable stent then available in India, to the patient, was 200,000 Indian Rupees (a little under USD 3000), whereas the US or European-manufactured (“Imported”) drug eluting stents (DES) would cost anywhere between INR 85,000 to 160,000. Stents manufactured within India (“Indigenous”) were cheaper. The real cost of manufacture or import was hidden from public view. It was left to the eventual vendor, with alleged involvement of the user hospitals, to determine the Maximum Retail Price (MRP). It was speculated that a huge margin was worked into it, and the profit was split between manufacturers, distributors, and hospitals. Allegedly, some unscrupulous physicians received kickbacks for implanting these devices. Even in government-run hospitals, foul play was suspected.
By a single stroke of the pen, Prime Minister Narendra Modi government slashed stent prices substantially. The bioabsorbable stent cost, to the patient, was capped at INR 60,000 (< USD 1000). Bare metal stents (BMS) and Drug-eluting stents (DES) were capped at INR 7500 and 30,000, respectively. The government seemed to have done its homework: these figures were arrived at from industry-supplied figures on manufacturing or import costs. The cosy network of coronary stent food chain was set on fire with this move: with sudden diminution of profit margins, it was feared that multinational companies would cut Indian workforce; stent distributors & vendors (especially small vendors) were expected to be wiped out or cut in size; doctors worried that with low profitability, multinational stent manufacturers would exit the country or at least, stop importing newer technologies; and hospitals feared revenue loss.
Following this, Industry and Hospital-chain representatives are said to have had series of discussions with the government. Rumours were that the Central Government was arm-twisting traders and that it would relent and raise price limits after these ‘talks.’ The National Pharmaceutical Pricing Authority (NPPA) promised a price revision, one year after the price cap. Meanwhile, some multinationals informed the government that they would withdraw some of their ‘top-end products’ from the Indian market, citing financial nonviability, obviously to put pressure on the government. The Bioresorbable Scaffold from Abbott actually disappeared from Cath lab shelves.
I was born in a rural village outside of Hue, Vietnam in 1976, a year after Saigon fell and the war ended. My family of four struggled to survive in the post-war shambles, and in 1981, my mother had no choice but to flee Vietnam by boat with my older sister and myself. Through the support of the refugee resettlement program, we began our lives in the United States in 1982, wearing all of our belongings on our backs and not knowing a word of English.
Though we struggled for years to make ends meet, we sustained ourselves through public benefit programs: food stamps, Medicaid, Section 8 Housing, and cash aid. These programs were lifelines that enabled me to focus on my education, and they allowed me to be the physician and public health expert that I am today. Looking back, I firmly believe that the more we invest in the lives and livelihoods of immigrants, the more we invest in the United States, its ideals, and its future.
So, when I first learned of the current administration’s plan to make it harder for immigrants with lower socioeconomic statuses to gain permanent U.S. residence, the so-called changes to the “Public Charge” rule, I felt outraged and baffled by its short-sightedness. Continue reading…
The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have published proposed final rules on interoperability and data blocking as part of implementing the 21st Century Cures act. In this series we will explore the ideas behind the rules, why they are necessary and the expected impact. Given that these are complex, controversial topics, and open to interpretation, we invite readers to respond with their own ideas, corrections, and opinions.
Health IT 1.0, the basic digitalization of health care, succeeded in getting health care to stop using pens and start using keyboards. Now, Health IT 2.0 is emerging and will build on this foundation by providing better, more diverse applications. Health care is following the example set by the rest of the modern digital economy and starting to leverage existing monolithic applications like electronic health records (EHRs) to create platforms that support a robust application ecosystem. Think “App Store” for healthcare and you can see where we are headed.
This is why interoperability and data blocking are two of the biggest issues in health IT today. Interoperability – the ability of applications to connect to the health IT ecosystem, exchange data and collaborate – is a key driver of the pace and breadth of innovation. Free flowing, rich clinical data sets are essential to building powerful, user-friendly applications. Making it easy to install or switch applications reduces the cost of deployment and fosters healthy competition. Conversely, when data exchange is restricted (data blocking) or integration is difficult, innovation is stifled.
Given the importance of health IT in enabling the larger transformation of our health system, the stakes could hardly be higher. Congress recognized this when it passed the 21st Century Cures Act in 2016. Title IV of the act contains specific provisions designed to “advance interoperability and support the access, exchange, and use of electronic health information; and address occurrences of information blocking”. In February 2019, ONC and CMS simultaneously published proposed rules to implement these provisions.
I once made a serious error. The patient had taken an overdose of paracetamol, but because I was single-handedly covering three inpatient acute psychiatric wards due to sickness of two other trainees which medical HR had been unable to cover, with a lot of agency nurses who did not know any of the patients well at all, and also because this patient frequently said she had taken overdoses when she had not, and declined to let me take bloods to test for paracetamol levels, I believed she was crying wolf. She collapsed several hours later, and died. I was overwhelmed with feelings of guilt, inadequacy, but also fear – was this the end of my career? I was a trainee psychiatrist at the time – and was immensely fortunate in that my supervising consultant was robust in his defence of me, supported me, whilst fronting the complaint from the patient’s family and attending the inquest. He had been covering two outpatient clinics himself while I was on the ward.
The patient was only 26 years old. Her parents were very angry with me, and not unreasonably so; at the time, it seemed to me that they wanted me to suffer. Twenty years later, I believe they wanted to understand how I made the decision I did. Eventually, the consultant arranged for me to meet the parents. They were very kind to me, all of them, I realise that now. I wasn’t able to give them the answers they wanted. I just cried and said I was sorry.
The mother sent the consultant a letter afterwards which he gave me when I was about to complete that training placement. I did not read it for many months. When I did, I cried. The mother described her daughter’s childhood, the family’s loss, and her own incomprehension that the NHS – which she and generations of her family had venerated as a great institution – could have failed her child. It said very little about me, certainly didn’t seek to blame me, but said a few times that she wanted justice for her daughter. It was an exploration of grief by a bereft mother.
I often think about the mother – I cannot recall the face of the 26 year old patient – but remember perfectly well the mother, who said very little, didn’t even cry, leaving her husband to talk incoherently about justice and a referral to the GMC and the police (they did not do any of these things). And I often ponder the nature of justice they wanted. This was well before the advent of Duty of Candour and rigorously completed serious incident investigations.
Did they get justice? The coroner returned a verdict of suicide, but failed to acknowledge the systemic problems of lack of staff, merely noting that there had a “gap in clinical assessment”. It was not untrue, yet I experienced it as unfair. The consultant reminded me that I was fortunate that the family had not made more fuss. So I let it be. Until the case of Dr Bawa-Garba.
Imagine solving wicked problems of patient matching, consent, and a patient-centered longitudinal health record while also enabling a world of new healthcare services for patients and physicians to use. The long-awaited Notice of Proposed Rulemaking (NPRM) on information blocking from the Office of the National Coordinator for Health Information Technology (ONC) promises nothing less.
Having data automatically follow the patient is a laudable goal but difficult for reasons of privacy, security, and institutional workflow. The privacy issues are clear if you use surveillance as the mechanism to follow the patient. Do patients know they’re under surveillance? By whom? Is there one surveillance agency or are there dozens in real-world practice? Can a patient choose who does the surveillance and which health encounters, including behavioral health, social relationships, location, and finance are excluded from the surveillance?
The security issues are pretty obvious if one uses the National Institutes of Standards and Technology (NIST) definition of security versus privacy: Security breaches, as opposed to privacy breaches, are unintentional — typically the result of hacks or bugs in the system. Institutional workflow issues also pose a major difficulty due to the risk of taking responsibility for information coming into a practice from uncontrolled sources. Whose job is it to validate incoming information and potentially alter the workflow? Can this step be automated with acceptable risk?
It’s not hard to see how surveillance as the basis for health information sharing would be contentious and risk the trust that’s fundamental to both individual and public health. Nowhere is this more apparent than in the various legislative efforts currently underway to expand HIPAA to include behavioral health and social determinants of health, preempt state privacy laws, grant data brokers HIPAA Covered Entity status, and limit transparency of how personal data is privately used for “predictive analytics”, machine learning, and artificial intelligence.