Sudden Infant Death Syndrome (SIDS)

Sudden Infant Death Syndrome (SIDS): The sudden and unexpected death of a baby with no known illness, typically affecting sleeping infants between the ages of two weeks to six months. Infants with a brother or sister who died of SIDS; babies whose mothers used heroin, methadone, or cocaine during pregnancy; infants born weighing less than 4.4 pounds; children with an abnormal breathing pattern that includes long periods without taking a breath (apnea); and babies who sleep on their stomachs are at increased risk for SIDS. Since babies who sleep on their stomachs are at least three times more likely to die of SIDS than babies who sleep on their backs, children's health authorities recommend always placing infants on their backs to sleep.

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The Perversion of Fiscal Federalism: Daniel L. Hatcher's, “The Poverty Industry: The Exploitation of America's Most Vulnerable Citizens”

By DAVID INTROCASO

It's not that we do not know that Medicaid and Medicare fraud is rampant.  A 2012 estimate by the former CMS administrator, Donald Berwick, estimated the amount at $100 billion annually.  Nor are we unaware, that drug companies routinely pay massive fines for illegal business practices: eight firms have paid in sum over $11.2 billion in civil and criminal fines since 2010.  Beyond these issues what is possibly most disturbing about the numerous inter-related health and human services issues “The Poverty Industry” raises is Professor Hatcher's detailed discussion of how state human service agencies, in partnership with private contractors, have monetized poverty or turned vulnerable populations into a source of state revenue.  As Hatcher says in his introduction, states are, “strip-mining billions in federal aid and other funds from impoverished families, abused and neglected children and the disabled and elderly poor. ” 

Hatcher, a law professor at the University of Baltimore, is largely concerned with state abuse or misuse of federal foster care (Title IV-E) and federal Medicaid funding.  What drives abuse, he argues in this thoroughly researched work, is rampant self-interest, that has resulted in “poverty's iron triangle” in which self-dealing states and state agencies sustain or gain power by furthering mutually beneficial relationships with business constituents who, being fare more resourced and organized, outmaneuver the poor.  This enables them to have, as President Eisenhower infamously noted two weeks before he left office, “unwarranted influence,” leaving agency clients, again the poor children and elderly, as a source of income or collateral in instances of child custody.

In foster care, children become, as the consulting firm MAXIMUS states, a “revenue generating mechanism”.  Hatcher estimates that foster care agencies, aided by contingency pay-based contractors, take more than $250 million in assets each year from children under their care.  This is typically accomplished by agencies presumptively assigning themselves the role of the foster child's representative Social Security Insurance (SSI) payee despite the fact that, per federal regulation, the payee must use SSI funds “only for the use and benefit” of the child.  Hatcher provides several examples, including one of a Maryland boy who, after the death of his mother, father and brother, was left penniless when the state foster care agency acquired, unbeknownst to the child, his Social Security survivor benefits.  “The Poverty Industry” details how the Kentucky foster care agency's contractor mines disabled children's SSI benefits; how Nebraska's contractor so automated the state-as-representative-payee system that the state's foster care agency ceased to even be a part of the process.  (Nebraska even obtains foster children's burial spaces.)  Foster care agency contractors in Georgia, Iowa, and Florida use sophisticated data mining algorithms and predictive analytics to maximize SSI “units” and SSI “penetration rates.” Professor Hatcher details how these practices are enabled by the Social Security Administration (SSA), which routinely fails to identify the most appropriate person as the foster child's representative payee.  The SSA has so abrogated its responsibility that it runs a computer program, termed the “kiddie loop,” to process faster foster agency SSI payee application approvals.

State foster care agencies explain their malfeasance by arguing that taking SSI benefits reduces their  funding needs and that if the foster care agency does not act as the SSI representative payee, the foster child will lose their SSI benefits.  Agencies also point out that since they spend money to care for foster children, they should be able to reimburse themselves via a maintenance fee.  Hatcher demonstrates instances in which states go so far as to hold children as de facto collateral or terminate parental rights, all in the name of enforcing maintenance fee collections.  Furthermore, states claim that by taking the foster child's SSI benefits, that child's $2,000 asset limit is avoided.  Hatcher points out that states are legally required to provide and pay for foster care for abused and neglected children.  The state's share of foster care costs must be paid with state, not the child's, funds.  If no suitable representative SSI payee is found, the SSA is required to conserve SSI benefits until a suitable representative payee is found or benefits are to be paid to the child upon their reaching adulthood.  Hatcher also notes per the 1967 Supreme Court case, In re: Gault, children have constitutional due process rights.  A state foster care agency cannot simply expropriate a foster care child's property, here moreover income.      

As startling as these foster care practices are, Hatcher notes, they pale in comparison “to the scope of revenue strategies involving Medicaid,” that Hatcher generally terms, “Medicaid money laundering.”  Readers familiar with the Medicaid program are likely aware of how states have been gaming federal matching Medicaid funding, largely via Medicaid “enhancement” or “bed” taxes, for years.  Hatcher describes how states like New Hampshire, Wisconsin, Massachusetts and Missouri use a strategy of imposing a tax on a hospital or other provider based on revenues that drive greater federal Medicaid matching, or FMAP (Federal Medicaid Assistance Percentage) funding.  Once that additional federal funding is received, the tax dollars are refunded to the hospital, nursing home, psychiatric institution or other provider.  These additional federal Medicaid dollars are then used as the state wishes.  In a 2007 GAO report, Hatcher cites, auditors estimated these financing arrangements amounted to billions of dollars in Medicaid fraud.  Variations on this approach include, again with the help of private “revenue maximization consultants,” falsely relating the federal Medicaid match funding to pre-school and special education programming.  Hatcher is particularly interested in how Medicaid-reimbursed nursing home care is gamed.  He notes as an example that Indiana, via a bed tax termed a “quality assessment fee,” was able to divert $136 million in federal Medicaid funds to its general fund between 2011 and 2013.  Maryland's nursing home bed tax has proven so useful, the state increased the tax from two to six percent between 2010 and 2012 and in 2010 statutorily required 35 percent of moneys be used for general fund purposes.   

Hatcher makes special note of the use of Medicaid funds to over-prescribe anti-psychotics to sedate nursing home residents and foster children, thereby allowing for lower staffing levels and driving increased profits.  This practice is particularly perverse, because side effects of these medications can include instant death.  In 2007 Congressional testimony, the FDA estimated that 15,000 nursing home residents die each year from anti-psychotic medication misuse.  Foster children, including infants, particularly those in group settings, Hatcher found, comparatively are given much higher rates of psychotropic drugs, including anti-psychotic medications.  In Massachusetts and Texas, for example, upwards of 40 percent of foster children were found to be taking psychotropics.  In Colorado, nine of the ten most prescribed Medicaid medications for foster children were psychotropics, compared to one of ten for non-foster children in Medicaid.

After documenting “poverty's iron triangle,” Hatcher is left to call into question the legitimacy of fiscal federalism, the framework upon which grant in aid programming is conducted.  In theory, fiscal federalism is defined as a cooperative effort whereby the federal government efficiently raises revenue that is dispersed to states better able to define programs that address regional needs.  Federal funding is conditional in that states agree to spending instructions.  Since Hatcher is so unsparing in his account of failed fiscal federalism in practice, his recommendations for “reeling in the poverty industry” are surprisingly optimistic.  State agencies, he says, need to be more “enlightened” and begin to act in the best interests of their beneficiaries.  State agencies also need to abandon contingency fee contracting that, in part, increases the occurrence of fraudulent federal claims (and False Claim Act settlements from which poverty triangle contractors are far from immune).   Litigation must continue, particularly since Hatcher notes the courts have in sum failed to adequately address the fact that foster care agencies have a legal obligation to pay foster care costs.  He argues that the Congress should pass legislation to ensure the resources allocated to foster children are not abused, and cites the 2010 Foster Children Self Support Act as an example.  He believes CMS should better monitor how states claim Medicaid moneys, that the SSA should improve its monitoring of the representative payee system.  Federal grant in aid programming, such as-open ended block or opportunity grants, or so called flex funds, popular among Republican members of Congress, should be evaluated with, Hatcher states, “caution and concern. ”  Regardless of whether any or all of these recommendations can be implemented to effectively reel in the poverty industry, Hatcher's effort to expose pervasive abuse and raise awareness of the devastating effects they have on our nation's most vulnerable populations is of significant value. 

Ushering In The New Era Of Health Equity

Editor's note: Joseph Betancourt is one of the theme advisors for the June 2017 Health Affairs equity theme issue.

The passage of health care reform and current efforts in payment reform have fueled a significant transformation of the US health care system. An entire new set of structures is being developed to facilitate increased access to care that is cost-effective and high quality. High-value health care is the ultimate goal. Guided by the 2001 Institute of Medicine (IOM) report, Crossing the Quality Chasm, the nation has charted a path to deliver care that is safe, efficient, effective, timely, patient-centered, and equitable. There is no doubt that significant gains have been made in this effort, particularly in the area of patient safety. However, one key pillar of quality-achieving equitable care-has garnered significantly less attention than the others. Equity is the principle that quality of care should not vary based on patient characteristics such as race and ethnicity, gender, geographic location, or socioeconomic status.

The inclusion of equity among the pillars of quality emerges from longstanding research that has identified disparities in health and health care based on all of these patient characteristics. For example, minorities are significantly more likely to be diagnosed with and die from diabetes compared to whites. There is little doubt that negative social determinants-such as lower levels of education, lower socioeconomic status, unsafe neighborhoods, and “food deserts”-disproportionately impact minority populations, and thus contribute to their poorer health outcomes. Minorities are also more likely to be uninsured, and thus less likely to have a regular source of care, more likely to report delaying seeking care, and more likely to report that they have not received needed care - resulting in avoidable hospitalizations, emergency hospital care, and adverse health outcomes.

To further complicate matters, the 2002 IOM report Unequal Treatment found that even when minorities and whites had the same insurance and socioeconomic status, and when comorbidities, stage of presentation, and other confounders were controlled for, they still often received a lower quality of health care than whites. While these examples focus on disparities related to race and ethnicity, more recently disability and sexual orientation have been included as key components of equity, as well.

Earlier this year, Don Berwick laid out his vision of what will be “era three” of medicine and health care, sharing his perspectives about where health care has been, and where it's headed in this country. As someone who has focused on health equity for close to 20 years-with a particular focus on racial and ethnic disparities in health care-I thought this was an interesting lens to view equity through, examining where this field has been, and where it is headed.

The First Era of Health Equity

With the release of Crossing the Quality Chasm, followed shortly after by Unequal Treatment, the first modern era of equity was underway. I say “modern” because the issue of disparities and equity was an issue well before the early 2000s, and to dismiss this reality would do a disservice to the many leaders and incredible work that occurred in decades past. Nevertheless, given the imprimatur of the IOM, these reports made disparities real and the need for equity legitimate, and caused health care leaders to take notice in ways they hadn't before.

Equity was no longer part of an activist agenda, but instead an issue that required mainstream focus and attention. That's not to say that leaders jumped into action. In fact, the predominant sense across the nation within health and health care was one of “not here, not me.” Aside from progressive leaders and early adopters who began to place equity on the same footing as the other pillars of quality, the overwhelming majority either remained reluctant to admit that disparities existed in the health care settings they oversaw, or went on the slow burn, multiyear path of “studying the issue and what could be done.”

Nevertheless, leaders were slowly socialized with facts in this period, and the mantra of “no one suspect, no one solution” allowed them to better understand the multifactorial nature of the problem, and the complexity of solutions needed to address them. Organizations such as the Joint Commission, the National Committee for Quality Assurance, and the National Quality Forum-often supported by foundations such as The Commonwealth Fund, The California Endowment, and Robert Wood Johnson-began to explore how they could exert their influence to drive change in this area. Whether through accreditation standards, incentives and awards, or new measures, these organizations set the table for significant progress in legitimizing equity and the need to address disparities. During this time there was little discussion about other areas of disparities beyond racial and ethnic disparities. Disparities that impacted individuals by disability status or sexual orientation, and the impact of social determinants on health, health care, and health disparities received limited attention. Most importantly, there wasn't much work on solutions to speak of. All of this notwithstanding, the first era was one of energy, optimism, and the building of some key foundational elements of the field.

The Second Era of Health Equity

The passage of the health care reform in 2010 and the push to increase value in health care, including achieving the triple aim of better care, better health, and lower costs, heralded the beginning of the second era of equity. A lot of energy was devoted to health insurance enrollment, and a litany of new structures (and acronyms) evolved to improve care delivery and to deliver on value, including ACOs (Accountable Care Organizations) and PCMHs (patient-centered medical homes), among others.

New cost “pressure points” such as readmission penalties and financial skin-in-the-game for population health, patient safety, and patient experience also took root. The emergence of electronic health records and meaningful use requirements became all consuming. “Hot spotters,” “super-utilizers,” and the “duals” (individuals covered by Medicare and Medicaid) became targets for new efforts to improve community health and control cost. The net-net here was that much of the oxygen was sucked out of the health care room and fledgling activities focusing on equity and disparities were receiving little attention. Foundations and other organizations that had been essential in the first modern era of equity now moved away from equity- or disparities-specific funding or activities in favor of “mainstreaming” this work (folding disparities into quality work, or as part of healthy communities' agendas, for instance) or focusing on other more pressing areas.

Despite this, advocates for improving quality, addressing disparities, and achieving health equity began to connect the dots for health care leaders, highlighting that if they really cared about quality and controlling costs, they needed to care about equity. Research had demonstrated that minorities, when compared to whites, tended to suffer more medical errors with greater clinical consequences; have longer length of hospital stays for the same clinical condition; experience higher rates of avoidable hospitalizations and 30-day readmission rates for congestive heart failure; experience more test ordering for similar conditions (particularly when there was a language barrier); and were under-used clinically beneficial, evidence-based care. Improving quality, addressing disparities, and achieving equity was not just the right thing to do, but also the smart thing to do, given the new financial structures developed to drive quality and value.

During this time, increasing attention was paid to the social determinants of health, and new efforts were launched to collect patient data related to disability and sexual orientation. We also began to see the first unintended consequences of health care transformation: for instance, hospitals that historically served poor, underserved, vulnerable, and minority communities were subject to significant readmissions penalties. A fierce debate began about whether organizations that serve larger vulnerable populations should be able to risk-adjust for patient socioeconomic status, thus allowing them a better chance at success. Proponents feel this is appropriate and reflects reality; opponents suggest that risk adjustment creates two standards of care, one for hospitals who care for vulnerable populations, and another for those who don't - in other words, it lets the former off the hook for delivering high-value, efficient, and effective care.

In sum, the second era of equity is one of rapid flux and a turning away from disparities and equity explicitly, while at the same time a period where a strong business case for addressing disparities and achieving equity has been made. The equity umbrella also began to expand to other groups and issues-such as individuals with disabilities and those from the Lesbian, Gay, Bisexual, and Transgender community-and incorporate the importance of the social determinants of health. Solutions still are few and far-between, hard to come by, and difficult to sustain - yet the hope remains that the movement to high-value care will finally make achieving equity a smart business decision.

The New Era of Health Equity

The new era of health equity is upon us. Health care reform marches forward, albeit with some real challenges ahead: care is costlier than anticipated under Obamacare, commercial insurers are pulling out of exchanges, and fickle political winds remain a constant threat. The real push towards value begins with the best ABC of health care yet-an acronym within an acronym-MACRA. The Medicare Access and CHIP Reauthorization Act is the Centers for Medicare and Medicaid Services' (CMS) effort to shift how providers are paid, from quantity of care to quality of care. Already we see the unintended consequences brewing, as ACOs are the better rewarded option in MACRA compared to the Merit-Based Incentive Program (MIPS), yet are less likely to exist in minority communities. ACOs are also less likely to recruit providers who take care of large minority populations.

That being said, several promising opportunities are on the horizon. First is the much greater focus on the social determinants of health. Serious efforts, especially as part of population health, are underway to meet the broader social needs of patients. This will, if constructed with attention to the needs of diverse populations, undoubtedly go a long way to address disparities and foster equity. Second, much more attention is being paid to all aspects of equity, and not just racial and ethnic disparities. Third, activities focused on diversity and inclusion, and especially new conversations about racism, implicit bias, and stereotyping as root causes for disparities, are bubbling up now more than ever before. This is likely a direct consequence of the coverage of police violence against Black citizens, the Black Lives Matter movement, and the current and toxic political climate around race relations. Although difficult and painful, it is fair to believe that these difficult conversations can take us to a better place on issues of disparities and equity, especially in health care. Fourth, we are seeing major campaigns encouraging hospitals to place a premium on equity, most prominent among them being the American Hospital Association's annual Equity of Care Award, and its #123forEquity pledge campaign, which over 1,300 hospitals nationwide have signed on to. Fifth, CMS has developed a major Equity Plan for Medicare that looks to drive the health care system toward a robust set of activities focused on addressing disparities and achieving equity, using CMS' influence as the nation's largest payer.

These are just some of the major trends and activities that will define the new era of health equity. It is important, however, to continue to highlight the importance of having multiple stakeholders at the table. Currently, health plans have been minimally engaged in this work, and the National Health Plan Collaborative, the nation's first and only effort to bring large health plans together to partner around addressing disparities and achieving equity, has long since faded into the sunset. What is needed now are concrete strategies, solutions and interventions to address disparities and achieve equity in all its facets. More research documenting problems is nice but unnecessary. We need to move beyond diagnosing the problem to addressing it. If we are in fact going to emerge from this next era of health equity successfully, the summary we'll write in 10 years should highlight all the new, sustainable, and financially viable interventions that finally allowed us to thread the needle and sew together cost, quality, safety, equity, and value for the purpose of eliminating disparities once and for all.

A New Health Affairs Blog Featured Topic: 'Health Equity'

Health Affairs Blog is launching a new featured topic on “Health Equity.”

Health disparities and health care disparities-including differential access to treatment and inequity in the quality of care-have been covered extensively in our journal and on the Blog, including most recently in our August 2016 issue and companion disparities eBook. In June 2017, Health Affairs will publish the first of two theme issues that builds on this literature, with an eye toward not just documenting disparities but also finding solutions for achieving equity. Many solutions will be cross-sectoral in nature, as we increasingly recognize that good health often begins in the social arena - influenced by access to adequate and safe housing, educational opportunities, child care, and other social determinants.

In the lead-up to the June 2017 issue, and continuing afterwards, we will publish blogs focused on achieving health equity as part of this new featured topic. We'll feature leading voices in the field, and encourage you to join the conversation by commenting on Health Affairs Blog posts. We also invite you to submit your own posts on topics such as achieving health equity, factors that contribute to disparities in health and health care, and interventions both inside and outside the health services sector that improve health and reduce disparities, including cross-sector collaborations. Read the first post in the series.

We are grateful for the support of The Kresge Foundation, The California Endowment, the Aetna Foundation, Episcopal Health Foundation, and The Colorado Health Foundation for this series on the Blog and for support of the larger health equity project.

All blog posts submitted for this topic are subject to Health Affairs' standard vetting and selection process. You can find our complete archive of historical posts on topics surrounding equity and disparities here.

Watch for another new Health Affairs Blog featured topic in the coming months on end-of-life issues. Follow new postings @Health_Affairs and through Health Affairs Today.

Can Social Impact Bonds Improve Healthcare?

By CAITLIN BREANNE SMITH

It's been established that an effective way to manage an individual's health is to address the root cause of health complications, known as social determinants of health (SDOH).  Unfortunately, interventions that address SDOH often exist outside the scope of the traditional healthcare payment system. 

There is a relatively new methodology that can be used to increase spending on SDOH while transparently enforcing accountability and outcomes. Social impact bonds, also known as  “pay-for-success” models, are multi-stakeholder performance-based contracts.

The five key stakeholders and their roles are as follows:

1) Service Provider:  Agrees to conduct a program designated to yield a future outcome that is valuable to the payer.  (Usually a nonprofit organization.)

2) Investor:  Provides up-front working capital for the service provider to channel toward the designated program.  In exchange, the investor will receive a “success payment” if the committed outcome is produced on schedule.

3) Payer:  Commits to pay the service provider a “success payment” when the specified outcome is produced.  (Usually a government agency.)

4) Intermediary Organization:  Facilitates the SIB contract, establishes payment and financing terms, and supervises the service provider's program.

5) Independent Evaluator:  Determines if the committed outcome was achieved upon conclusion of the contracted period.

Hemorrhage

Hemorrhage: Bleeding or the abnormal flow of blood.

A hemorrhage may be "external" and visible on the outside of the body or "internal," where there is no sign of bleeding outside the body. Bleeding from a cut on the face is an external hemorrhage. Bleeding into the spleen or liver are examples of internal hemorrhage.

The term "hemorrhagic" comes from the Greek "haima," blood + rhegnumai," to break forth; a free and forceful escape of blood.

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New Rule On Excepted Benefits, Short-Term Coverage; Mental Health And Substance Use FAQs

On October 28, the Departments of Health and Human Services, Labor, and Treasury released a final rule governing excepted benefits coverage, lifetime and annual limits, and short-term limited duration coverage. The regulations finalize in part proposed regulations issued by the departments in June.

The Final Rule

The final rule adopts essentially unchanged the portions of the proposed rule it covers. However, two of the topics addressed by the proposed rule-group fixed dollar indemnity coverage and expatriate plans-are not being finalized at this time. The final regulations also do not address specified disease policies (such as cancer policies), a topic on which the departments had requested comment in the notice of proposed rulemaking.

Excepted Benefits

Most of the Affordable Care Act's insurance reforms apply to non-grandfathered individual and group insurance coverage and self-insured group coverage. They do not apply, however, to a category of insurance coverage called excepted benefits. This category was created by the Health Insurance Portability and Accountability Act (HIPAA), an insurance reform statute from the late 1990s. Excepted benefits are a diverse assortment of insurance coverage, including

• insurance that only incidentally provides health benefits (like auto liability or worker's compensation coverage);


• limited scope health coverage (such as dental, vision, and long-term care coverage);


• “noncoordinated” excepted benefits coverage, which is not coordinated with group health coverage and pays benefits regardless of whether such benefits are provided (such as specified disease or indemnity coverage); and


• coverage that is supplemental to some other form of coverage (like Medicare or Tricare supplemental coverage or coverage supplemental to a group health plan.)

Excepted benefit coverage is not minimum essential coverage under the ACA, so individuals who have only excepted benefit coverage must still pay the individual responsibility coverage tax and large employers that offer only excepted benefit coverage to their full-time employees will have to pay the employer responsibility penalty if it otherwise applies. There is concern that individuals who purchase excepted benefits may not be aware how limited the coverage is and that they may not know that they will have to pay the penalty. There is also concern that individuals who purchase excepted benefit coverage rather than ACA-compliant coverage may be healthier than average purchasers of ACA-compliant coverage; thus, their absence from the individual insurance market may be a factor contributing to destabilization of the individual market risk pool.

Short-Term Coverage

Short-term, limited duration coverage is not excepted benefit coverage under HIPAA and the ACA. Rather, it is sui generis-it can only be sold in the individual market but is not individual market coverage subject to the ACA. Short-term coverage was intended to be transitional coverage, for example for individuals between jobs.

There is evidence, however, that insurers have been selling short-term coverage for terms of up to a year and extending the coverage indefinitely so that it effectively substitutes for ACA-compliant coverage. The preface to the regulation notes that short-term coverage grew from 1 to 1.5 million member months from 2013 to 2015. It is quite possible that some purchasers did not realize how limited their coverage was, that it was not guaranteed renewable, and that it did not free them from having to pay the individual responsibility penalty.

Neither HIPAA nor the ACA defined how short “short-term” is, but prior regulations required the term of coverage to be less than 12 months. The October 28 final regulations provide that short-term coverage must be for a period less than three months. This accords with the time period that individuals may remain without coverage without having to pay the individual responsibility penalty. The policy contract and all application materials connected with enrollment must also prominently display a warning stating:

THIS IS NOT QUALIFYING HEALTH COVERAGE (“MINIMUM ESSENTIAL COVERAGE”) THAT SATISFIES THE HEALTH COVERAGE REQUIREMENT OF THE AFFORDABLE CARE ACT. IF YOU DON'T HAVE MINIMUM ESSENTIAL COVERAGE, YOU MAY OWE AN ADDITIONAL PAYMENT WITH YOUR TAXES.

The regulation also provides that the less-than-three-month limit applies to any extensions “that may be elected with or without the issuer's consent.” This provision is intended to keep insurers from indefinitely extending short-term coverage. The Departments, however, rejected the suggestion from commenters that individuals not be allowed to purchase short-term coverage if they had previously been covered under a short-term policy, deeming such a policy to be too difficult to enforce. Insurers are not therefore, actually prohibited from renewing short-term policies as long as they do not guarantee renewability.

Similar Supplemental Coverage

“Similar supplemental coverage” that supplements and fills gaps in group health coverage is excepted benefit coverage. The final rule clarifies that supplemental coverage must either

1. cover benefits that are not covered by the primary coverage and are not essential health benefits in the state where the coverage (including expatriate coverage) is issued;


2. cover cost-sharing for primary benefits; or


3. both provide supplemental benefits and cover cost-sharing.

Similar supplemental group coverage does not include coverage that becomes secondary or supplemental only under a coordination of benefit provision. The regulation does not explicitly supersede earlier guidance that provided that supplemental coverage could not cost more than 15 percent of the cost of the primary coverage and could not differential among individuals in eligibility.

Travel Insurance

The final rule also recognizes travel insurance as a new category of excepted benefits. It defines travel insurance as insurance coverage for the personal risks of planned travel, such as trip interruption or cancellation, loss of baggage, damages to accommodations or rental vehicles, and sickness, accident, disability, or death during travel, as long as health benefits are not offered on a standalone basis and are incidental to other coverage. Travel insurance does not include comprehensive medical protection for travelers with trips lasting six months or longer, such as expatriates or deployed military personnel.

Essential Health Benefit Definition For The Purposes Of Annual And Lifetime Dollar Limits

Finally, the final rule defines essential health benefits (EHB) for purposes of the ACA's annual and lifetime dollar limits. Non-grandfathered health plans subject to the ACA cannot impose annual or lifetime dollar limits on EHB. This prohibition applies to large group plans, but large group plans are not required to cover the EHB, which must be covered by individual or small group plans.

The final rule defines EHBs for plans that are not required to cover EHB as any EHBs covered by an EHB-benchmark plan in any state (including state-mandated benefits that qualify as EHB) or benefits under one of the three largest Federal Employees Health Benefit Program plans (including any benefits added to meet EHB regulatory requirements).

Group Fixed Dollar Indemnity Plans

As noted at the outset, the final rule does not include proposed provisions governing group fixed dollar indemnity plans. These proposed rules would have required group fixed indemnity plans to be offered on a per-time-period rather than per-service basis and would have required a warning in application, enrollment, and reenrollment materials that fixed-dollar indemnity coverage is not minimum essential coverage and cannot be relied to meet the individual responsibility requirement. A similar notice requirement already applies to individual fixed indemnity coverage. A further requirement for individual fixed indemnity coverage-that the coverage be sold only to individuals who attest that they have ACA-compliant primary coverage-was invalidated by a federal court earlier this year, but was not part of the proposed rule for group fixed indemnity coverage.

The final rule takes effect for coverage for policy and plan years beginning after January 1, 2017. The Departments will not enforce the requirement that short-term coverage be less than three months, however, for products sold before April 1, 2017, as long as the coverage ends on or before December 31, 2017. States may also elect not to enforce the time limit for coverage sold before April 1.

Mental Health And Substance Use Disorder Parity Report And FAQs

On October 27, the President's task force on Mental Health and Substance Use Disorder Parity released its final report. The report was accompanied with a blog post, fact sheet, disclosure guide for making the most of mental health and substance use disorder benefits, and a set of frequently asked questions (FAQs) issued jointly by the Departments of Labor, Health and Human Services, and Treasury. HHS is also unveiling a beta version website designed to help consumers find the appropriate federal or state agency to help them with mental health and substance use disorder parity complaints, appeals, or other actions.

This post will not review the Task Force report itself, but rather focuses on the FAQs, which implement certain recommendations of the report. These FAQs supplement and clarify a number of FAQs and other guidance issued by the Departments in the past on MHSUD parity.

Tobacco Cessation Services

The first FAQ is really a request for information. The Affordable Care Act requires health plans and insurers to cover preventive services given an “A” recommendation by the United States Preventive Services Task Force (USPSTF). On September 22, 2015, the USPSTF updated its tobacco cessation “A” recommendation; the group recommended that “clinicians ask all adults about tobacco use, advise them to stop using tobacco, and provide both behavioral interventions and FDA-approved pharmacotherapy for cessation to adults who use tobacco.” The USPSTF further recommended that “[b]oth intervention types (pharmacotherapy and behavioral interventions) are effective and recommended; combinations of interventions are most effective, and all should be offered.” The USPTSTF recommendation identifies seven FDA-approved over-the-counter and prescription drugs that are effective for tobacco cessation; it also indentifies effective individual, group, and telephonic behavioral interventions.

Health plans and insurers must cover tobacco cessation services consistent with this recommendation without cost sharing for plan years beginning a year after the recommendation was made-that is, September 22, 2016. Even though the date for compliance has passed, the Departments request comments on whether plans and issuers may use reasonable medical management techniques to limit pharmaceutical tobacco cessation interventions available without cost-sharing, individually or in combination; the number of quit attempts that should be allowed per year or the duration of interventions; or the behavioral interventions available without cost sharing.

Mental Health Parity and Addiction Equity Act

The remainder of the FAQs deal with the Mental Health Parity and Addiction Equity Act of 2008 (MHPAEA). The MHPAEA provides that group health plans and insurers that offer mental health or substance use disorder (MH/SUD) service benefits may not impose financial requirements and quantitative and non-quantitative treatment limitations (NQTLs) that are more restrictive than the predominant financial requirements and treatment limitations that they apply to substantially all medical and surgical benefits. The FAQs address in detail what these requirements mean.

Disclosure Of MH/SUD Medical Necessity Determinations And Reasons For Claims Denials

The requirements of the MHPAEA can only be enforced if the financial requirements and treatment limitations imposed by an insurer are health plan are known. The MHPAEA requires, therefore, the health plans and insurers disclose their criteria for MH/SUD medical necessity determinations and reasons for claim denials to consumers, providers, and regulators. Information on standards applied for medical benefits may also be necessary to perform parity analysis. The FAQs ask whether model forms for requesting disclosures would be helpful to consumers, providers, and regulators, and whether additional steps would be helpful to ensure compliance with disclosure requirements. The FAQs specifically cite the portal mentioned above which consumers can use to identify the federal or state agency that can help with disclosure requirements and appeals.

The financial parity requirements of the MHPAEAA prohibit group health plans or insurers from imposing financial requirements (such as copayments or coinsurances) or quantitative treatment limitations (such as day or visit limits) on MH/SUD benefits in a classification (such as inpatient or outpatient treatment or prescription drugs) that are more restrictive than the predominant levels that apply to substantially all medical and surgical benefits in the classification of services. A requirement is considered to apply to substantially all medical/surgical benefits in a classification if it applies to at least two-thirds of all medical/surgical benefits in the classification. If it does not apply to at least two-thirds of medical/surgical benefits, it cannot be applied to MH/SUD benefits in that classification.

Financial Requirements And Quantitative Treatment Limitations

If a financial requirement or quantitative limitation does apply to at least two-thirds of medical/surgical benefits in a classification, the level that may be applied to MH/SUD benefits in the classification may not be more restrictive than the predominant level that applies to medical/surgical benefits (defined as the level that applies to more than one half of medical/surgical benefits subject to the limitation in the classification). The determination of the portion of medical/surgical benefits subject to the quantitative limit is based on the dollar amount of all plan payments for medical/surgical benefits in the classification expected to be paid under the plan for the plan year. The MHPAEA regulations provide that “any reasonable method” may be used to determine the dollar amount of all plan payments.

The FAQs discuss at length how these determinations are to be made for small plans that lack sufficient claims volume to provide credible projections for the predominant levels that apply to substantially all claims. In these situations, the plan should not rely on data from its insurer or third party administrator's larger book of business, but should rather have a qualified actuary use a reasonable method for making projections, using data from similar plans with similar demographics and documenting assumptions used for the projections.

Non-Quantitative Treatment Limits

The remaining FAQs deal with non-quantitative limits. A plan or insurer cannot impose a NQTL with respect to MH/SUD benefits in a classification unless under the terms of the plan as written and in operation, any processes, strategies, evidentiary standards, or other factors used in applying the NQTL to MH/SUD benefits in the classification are comparable to, and are applied no more stringently than, those applied to medical/surgical benefits in the classification. Several of the FAQs address drugs that are used for treating opioid addiction.

The FAQs clarify that:

• A plan or insurer may not require an enrollee to be examined in person by a representative of the plan prior to a MH/SUD inpatient admission if enrollees can be admitted for medical/surgical services with only a telephone interview;


• A plan or insurer may not require an enrollee to participate in an intensive outpatient treatment program for MH/SUD before an inpatient admission, even though the same requirement is applied for medical/surgical services, if no such program is available for MH/SUD treatment in the enrollee's area;


• A plan or insurer may not impose prior authorization or “fail-first” requirements for drugs used for treating opioid addiction if these requirements are not imposed on drugs used for treatment of medical/surgical conditions that have similar risks or indications;


• A plan or insurer may not impose prior-approval for 30 day refills of opioid addiction treatment drugs, a requirement not consistent with nationally recognized treatment guidelines, if it follows nationally recognized treatment guidelines for requiring prior authorizations for medical/surgical drugs; and


• Plans and insurers may not exclude coverage for court-ordered SUD treatment if they do not exclude coverage for court ordered medical/surgical treatment, but may require that court-ordered treatment be medically necessary.

Et Tu, Dr. Noseworthy?

By NIRAN AL-AGBA,MD

Should patients fire their doctors if they suspect burnout? 

In a recent PBS interview, Mayo Clinic CEO Dr. John Noseworthy suggested patients should “change physicians” when faced with non-empathetic doctors suffering from burnout.  His cavalier resolution to our occupational struggle feels like a betrayal, to both his esteemed colleagues across the country and our profession.  In my opinion, firing your physician is a risky proposition in light of the looming physician shortage.  

 

Burnout is an overwhelming sense of disillusionment a physician experiences when the practice of medicine holds no joy.  It is not a psychological problem, yet can lead to a downward spiral of impairment.  According to a recent article in US News, almost half of physicians have symptoms of burnout. Seven percent of physicians aged 29-65 contemplated suicide in the last year.  These statistics are troubling on many levels.

Over half of current physicians state if given the opportunity to choose again, they would not choose medicine as a career.  Why?  Our once noble profession has lost its magnificence in an explosion of technology, nonsensical regulations, and increased clerical burden.  According to a study in the Annals of Internal Medicine, for every one hour of patient contact, a physician spends two hours doing administrative work.  Never-Had-a-Bad-Day-Noseworthy said, “EHR's are not easy to use.”  Why are physicians being required [forced] to utilize useless technology if it does not reduce burnout while improving efficiency and care quality? 

Look, we sacrificed our youth seeking delayed gratification that may never come; physicians have responsibility, but no authority, and vast quantities of knowledge, yet no autonomy. Sadly, we have ceded it to arrogant administrators running amok in a system of unfettered capitalism.  Regrettably, this oppression has taken a toll on us all, patients included.

How did physician burnout become linked to increased medical errors?  A study examined the relationship between the burnout experienced by surgeons and frequency of medical errors.  The more exhausted and depersonalized your physician has become the greater your likelihood of experiencing a medical error. 

How common are these so-called medical errors?  Last May, the British Medical Journal released a study ranking medical errors as the third leading cause of death in the U.S., after heart disease and cancer, killing 250,000 people a year. From my perspective, an overwhelming workload also plays a significant role.  A recent study in JAMA found increasing a nurses' workload from four to six patients increases the death rate by 14 percent, while going from six to eight patients is tied to a 31 percent increase in death rate.  The wheel is turning, but the hamster is dead, literally. 

If a physician is suffering from burnout, let us walk through the conversation Dr. Noseworthy is so naively proposing. 

Patient:  “Doc, You are not as empathetic as you used to be.  I am thinking about changing physicians?” 

Physician:  “Well, what exactly is the problem?” 

Patient:  “Well you used to spend more time with me at appointments and seemed to care.”

Physician:  “I wish there was more time to talk. I sure loved my job back then…”  (Sigh.  Continual tapping of computer keys heard in the background while trying to seem empathetic.)   

Valuing the physician-patient relationship allows it to be a central transformative therapeutic force.  Obamacare expanded coverage for almost 20 million Americans seemingly overnight.  Patient volumes doubled due to the unprecedented surge in insurance coverage?  There were not enough physicians in reserve to care for the overwhelming onslaught especially in underserved rural areas; most of us on the front lines are drowning in paperwork, administrative and regulatory burdens.  Being a physician under current circumstances is like trying to get a sip of water out of a fire hose.  Every physician in this country is on the train barreling toward burnout.    

Last week, I referred four different patients to four different local pediatric specialists.  Three of those four physicians called to let me know they are retiring at the end of the year.  With all due respect to Dr. Noseworthy, at the rate things are going, firing your physician will land a patient in medical limbo until they can find a physician desperate enough to accept them.  This man is so out of touch with reality outside the ivory tower, he is completely oblivious to the larger implications of the looming physician shortage. 

According to the Association of American Medical Colleges report, the projected shortage will reach 85,000 physicians by 2020.  In Will the Last Physician in America Please Turn Off the Lights, three co-authors from Merritt, Hawkins & Associates say the wait to see a physician will jump to three to four months for a non-emergent visits, and it will cost two to three times what it does now–whether you are insured or not. Guess what? I am already at the three month mark for non-emergent appointments and struggling to keep up with the growing patient demand. 

Physicians are resilient to a fault, coupled with stoic demeanors, inquisitive minds, and strongly empathetic natures, but we all have our limits.  Reducing burnout will only be feasible when we have more independence over the particulars of our self-sacrificing occupation.  If every physician in this country insisted on caring for patients as we saw fit and refused to click even one more box, a revolution would ensue.  We must stop “rolling over” when asked to do more with fewer resources, reduced pay, and even less time.  Physicians must put on their own oxygen masks before helping others with theirs.   

Despite his insulting recommendation, Dr. Noseworthy might actually be on our side.   “Physicians are highly dedicated professionals, who are good people, but have been crushed [by the system.]”  Do not allow yourself to be destroyed by a system we cannot control.  Take back medicine for yourself and your patients.  Know your value.  Do not bend to the demands of managers and administrators; refuse to accept a workload that prohibits attaining occupational jubilation and enlightenment. 

There is an impending crisis no one has foreseen; the winds are about to shift in our direction. Rules of supply and demand are universal. Soon, it will be a “physicians market”; we will cherry pick patients based on their having good insurance, a healthy medical profile, and a pleasant demeanor. 

Let us circle back to Dr. Noseworthy, “Change physicians.  It is too risky to be cared for by someone who is impaired.”  You know what is more risky than that?  It is having no physician at all when you desperately need one.  My advice is to build a relationship with a physician while you still can.  If your physician is not empathetic or appears to be suffering from burnout, my cautionary recommendation is to be careful what you wish for, because you just might get it.

Niran al-Agba, MD is a pediatrician based in Washington state.

 

 

Boerhaave's syndrome

Boerhaave's syndrome: Spontaneous tearing and rupture of the esophagus. Typically, Boerhaave's syndrome requires an operation for repair.

MedTerms (TM) is the Medical Dictionary of MedicineNet.com.
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Hallermann-Streiff syndrome

Hallermann-Streiff syndrome: a rare congenital condition characterized by abnormalities of the skull and bones of the face; characteristic facial features; sparse hair; degenerative skin changes; eye abnormalities; dental defects, and proportionate short stature. Some affected people have intellectual disability. The condition has also been referred to as HSS or Hallermann Streiff Francois syndrome. The abnormal facial features can include a short, broad head (brachycephaly), a prominent forehead and/or sides of the skull (frontal bossing); a small lower jaw (micrognathia); a narrow, highly arched palate; and a thin, pinched, tapering nose (beaked nose). The genetic cause of Hallermann-Streiff syndrome is not understood and most cases occur randomly for unknown reasons (sporadically).

MedTerms (TM) is the Medical Dictionary of MedicineNet.com.
We Bring Doctors' Knowledge To You

Join Us For A #CultureofHealth Briefing

In 2014 the Robert Wood Johnson Foundation launched its quest to create a “Culture of Health,” a new approach to the interconnected nature of health and social issues, with major implications for health policy and health philanthropy.

The November 2016 thematic issue of Health Affairs is devoted to the topic of Culture of Health - our contribution to understanding this new vision. In the issue we attempt to answer some of the questions that come along with the endeavor: How will we know when we have created a culture of health, if and when we do? How do we map culture, a term many of us associate with anthropology, onto the specialized language of health policy, health care, and health services research?

You are invited to join us for a forum on Thursday, November 10, 2016 at the Capital Hilton in Washington, D.C., at which we will discuss the issues in detail.

Register today!

Follow Live Tweets from the briefing @Health_Affairs, and join in the conversation with #CultureofHealth. 

Premium Hikes in the Exchanges: Not Good News, But Not the End of Obamacare Either

By STEVEN FINDLAY

OK.  Yes, this is bad.  The Obama administration is being disingenuous if it tries to spin it any other way.   And, as has been clear for several months, this hands Hillary a “nasty” issue (pun intended). 

The “this,” of course, is the administration's announcement on Oct. 24-after weeks of speculation and anticipation-that premiums in the exchanges will rise by an average 22% for 2017 coverage (if both state- and federally-run exchanges are included in the count.)

Despite the fact that tax subsidies will significantly soften the blow for the vast majority of people buying health insurance in the exchanges, millions of families will still be adversely affected.  

Specifically, about 2 million people who will buy coverage through the exchanges in 2017 will not get subsidies because their incomes are too high.  You could argue: hey, they can afford it.  But it's still a pretty big hit when your monthly premium goes from $500 a month to $625.   

Less well understood and hardly mentioned in the media coverage is that some 7 million people buy “off-exchange” individual insurance.  Premiums for many if not most in this group are going to spike up, too, and from an already more expensive base.   (Off-exchange policies have to comply with ACA requirements and are for the most part comparable to policies sold on the exchanges.)

According to a blog by Katherine Hempstead posted Oct 24, the average off-exchange policy costs $314 in 2016, compared to an average $279 for an unsubsidized on-exchange silver premium.  Deductibles were higher, too, for the off-exchange policies, averaging above $3,000.   

We don't yet know what the 2017 increases are for off-exchange coverage because no one has done that analysis.  It's a tough analysis, too, because there are-wait for it-over 13,000 unique ACA-compliant individual market products nationwide sold off-exchange.  (Additionally, there were nearly 30,000 small group plans nationwide in 2016, of which nearly 90 percent were “off exchange” according to Hempstead's piece.)   

To quote from her blog:  we badly need to better understand “the extent to which the individual market is appropriately priced… in both market segments.  While the federal and state exchanges….have done much to present comprehensive information to consumers about on-exchange plans, similar information has thus far been lacking for off-exchange and small group plans.”   

Despite the bad news, Republican lawmakers' fulminations about this year's premium hikes being the beginning-of-the-end for Obamacare are vastly overstated. 

As has been noted in most of the coverage, the range of the percentage increase varies widely from state to state.  In 10 states, for example, premium increases are 7 percent or less.  In two (Indiana and Massachusetts), premiums are actually decreasing.

Also, the states (mostly red/Republican-led) where consumers are getting hit the hardest are, predictably, those that have not expanded Medicaid and where lawmakers did nothing to create their own exchange or help get people enrolled.   

So, Republican lawmakers still opposed to the ACA in those states are being even more disingenuous than Obama administration officials-since their actions have ended up hurting their own citizens.   All for the sake of political posturing.  As a recent Kaiser Family Foundation analysis found: of the 27 million people who still don't have health insurance in the U.S., about 5.3 million would be eligible to buy coverage through an exchange and qualify for a federal tax subsidy. 

Several million more would gain Medicaid coverage if the 19 states that have not expanded that program do so-especially Texas and Florida, which have large pockets of low income, uninsured people.    

The other reasons some exchanges are struggling have been widely discussed, including on THCB.   And ideas for fixes are starting to emerge and be debated at the state and federal level.  For example, several states are now debating taking urgent action in 2017 to create reinsurance pools to shore up their exchanges. 

See Peter Lee's excellent Oct. 24^th blog on how and why California's exchange has succeeded to date and his advice for addressing problems in other states.  Peter runs the California exchange. 

The overall challenge is political, of course.  If Hillary becomes president and the Senate remains split (as expected), repealing Obamacare continues to be a legislative non-starter.  Republicans (state-level and in Congress) will then have to decide whether to work with the new administration to fix flaws in the exchanges and help millions of families….or persist in their opposition.  We can only hope sanity prevails.    

Addendum:  For a detailed portrait of predicted exchange enrollment in 2017, see ASPE's 17-page policy brief released Oct. 19.  ASPE is HHS' Office of Assistant Secretary for Planning and Evaluation.   

Steven Findlay is an independent healthcare journalist, policy analyst, researcher and consumer advocate.    

Artificial Patients need Artificial Intelligence; The Sick and Worried Amongst Us Deserve Better

ByROBERT MCNUTT, MD and NORTIN HADLER, MD 

Every conversation with a patient is an exercise in the analysis of “big data.” The patient's appearance, changes in mood and expression, and eye contact are data points. The illness narrative is rich in semiotics: pacing, timing, nuances of speech, dialect are influenced by context, background, and insight which in turn reflect religion, education, literacy, numeracy, life experiences and peer input. All this is tempered by personal philosophy and personality traits such as recalcitrance, resilience, and tolerance. Taking a history, by itself, generates a wealth of data but that's just the start.

Add into the mix physical findings of variable reliability, laboratory markers of variable specificity, imaging bits and bytes and you have “big data.” Then you mine this data for the probabilistic variance of the potential causes of a complaint based on which you begin to consider values for numerous options for care. So armed, the physician next needs to factor the benefits and harms of multiple treatments' derived from populations that never perfectly reflect the situation of the individual in the chair next to us, our patient. This is the information necessary to empower our patient to make rational choices from the menu of options. That is clinical medicine. That is what we do many times a day to the best of our ability and to the limits of our stamina.

Take that Watson. You need a lot more than 90 servers and megawatts of electricity to manage our bedside rounds. You need to contend with the gloriously complicated and idiosyncratic fabric of human existence. Poets might be a match, but Watson is not.

Watson is doomed not just from its limited technical sufficiency compared our cognitive birthright. Even if Watson could grow its server brain to match ours, it won't be able to find measurable quantities for the independent variables captured during a patient encounter nor the role of personal values that temper that patient's choice. Life does not have independent and dependent variables; the things that matter to us are on both sides of a regression model. Watson needs rules to violate this statistic and there are none that generalize. Somehow, our brains have a measuring instrument that no data query can find or measure and that we innately understand but can't fully communicate. Also, our brains seem to intuitively understand statistics; our brains know that the variations around the regression lines (residuals) mean more to us than the models themselves. Sure, if there is something discrete to know, a simple, measurable deterministic item, or an answer to a game show question, Watson will kick most, and maybe all, of our butts. But, what if what is important to us is not deterministic, nor discrete? What if life is more importantly measured in “when” than “if”? And what if the “when, and how we feel about the when” are intertwined? What if medical life is not even measured in outcomes, but, instead, relationships that foster peaceful moments? In this reality, Watson will be lost.

Watson is doomed on yet another level beyond a dearth of “code friendly” meaningful measures of humanity. It is doomed in that it is capable of reading the “World's Literature”. Our desires and motives to improve the care of individuals is being buried in reams of codependent, biased, unrestricted, marketed, false positive or false negative associated, and poorly studied information that sees the light of Watson's day because it can read every report published in the massive number of nearly 20,000 biomedical journals. A “60 Minutes” report on AI reveled in Watson's prowess at searching the literature. We can't substantiate one particular quote in the report, and bet the quoted can't either, that there are 8000 research reports published daily. But, that is Watson's problem. Watson fails to recognize that it is more important to know what we should not read rather than to be able to read it all. There is just too much precarious information being perpetrated on unsuspecting readers, whether the readers have eyes or algorithms.

Science is the glue that holds medical care together but it is far from a perfect adhesive. We have both served long tenures on the editorial boards of leading general and specialty clinical journals. We have many an anecdote about the rocky relationship between medical care and the science that informs it. An anecdote from Dr. McNutt serves as a particularly disconcerting object lesson. He commented on a paper being brought for publication, a paper that he argued should be rejected because it was a Phase 2 study. The study was not fatally flawed by design, just premature, as many Phase 2 studies fail to be replicated after better-designed Phase 3 studies are performed. Science is about accuracy and redundancy and timelessness and process, not expediency. Despite his arguments the paper was published and became highly cited. Sure enough a better-designed Phase 3 study rejected the hypothesis supported by the Phase 2 study vindicating Dr. McNutt on this occasion. But that is not the point. The point is that Watson knows of both studies. You only need to know one of them. How did Watson handle the irreproducible nature of the studies and their contrary insights? One might wonder if the negative study was cited as often as the positive, premature study. Watson would know.

Are we being too tough on AI? We are not writing about Watson's specific program but, instead, using it as a metaphor for big data analytics and messy regression models. It is not clear if Watson has been tested in a range of clinical situations where inherent uncertainty prevails.  No pertinent randomized trials are cited when “Watson artificial intelligence” is entered into “PubMed”. There are attempts to match patients to clinical studies, but no outcome studies. This is important since that 60 Minute episode told of a patient who was treated after a “recommendation” from Watson. We assume that the treatment met ethical standards for a Phase 1 study and that the patient was fully informed. We are left to assume, also, that the information found by AI was reliable and adequately tested.  After all, this compliant-with-Watson, yet unfortunate patient succumbed to an “infection” several months after receiving the treatment.  We worry about the validity of the information spewed by the algorithm and how on earth the researchers planned to learn anything about the efficacy of the proposed intervention from treating their patient. Science requires universal aims and adequate comparisons. In our view, any AI solution for any patient should be subjected to stringent, publicly available scientific testing. AI, to us, is in dire need of Phase 1 testing.

Science can be better. Watson will not advance science, scientific inquiry will. Better designs for clinical care and insights from scientific data need to be developed and implemented. We do not need massive amounts of data, just small amounts gathered in thoughtfully planned studies. And with better science, we will not need AI. Instead of banking, or breaking the bank, on AI, we should use our remarkable brains to learn by rigorous scientific enquiry and introduce valid scientific insights into the “big data” dialogue we call the patient's “history” and do so in the service of what we call “patient care.” Watson and other systems may be able to do a wonderful job determining what books we buy, and, from a medical perspective, it might be able to pick a particular antibiotic given a known infection due to the deterministic nature of that task. But, treating infection, as an example, is a small data part of what we do; we help sick people and for that big data task, Watson will, in our view, not be sufficiently insightful.

Examining The Nurse Pipeline: Where We Are And Where We're Headed

Nurses play a central role in our health care system. Key factors determining the future supply of nurses are the number who are being educated by US nursing programs and the number entering the US after graduating from foreign nursing programs. The number of first-time takers of the National Council Licensure Examination (NCLEX), a prerequisite to become licensed as a Registered Nurse (RN), provides a good metric for the number of new nurses.

The National Council of State Boards of Nursing (NCSBN), the sponsor of the NCLEX, publishes data quarterly on the number of exam takers and pass rates. While the NCSBN publishes data for first-time and repeat exam takers, the vast majority of first-time takers end up passing the exam. The data presented below-which updates my post from last year-is for first-time exam takers only, as that data represents a simpler, easy-to-understand metric of the pipeline of new nurses. First-time takers are also a direct reflection of the output of the nation's nursing programs.

Parsing The Numbers: Varying Trends Underneath An Overall Leveling Off Of Growth Well Above Historical Levels

After 14 years of steady growth, the number of newly educated registered nurses in America appears to be leveling off. According to the NCSBN, the number of first-time takers in 2015 (157,843) decreased very slightly compared to the number in 2014 (157,879) (Figure 1). Even with this leveling off, the 2015 number is 130 percent higher than the first-time takers in 2001 (68,700).

The trends are very different for baccalaureate (BSN) and associate degree (AD) exam takers. BSN programs require four years of education while Associate Degrees (AD) require two years. “Diploma” graduates from hospital-based programs generally require about two years of education and training.

BSN first-time exam takers continued their steady, long-term growth, increasing by 2,142 in 2015 to 70,857, a growth of 3.1 percent compared to 2014. This was the 14th year of steady growth for this group, with 2015 numbers up 186 percent over 2001 (Figure 2).

By contrast, for the second year in a row, the number of first-time associate degree exam takers decreased, down nearly 2,000, or 2.3 percent, in 2015 compared to 2014 (Figure 2). This could reflect a tightening job market for AD nurses, which would be consistent with anecdotes of new ADs having a more difficult time finding a job than BSNs. It is too early to know whether this is the beginning of a long-term trend.

The number of new diploma-prepared nurses entering the pipeline continues to decrease. After rising between 2001 and 2006, at the height of the nursing shortage, the number has generally been declining and is down by nearly a third since 2010.

The number of new foreign-educated RNs taking the NCLEX rose to its highest level in hour years. However, it is too soon to know if this is the beginning of a new trend, and the total is still only about a quarter of the peak reached in 2007 (Figure 3).

Progress And Remaining Challenges

Progress On Tackling Predicted Nursing Shortage; Projections Vary By Community

In response to concerns with nursing shortages in the early 2000s, there was a concerted effort to increase the number of new nurses. The nation's nursing programs have clearly responded. A recent projection of the future supply and demand for registered nurses by the federal Health Resources and Services Administration finds that some communities are likely to face a surplus, although others will likely face a shortage. One implication is that efforts to spur future growth of the pipeline should be targeted to specific communities, rather than across all communities.

Progress On Increasing Percentage Of Baccalaureate Nurses But Work Remains To Meet Goal

The 2010 Institute of Medicine report, The Future of Nursing: Leading Change, Advancing Health, recommended that 80 percent of the nursing workforce have a BSN by 2020. Clearly, a growing number of registered nurses in the US have a BSN: BSNs now represent 46 percent of new exam takers, compared to 36 percent in 2001. The steady growth in BSN first-time takers and the decrease in AD first time-exam takers have narrowed the gap that previously existed in terms of the source of new nurses (Figure 4). If the number of first-time US-educated BSN exam takers in 2015 (70,857) is combined with the more than 56,000 registered nurses who completed RN to BSN programs, the annual BSN pipeline (126,857) far exceeds the 84,379 AD first-time takers.

If current trends continue, in the near future half of new nurses may be entering the field with a BSN. Moreover, according to the Association of American Colleges of Nursing (AACN), the number of existing registered nurses with associate degrees and diplomas completing their BSN degree has been growing rapidly. However, it will take many more years before 80 percent of RNs have BSNs.

Progress On Lessening Nursing 'Brain Drain' Despite 2016 Backslide

The continued low number of foreign-educated nurses taking the NCLEX compared to the mid-2000s-even with the 2016 increase in foreign-educated nurses-is consistent with the World Health Organization's Global Code of Practice on the International Recruitment of Health Personnel signed by the US and 191 other countries in 2010. The Code of Practice called for all countries to do a better job of educating and training the health workers they need rather than taking health professionals from less developed countries.

In 2015, international nursing graduates represented only about 5 percent of first time NCLEX takers. This is very modest in comparison to the 23 percent of the physicians entering graduate medical education in 2014-15 who were graduates of foreign medical education.

Figure 1

Figure 2

Figure 3

Figure 4

Computer vs. Patient

By NORTIN HADLER, MD and ROBERT MCNUTT, MD

Every conversation with a patient is an exercise in the analysis of “big data.” The patient's appearance, changes in mood and expression, and eye contact are data points. The illness narrative is rich in semiotics: pacing, timing, nuances of speech, dialect are influenced by context, background, and insight which in turn reflect religion, education, literacy, numeracy, life experiences and peer input. All this is tempered by personal philosophy and personality traits such as recalcitrance, resilience, and tolerance. Taking a history, by itself, generates a wealth of data but that's just the start.

Add into the mix physical findings of variable reliability, laboratory markers of variable specificity, imaging bits and bytes and you have “big data.” Then you mine this data for the probabilistic variance of the potential causes of a complaint based on which you begin to consider values for numerous options for care. So armed, the physician next needs to factor the benefits and harms of multiple treatments' derived from populations that never perfectly reflect the situation of the individual in the chair next to us, our patient. This is the information necessary to empower our patient to make rational choices from the menu of options. That is clinical medicine. That is what we do many times a day to the best of our ability and to the limits of our stamina.

Take that Watson. You need a lot more than 90 servers and megawatts of electricity to manage our bedside rounds. You need to contend with the gloriously complicated and idiosyncratic fabric of human existence. Poets might be a match, but Watson is not.

Watson is doomed not just from its limited technical sufficiency compared our cognitive birthright. Even if Watson could grow its server brain to match ours, it won't be able to find measurable quantities for the independent variables captured during a patient encounter nor the role of personal values that temper that patient's choice. Life does not have independent and dependent variables; the things that matter to us are on both sides of a regression model. Watson needs rules to violate this statistic and there are none that generalize. Somehow, our brains have a measuring instrument that no data query can find or measure and that we innately understand but can't fully communicate. Also, our brains seem to intuitively understand statistics; our brains know that the variations around the regression lines (residuals) mean more to us than the models themselves. Sure, if there is something discrete to know, a simple, measurable deterministic item, or an answer to a game show question, Watson will kick most, and maybe all, of our butts. But, what if what is important to us is not deterministic, nor discrete? What if life is more importantly measured in “when” than “if”? And what if the “when, and how we feel about the when” are intertwined? What if medical life is not even measured in outcomes, but, instead, relationships that foster peaceful moments? In this reality, Watson will be lost.

Watson is doomed on yet another level beyond a dearth of “code friendly” meaningful measures of humanity. It is doomed in that it is capable of reading the “World's Literature”. Our desires and motives to improve the care of individuals is being buried in reams of codependent, biased, unrestricted, marketed, false positive or false negative associated, and poorly studied information that sees the light of Watson's day because it can read every report published in the massive number of nearly 20,000 biomedical journals. A “60 Minutes” report on AI reveled in Watson's prowess at searching the literature. We can't substantiate one particular quote in the report, and bet the quoted can't either, that there are 8000 research reports published daily. But, that is Watson's problem. Watson fails to recognize that it is more important to know what we should not read rather than to be able to read it all. There is just too much precarious information being perpetrated on unsuspecting readers, whether the readers have eyes or algorithms.

Science is the glue that holds medical care together but it is far from a perfect adhesive. We have both served long tenures on the editorial boards of leading general and specialty clinical journals. We have many an anecdote about the rocky relationship between medical care and the science that informs it. An anecdote from Dr. McNutt serves as a particularly disconcerting object lesson. He commented on a paper being brought for publication, a paper that he argued should be rejected because it was a Phase 2 study. The study was not fatally flawed by design, just premature, as many Phase 2 studies fail to be replicated after better-designed Phase 3 studies are performed. Science is about accuracy and redundancy and timelessness and process, not expediency. Despite his arguments the paper was published and became highly cited. Sure enough a better-designed Phase 3 study rejected the hypothesis supported by the Phase 2 study vindicating Dr. McNutt on this occasion. But that is not the point. The point is that Watson knows of both studies. You only need to know one of them. How did Watson handle the irreproducible nature of the studies and their contrary insights? One might wonder if the negative study was cited as often as the positive, premature study. Watson would know.

Are we being too tough on AI? We are not writing about Watson's specific program but, instead, using it as a metaphor for big data analytics and messy regression models. It is not clear if Watson has been tested in a range of clinical situations where inherent uncertainty prevails.  No pertinent randomized trials are cited when “Watson artificial intelligence” is entered into “PubMed”. There are attempts to match patients to clinical studies, but no outcome studies. This is important since that 60 Minute episode told of a patient who was treated after a “recommendation” from Watson. We assume that the treatment met ethical standards for a Phase 1 study and that the patient was fully informed. We are left to assume, also, that the information found by AI was reliable and adequately tested.  After all, this compliant-with-Watson, yet unfortunate patient succumbed to an “infection” several months after receiving the treatment.  We worry about the validity of the information spewed by the algorithm and how on earth the researchers planned to learn anything about the efficacy of the proposed intervention from treating their patient. Science requires universal aims and adequate comparisons. In our view, any AI solution for any patient should be subjected to stringent, publicly available scientific testing. AI, to us, is in dire need of Phase 1 testing.

Science can be better. Watson will not advance science, scientific inquiry will. Better designs for clinical care and insights from scientific data need to be developed and implemented. We do not need massive amounts of data, just small amounts gathered in thoughtfully planned studies. And with better science, we will not need AI. Instead of banking, or breaking the bank, on AI, we should use our remarkable brains to learn by rigorous scientific enquiry and introduce valid scientific insights into the “big data” dialogue we call the patient's “history” and do so in the service of what we call “patient care.” Watson and other systems may be able to do a wonderful job determining what books we buy, and, from a medical perspective, it might be able to pick a particular antibiotic given a known infection due to the deterministic nature of that task. But, treating infection, as an example, is a small data part of what we do; we help sick people and for that big data task, Watson will, in our view, not be sufficiently insightful.