The Changing Landscape of Health Information Regulation

There is an impressive new issue of the American Journal of Law & Medicine out, with top names in the field participating in a symposium entitled “Marketing Health: The Growing Role of Commercial Speech Doctrine in FDA Regulation.”  I also wanted to recommend a piece from Simon Stern and Trudo Lemmens on pharma ghostwriting, which is getting a lot of play in Canada.  Titled “Legal Remedies for Medical Ghostwriting: Imposing Fraud Liability on Guest Authors of Ghostwritten Articles,” the piece could lead to some interesting litigation opportunities.  Here is the abstract:

Ghostwriting and guest authorship of medical journal articles raise serious ethical and legal concerns, bearing on the integrity of medical research and evidence used in legal disputes. Ghostwriting involves undisclosed authorship, usually by medical communications agencies or a pharmaceutical sponsor of the published research; guest authorship involves taking authorial credit for the published work without making a substantial contribution to it. Commentators have objected to these practices because of concerns involving bias in ghostwritten clinical trial reports and review articles. We also note the effects of ghostwritten articles on questions involving the legal admissibility of scientific evidence. Efforts to curb ghostwriting practices, undertaken by medical journals, academic institutions, and professional disciplinary bodies, have thus far had little success and show little promise.These organizations have had difficulty adopting and enforcing effective sanctions, for specific reasons relating to the interests and competencies of each kind of organization.

Because of those shortcomings, a useful deterrent in curbing the practice may be achieved through the imposition of legal liability on the ‘guest authors’ who lend their names to ghostwritten articles. We explore the doctrinal grounds on which such articles might be characterized as fraudulent. A guest author’s claim for credit of an article written by someone else constitutes legal fraud, and may give rise to claims that could be pursued in a class action based on the Racketeer Influenced and Corrupt Organizations Act (RICO). The same fraud could support claims of “fraud on the court” against a pharmaceutical company that has used ghostwritten articles in litigation. This doctrine has been used by the U.S. Supreme Court to impose sanctions on the authors and corporate sponsors of a ghostwritten article. We discuss the potential penalties associated with each of these varieties of fraud.

This promises to inspire some difficult legal challenges to industry practices that have long been considered undesirable as a policy matter.

Beyond Innovation and Competition, Health IT Edition

Last year I published a piece called “Beyond Innovation and Competition,” questioning the dominance of those values. Economists celebrate innovation and competition as the main source of future growth. Innovation has become the central focus of Internet law and policy. While leading commentators sharply divide on the best way to promote innovation, they routinely elevate its importance. Business writers have celebrated search engines, social networks, and tech startups as model corporations, bringing creative destruction and “disruptive innovation” in their wake. Maximum innovation is the goal, and competition is billed as the best way of achieving it. Players in the vast and dynamic tech marketplace are supposed to constantly strive to innovate in order to attract consumers away from rivals.

In the piece, I explain how both competition and innovation can be as destructive as they are constructive. There are many social values (including privacy, transparency, predictability, and stability), and companies can compete for profits in ways that erode those values. In an era of inequality and hall-of-mirrors stock market valuations, innovations of marginal or negative impact on society at large can be vastly overvalued by a stampede of fickle investors.

The shortcomings of the innovation and competition story also play out in health information technology. Stimulus legislation in 2009 provided many carrots and sticks for doctors to digitize their recordkeeping systems, ranging from bonuses now to reimbursement haircuts later this decade if they fail to implement the technology. Congress structured the incentives to encourage a competitive and innovative marketplace in health information technology. But many doctors are shying away from implementation, in part because they fear that the fast and loose ethics of the market can’t mesh with a medical culture of constant commitment to quality care.

Susan Jaffe’s article for the Center for Public Integrity examines doctors’ fears about adopting any given software suite. According to Jaffe, “570 different electronic health systems certified by private organizations for non-hospital settings may be used to qualify for the” stimulus funds. The long-term consequences of the choice make the jam-shopping examples in Barry Schwartz’s book The Paradox of Choice seem quaint:

The systems can vary in appearance, content, organization and special features. Some can be customized by users in different ways, at no cost or some cost, or not at all. Some are compatible with other systems now, eventually or, some critics say, maybe never. . . . The costs of the systems remain daunting, despite the bonuses, particularly in areas that have been hit hard by an ailing economy.

The pricetag varies widely depending on the type and size of the medical practice, whether new computers are purchased and the extent of customization, among other things. Software alone can cost from $2,000 to $10,000 per doctor. All told, the cost jumps to about roughly $20,000 per doctor, according to a regional extension center consultant who advises physicians in northeast Ohio. On top of that, manufacturers charge hefty annual fees for technical support and periodic upgrades that together can amount to about 35 percent of the upfront costs. The systems are priced in a way that does not make comparison shopping “easy or necessarily valid,” said Dottie Howe, a spokeswoman for the Ohio regional extension center. There is no basic price because each company offers different components, features, options, and level of technical support. . . .

Most manufacturers will also charge the doctors to move the information in their current system to the new one. There could be extra [ongoing, monthly] charges to connect to other systems too.

Doctors have also been burned by sharp operators that emphasize slick salesmanship over solid service:

[T]he Southwest Family Physicians group is worried . . . They bought an electronic health record system five years ago that is now nearly obsolete. The manufacturer was taken over by another company that provides minimal technical support . . . “The salesman said ‘you’re buying a Cadillac, this is going to be the greatest thing,’ ” [one doctor] recalled. But that system can’t display an X-Ray image or send a prescription electronically to a pharmacy. “We’ve got the Model T Ford,” he said.

It does appear that regional extension centers are doing some work to keep pricing reasonable. Jaffe’s article focuses on Ohio, where five “preferred vendors” “agreed to charge prices ‘as good as or better than’ prices offered to other regional extension centers, to provide onsite assistance when a practice turns on its electronic health record system for the first time, offer technical support for at least six years, and limit annual cost increases for continuing technical support, among other things.” But consider the bizarrely proprietary nature of pricing data:

Whether the five preferred vendors offer a better deal than their non-preferred competitors is not known because the state regional extension center doesn’t have pricing information from non-preferred vendors, said Howe, the spokeswoman for the state’s regional extension center. Pricing from the preferred vendors are confidential, she said. And despite their preferred status, the five companies do not guarantee that eligible health care providers who purchase their systems will receive the government’s bonus payments.

I discussed the troubling degree of secrecy in health care before, and I’m very sad to see it persist here. The doctors in Jaffe’s story are making reasonable demands: to be able to understand the nature of the commitment they are making, to avoid big financial losses, and not to be burned by fly-by-night operators attracted only by the government subsidy money. They want to assure that the basic health care values of access, cost-control, and quality are reflected in the software they use.

We are seeing the opening stages of a battle between a medical sector committed to maintaining its own autonomy and traditions, and a tech sector that wants to commoditize health data in as standardized a form as futures markets homogenized corn grades, or credit scores tranched residential mortgage backed securities. Commenting on the demise of Google Health, an informatics expert said that “Google is unwilling, for perfectly good business reasons, to engage in block-by-block market solutions to health-care institutions one by one, and expecting patients to actually do data entry is not a scalable and workable solution.” To be sure, the company can’t expect to make the same profit margins in the health sector as it does in the online ad business. But the “instant millions” ethos of Silicon Valley doesn’t fit well with a sector where we are in principle committed to serving everyone, regardless of ability to pay.

Economist John Van Reenen has observed that the US has a particularly innovative economy in part because our markets are so good at crushing badly run firms. It’s probably good that garden equipment suppliers, toothpaste makers, and pie bakers know they can be out of business in a month or two if they’re “off their game” for a short time. But if I just entrusted three years of medical records to a vendor who suddenly went out of business, I’d take little comfort in the idea that a marginally better competitor had knocked it out of the market. The transition to a new vendor can be slow and costly—doctors in Jaffe’s story speak of seeing 1/3 to 1/2 less patients over weeks or months as they learn a new system.

At a Yale SOM Health Care conference in 2009, the Chief Medical Officer of a major player in the field once remarked to me that choosing an HIT vendor is “like a marriage—you don’t end the relationship lightly.” I first thought that remark was self-serving. But the more one examines the HIT field, the more important it appears to get standard recordkeeping, support capabilities, and interoperability right at the outset, rather than leaving doctors to negotiate the wreckage of several generations of battling systems. Think about how chaotic online music sales seemed before iTunes. Perhaps Apple (whose iPads are already beloved by many docs) is going to bring a swift and highly profitable order to this field, too. I hope the ONC and other decisionmakers will well-regulate whatever behemoth eventually emerges, vindicating the public values that competition and innovation are unlikely to promote.

Photo credits to  Aleksandar Šušnjar, Jakub Halun and loki11.

Personal Health Records: Is Unraveling Inevitable?

I look forward to reconnecting with everyone who is attending the health law professors conference in Chicago.  My presentation will be applying some of the ideas of Scott Peppet (on self-quantification and unraveling) to personal health records.  I found these ideas from Peppet’s post on biometric identification particularly interesting:

The biometric technologies firm Hoyos (previously Global Rainmakers Inc.) recently announced plans to test massive deployment of iris scanners in Leon, Mexico, a city of over a million people. . . . [T]he company’s roll-out strategy is explicitly premised on the unraveling of privacy created by the negative inferences & stigma that will attach to those who choose not to participate. Criminals will automatically be scanned and entered into the database upon conviction. Jeff Carter, Chief Development Officer at Hoyos, expects law abiding citizens to participate as well, however. Some will do so for convenience, he says, and then he expects everyone to follow: “When you get masses of people opting-in, opting out does not help. Opting out actually puts more of a flag on you than just being part of the system. We believe everyone will opt-in.” (For the full interview, see Fast Company’s post on the project.)

I’ve previously looked at the limits of individualist accounts of autonomy in work on pharmaceuticals (here and here), and scholars like Robert Ahdieh are questioning individualism in law & economics generally.  As Nic Terry has argued, many of the critiques of CDHC apply to PHRs, and vice versa.

As of a few years ago, “it wasn’t illegal to hire and fire people based on their smoking habits” in 21 states. I think there will be many difficult questions raised in coming years by the growth of medical records of all types, and how many secondary uses of them are permitted.  For example, some dating sites will now verify the income and assets of their users.  How soon before they (and other certification and evaluation intermediaries) start vouching for health profiles?  Does law have a role in these situations?  I’ll try to explore these questions, and I’ll post more details about the presentation after getting some feedback.

It’s Not the ‘Shared Savings’, Stupid: Why ACOs Under the Proposed Rule Will Change Medicine As We Know It

CMS got the Medicare Shared Savings Program (MSSP) proposed rule largely right, but not because of the actual “shared savings” that the ACO model is commonly associated with. Rather, the MSSP will usher in a shift from the practice of medicine as primarily an art, to the practice of medicine as primarily a science.

The explosion over the last 50 years of drugs and devices — and the studies and guidelines concerning their effectiveness — is staggering. Couple this explosion with the lack of effective means for physicians and health care providers to make sense of the information, and it’s not surprising that we have a bloated, inefficient, and costly system that fails to provide value commensurate with our health care budget.

This systemic problem is no secret. The HITECH Act attempts to target the health information technology (HIT) problem with an incentive program, and PPACA attempts to increase evidence-based medicine (EBM) with projects like the Patient-Centered Outcomes Research Institute. But a piecemeal approach does not ensure the necessary integration between HIT and EBM, nor sufficient incentives for industry to embrace them.

Why such faith in the MSSP?

Because if ACOs want to participate in the shared savings they must meet the dual requirements of EBM and HIT. It’s this double-envelopment — combined with the ‘carrot’ of shared savings — that will finally usher in a medical revolution.

Thomas Kuhn, a trained physicist who is better known for his contributions to the philosophy of science , introduced the idea of “paradigm shifts” that occur as science evolves. In “The Structure of Scientific Revolutions,” Kuhn posits that instead of a linear evolution of scientific discovery, the discovery of anomalies can force traditional explanations of natural phenomena to be questioned. If enough anomalies accrue that seriously undermine an accepted explanation, a “crisis moment” occurs. In this circumstance “a scientist’s world is qualitatively transformed [and] quantitatively enriched by fundamental novelties of either fact or theory and a scientific revolution is born.” But as Kuhn notes — with import to our discussion of the MSSP — prior beliefs and experiences can make accepting a new paradigm difficult for scientists.

Kuhn’s theory of the evolution of science helps to explain health reform, or the lack thereof. Our health care paradigm — the spending of significant resources on health care per capita — has accrued significant anomalies, most notably outcomes that do not match up with our spending. We have tried HMOs, PPOs, and every many other types of arrangements, but to no avail. We are in a “crisis moment.” And we have a new paradigm: health care decision making that utilizes EBM at the point of care.

And that, my friends, is where the savings will ultimately be found.

A 2004 study demonstrated that following evidence-based guidelines for the treatment of hypertension in the elderly would save $1.2 billion annually.

There is no shortage of similar studies showing billions of dollars, and better health outcomes, waiting to be unlocked. So why isn’t it occurring?

A new review by Stanford University’s Adam Elshaug, M.P.H., Ph.D., and Alan Garber, M.D., Ph.D. demonstrates that recent studies on complex vertebral spinal procedures point have “cast doubt on the magnitude of any benefits from these procedures and at worst established their ineffectiveness.” The studies have caused payers like Blue Cross to limit or withdraw coverage of the procedure. After analyzing the data, the authors found that a conservative estimate of the savings of scaling down the costly and ineffective procedure would yield between $450 million and $725 million depending on the continued use of the procedures.

But the authors make a crucial point at the end of their piece:

Of course, savings will be derived from [comparative effectiveness research] CER only if practice changes. In the United States, it’s unclear whether these studies are powerful enough to overturn coverage decisions or cut utilization of established procedures. . . ACA features such as bundled payments, shared savings programs, and outcomes-based payments offer mechanisms for stimulating the adoption of practices that are supported by CER and the abandonment of practices that CER calls into question.

I interpret this as an acknowledgment that we have enough data to start saving money and increasing care, but that we are stuck in a rut where the practice of medicine itself is having troubling embracing science, and we are relying on the payers to pick up the slack.

This is not to say that medicine can ever — or should ever — become entirely science-based. There are embedded values in the process of health care decision making that science cannot determine, such as a patient’s desire for aggressive treatment and the risks or costs they are willing to incur. Regardless, there is a baseline degree of science-based medicine that will improve quality, afford greater patient (and physician) autonomy, and decrease cost. Moreover,  studies have shown that better informed patients make more cost-effective choices.

The problem is our inability and/or our unwillingness to embrace the inevitable paradigm shift to a greater science-based medicine even during a crisis moment. That is where the MSSP double-envelopment strategy comes in.

CMS’s Double-Envelopment Strategy: Attract with the Savings, Surround with EBM and HIT

The MSSP allows an ACO, each year, to recoup some of the savings that they have realized in reference to a benchmark cost. There is a fairly complicated procedure for determining the actual savings that the ACO can collect, but the idea is simple: incentivize the health care providers to reduce the cost of care. Health care organizations are racing to form ACOs, but while doing so they are being surrounded by EBM and HIT requirements that will drive a shift in health care delivery.

With respect to EBM, the proposed rule requires ACOs to implement evidence-based medicine or clinical practice guidelines and processes in an effort to improve individual care, improve the health of the population, and lower the growth of health care expenditures. The guidelines and processes must cover diagnoses with “significant potential” for the ACO to achieve quality and cost improvements, taking into account the circumstances of individual beneficiaries. All ACO participants and suppliers/providers must agree to abide by these guidelines and processes, and must be evaluated for their compliance. The rule also states that remedial actions must be a possibility for non-compliance, and ACOs must have policies and procedures for ACO expulsion of participants and/or providers/suppliers.

On the HIT side, ACOs are required to have an infrastructure, such as information technology (which may include EHR technology that is certified for CMS’s incentive-based meaningful use program). This infrastructure must enable the ACO to collect and evaluate data and provide feedback to ACO participants and ACO providers/suppliers across the entire ACO, including providing information to influence decision making at the point of care. Moreover, fifty percent of the primary care providers of an ACO must be “meaningful users” as defined by the HITECH Act by the second year of their ACO contract. As others have noted, the meaningful use requirement is extremely aggressive when considering that the proposed rule allows ACOs to come online as soon as Jan 1st, 2012. Industry has seen the writing on the wall, and has responded with nothing short of an ACO arms race.

The ACO-driven Paradigm Shift

Thus, the proposed rule requires ACOs to leverage HIT to evaluate data and provide feedback to others in the ACO, and do it in such a way that the feedback influences decision making at the point of care.  In other words, it is setting the stage for informed decision making for both physician and patient alike. This is the holy grail of health care reform: that is, an HIT network with users that are reporting data that can be leveraged to enable providers to suggest treatments that are proven to have better outcomes for their specific patient, and to do so at the point of care.

This is in contrast to the current paradigm of managing costs by relying primarily on ex post decision making at the payer level. Often, however, the consumer who has their desired procedure or drug denied (for reasons often opaque to either the physician, insurer, or patient) will decide to pay out of pocket, and can go bankrupt in the process. In this case, no costs have been reduced, rather, they have been shifted to the consumer. While some insurers create and use HIT and EBM, their behind-the-scenes decision making has not been embraced by physicians or patients. That’s because patients trust their physicians, not their insurers. The locus of reform must be on the decision making at the physician-patient level, and that is precisely where the proposed rule places it.

The proposed rule also clearly addresses the fact that you can’t get new practices adopted if physicians have to, for example, minimize their EHR application, fire up their web browser, and start searching the Cochrane Collaboration or some other site for possibly relevant data. They are going to have to do it from within the HIT system.

There is an added benefit politically to this paradigm shift: if the focus is on data-driven doctor-patient decision making, we bypass the political push and pull often associated with determining what treatment is “medically necessary.” This would satisfy the progressive ideal of providing high quality care without overbearing cost-control, while also satisfying the conservative refrain that the doctor-patient relationship remains independent. If the process of creating EBM decision making is HIT-focused, it also encourages the antithesis of cookbook medicine by tailoring the process to the individual patient.

The Long View

Too much focus has been placed on the short term issue of how much money the ACOs can recoup. This is a valid worry for the industry, particularly the smaller practices that can’t afford setting up an ACO. The federal government must do whatever it can to allay these worries so that industry further strives to create the HIT-EBM framework that the shared savings program envisions. If it means increasing the percentage of savings that the ACOs can receive, then so be it. Or perhaps ACOs should come online a year later after the meaningful use stage of EHRs has progressed.

Regardless of how the final rule mitigates industry difficulties, the ACO model is our best chance at creating a true paradigm shift that will better provide the medically necessary and efficient delivery of health care resources. It may take 5, 10, or 20 years to robustly develop the systems and the data, but nobody said a medical revolution would be easy.

Linnaean Regulation in Health Insurance and Information Technology, Part II

[Ed. note: This is the second part (perhaps evident from the title) of a two part post. Though each could well stand on its own, the first part can be found here.]

Insurance Reporting and Classification

Reporting requirements may not seem like a notable accomplishment. Nevertheless, the trend toward monitoring the products and services offered by insurance companies is an important step toward accountability. HHS needs to impose some order, some translatable logic, on fields that have threatened to become enormously parasitic and unproductive by or masking the true nature of their commitments.

Consider the practical illegibility of the average insurance plan. A vanishingly small number of subscribers actually read such plans. A plan may have complex cost-sharing requirements that vary among in-network and out-of-network primary care doctors, specialists, surgeons, hospitals, and procedures. While a “great risk shift” makes consumers all the more responsible for their choices in health care, it’s hard to imagine anyone accurately mapping the true fiscal consequences of given disease episodes in an aggressively complex plan.

By setting “a minimum level of health benefits, called the essential health benefits, that must be offered by certain health plans.” As Jessica Mantel explains, the term “‘essential health benefits package’ means coverage that not only provides for the essential health benefits defined by the secretary, but also limits cost-sharing for coverage of the essential health benefits in accordance with the parameters specified in the statute.” The Cancer Action Network has applauded the ACA for promoting “more standardization in the scope and value of private health insurance coverage available.”

Similarly, setting a “medical loss ratio” involves a careful delineation of insurer payments and functions that actually contribute to care. As Tim Jost explained in Health Affairs:

Medical loss ratios have long been of interest primarily to investors. An insurer that could achieve a low MLR by holding down expenditures on health care for its enrollees was a good investment. . . . On November 22, 2010, the Department of Health and Human Services released its interim final rule implementing the requirements of the new section 2718 of the Public Health Services Act (added by section 10101 of the Affordable Care Act), entitled, “Bringing Down the Cost of Health Care Coverage.” This provision is usually referred to as the “medical loss ratio” (or MLR) requirement . . .

Section 2718 requires health insurers (including grandfathered but not self-insured plans) to report to HHS each year, the percentage of their premium revenue that the insurer spends on 1) clinical services for enrollees, 2) “activities that improve health care quality,” and 3) all other non-claims costs, excluding federal and state taxes and licensing or regulatory fees. . . .

Jost describes in details how the classification works, and how it is designed to encourage more responsible insurer behavior.

Setting a Standard for Electronic Medical Records

Electronic health records systems will also need to develop shared data management standards. EMR vendors long argued that they needed flexibility to innovate in order to best reflect doctors’ practices and improve the capture of medical information. However, there is a tension between untrammeled innovation by vendors at any given time and later, predictable needs of patients, doctors, insurers, and hospitals to compare their records and to transport information from one filing system to another.

One system may be able to understand “C,” “cgh,” or “koff” as “cough,” and may well code it in any way it chooses. But to integrate and to port data, all systems need to be able to translate a symptom into a commonly recognized code. Health care providers can only avoid getting “locked into” a system if they can transport their records from one vendor to another. Patients want their providers to seamlessly integrate records.

HHS rulemaking has lain a groundwork for this type of common language of medical recordkeeping. As Sharona Hoffman and Andy Podgurski explain,

To address this problem, it is necessary for all vendors to support what we will call a “common exchange representation” (“CER”) for EHRs. A CER is an artificial language for representing the information in EHRs, which has well defined syntax and semantics and is capable of unambiguously representing the information in any EHR from a typical EHR system. EHRs using the CER should be readily transmittable between EHR systems of different vendors. The CER should make it easy for vendors of EHR systems to implement a mechanism for translating accurately and efficiently between the CER and the system’s internal EHR format.

There are also important opportunities for standardization in the security field:

As is true for a common exchange format, standardized security policies and mechanisms are unlikely to be adopted by vendors and providers without a regulatory mandate. In order to facilitate compliance and provide vendors with clear guidance, the regulatory mandate might incorporate, by explicit reference, some established and emerging security standards, such as the Internet Engineering Task Force’s Transport Layer Security (“TLS”) standard or its Public-Key Infrastructure (X.509) standard.

The discussion can quickly become technical, and it is difficult to explore all the ins and outs of the process. But the underlying purpose is clear: to develop some standard forms of interacting in a realm where “spontaneous order” is unlikely to arise and “network power” could lead to lock-in.

Of course, there are important differences between the EHR and health insurance landscapes. Symptoms refer to conditions that are, by and large, objective. (One can even imagine ubiquitous video cameras and sensors creating something like a complete patient record (or medical life log) for patients who consent to that type of monitoring.) Insurance contracts, by contrast, do not have the same “ontological firmness.” They must contemplate vague and open-ended spells of illness.

Nevertheless, a process similar to common exchange representation is now going on in the consumer affairs office of HHS. As the Office of Consumer Information and Insurance Oversight lays ground rules for ACA implementation, it must decide on some basic questions: what counts as insurance? What is a deductible? The ultimate goal is to require insurers to convey with far more precision what services they truly cover. The health insurance and health IT landscapes will only become governable when practices are nameable, classifiable, and comparable.

X-Posted: Concurring Opinions.

Linnaean Regulation in Health Insurance and Information Technology, Part I

I was recently listening to Health Affairs’s “Newsmaker Breakfast with Karen Pollitz.” She gave a fascinating presentation on the challenges she faces as she develops HealthCare.Gov as a portal for information about health insurance. As I noted a few years ago, health insurers can easily mislead consumers about the nature of their coverage, and disclosure charts can be very helpful.

But even disclosure charts run up against the slipperiness of language. Pollitz noted that for some plans, a “deductible” was not really a deductible; you could easily spend much more out-of-pocket on health care than the stated “deductible level” before coverage kicked in.

How can an individual make an informed choice when words lose their meaning in a tangle of qualifications and conditions? At what point does a deductible cease being a deductible? While this might seem like a relatively technical question of insurance regulation, it is reflects a more general information-gathering problem that will confront regulators in coming years. Scientists could only predict and control aspects of the natural world when they could be named and classified. Any successful regime of healthcare reform will depend, at a bare minimum, on a flexible yet standardized classification system that can map what health insurers are doing. Like Linnaeus patiently organizing a welter of living forms, regulators will need to taxonomize pullulating permutations of insurer practices.

The Rise of Health Care’s Middlemen

The United States leads the world in payments to private insurance providers. The industry has extraordinary power over access to health care. In 2010, long-standing dissatisfaction with the sector culminated in the Patient Protection and Affordable Care Act (ACA). Congress rejected changes like a public option in healthcare, in favor of a complex and reticulated statutory scheme to better regulate insurers. There have not been dramatic changes in the way that health insurance companies are run, and their stock prices tended to rise as reform became more certain.

The ACA has set in motion dozens of regulatory proceedings. The government also allocated $20 billion toward equipping all medical offices with electronic health records in the 2009 stimulus bill, the American Reinvestment and Recovery Act. Health regulators must now try to catch up with technologically advanced intermediaries in insurance and IT fields.

Immediately after the ACA passed, naysayers on both left and right complained that divisions like OCCIO were unprepared for their new regulatory roles. Perhaps the most compelling case for repealing the ACA is a belief that regulatory agencies will inevitably be captured, or overwhelmed with information from far far better funded attorneys and lobbyists representing insurance and IT firms.*

Nevertheless, the ACA has catalyzed one very important process: the development of an infrastructure of monitoring and reporting that will be necessary for any future informed regulation. It’s shocking to consider how inadequate past reviews were here. As of 1997, the “US Department of Labor had resources to review each employer-sponsored group health plan under its jurisdiction once every 300 years.” The Bush years did not significantly address that shortage. Moreover, “state insurance department staff levels declined 11% in 2007 while premium volume increased 12%.” The personnel simply haven’t been around.

Starting essentially from scratch, Pollitz and her fellow regulators are engaging in a painstaking rebuilding of the foundations necessary for substantial regulation. Having long neglected even to closely monitor the sharp practices of health insurers, federal regulators are now beginning new programs of surveillance.**

*The latter point does appear to be valid with respect to the public record now being compiled in dozens of rulemaking processes. In rule after rule, industry comments overwhelmingly dominate public interest or academic contributions. It’s sad to think that groups like Campaign for America’s Future, or labor unions, having spent so much time getting the ACA passed, are now ceding much of the regulatory field to insurers. On the other hand, given the Administration’s recent appointments, and recent McSurance waivers, who knows whether good comments would have an impact.

**For more on the importance of ongoing surveillance in complex business environments, see Larry Cata Backer on SarBox, and the last part of my earlier post on high finance.

Part II

X-Posted: Concurring Opinions.

Reform Rodeo

1. Maggie Mahar at Health Beat discusses a new report published in the NEJM that supports the importance of the individual mandate in combating adverse selection.

2. At the Health Care Blog, Paul Levy writes sardonically about the accountability of accountable care organizations.

2a. On a less sardonic note, Chris Fleming gives an overview of Health Affairs’ special issue covering ACOs.

2b. Thomas Greaney writes in the NEJM about how the federal government’s can help ACOs navigate an already concentrated health care landscape.

3. The Hill reports on the essential items and services that health insurers will have to provide when offering their products in the new exchanges.

4. David Kibbe and Brian Klepper document the federal government’s initiatives in giving the HIT market a much needed shot-in-the-arm.

5. The Commonwealth Fund’s Melinda Abram’s discusses one of the most important facets of health care reform: how the ACA will bolster primary care.

Reform Rodeo

1. ProPublica details the incessant problem that medical schools face in preventing their faculty from accepting money in exchange for speaking on behalf of pharmaceutical companies. As previously noted on this blog, these conflicts of interests are in addition to those conflicts found in spinal surgery and cardiac stenting.

2. For the New England Journal of Medicine, Michael E. Porter introduces two recently published papers that explore the concept of value in health care.

3. The Commonwealth Fund provides a summary of a briefing on the ACA’s initiatives to reform primary care. A full video of the briefing (which was co-hosted with the Alliance for Health Reform), as well as a podcast of the audio, can be found here.

4. The Health Care Blog has a nice bulleted Year in Review for Health Information Technology (HIT), including topics such as the HITECH Act, E-prescribing, EHRs, and Health Information Exchanges.

5. The  New York Times discusses a new Medicare rule that will cover the costs of voluntary end-of-life treatment planning.

Reform Rodeo

1. The Health Care Blog has an important piece on the role of HIT in Accountable Care Organizations (ACOs) and whether they will be open networks or walled gardens.

Will ACO (accountable care organization) IT models be walled gardens or open platforms?  i.e., will ACO IT platforms focus on exchanging information within the provider network of the ACO, or will they also be able to exchange information with providers outside the ACO network?

2. Kaiser Health News  discusses rules proposed by the Obama administration that would require health insurers to justify double-digit increases in premium rates.

Under the proposal, the flagged premium increases would be subject to review by the states – or the federal government in some cases – to determine if they are unreasonable.

In following years, the Department of Health and Human Services will adjust the specific percentage threshold for each individual state. Thresholds would vary partly because medical costs vary by state.

3. The New York Times has run a piece on a new antitrust lawsuit filed against Blue Cross Blue Shield of Michigan.

Federal prosecutors contend that Blue Cross in Michigan thwarts competitors by pressuring hospitals to charge rival insurers more to provide care, a practice prosecutors say has made health care extremely expensive in a state that can’t afford it.

4.  Tim Jost provides an overview at Health Affairs of the current state of the argument over the constitutionality of the individual mandate — including the recent decision by a federal judge in Virginia ruling the mandate unconstitutional.

Virginia adopted a statute purporting to nullify the minimum essential coverage requirement even before Congress enacted the Affordable Care Act, and the lawsuit was brought to enforce this statute.  Judge Hudson had earlier this year denied a Justice Department motion to dismiss the Virginia case, holding that the Commonwealth had standing to defend its legislation.  In his earlier decision, Judge Hudson had also held that the Commonwealth had an arguable claim that the minimum coverage requirement was unconstitutional.  Subsequent briefs filed by the Justice Department and by amici (interested parties who file as “friends of the court,” or amici curiae) supporting the reform law apparently failed to change Judge Hudson’s mind.

5. The Wall Street Journal has a story outlining the tremendous pecuniary benefits that certain spine doctors are receiving for conducting spine surgeries that some question as unnecessary.

The five surgeons are also among the largest recipients nationwide of payments from medical-device giant Medtronic Inc. In the first nine months of this year alone, the surgeons—Steven Glassman, Mitchell Campbell, John Johnson, John Dimar and Rolando Puno—received more than $7 million from the Fridley, Minn., company.

Patient Autonomy and Personal Health Records

I recently gave remarks as part of a panel at the roundtable “Personal Health Records: Understanding the Evolving Landscape,” sponsored by the Office of the National Coordinator for Health Information Technology (ONC). There were many interesting speakers, including some of the leading businesses in the PHR space and regulators from FTC, HHS, and the California state Office of Privacy Protection. The roundtable exposed the promise–and limits–of a personalized health record model. Databases may help both public health and patient care, but the many stakeholders in PHR’s may have very different views about how much control patients should have over the presentation of their medical selves in everyday life.

Discussions about health records can get forbiddingly abstract and technical, but a real-world dilemma can help concretize the problem. As Lisa Wangsness’s Boston Globe article shows, at least one individual feels “burned” by his effort to quickly port past data into a PHR:

When Dave deBronkart, a tech-savvy kidney cancer survivor, tried to transfer his medical records from Beth Israel Deaconess Medical Center to Google Health, a new free service that lets patients keep all their health records in one place and easily share them with new doctors, he was stunned at what he found. Google said his cancer had spread to either his brain or spine — a frightening diagnosis deBronkart had never gotten from his doctors — and listed an array of other conditions that he never had, as far as he knew, like chronic lung disease and aortic aneurysm. A warning announced his blood pressure medication required “immediate attention.” “I wondered, ‘What are they talking about?’ ” said deBronkart . . .[He] eventually discovered the problem: Some of the information in his Google Health record was drawn from billing records, which sometimes reflect imprecise information plugged into codes required by insurers.

According to one doctor consulted by the Globe, “an inaccurate diagnosis of gastrointestinal bleeding on a heart attack patient’s personal health record could stop an emergency room doctor from administering a life-saving drug.” For the critically or chronically ill, the record is literally a life-or-death matter.

Admittedly, the level of personal control an individual has over a PHR also offers a solution to this problem. If we follow the same model as credit reporting, patients should be able to review their reports without charge, and make corrections. The Markle Foundation has done a superb job highlighting the importance of accountable health technology. But, as the Center for Democracy and Technology argues, rulemaking on EHRs will need to build in a number of consumer safeguards to assure that other stakeholder interests do not trump patients’ interests.

The CDT recommends that HHS require “PHR providers to provide opportunities for consumers to amend, correct or annotate information in a PHR,” and “to have policies for handling disputes concerning information in the PHR.” CDT expands on the obligation in these paragraphs:

Many PHRs contain data from two categories of sources: copies of information obtained from members of the traditional health system (including health care providers, insurers, etc.) and data generated or acquired by consumers themselves, whether directly entered by them, or fed into the PHR by devices or
other sources that are not part of the traditional health care system (including data from a monitoring device that the consumer operates, from a commercial Web site, or from a consumerʼs own health-related observations).

Policies governing disputes about the validity of data should draw a distinction between these different categories of data. With respect to copies of data that users might not be permitted to change directly (including but not limited to data that originates with members of the traditional health system), users should be given a way to attach notes or complaints to the PHR disputing the validity of the data – and the note should remain appended to the data any time it is disclosed from the PHR. (This is similar to how the HIPAA Privacy Rule treats patient amendment of data in covered entity records.) PHR vendors also should consider mechanisms for communicating patient disputes about data back to the original source for consideration.

Even in a world where PHR’s are ubiquitous, there’s almost certainly going to be some “objective health record” in the medical system about any individual. (And, if key software engineers get their way, there will be a unique “personal health identifier” for everyone once health records systems are up and running.) So why should the integrity of PHRs matter to anyone other than the person recording them?

First, the more legible, portable, and useful PHRs are, the more they may displace other records of patient information. Emergency rooms may only have a chance to look at one HR–the one given to them by the patient they are treating.

Second, we can assume that as PHR’s become a bigger part of larger employers’ cost-control programs, they are going to want to make sure that “quantified selves” are accurately reporting their health efforts and achievements. Health reform has taken a “preventive turn,” and the ACA gives employers new latitude to reward and punish employees:

Although it prohibits insurers from charging higher premiums based on an individual’s health risks, it allows them to charge a smoker as much as 50 percent more than a nonsmoker. It also permits employers to increase rewards for participation in wellness and disease-prevention programs from 20 percent to 30 percent of the costs of insurance premiums.

To verify participation, an employer may want access to an employee’s PHR, particularly if it is much easier for its own computer systems to read and understand than the “objective health record” existing in the health care system itself. Yet the employer may also want to ensure that the PHR is populated by materials validated by third parties (such as doctors’ offices, fitness clubs, scales, or blood sugar monitors). Presently, this is not a major issue; as Nicolas Terry warns, “sharing or exchange of data between PHRs and providers or their EMRs is as speculative as it is controversial.” However, technological advances could promote PHRs with inputs from providers, apps, and even RFID chips. What happens if the employer tries to condition participation in a wellness program on an employee’s agreement not to try to change whatever is reported by those “trusted” third parties?

The CDT suggests some principles that should guide this situation as well. They recommend that:

Employers, health plans, and others should be explicitly prohibited from requiring individuals to open PHR accounts as a condition of employment, membership, or for any other reason. PHR accounts should also not be routinely opened for consumers who do not explicitly activate them, as this can expose personal data to uses not necessarily anticipated by the consumer. Similarly, consumers should not be compelled to disclose the information held within the PHR, or whether they are using a PHR, without due process of law.

I believe these “compulsion” points should go beyond the decision to open a PHR, to the more granular rights and responsibilities associated with the maintenance of one. However many times employers sing the praises of contract law, the truth remains that employees in this tight labor market have very little bargaining power. That’s one reason why Nicholas P. Terry’s recommendation of inalienable rights to control data in the PHR context was one of the most provocative and compelling comments at the roundtable.

I am not here advocating for complete autonomy of the patient over records in all contexts. As Sharona Hoffman has argued, in the realm of treatment, there are important rationales for prioritizing the independent medical judgment of professionals whose first obligation is to maintain health:

If patients are empowered to opt out of EHR use or to disallow treating physicians’ access to their records, they may lose much of the benefit of computerization. Many clinicians would continue to care for patients in ignorance of essential facts that could make the difference between appropriate and inappropriate treatment decisions. For example, it might seem at first blush that most physicians would not need access to a patient’s psychiatric records. However, a psychiatric diagnosis may help other specialists better understand the patient’s symptoms, and the patient’s complete drug list, including psychiatric drugs, is vital for purposes of safely prescribing additional medications.

Some commentators at the roundtable also offered creative solutions for the “sensitive health data” conundrum raised by Hoffman; for example, a patient could include an “envelope” in their EHR or PHR that would only be opened in case of emergency, or when authorized directly by the patient. Regardless of how one feels about this issue, outside the treatment context, it is critical for consumers to have reasonable opportunities to review, correct, and withhold their personal health records.

When all is said and done, people have to “buy in” to EHR for it to work effectively, and rational individuals are going to avoid any system where medical history can be as effective as credit history at denying them opportunities. One commentator at the roundtable said that her patients “didn’t care” about health data or security; they just wanted some quick and dirty method of digitizing their records. However compelling this perspective may seem for those “on the front lines,” the perils of “wikileaked world” should end any complacency about the use and misuse of computer records. We should avoid the temptation of letting cut-rate or subpar EHR and PHR systems develop, especially since they are likely to target the most vulnerable patients. Robust regulatory requirements can spark a race to the top for data privacy and security.

In the film Sleep Dealer, a laborer encounters a “memory recorder,” a computerized transcription machine that translates past experiences into video re-enactments. The machine occasionally blanks out as the laborer narrates his story, and its operator chides him to “be more truthful,” to hew closer to the actual truth of the matter. The film is ambiguous as to whether the machine, its operator, or the laborer himself have real access to what actually happened. In the treatment context, best practices may inevitably consign us to a messy, multi-stakeholder effort to set forth the “real truth” of a health record. However, the personal health record should be primarily a project of the person it describes, with no undue influence from the growing number of reputation raters and shapers with a pecuniary interest in particular representations of that person.

Reform Rodeo

1. Bob Laszewski at the Health Care Policy and Marketplace Review discusses the interesting bi-partisan bill recently announced by Scott Brown and Ron Wyden.

2. Brian Klepper and David Kibbe detail what would happen if employers walked away from health coverage.

3. The Health Care Blog: The Direct Project — formerly NHIN Direct — recently announced the release of its open-source software aimed at enabling secure messaging between health care providers.

4. The Health Care Economist reports on a Commonwealth Fund study which examines concentration in the Medicare Advantage market.

5. The New England Journal of Medicine has a piece on the complexity between the ACA and Medicaid expansion.

Online Health Data in Employers’ and Insurers’ Predictive Analytics

Did you know that buying generics instead of brands could hurt your credit? Or that a subscription to Hang Gliding Monthly could scare off life insurers? Or that certain employers’ access to electronic health records could lead them to classify you as “high-risk” or “high-cost”?

In all these cases, firms use “predictive analytics” to maximize profits. Consumers are the guinea pigs for these new “sciences” of the human. As Scott Peppet argues, it becomes more difficult to opt out of analytics systems as more people use them. What type of world are they leading us to?

Credit Analytics: Should Frugality be Punished?

One credit analytics company determined that buyers of cheap automotive oil were “much more likely to miss a credit-card payment” than those who paid for a brand-name oil. Spending on therapy sessions may also be a red flag. Appearing too frugal, too anxious, too spendthrift—all might lead to higher interest rates or lower credit limits. One R&D head at a credit analytics firm bragged that they consider over 300 characteristics to discover delinquency risk. He was not nearly as forthcoming about how the data is aggregated. Analyzing millions of transactions, the companies observe customers as a gardener might observe a rose garden: weeding out unpromising specimens, and giving a boost to incipient flourishers.

Many have complained about inaccuracy in these new forms of profiling, and consumers’ inability to review and correct digital dossiers collected about them. But let’s just assume that this profiling is correct, and choosing a generic really does correlate with increased credit risk. What’s the social value of this discovery? Maybe credit card companies can reduce rates infinitesimally (and increase profits) by burdening the generic buyers. But I’d be willing to bet that, for every few people whose generic purchases indicate financial trouble, there is another shopper who’s wisely frugal and increasing her chances of successfully repaying all her loans. It seems very odd to penalize the financially responsible merely because they happen to engage in an activity shared by the distressed.

The Dream of the Perfect Profile

Ahh, predictive analysts might reply, you just oversimplify our process. We would never reduce the credit line of someone who purchases generics if that person also, say, has a subscription to Travel and Leisure, or drives a Nexus, or gives over $1,000 a year to the Republican National Committee. They’re not desperate—they’re just careful shoppers. The more information we have, the more fair and accurate we can be. (I can only propose this response, since the industry is so careful about protecting its trade secrets. But this seems like a plausible counterargument.)

Just as free speech advocates often say that the answer to “bad speech” is more or “counter” speech, predictive analysts may argue that the cure for the mistreatment of any given individual is more information about the person’s true motives or opportunities. If privacy advocates are worried that certain surveillance practices will unfairly tarnish the reputation or profile of an individual, the answer is more, not less, information, on that person. The more comprehensive a picture that firms can develop of the individual, the better they are able to properly target resources.

Whatever the merits of this approach, it appears to me that it only applies to one dimension of the credit analytics example above. Rewarding “brand buyers,” in general, is not that likely to alter behavior in ways that could seriously undermine someone’s quality of life. But effectively punishing those who seek therapy or marriage counseling creates a different set of concerns, showing once again the ways in which health care decisionmaking needs to be distinct from the Procrustean forces of market pressures.

Stressed by Sickness in the Risk Society

A recent article by Sharona Hoffman illuminates some problems with pervasive use of health data in predictive analytics.

Employers may obtain and process EHRs [electronic health records] for a variety of reasons. Many require applicants who have received employment offers to provide authorizations for release of medical records in order to verify the individuals’ fitness for duty. At times, employers require records for purposes of workers’ compensation claims, reasonable accommodation requests by individuals with disabilities, or Family Medical Leave Act (FMLA) requests. Employers who are self-insured also process employees’ medical data in order to pay insurance claims.

EHRs will likely provide employers with unprecedented amounts of data. . . . Employers or their hired experts may develop complex scoring algorithms based on EHRs to determine which individuals are likely to be high-risk and high-cost workers. . . . Employers with access to EHRs containing a wealth of medical information may be sorely tempted to exclude certain individuals from the workforce because of concerns about the employees’ future productivity, absenteeism, or medical costs. To disguise unlawful conduct, employers may not act immediately to withdraw a job offer or terminate an employee, but rather, decide not to promote an individual with a disability or to select her for a layoff at a later time.

In other words, predictive analytics in health can lead to more “death spirals” for the sick: lost employment, lost insurance due to that lost employment, and future inability to find work due to poor health. Hoffman’s concerns about employers sidestepping relevant regulations were reflected in today’s WSJ article on insurance profiling, too:

[G]iant data-collection firms . . . sort details of online and offline purchases to help categorize people as runners or hikers, dieters or couch potatoes. They scoop up public records such as hunting permits, boat registrations and property transfers. They run surveys designed to coax people to describe their lifestyles and health conditions. Increasingly, some gather online information, including from social-networking sites.

For insurers and data-sellers alike, the new techniques could open up a regulatory can of worms. The information sold by marketing-database firms is lightly regulated. But using it in the life-insurance application process would “raise questions” about whether the data would be subject to the federal Fair Credit Reporting Act, says Rebecca Kuehn of the Federal Trade Commission’s division of privacy and identity protection. The law’s provisions kick in when “adverse action” is taken against a person, such as a decision to deny insurance or increase rates. The law requires that people be notified of any adverse action and be allowed to dispute the accuracy or completeness of data, according to the FTC. Deloitte and the life insurers stress the databases wouldn’t be used to make final decisions about applicants. Rather, the process would simply speed up applications from people who look like good risks.

Many aspects of FCRA have been rendered irrelevant by the all-importance of credit scoring—it’s hard to care too much about one’s ability to “correct” one’s credit report if the only thing that really matters is a score whose calculation only contingently depends on any given piece of information in the report. But I had not heard before Deloitte’s assurance that information would “simply speed up” applications, and not “be used to make final decisions.” Quite the creative lawyering behind that distinction.

Relating the Real and the Digital Body

Dan Solove has written extensively on the “digital person,” and perhaps we can see predictive health analytics as an effort to create a “digital body.” As the WSJ reports, we are reaching a point where online “data can reveal nearly as much about a person as a lab analysis of their bodily fluids.” The least we can ask is for the purveyors of data-driven decisionmaking to be much clearer about how they profile individuals. Moreover, in the case of employment, we should seriously consider expanding disability discrimination laws to prevent employers from stratifying employees based on health data. Profits are important, but they shouldn’t come at the expense of sick people who already have enough problems to contend with. As HHS implements PPACA’s promotion of “wellness programs” at workplaces, they should also try to avoid the “Orwellness” of data-driven health profiling.

X-Posted: Concurring Opinions.

Privacy Paradigms: From Consent to Reciprocal Transparency

Computational innovation may improve health care by creating stores of data vastly superior to those used by traditional medical research. But before patients and providers “buy in,” they need to know that medical privacy will be respected. We’re a long way from assuring that, but new ideas about the proper distribution and control of data might help build confidence in the system.

William Pewen’s post “Breach Notice: The Struggle for Medical Records Security Continues” is an excellent rundown of recent controversies in the field of electronic medical records (EMR) and health information technology (HIT). As he notes,

Many in Washington have the view that the Health Insurance Portability and Accountability Act (HIPAA) functions as a protective regulatory mechanism in medicine, yet its implementation actually opened the door to compromising the principle of research consent, and in fact codified the use of personal medical data in a wide range of business practices under the guise of permitted “health care operations.” Many patients are not presented with a HIPAA notice but instead are asked to sign a combined notice and waiver that adds consents for a variety of business activities designed to benefit the provider, not the patient. In this climate, patients have been outraged to receive solicitations for purchases ranging from drugs to burial plots, while at the same time receiving care which is too often uncoordinated and unsafe. It is no wonder that many Americans take a circumspect view of health IT.

Privacy law’s consent paradigm means that, generally speaking, data dissemination is not deemed an invasion of privacy if it is consented to. The consent paradigm requires individuals to decide whether or not, at any given time, they wish to protect their privacy. Some of the brightest minds in cyberlaw have focused on innovation designed to enable such self-protection. For instance, interdisciplinary research groups have proposed “personal data vaults” to manage the emanations of sensor networks. Jonathan Zittrain’s article on “privication” proposed that the same technologies used by copyrightholders to monitor or stop dissemination of works could be adopted by patients concerned about the unauthorized spread of health information.

If individuals had enough time to manage their personal data the way they manage their checkbooks and gardens, perhaps the consent paradigm would be a good foundation for addressing public concerns about privacy. If applicants could easily bargain with would-be employers over privacy, or patients with hospitals, perhaps we could rely on them to protect their interests. But actual occurrences of such acts of self-assertion and self-protection are rare. Given the frequently abstract benefits that privacy and reputational integrity afford, they are often traded away for competitive economic advantage. This process further erodes societal expectations of privacy.

A collective commitment to privacy is far more valuable than a private, transactional approach that all but guarantees a race to the bottom. If such a collective commitment does not materialize, record systems will only deserve trust if they become as transparent as the patients and research subjects they profile. Given corporate assertion of trade secrecy (and even privacy rights), reciprocal transparency will not be easy to achieve. Nevertheless, repeated breaches, fraud, and data meltdowns in the US should provoke an alliance of socially responsible researchers to lobby the US government to set minimal standards of reciprocal transparency and auditing. Consumers can only trust innovators if they can understand what is being done with data. As we become “transparent citizens” (as Joel Reidenberg puts it), we should demand that the corporate, university, and governmental authors of that trend reciprocate, and become more open about the data they gather.

Fortunately, as a recent presentation by Deborah Peel reminded me, there is significant audit authority built into the recent HITECH act which may curb some abuses. Audits will become increasingly important as a “wild west” of health data is excavated by scrapers, marketers, and other data miners.

Consider, for instance, the following scenario: contributors to the medical website PatientsLikeMe.com found that “Nielsen Co., [a] media-research firm . . . was ‘scraping,’ or copying, every single message off PatientsLikeMe’s private online forums.” Had the virtual break-in not been detected, health attributes connected to usernames (which, in turn, can often be linked to real identities) could have spread into numerous databases. A reciprocal transparency paradigm would require all those harboring health data to have some certified indication of its legitimate provenance. Data would not be allowed to persist without certification of its provenance.

Unforeseen spread of inaccurate or inappropriate health data is not just a problem for those who want to avoid getting solicitations for burial plots after a sensitive appointment. Given law enforcement exceptions to medical privacy laws and regulations, it should come as little surprise that the government claims that “a 2005 law authorizes it to monitor and record all prescription drug use by all citizens via so-called “Prescription Drug Monitoring Programs.” Such programs may just be the tip of an iceberg of new domestic intelligence programs that rely on private companies to act as “big brother’s little helpers.”

Whenever health data is fed into an evaluative profile of an individual, there should be safeguards in place to assure that the data is accurate, and that the resulting profile is, if at all possible, not used to harm or disadvantage the individual. Without assurances like these, we can count on continued resistance to the development of health data infrastructures.

Reform Rodeo

1. The American Medical Association: In the face of new health reform requirements that are now in effect, many of the top insurers have dropped child-only health plans.

2. Kaiser Health News Daily Report: Health Care reform’s elimination of discrimination based on pre-existing conditions has not fully materialized; In a sign of what could be a backlash against health care reform, the 3M corporation announced that it will stop offering its health insurance plan to retirees. Click here for the Daily Report.

3. In a sea of pessimism, the New England Journal of Medicine explores the lessons of a health care success story: Grand Junction, Colorado — one of the cities that Atul Gawande detailed in his celebrated article in the New Yorker.

4. At the Health Care Blog, Michael Lake explores recent trends in HIT, while providing many helpful links.

5. Webcast 1: On Tuesday, October 5th: Maggie Mahar and others will be participating in a webcast where they will discuss health care reform. Click here for Mahar’s overview on her Health Beat blog, including a link to the freely-accessible live stream.

Reform Rodeo

[Ed. Note: HRW welcomes back Jordan Cohen from his work in Washington at HHS this summer-- the place just wasn't the same without him]

Waste: The New York Times provides an overview of a new study detailing health care wastefulness — which the Times reports as being the first study to quantify the problem.

Berwick’s Pilots: Newly appointed Medicare director Donald Berwick is pushing for hundreds of new pilot programs that would seek to innovate the delivery of health care.

Prognostication: The Health Care Blog’s David Kibbe and Brian Klepper look beyond meaningful use and distill five future trends of patient health data and clinical health information technology.

Meaningful Use FAQs: For those with questions on meaningful use, John Halamka has created FAQs.

PPACA and Employees: Researchers at RAND have published a study predicting PPACA’s effect on workers’ health insurance coverage.

Medicaid Outside the Box: Health Affairs’ Michael O’Grady and Jennifer Baxendell Young have published a post that discusses new ideas for Medicaid financing.

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