From Viral Marketing to Medical Profile Contagion

As ACA implementation lumbers ahead, and challenges to it slouch toward the Supremes, the U.S. health care system’s arbitrary old ways continue to mystify and frustrate. Consider this story on one person’s quest to obtain insurance:

Most employees assume that if they lose their job and the health coverage that comes along with it, they’ll be able to purchase insurance somewhere. . . .My husband, teenage daughter and I were all active and healthy, and I naïvely thought getting health insurance would be simple. . . .

Then the first letter arrived — denied. . . .What were these pre-existing conditions that put us into high-risk categories? For me, it was a corn on my toe for which my podiatrist had recommended an in-office procedure. My daughter was denied because she takes regular medication for a common teenage issue. My husband was denied because his ophthalmologist had identified a slow-growing cataract. Basically, if there is any possible procedure in your future, insurers will deny you. . . .

As I filled out more applications, I discovered a critical error in my strategy. The first question was “Have you ever been denied health insurance”? Now my answer was yes, giving the new companies reason to be wary of my application. I learned too late that the best tactic is to apply simultaneously to as many companies as possible, so that you don’t have to admit to a denial.

As was recently reported, “50 to 129 million (19 to 50 percent of) non-elderly Americans have some type of pre-existing health condition.” The “health care market” is sending a strong signal: don’t step out of the system if you have any continuing need for even minor care.

But what’s more worrisome are the types of information circulating about you that you aren’t even aware of. Consider this story from Businessweek about the profiling of insurance applicants by third-party intermediaries:

Most consumers and even many insurance agents are unaware that Humana, UnitedHealth Group , Aetna (AET), Blue Cross plans, and other insurance giants have ready access to applicants’ prescription histories. These online reports, available in seconds from a pair of little-known intermediary companies at a cost of only about $15 per search, typically include voluminous information going back five years on dosage, refills, and possible medical conditions. The reports also provide a numerical score predicting what a person may cost an insurer in the future. . . .

[A] 57-year-old safety consultant in the oil and gas industry, says he tried to explain that the medications weren’t for serious ailments. The blood-pressure prescription related to a minor problem his wife, Paula, had with swelling of her ankles. The antidepressant was prescribed to help her sleep—a common “off-label” treatment doctors advise for some menopausal women. But drugs for depression and other mental health conditions are often red flags to insurers. Despite his efforts to reassure Humana, the phone interview with the company representative “just went south,” Walter recounts. He and his wife remain uninsured [as of 2008].

Health-related data from a wild west of unregulated intermediaries may spread to employers and other decisionmakers, just as credit scores have migrated from the bank context to influencing insurance pricing, and credit histories now influence employers. Sharona Hoffman has observed that “It is not uncommon for employers to obtain applicants’ and employees’ medical records. According to one source, every year, over ten million authorizations for release of medical information are signed by workers prior to the commencement of employment.” She has predicted disturbing possibilities arising out of that access to data:

Existing laws, including the ADA, GINA, HIPAA, and their state counterparts, provide important assurances to applicants and employees but are insufficient to guarantee that they will suffer no ill consequences as a result of EHR disclosure to employers. Employees may be especially concerned in times of recession, knowing that financial pressures make workers with health problems particularly unattractive to employers. 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. In addition, in times of financial difficulty, limited resources may be available to implement technology and policies that will secure EHR confidentiality.

Secondary uses of health data could be a very lucrative niche for profilers of the future.

Given these possibilities, individuals should at least have the right to access and correct the health data that intermediaries have compiled about them. The FTC recognized this right, and “forced the [insurance] industry to begin disclosing the use of prescription information under . . . the Fair Credit Reporting Act. . . . Copies of prescription reports are supposed to be available to consumers at no charge under federal law.” This is a small step forward. But if the “scores” assessing individual risk are compiled according to proprietary algorithms, the consumer may still feel “in the dark,” unable to adequately influence the presentation of herself to the insurer.

As Esther Dyson has stated in another context, mysterious data flows can jeopardize individual autonomy:

The comforting thing about the kind of data that Facebook primarily deals with is that it’s public. If your friends and other people can see it, so can you.

More troubling is the data you don’t even know about – the kind of data about your online activities collected by ad networks and shared with advertisers and other marketers, and sometimes correlated with offline data from other vendors. By and large, that’s information you can’t see – what you clicked on, what you searched for, which pages you came from and went to – and neither can your friends, for the most part. But that information is sold and traded, manipulated with algorithms to classify you and to determine what ads you see, what e-mails you receive, and often what offers are made to you. Of course, some of that information could go astray.

Online advertisers already slice and dice population segments (and distribute opportunities & exposure to ads) via marketing discrimination. Will the “e-health revolution” bring their methods out of cyberspace, and into the deadly serious business of offering employment and insurance based on estimates of health status that applicants can’t understand or challenge?

CMS and HHS Release New Proposed Rules Governing Health IT – Part 1: Overview of Proposed Rule on “Meaningful Use”

Issues surrounding the implementation of health information technology (HIT) have not garnered anywhere near the amount of attention as issues such as the public plan, the intersection of abortion and health insurance, pre-existing condition provisions, etc. There are a variety of reasons for this.

First, HIT is not as accessible as these other issues. Discussions of HIT often involve the heavy use of acronyms as well as technical jargon that can be intimidating and confusing. This will not likely change in the future. HIT will increase in complexity, especially as variegated computer systems used by providers and hospitals are to be linked together.

A second reason for the lack of coverage of HIT is that there have been few if any significant steps on the federal level towards implementing a national HIT system. As I will discuss below, this is beginning to change, and this change provides for an important New Year’s resolution that all of those interested in health policy should make: stay informed about the changes in the HIT landscape. To make this resolution easier, I will write a series of posts describing the changes.

One of the more recent changes occurred with the passing of the American Recovery and Reinvestment Act (ARRA), and more specifically, portions known as the Health Information Technology and Clinical Health Act (HITECH Act). The HITECH Act initiated, among other things, an incentive-driven paradigm for transforming our health information system. The general idea is that physicians and hospitals will be paid for using HIT. However, in order for this transformation to take place, guidelines must exist such that physicians, providers and vendors of HIT products understand how to operate within this new system.

On December 30^th 2009, CMS and the Office of the National Coordinator of Health and Human Services (ONC), released two rules. ONC released an interim final rule regarding the standards that will govern the Medicare and Medicaid incentive program. Additionally, CMS released their proposed rule on what is considered meaningful use.

The interim final rule regarding the standards can be found here.

The proposed rule regarding meaningful use can be found here.

Meaningful Use

CMS’s proposed rule on meaningful use is important because it defines how physicians and providers must implement HIT in order to qualify for CMS’s incentive payments for the use of such technology.  Much of the proposed rule is based on the HIT Policy Committee’s proposals on Meaningful Use, but comments had been solicited and incorporated from other committees, HIT vendors, and providers. The proposed rule states that incentive payments will begin in 2011, and that there will be two different payment methodologies: one for Medicare and one for Medicaid. Those receiving incentives must choose either the Medicaid or the Medicare plan. Furthermore, the rule states that hospitals and providers that are not meaningfully using HIT will have their payments from Medicare reduced, with the reductions taking effect in 2015.

The HITECH Act amended the Social Security Act, and in doing so, incorporated a broad definition of what constitutes a meaningful user of Electronic Health Records (EHR). Specifically for a provider to be a meaningful user they must:

1. Demonstrate use of certified EHR technology in a meaningful manner;
2. Demonstrate to the satisfaction of the Secretary that certified EHR technology is connected in a manner that provides for the electronic exchange of health information to improve the quality of health care such as promoting care coordination, in accordance with all laws and standards applicable to the exchange of information; and
3. Use its certified EHR technology, submits to the Secretary, in a form and manner specified by the Secretary, information on clinical quality measures and other measures specified by the Secretary.

The proposed rule is an extension of this definition, and aims to provide those EPs and hospitals with the proper information to become a meaningful user.

Specifically, the rule provides for two classes of providers to participate in the incentive system: eligible professionals (EPs) and hospitals.  EPs are defined as non-hospital-based physicians, who either receive reimbursement for services under the Medicare Fee-For-Service program (FFS) or have an employment or contractual relationship with a qualifying Medicare Advantage organization (MA); or healthcare professionals meeting other requirements. (See page 22 of PDF). Hospitals are defined as hospitals that either receive reimbursement for services under the Medicare FFS program or are affiliated with a qualifying MA organization as described in section 1853(m)(2) of the Act; critical access hospitals (CAHs); or acute care or children’s hospitals. (See page 22 of PDF).

Transitioning to the meaningful use of EHRs will be phased in, taking place in three stages. On page 40 of the proposed rule, CMS describes the stages as follows:

Stage 1 (beginning in 2011):  The Stage 1 meaningful use criteria focuses on electronically capturing health information in a coded format; using that information to track key clinical conditions and communicating that information for care coordination purposes (whether that information is structured or unstructured, but in structured format whenever feasible); consistent with other provisions of Medicare and Medicaid law, implementing clinical decision support tools to facilitate disease and medication management; and reporting clinical quality measures and public health information.

Stage 2: Stage 2 expands upon Stage 1 to use HIT for continuous quality improvement at the point of care and the exchange of information in the most structure format possible, such as the electronic transmission of orders entered using computerized provider order entry (CPOE) and the electronic transmission of diagnostic test results such as blood tests and nuclear imaging tests.

Stage 3: Stage 3 focuses on improving the quality, safety, and efficiency of health care, focusing on decision support for national high priority conditions, patient access to self-management tools, access to comprehensive patient data, and improving public health.

The proposed rule that was recently released only describes the specific criteria for Stage 1, with the criteria for Stage 2 and Stage 3 to be released at the end of 2011 and 2013 respectively. In terms of Stage 1 criteria, there is a hierarchy of organizational structure. At the broadest level there are “health outcome policy priorities.” Within each of these policy priorities there is a group of “care goals,” and associated with each group of care goals are the specific “objectives.” CMS has provided a very helpful table which breaks down the hierarchy, including the various objectives. I have extracted the table, which can be accessed here. However, for reference purposes, I have summarized the organization below, and provided the objectives for the first health policy priority. Note that there is a different list of objectives for hospitals, many of which are similar or identical.

The organization is as follows:

Health Outcome Policy Priority 1: Improving quality, safety, efficiency and reducing health disparities.

Health Outcome Policy Priority 2: Engaging patients and families in their healthcare

1. Care Goal 1: Provide patients and families with timely access to data, knowledge, and tools to make informed decisions.

Health Outcome Policy Priority 3: Improving care coordination

1. Care Goal 1: Exchange meaningful clinical information among professional health care team.

Interestingly, for CPOE, EPs are required to use CPOE for at least 80 percent of all orders whereas hospitals are only required to use CPOE for 10 percent of orders. Why such a discrepancy exists is presently unclear.

In terms of the requirement for reporting clinical quality measures (as described in the original definition of meaningful use in the HITECH Act), the proposed rule adopts different measurements for EPs and hospitals. For EPs, the proposed rule utilizes the quality measures endorsed by the National Quality Forum (NQF) including selected for the Physician Quality Reporting Initiative (PQRI) program that had previously been endorsed by the NQF. For hospitals, the measures are a combination of the NQF measures and those measures from the Reporting Hospital Quality Data for Annual Payment Update (RHQDAPU).

Reporting of these clinical quality measures would be accomplished by one of three methods. The primary method would require EPs or hospitals to log onto a CMS-designated portal and upload the clinical quality data in a specific data structure (as defined by the ONC’s standards). Alternatively, data could be submitted through a Health Information Exchange(HIE)/Health Information Organization (HIO) depending on whether the Secretary can access that network. Another alternative is submission through registries dependent upon the development of the necessary capacity and infrastructure to do so using certified EHRs. See page 169 of the PDF for more details on the uploading process.

As discussed earlier on this blog, one aspect of the transition that remains to be addressed is whether the incentives provided to EPs and hospitals will be sufficient to encourage physicians to take on the initial outlays associated with EHRs. H.R. 3014 ,a bill to provide loans guarantees to solo and small group practices, has been passed by the House and is currently being reviewed by the Senate Committee on  Small Business and Entrepreneurship. Without such measures to spur the initial implementation of EHRs, the incentives or downward payment adjustments may not be sufficient to implement the bold plan set out by CMS.

Electronic Medical Records: It’s Not too Late to Build the Tower on an Interoperable Platform

Tower of Babel by Sibeaster via Wikimedia Commons

Both the NY Times and the Boston Globe’s Health Blog, White Coat Notes , have recently run interesting articles on Electronic Medical Records (EMR). Both are based on articles published this last week in the New England Journal of Medicine. We’ve recently posted on the subject of EMR, and if you’d like some background information (as well as an introduction and a link to the pivotal work of Professors Sharona Hoffman and Andy Podgurski) you can find it here: Electronic Medical Records: How to Prevent the Creation of a Costly High-Tech Tower of Babel.

The first NEJM article, Use of Electronic Health Records in U.S. Hospitals, Ashish K. Jha, M.D., M.P.H., et al., was financed by the federal government and the Robert Wood Johnson Foundation and was based on a survey of nearly 3000 hospitals. The report, described by the Times as “the most definitive measure to date of the use of computerized patient records by hospitals,” shows that

…only 1.5% of U.S. hospitals have a comprehensive electronic-records system (i.e., present in all clinical units), and an additional 7.6% have a basic system (i.e., present in at least one clinical unit). Computerized provider-order entry for medications has been implemented in only 17% of hospitals. Larger hospitals, those located in urban areas, and teaching hospitals were more likely to have electronic-records systems.

A further breakdown of the components which constitute “comprehensive” and “basic” can be seen here.

Prior to this study, the numbers, based on what Steve Lohr of the NY Times described as “less rigorous studies,” were thought to be higher. The authors of Use of Electronic Health Records in U.S. Hospitals conclude that

The very low levels of adoption of electronic health records in U.S. hospitals suggest that policymakers face substantial obstacles to the achievement of health care performance goals that depend on health information technology. A policy strategy focused on financial support, interoperability, and training of technical support staff may be necessary to spur adoption of electronic-records systems in U.S. hospitals.

Perhaps the good news here is that the relative scarcity of EMR implementation thus far means that we can yet still devise an interoperable system without rendering substantial but incompatible investments obsolete. Which is to say that we are not yet too far down nine different non-intersecting roads and that “a communicative Tower” can still be built, and sustained, on a Platform.

No Small Change for the Health Information Economy

Interoperability brings us to Elizabeth Cooney’s thoughtful and succinct post in the Boston Globe regarding the other NEJM article,  No Small Change for the Health Information Economy, Kenneth D. Mandl, M.D., M.P.H., and Isaac S. Kohane, M.D., Ph.D.

As do Professors Sharona Hoffman and Andy Podgurski, the authors of “No Small Change…” stress the need for flexibility, interoperability, liquidity of information, and the ability to substitute technologies as the need arises.  To do this they propose governmental encouragement of the use of a platform with interoperable applications (blog builders, think: “plug ins” and “widgets”)  In a recent post we noted that

In the words of Dr. Farzad Mostashari,  an assistant commissioner in New York City’s health department and head of the much heralded Primary Care Information Project (which is functioning as a sort of I.T. Department for many of the City’s doctors using EMR),  “There’s no way small practices can effectively implement electronic health records on their own. This is not the iPhone.”

Mandl and Kohane suggest that it should be. They make apt comparisons to the iPhone and ATM machines. Elizabeth Cooney’s article, “Health IT can learn from the iPhone and ATMs,”  explains the comparisons quite well and is well worth the minute it will take to read– and if you have another three minutes, I highly recommend you take a quick look at Mandl and Kohanes’ brief but important article. There’s a link to it here, and there’s one in Elizabeth Cooney’s article also.