 To determine whether labor market effects were the result of diabetes per se or rather depended on the degree to which diabetes was controlled through management of blood sugar levels.

This study utilized data from a recently completed survey of households in Brownsville, Texas, a largely Mexican American community with a high prevalence of diabetes that is located on the Texas-Mexico border. Diabetes management, or control, was measured by blood sugar levels, glycosylated hemoglobin (A1C) levels, and interaction terms. Methods used were probit and Heckman regression.

 Management of diabetes did not appear to have a discernible impact on labor market outcomes in the short run. However, diabetes was negatively associated with male productivity, particularly in males’ propensity to work. The new American Diabetes Association (ADA) definition of diabetes is based on having an A1C level of <6.5%. Using the new ADA definition, diabetes was negatively associated with female productivity. Female productivity was also negatively associated with the new ADA definition of prediabetes (A1C levels between 5.7% and 6.4%). However, very few people with diabetes actually controlled their blood sugar or A1C levels.

These results imply that in order to avoid productivity losses associated with diabetes, more scarce prevention resources should be spent on prevention of the onset of diabetes than on the management of A1C for those already diagnosed with diabetes. For women, the prevention of prediabetes is key.

	Utilizing data from a largely Mexican American community with a high prevalence of diabetes, we tested whether labor market effects were the result of diabetes per se or depended on the degree to which diabetes was controlled through management of blood sugar levels. We observed that:

		Diabetes had a discernible impact on labor market outcomes.

		Management of diabetes did not appear to have a discernible impact on labor market outcomes in the short run.

		 Female productivity was negatively associated with the new American Diabetes Association definition of prediabetes (glycosylated hemoglobin levels between 5.7% and 6.4%).

	Diabetes is a chronic health condition which has substantial economic implications. The American Diabetes Association (ADA) estimated that diabetes cost the US economy $174 billion in 2007.

 An important part of this cost is associated with lower labor productivity.

Public health officials argue that diabetes prevention is important, but prevention could mean 1 of 2 things: prevention or delay of the onset of diabetes, or prevention of diabetes-related problems through the management or control of glycosylated hemoglobin (A1C) levels. If the productivity costs of controlled diabetes are low, scarce prevention dollars could be concentrated on the much smaller population already diagnosed with diabetes. On the other hand, if the costs associated with diabetes are substantial whether the condition is managed or not, then prevention dollars must be spread over the much larger general population. There is currently no information to inform policy makers how to apportion scarce prevention dollars between diabetes onset and diabetes management.

	A clue to untangling whether labor productivity is due to diabetes per se or uncontrolled diabetes lies in the differential effects of diabetes on male and female labor productivity. While the labor costs of diabetes are clear for men, the effect of diabetes on female productivity is less clear.

 It is hypothesized, but has not been proved, that women are more inclined to manage their diabetes than men and therefore face a lower labor productivity penalty due to diabetes.

 Management of blood sugar levels can occur through a combination of physician visits, diligent use of pharmaceuticals, use of monitoring devices, and health behavior modification. Many national surveys (eg, the National Health Interview Survey) have self-reported indicators of physician visits, exercise, and diet. Our study features the gold standard summary variable for health behaviors: individual, laboratory-measured A1C levels as well as blood sugar levels. Our results enabled us to determine whether women manage their diabetes better than men and, if so, whether this better self-management partly or fully explains the differential effects in terms of labor productivity.

	While overall diabetes-related labor costs are rising, it is not clear that labor costs associated with diabetes are increasing at the individual level. If per capita diabetes-related productivity costs are falling, a portion of prevention dollars should be shifted toward managing, rather than preventing, diabetes. Technological changes over the last 3 decades have led to changes in the labor market and in the medical field. First, there has been an increase in the number of jobs that are less physically demanding and therefore accessible to persons who have diabetes or who are obese.

 Second, new drugs, A1C monitoring devices, and food science advances (eg, artificial sweeteners) are making diabetes management easier and less costly than ever before. On the other hand, environmental changes (eg, fast food availability) continue to make preventing or delaying the onset of diabetes more difficult.

 However, these environmental changes also make managing diabetes more difficult.

	This study adds 2 important elements to the growing literature on diabetes and labor market outcomes. First, we examined whether poor diabetes management was the cause of adverse labor market outcomes rather than diabetes per se. In our study, A1C levels were measured in a laboratory for all participants, whether or not they were diagnosed with diabetes by a physician. Second, we examined whether diabetes management explains the lack of association between female productivity and diabetes.

	Our study population, Mexican Americans living on the border of Mexico, had a high prevalence of diabetes. The percentage of this population diagnosed with this health condition is expected to rise from 1.4 million nationally in 2002 to 2.9 million in 2020, a 107% increase.

 In contrast, the total US population diagnosed with diabetes is expected to increase by 44% during the same time period.

DIABETES SELF-MANAGEMENT AND HEALTH CAPITAL

	Glycosylated hemoglobin measures blood glucose over a 2- to 3-month period. The greater the percentage of sugar that is in the blood supply, the higher the percentage of hemoglobin that has been glycosylated. Unlike blood sugar readings, the percentage of hemoglobin that is glycosylated is invariant to day-to-day blood sugar levels.

 If one’s management (eg, exercise, diet) is consistent, A1C levels will be better than if management is consistently poor. Thus, A1C is an excellent measure of health capital or stock in the Grossman sense.

 Blood sugar, which we will also consider, varies more because it depends on recent behavior,

 and therefore is less reliable as a health stock measure.

	For persons with diabetes, having A1C levels of 7% or less indicates that the person is managing his or her diabetes. 

 (The ADA recommends that diabetes be diagnosed using an A1C level of 6.5% or more.

) Labor productivity for adults with diabetes who have low A1C levels should be higher than for persons who have high

	A1C levels, even if A1C levels are not below 7%.

 On the other hand, an alternative hypothesis is that time and effort expended to manage diabetes may come at the expense of current, short-term labor productivity. Thus, it may be that efforts to manage diabetes lower productivity in the short term.

	Our strategy to test the hypothesized association between labor productivity and unmanaged diabetes involved creating an interaction term between diabetes and A1C levels. Persons with diabetes had an interaction term value of 7 or lower if they were managing their diabetes, but persons with diabetes who were not managing their diabetes had an interaction term value of greater than 7. Persons without diabetes had an interaction term value of zero. Thus, we expected to find a negative relationship between this interaction term and log wage. We also examined the association between blood sugar levels interacted with diabetes status (persons who managed their diabetes would tend to have lower blood sugar levels) and employment and wages.

	The data for this study came from a household survey conducted in Brownsville, Texas, a metropolitan area with a total population of 175,494 in 2008, located in the US-Mexico border region.

Brownsville is the most southernmost city in Texas and 91.3% of its population is of Hispanic origin.

 Brownsville, like many other Texas border cities, is characterized by high poverty levels and low educational attainment. For example, 36.5% of people in Cameron County, where Brownsville is located, live below the poverty level (which ranks the county next to last in the United States). Only 60% of the population aged 25 years and over have completed high school, which ranks the county last in the United States. Approximately 46.5% of children under age 18 years are below the poverty level, which ranks the county next to last in the United States.

	In order to ensure variation in household income, the survey team selected census blocks from census tracts with median household incomes in the first and the third quartiles. (Note that households selected within the census tracts may have differing income levels.) The 2000 US Census of Population and Housing was used to select the probability sampling frame. Within all randomly selected clusters (census blocks), all the households in the census block were contacted. A participant between ages 35 and 64 years from each household was randomly selected using a 10-digit permutation algorithm.

	For our purposes, the key features of our data were the laboratory-measured A1C levels, blood sugar levels, and labor variables. To our knowledge, the Health and Retirement Study is the only national data set that features A1C as a variable, but the average age in that sample is much older. Our sample was exclusively Mexican in origin, so the diabetes prevalence was higher despite it being a younger sample than that in the Health and Retirement Study. The study was approved by the University of Texas—Houston Committee for the Protection of Human Subjects.

	We first estimated probit models for working status si (1 = yes, at least part-time, 0 = no)

i is a vector of characteristics related to working, including human capital variables, diabetes status, diabetes management, and so forth, and 

	In order to account for sample selection bias, we also estimated the log wage yi equation using the standard Heckman method using full maximum-likelihood.

	The Heckman model solves the selection problem by estimating the probability that wage is observed 

i (1 = yes, at least part-time, 0 = no) in equation 3. In equation 2, 

 represents associated coefficients. The function 

(·) returns 1 when the condition is true, 0 otherwise. 

are defined in equation 1. Note that accounting for selection is necessary when the correlation of 

 is nonzero. We included the log of other household income in the selection equation, but excluded it in the log wage equation in order to ensure identification.

i) in equation 2. The idea is that after controlling for human capital variables, differences in wages for people with similar educational and experience levels are due to differences in productivity, which may partly be explained by health differences. Work propensity, or the likelihood of working versus not working, is accounted for in equation 3.

 shows the laboratory data for survey participants with diabetes. Despite the general perception that women are more compliant with diabetes management, women had 10% higher A1C levels than men. This observation casts doubt on the notion that better labor outcomes for women are the result of better diabetes management.

 For both sexes, the confidence intervals, which were weighted to the population with diabetes, were narrow. Neither men nor women appeared to be managing their diabetes effectively.

reports the descriptive statistics for the variables used in the probit and Heckman regressions by sex. Note that women were less likely to be employed and had slightly less schooling than men, and were more likely to be immigrants. Men also were paid more than women. For both men and women, the sample size was weighted to the population size (208/7686 men; 436/9762 women).

 shows the results of the probit estimates by sex. These results were weighted to the population level of the first and third quartiles in Brownsville, Texas. Most signs were as expected, but were not statistically significant. For men, one would expect years residing in Brownsville and years of schooling to be positively related to the likelihood of working, but they were not significantly greater than zero. For most respondents to this survey, the number of years residing in Brownsville was synonymous with the number of years in the United States.

	For men, having diabetes lowered the likelihood of working by 5%. For women, the relationship between diabetes and working was positive, but not statistically significant. These results are similar to others

in that among persons with diabetes, men experienced greater productivity losses than women. Note further that for Hispanic men, diabetes has been shown to be endogenous. However, the primary aim of this article was to examine the direct effect of managing diabetes on productivity. We did not have any suitable instruments to examine diabetes management behavior.

shows the effects of blood sugar levels and A1C, respectively, on the likelihood of working. The controls were the same as in Table 3. Neither blood sugar nor A1C significantly affected the likelihood of working, and for women, the signs were not as expected. However, that is in accordance with previous research showing that diabetes affects men more than women.

 shows the effects of blood sugar levels and A1C, interacted with diabetes, on the likelihood of working, with the controls the same as in Table 3. The idea behind the interaction, as described earlier, is that nondiabetic persons should not have their work propensity affected by lower blood sugar or A1C levels. However, for those with diabetes, managing blood sugar and A1C may increase work propensity. For men, both the blood sugar interaction and the A1C interaction were significantly (negatively) related to work propensity. Glycosylated hemoglobin was more tightly correlated with work propensity than were blood sugar levels, likely because A1C is a more stable measure of diabetes management. If the A1C level for an adult with diabetes fell by 10% due to better diabetes management, the likelihood of working increased by 0.44%. However, note that having diabetes decreased the likelihood of working by 5%. For women, the signs were not as expected, but the elasticities were not significantly different from zero.

 reports the estimates for the Heckman model. For the selection model in the lower half of Table 6, the signs of the coefficients were as expected for both sexes, except for schooling among males. Being born in Mexico had a positive effect on working propensity for men, but not women. The variable “years in Brownsville” was negatively related to the likelihood of working. The selection model was warranted because both likelihood ratio tests rejected the null hypothesis that the selection equation and log wage equations had independent error terms.

Articles

POLICY

Diabetes itself affected working and wages more than control of blood sugar levels in a Mexican American population.

Diabetes and Employment Productivity: Does Diabetes Management Matter?

	The 2010 Patient Protection and Affordable Care Act included a provision to promote the formation of Accountable Care Organizations (ACOs). These organizations will be eligible to share in the savings to Medicare if they are able to reduce costs and provide high-quality care. The law allows a wide variety of organizations to become ACOs, even networks of providers that are small compared with major integrated delivery networks. The Center for Medicare and Medicaid Services recently proposed regulations, which are extensive and complex. They impose significant regulatory requirements on these new organizations, ranging from the structure of the organization to quality standards for qualifying for any shared savings. There are a number of challenges to ACOs and it is uncertain whether they can achieve the goals Congress had in mind or even whether many healthcare provider organizations will be interested in participating in the program. The potential for shared savings may be too small to justify the additional costs and regulatory burdens of becoming an ACO. In addition, the incentives to physicians may be inadequate to encourage behavior that reduces cost while maintaining quality. The article reviews the proposed regulations and discusses the prospects for success of ACOs.

		Many hospital administrators and physician groups will be interested in creating ACOs that can qualify for shared savings if they reduce Medicare costs per patient below a benchmark. However, before taking steps to qualify for the program, they will want to understand the new proposed regulations.

		The new ACO program contains a number of complex features, including the methodology for computing the savings to Medicare achieved by the ACO. The article describes the methodology in detail.

		Currently, CMS is evaluating comments on its proposed regulations. Healthcare organizations that are interested in the program will want to see if CMS revises them in light of the mostly negative reaction.

	Last year’s major healthcare reform bill, the Patient Protection and Affordable Care Act (ACA),

 provided for a new form of healthcare organization called Accountable Care Organizations, or ACOs. The concept of ACOs has been advocated by a number of healthcare experts for some time.

 In addition, the Center for Medicare and Medicaid Services (CMS) conducted a demonstration project during 2005-2009 to test the concept. The results of this demonstration, which are discussed below, were not completely encouraging. However, they did not dissuade Congress from authorizing CMS to implement a national program. ACOs now have new prominence because the ACA includes a section intended to promote their formation.

	Recently, CMS proposed regulations describing how hospitals and other providers can create an ACO and setting out the requirements to qualify for the program.

 The CMS has also published rules for ACOs to apply for waivers from certain federal laws in order to operate effectively.

 The reaction to the Proposed Rule was overwhelmingly negative. Major healthcare organizations, such as the American Hospital Association (AHA), the American Medical Association (AMA), and others criticized the proposal as too burdensome and costly considering the limited incentives offered by the program. I discuss some of these comments in this article in connection with particular provisions of the proposal.

	The ACA and the proposed regulations promote the formation of ACOs by providing for a creative form of reimbursement that is intended to encourage providers within the ACO to reduce costs while maintaining quality. In particular, an ACO may receive payments for shared savings if it can reduce costs for Medicare beneficiaries below a specified benchmark. These payments in turn can be shared with physicians and other providers in order to encourage more efficient healthcare delivery. But while ACOs have the potential to reduce costs, in large part by influencing physician behavior, as I discuss below, a number of challenges may prevent them from providing significant benefits.

	The ACO potentially has 2 advantages over other forms of organization. First, the ACA provides for considerable flexibility in how ACOs are organized. They need not be as large or integrated as an Integrated Delivery Network (IDN). Consequently, they can be developed more quickly and with fewer resources. The ACA provides that the following arrangements may qualify as an ACO

	1. ACO professionals in group practice arrangements. (“ACO professionals” are defined as physicians, physician assistants, nurse practitioners, and clinical nurse specialists.)

	2. Networks of individual practices of ACO professionals.

	3. Partnerships or joint venture arrangements between hospitals and ACO professionals.

	4. Hospitals employing ACO professionals.

	5. Such other groups of providers of services and suppliers as the Secretary of Health and Human Services (HHS) determines appropriate.

	The second potential advantage is that the ACA provides for a unique form of payment to an ACO: participation in “shared savings,” which are defined as a percentage of the difference between a benchmark determined by the Secretary and the costs to Medicare for services provided to beneficiaries who are assigned to the ACO.

 Although this type of reimbursement has features that resemble capitation, it is different in important respects. Capitation reimbursement pays the same amount for each enrollee in a plan, whether an individual uses services or not. An ACO is generally guaranteed at least the standard Medicare reimbursement levels for beneficiaries who require services. Under some circumstances, an ACO can experience a loss in reimbursement if its expenditures for beneficiaries are too high. Thus, total Medicare payments are higher for a population that experiences a greater need for services, while total payments are fixed under a capitation approach. As a result, ACOs face considerably less financial risk than a Health Care Organization (HCO) that depends on fixed capitation payments. (As used here, “HCO” is a generic term for an integrated network of healthcare providers, ranging from a single hospital affiliated with a physician group to a large IDN, which may include dozens of hospitals, affiliated physician groups, and other types of providers.)

	CMS’s Proposed Rule sets out the requirements for participating in the program, the formulas for shared savings, and other relevant regulations.

 The proposed regulations are complex and lengthy. In part, this is the result of the analytical challenges inherent in devising a rational way to calculate shared savings. In addition, it appears that CMS envisioned each ACO to be a model HCO, which incorporates all the ideal qualities of efficiency, high quality care, and sensitivity to patients. The complete regulatory scheme is quite daunting, so much so that it is likely to discourage many organizations from participating in the program.

	In order to qualify for participation in the Shared Savings Program, an ACO must agree to a series of conditions.

	1. become accountable for the quality, cost, and overall care of the Medicare fee-for-service beneficiaries assigned to it;

	2. enter into an agreement to participate for at least 3 years;

	3. have a formal legal structure that allows it to receive and distribute shared savings;

	4. include primary care professionals sufficient for the beneficiaries assigned to it (at least 5000);

	5. provide HHS with required information;

	6. have a management structure that includes clinical and administrative systems;

	7. adopt processes to promote evidence-based medicine and coordinate care; and

	8. meet patient-centeredness criteria specified by HHS.

	The statutory requirements are amplified in the proposed regulations. The following discussion summarizes the principal requirements:

 A participating ACO must agree to comply with certain requirements for 3 years.

 As discussed below, an ACO can choose to participate under Track 1 (the “one-sided” lower-risk, lower-reward model) or Track 2 (the “two-sided” higher-risk, higher-reward model). After the first 3 years, all ACOs must operate under the Track 2 model.

Creating a Separate Legal Entity to Serve Certain Functions.

 An ACO can be composed of several distinct legal entities, such as hospitals and physician practices. However, it must create a separate legal entity, such as a non-profit corporation, to serve certain functions, such as distributing shared savings.

While the statute and the Proposed Rule are flexible regarding the type of legal entity required, an ACO must have a governance structure that meets CMS’s requirements. The ACO’s participants must have at least 75% of “control” of the ACO.

 As a technical matter, it would seem that this 75% control requirement could be met by giving 1 physician practice, out of many participating in an ACO, the right to name, say, 8 of 10 board directors. However, the explanation of the Proposed Rule also states: “[W]e propose that the ACO must demonstrate a mechanism of shared governance that provides all ACO participants with an appropriate proportionate control over the ACO’s decision making process.”

 This statement suggests an additional requirement, that each participant must have a share in the control of the ACO that reflects its degree of participation in the ACO. In addition, beneficiaries are to play some role in governance as well.

	The idea of proportionate control is not a traditional one in HCOs or any other corporate structure, nor is “customer” participation in governance. Control of a traditional corporation is vested in a board of directors, which is chosen in a variety of ways, including by shareholders in a for-profit corporation. There is no requirement that service providers affiliated with a corporation, eg, physician groups affiliated with an HCO, share proportionally in its governance. Mandating a particular scheme of governance could undercut the efficiency of the ACO and require a major revision of existing governance structures of HCOs that want to qualify as ACOs. There is certainly a value in ensuring the accountability of the leadership of an ACO, but “proportionality” is an unwieldy and unnecessary requirement. Note, for example, the suggestion made by Delos M. Cosgrove, MD, on behalf of the Cleveland Clinic, in his letter (May 26, 2011) (Cleveland Clinic Comment) to Donald Berwick, MD: “We recommend that CMS drop its specific Board composition and relationship requirement.” Note also the suggestion made by Rick Pollack, on behalf of the AHA, in his letter (June 1, 2011) (AHA Comment) to Donald M. Berwick, MD: “We urge CMS to moderate its proposed governance requirements to allow providers to use their current governance process…as long as they can demonstrate how they achieve shared governance on care delivery policies.”

 The ACO must satisfy CMS that it has a particular management structure that accomplishes the goals that CMS envisions. For example, there must be a full-time senior-level medical director physically present at one of the ACO participant facilities who is a board-certified physician.

 An ACO’s participants must have a meaningful investment in the ACO but the investment need not be financial. It can be a “meaningful human investment (for example, time and effort) in the ongoing operations of the ACO....”

 There must also be an “infrastructure” (eg, information technology) that enables the ACO to collect and evaluate data.

One of the most demanding—and probably unrealistic&mdash;requirements is that 50% of primary care physicians participating in the ACO meet the CMS standard for “meaningful use” of information technology.

 These notices include informing beneficiaries that their ACO providers are participating in the ACO, that they have a right to use other providers, and that they can opt out of CMS sharing data on the services they receive.

Taking Responsibility for the Care of at Least 5000 Beneficiaries.

 All ACOs must have responsibility for at least 5000 beneficiaries, although CMS contemplates that some ACOs will be much larger.

 A beneficiary does not “choose” an ACO, at least not directly, and an ACO does not “choose” a beneficiary. Instead, the Proposed Rule states: “The term ‘assignment’.... refers only to an operational process by which Medicare will determine whether a beneficiary has chosen to receive a sufficient level of the requisite primary care services from physicians associated with a specific ACO so that the ACO may be appropriately designated as exercising basic responsibility for that beneficiary’s care.”

 In general, CMS determines whether a patient is assigned to an ACO based on whether a patient is receiving a “plurality” (not a majority) of his or her primary care services from participants in the ACO.

 This determination is made “retrospectively,” that is, it is based on use of services during the 3-year period before the ACO agreement begins by beneficiaries that “would have” been beneficiaries of the ACO if they had kept using the same primary care providers during the agreement period that they used during the benchmark period.

 “Performance period” and “performance years” are CMS’s terms for the period of the ACO’s agreement when determinations of shared savings are made.

Complying With Extensive Reporting Requirements.

 These include reporting information about participating providers, submitting extensive information in the original application and in the event of significant changes, and reporting information related to quality of care and making public disclosures.

Adopting Procedures to Achieve “Evidence-Based Medicine,” “Patient Engagement,” “Coordination of Care,” and “Patient-Centeredness.” 

These terms are not self-defining and there are obviously a wide variety of approaches to achieving these goals, depending on how they are defined. The explanation of the Proposed Rule states: “Evidence-based medicine can be generally defined as the application of the best available evidence gained from the scientific method to clinical decision-making.”

 The Proposed Rule also includes several criteria for determining whether the “patient-centeredness” requirement is met. These include, for example, making beneficiaries and their families partners in caregiving and ensuring patient involvement in governance. The ACO must also have a “beneficiary experience of care survey” in place and a plan for using the results of the survey.

Submitting All Marketing Materials to CMS for Advance Approval.

 States CMS: “We believe there is a potential for beneficiaries to be misled about Medicare services available from an ACO or about the providers and suppliers from whom they can receive those services.”

 For this reason, all marketing materials must receive advance approval from CMS. Note that this is a more burdensome requirement than the one imposed by the Federal Trade Commission (FTC) on advertisers generally. The FTC does not require advance approval of advertisements and marketing materials, but challenges advertising that it considers to be false or deceptive. This advance approval requirement puts a significant administrative burden on CMS and also risks substantial delays in marketing campaigns while CMS performs its review. In his letter to Donald Berwick (June 3, 2011) (AMA Comment), Michel D. Maves pointed out: “[The] requirement that CMS approve all ACO marketing materials is an unprecedented, unnecessary, inappropriate, and unworkable requirement.” Additionally, it does not seem likely that ACOs have a greater potential to engage in deceptive advertising than advertisers in general. Therefore, it is difficult for CMS to justify this unusual advance review requirement.

Complying With Other Legal Requirements. 

The Proposed Rule requires that the ACO have a compliance plan to ensure compliance with all legal requirements, including the Anti-Kickback Statute, the False Claims Act, etc.

 One of the most significant requirements is intended to prevent conflicts of interest by mandating that ACOs require members of their governing body (not all ACO participants) to disclose relevant financial interests.

 A waiver procedure proposed by CMS would allow ACOs to be exempt under some circumstances from the Physician Self-Referral Law, the Anti- Kickback Statute, and other restrictions.

 Obviously, CMS and the antitrust agencies that participated in developing the Proposed Rule are concerned that the cooperation of multiple providers within an ACO might harm competition. An ACO would already be subject to federal and state antitrust laws without any new requirement, but the Proposed Rule and a Policy Statement issued by the FTC and Department of Justice provide for a special antitrust review procedure.

 The antitrust agencies already have in place a Health Care Policy Statement, which addresses the degree of integration required to be analyzed under a “rule of reason,” which takes into account market share and other facts that affect competition, rather than a “per se” analysis, which focuses only on the nature of the agreement. Arguably, the antitrust procedure in the Proposed Rule includes a more flexible standard for rule of reason analysis.

	In general, the required review is based on the ACO’s market share for a “common service” if 2 or more participants in the ACO offer the same service. If the total market share of all the ACO participants for that service is below 30% in the ACO’s geographic area called the Primary Service Area (PSA), the ACO is eligible for a “safe harbor” for that service and no review is required.

 For example, assume that: 1) 2 group practices that are participants in an ACO offer cardiology services, and 2) the combined market share of these 2 group practices for cardiology services is less than 30% in the relevant PSAs. Under those circumstances, there is a safe harbor for cardiology services and no special review is required. However, if the market share is above 50%, the ACO must seek an antitrust review and obtain approval from the agencies.

 If the share is between 30% and 50%, the ACO has the option to seek a review.

 In that intermediate zone, the Policy Statement provides that, if the ACO avoids certain types of conduct, it is more likely to obtain clearance from the agencies.

 For example, conduct that should be avoided includes discouraging payers from directing patients to use providers outside the ACO and contracting with physician specialty groups on an exclusive basis.

	Note that the standard of review—safe harbor, optional review, or required review&mdash;is based on a particular service, not the overall percentage of patients who are assigned to the ACO in a particular geographic area. Even if the market share under the above analysis is less than 30% for all services but 1, review is required for the remaining service.

 Note also that, except for the “dominant provider” limitation discussed below, no review is required if there is only 1 participant in the ACO that offers a particular service.

 To take the cardiology services example, assume that there is only 1 group practice within the ACO that offers cardiology services, but its market share in the PSA is 75%. There would be no mandatory review. However, to come within a safe harbor, “The ACO participant (a ‘dominant provider’) must be non-exclusive to the ACO to fall within the safety zone. In addition, to fall within the safety zone, an ACO with a dominant provider cannot require a commercial payer to contract exclusively with the ACO or otherwise restrict a commercial payer’s ability to contract or deal with other ACOs or provider networks.”

	The antitrust agencies are obviously worried that the consolidation of hospitals and physician practices within an ACO can threaten competition, and therefore a special review process is needed. However, like the requirement for advance approval of marketing materials, this new review procedure may end up delaying the operation and formation of ACOs and imposing unnecessary burdens and costs on ACOs as well as the agencies. Some commenters argued that, if there is to be a mandatory review threshold, the one proposed by CMS and the antitrust agencies is too low. In contrast, the health insurance industry tended to take the position that the antitrust standards should be stricter. That is presumably because health insurers are worried that consolidation may allow an ACO to have enough market power to drive down health insurance premiums.

	As a practical matter, many HCOs with even a modest degree of integration will exceed the 50% threshold in at least 1 area, triggering an expensive mandatory review. For example, the AHA found that: “[I]n the overwhelming majority of these areas, hospitals that sought to partner with any other hospital likely would exceed the 50 percent review threshold…and, thus be faced with costs of potentially several hundred thousand dollars in order to defend their ACO application before one of the Agencies.” In light of these difficulties, CMS and the antitrust agencies should consider scrapping the special review process altogether in favor of issuing more specific enforcement guidance and offering to give expedited advisory opinions.

 Section 1899(b)(3)(A) of the Act requires the Secretary to determine appropriate measures to assess the quality of care furnished by the ACO. As a first step, the Proposed Rule identifies performance criteria and reporting requirements but does not set specific quality standards.

 The Proposed Rule describes 5 “domains” of quality measures. Those standards will be developed in future rule making. The Proposed Rule includes 65 measures to calculate the “ACO Quality Performance Standard.”

 In the first year, the ACO would meet the quality performance standard by full and accurate reporting. In subsequent years, the ACO would have to meet certain minimum quality standards, which will be announced by CMS. If it does not meet the minimum quality performance standard for at least 1 domain, it would not be eligible for shared savings.

 In addition, the level of shared savings allocated to an ACO will be reduced if it falls below a perfect score on the quality standards. This is termed the “performance score approach” by CMS, to be distinguished from the “threshold approach,” which would allow maximum shared savings if all minimum quality standards are met.

 The effect may be that it is impossible for most ACOs to achieve the maximum possible savings. As noted in the AHA Comment, “[T]he manner in which CMS proposes to use the ACO’s quality score to reduce the sharing rates makes these maximums unattainable. This is because, unless an ACO scores 100 percent on all 65 proposed quality measures, which may not be possible, the quality score will always serve to reduce the sharing rate from the stated 50 and 60 percent.”

	The most significant element of the ACO program is the potential for ACOs to participate in “shared savings,” that is, some portion of the savings to Medicare from their efficient delivery of care. That possibility is the incentive for organizations to participate in the program in the first place. The question is whether the incentive is strong enough, given the administrative burden, implementation costs, and financial risks that the ACO must assume.

MANAGERIAL

CMS recently proposed regulations for Accountable Care Organizations which are extensive and complex. This article reviews the proposed regulations and discusses the prospects for success.

Accountable Care Organizations: The Proposed Regulations and the Prospects for Success

 The Centers for Disease Control and Prevention recommends routine screening for the hepatitis C virus antibody (anti- HCV) among persons most likely to be infected. Little is known about anti-HCV screening and prevalence in routine practice settings. We studied anti-HCV screening rates, anti-HCV positivity, and demographic and risk factors associated with increased likelihood of anti-HCV screening or positivity in a managed care organization (MCO).

 This was a retrospective observational study of 17-to-74-year-old MCO enrollees from 2000 to 2007 (N = 557,056; 1,949,499 enrollee years). The primary outcome measures were likelihood of anti-HCV screening and HCV positivity (both in the total population and among those screened). Independent variables were: birth cohort, gender, HCV risk factors, and socioeconomic status (SES) and race of residents’ neighborhoods. Likelihood of each outcome as a function of the independent variables was estimated using logistic regression.

 Over the 8-year period, 4.31% of the total population received anti-HCV screening; 0.22% had a positive HCV result. Among those screened, HCV positivity was 5.15%. HCV screening and positivity rates increased over time. Both likelihood of HCV screening and HCV positivity were highest (

 <.05) among persons born during 1945-1964, males, those with HCV risk factors, and residents of neighborhoods of lower SES or with higher percentages of African Americans.

 Although HCV screening and detection improved in this MCO over an 8-year period, anti-HCV screening was lower than expected. Many persons at risk for HCV remained unscreened. Strategies for improving anti-HCV screening in routine practice are recommended for patients at increased risk.

	A study was performed of HCV screening and prevalence estimates in a managed care organization, unadjusted and adjusted for HCV risk factors.

		This study updates one of the few practice-based assessments of HCV prevalence and positivity previously published in AJMC.

		Study results indicate that HCV screening is more likely among adults with HCV risk factors, but that screening rates remain sub-optimal.

		Efforts to improve rates and timeliness of anti-HCV screening generally and in specific high prevalence subgroups could identify currently undiagnosed HCV-infected patients, lead to initiation of HCV pharmacotherapy, and reduce future rates of end-stage liver disease.

According to an Institute of Medicine report released in 2010, hepatitis C virus (HCV) infection is a serious public health concern.

 In liver transplant centers in the United States, HCV infection has been found to be the most frequent risk factor for liver cancer.2 Incidence rates of hepatocellular carcinoma in the United States have tripled from 1975 to 2005,

 and have increased at an average annual rate of 3.5% from 2001 to 2006.

 Five-year survival rates for liver cancer are less than 15%,

 and more than 35,000 incident deaths are forecast to be attributable to HCV by 2030 given the aging of the population with chronic HCV infection.

A study of HCV infection prevalence in the United States using the 1999-2002 National Health and Nutrition Examination Survey (NHANES) estimated that 1.6% of the non-institutionalized non-homeless US population had measurable antibody to HCV (anti-HCV).

 HCV prevalence was significantly higher among specific demographic groups (persons born 1945-1964 [“high prevalence birth cohort”]), males, individuals with specific behavioral risk factors (injection drug use [IDU]), medical and behavioral characteristics associated with HCV infection (elevated serum alanine aminotransferase [ALT] levels, HIV (human immunodeficiency virus) infection, blood transfusion before 1992, higher numbers of lifetime sexual partners), and those with selected socioeconomic characteristics (high school education or less, income below the poverty threshold). Screening among a random sample of Veterans Administration (VA) medical center users indicated that HCV positive rates were approximately 5.4%.

Since 1998, the Centers for Disease Control and Prevention (CDC) has recommended that screening for anti-HCV should be routinely offered to persons most likely to be infected with HCV.

 Yet, little is known about anti-HCV screening practices and HCV infection prevalence in routine practice settings. Analysis of UnitedHealthcare medical claims from 1997 to 1999 indicated that 0.7% of enrollees were ever screened for HCV and, of those, 6.7% were HCV-positive (approximately 0.08% of the enrollee population).

 This HCV infection prevalence was much lower than that detected in the NHANES and VA studies and suggests that current anti-HCV screening practice may fail to detect many infected persons who could benefit from primary and secondary prevention counseling and medical management.

Both provider and patient factors might influence anti-HCV screening in routine practice. Physicians frequently do not collect HCV risk factor information from new patients; and, even if a patient has a risk factor, providers often do not order anti-HCV screening tests.

 Patients may not admit to stigmatizing behaviors, such as IDU, that might prompt providers to screen.

 Consequently, the majority of HCV-infected adults are most likely unaware of their infection and therefore do not seek out appropriate treatment or prevention services.

To assess how CDC recommendations for anti-HCV screening are currently implemented in a typical healthcare setting, we conducted a retrospective observational study of HCV screening and HCV infection prevalence among adult enrollees of a managed care organization (MCO) from 2000 through 2007. Our study had 2 objectives: to estimate 1) cumulative rates of anti-HCV screening and positivity in this MCO, and 2) association of enrollee demographic and risk factors with likelihood of anti-HCV screening and positivity.

Kaiser Permanente Georgia (KPG) is a federally qualified, group- and network-model MCO that, during the study period, provided comprehensive medical services to approximately 275,000 members per year in the metropolitan Atlanta area. This study protocol was reviewed and approved by the KPG Institutional Review Boards (IRBs) and CDC.

KPG’s clinical practice guidelines recommend enzyme immunoassay (EIA) for anti-HCV screening, with confirmation by reverse transcriptase—polymerase chain reaction if the initial screening test is reactive. These guidelines recommend anti-HCV testing according to “risk for infection” including: IDU history or other illegal drug use, history of chronic hemodialysis, persistently abnormal ALT levels, receipt of clotting factor concentrate before 1987, and receipt of blood transfusion or organ transplant before July 1992.

KPG computerized databases were the source of data for enrollee demographics, enrollment history, laboratory screens and results, and diagnoses and procedures (both 

International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM]

Current Procedural Terminology, 4th Edition [CPT-4]

-coded) associated with ambulatory, emergent, and hospital care. All records can be linked at the individual level using unique identifiers. Residential addresses of KPG enrollees are geocoded to US Census tracts and block groups using MapMaker Plus (Mapinfo, Troy, New York) for linking to Summary File 3 (SF3) records.

The study population consisted of 557,056 enrollees, aged 17 to 74 years, impaneled to a KPG primary care physician, and enrolled at least 1 month during 2000-2007. The population was constructed year by year, with age defined as of January 1st of each year. Thus, an enrollee who was 17 to 74 years of age as of January 1st of a year and enrolled for at least 1 month during that year would be included for that year. An enrollee <17 years or >74 years as of January 1st of a year or an enrollee without enrollment in a year would not be included for that year. Thus, the final analysis data set included 1,949,499 enrollee-years.

 HCV screening was defined as having had an HCV antibody laboratory assay performed, either an anti-HCV EIA or recombinant immunoblot assay (RIBA). HCV RNA assays, for quantitative measurement of viral load, were not considered to be screening tests in this study.

Annual and cumulative anti-HCV screening rates were defined. For tracking annual rates of HCV screening, each age-eligible enrollee with enrollment in a study year was ascertained for receipt of at least 1 anti-HCV screening test in that year. History of anti-HCV screening for each enrollee was then assessed across the 8-year period to determine if the enrollee was “ever screened.”

 HCV positivity was defined as an indication in the laboratory records of a positive result on an anti-HCV screening test. Annual and cumulative anti-HCV positivity rates were defined similar to HCV screening.

 A neighborhood socioeconomic status (SES) index is defined from principal components analysis of 7 of the 2000 SF3 variables for each enrollee’s geocoded Census tract or block group (518,639 of the 557,056 enrollees in the study population): 1) Percent of households with income below the poverty level, 2) Percent of households receiving public assistance, 3) Percent of households with annual income below $30,000, 4) Percent of working age adult males not in the labor force, 5) Percent of adults 25 years and older with a high school education or less, 6) Log of median household income, and 7) Log of median value of single family homes. The selected variables are based on previous studies.

 Factor scores obtained from the principal components analysis are used to assign enrollees to quartiles of an SES index.

Percent African American Residents in Neighborhood. 

Percent of African American residents in a neighborhood was also obtained from the 2000 SF3 data set for each enrollee’s geocoded Census tract or block group. This variable serves as a proxy measure for race since individual-level race is not generally available. Internal KPG studies show a significant positive correlation at the Census tract level between self-report from surveys and this SF3 measure (Pearson coefficients >0.80).

 In addition to these 2 area-based measures, individual-level covariates were defined for duration of enrollment during 2000-2007 (<1, 1-2, 3-4, and >4 years), selected HCV risk factors, and birth cohort. Given the potential confusion caused by differences in terminology regarding behavioral risk factors, medical risk markers, and healthcare and environmental exposures, we consolidate these categories under the single term risk factors for the sake of brevity in the narrative. HCV risk factors were defined for IDU, coagulation defects (eg, hemophilia), dialysis, HIV, and elevated ALTs (

). These measures were selected because they were 1) listed as indications for HCV screening in KPG’s clinical practice guidelines or referenced in the provider focus groups and 2) could be measured using KPG computerized data beginning with 1995 (the first year for which reliable and complete computerized data were available). Other HCV risk factors (eg, blood transfusions prior to 1992) were not measured due to incomplete data prior to 1995. Birth cohorts were defined by year of birth and classified into 5-year subgroups.

For 2000-2007, we graphed the annual anti-HCV screening and HCV positivity rates per 10,000 enrollees both for the high-prevalence cohort and those born before 1945 or after 1964. We used a χ2-statistic to test for significance (

 <0.05) of associations of each covariate with the percent of the study population: 1) ever screened for HCV, 2) ever screened positive for HCV from 2000 to 2007, and 3) ever screened positive among those screened. We also estimated multiple logistic regression models for these 3 outcomes as a function of enrollment duration, birth cohort, gender, quartiles of neighborhood SES and percent African American residents, and the 5 HCV risk factors available in the medical record. In addition to the models with the HCV risk factors separately specified, we estimated another set of models with a single measure of HCV risk (any of the 5 vs none) in place of the 5 separate risk factors.

 displays the annual HCV screening rate per 10,000 age- and enrollment-eligible adults. On average, the annual HCV screening rate increased approximately 3-fold from 2000 to 2007. The annual HCV screening rate trends differed only slightly between the high prevalence birth cohort and the other birth cohorts.

 displays the annual HCV positive rate per 10,000 age- and enrollment-eligible adults. The annual HCV positive rate remained relatively constant until 2004, when the rate increased by about 30% for all ages. Over the 8 study years, the ratio of HCV positivity of the high prevalence birth cohort to those outside the cohort averaged 5.0, with a range of 4.0 (2001) to 7.3 (2003).

Approximately one-third of the study population represented the high prevalence birth cohort; and, approximately one-third of the population was enrolled with KPG for 4 or more years of the study period (

). There were slightly more women than men. Documented HCV risk factor prevalence was generally low; and, only 2.67% of the population had 1 or more of the 5 recorded risk factors.

Over the 8 year period, 4.31% of the total population was ever screened for HCV; 0.22% of the population ever screened positive for HCV; and, among those screened, 5.15% had a positive anti-HCV test (Table 1). Frequency of anti-HCV screening and HCV positivity (both within the entire study population and among those screened) were significantly associated with 4 or more years of enrollment, birth between 1945 and 1964, males, enrollees living in lower SES neighborhoods or neighborhoods with a high percentage of African American residents, and 1 or more of the 5 recorded risk factors.

 displays the adjusted odds ratios (aORs) from the multiple logistic regression models. Generally, the pattern of the aORs with respect to the covariates was similar to the pattern observed in the unadjusted associations (Table 1); however, there were some differences. The likelihood of ever being screened for HCV was generally higher among those who had longer enrollment duration, were younger, were females, lived in the highest SES neighborhoods or neighborhoods with high percentages of African Americans, or had any of the documented HCV risk factors. The likelihood of ever being screened positive for HCV was generally higher among those who had longer enrollment duration, were born from 1945 to 1964, were male, lived in the lowest SES neighborhoods or neighborhoods with high percentages of African Americans, or had any of the recorded HCV risk factors. This pattern of aORs for ever screened HCV positive with the covariates was also observed among the subgroup ever screened for HCV (with the exception of the distribution of aORs for enrollment duration). In the multiple logistic regressions with a variable for any of the 5 documented HCV risk factors (vs none) in place of the 5 separate risk factors, significant (

 <0.05) positive associations were again observed with HCV screening and HCV positivity.

For the multiple logistic regression models which grouped the 5 documented HCV risk factors into a single measure, we found significant, positive associations with HCV screening and HCV positivity—with aORs of 8.21 for ever being screened for HCV, 15.22 for ever being screened HCV positive, and 2.84 for ever being screened HCV positive among those ever screened.

CLINICAL

HCV screening and prevalence estimates, unadjusted and adjusted for HCV risk factors, are examined in this 8-year observational study of a managed care organization.

HCV Screening Practices and Prevalence in an MCO, 2000-2007

Treatment of dyslipidemia in high-risk patients specifies a low-density lipoprotein (LDL) cholesterol <100 mg/dL. The efficacy of higher-potency regimens in clinical practice in patients who have not achieved their LDL goal on generic therapy is not well characterized. The primary objective of this study was to determine the LDL-lowering efficacy of higher-potency strategies (ezetimibe/simvastatin, rosuvastatin, and atorvastatin) in high-risk patients who were switched from simvastatin therapy. Secondary objectives were to evaluate patient adherence to these therapies, determine the efficacy of these interventions on other lipid parameters, and define the incidence of adverse effects.

Retrospective data analysis derived from the Veterans Affairs Health Care System VISN 21 over a 3-year time period.

 Lipid data were assessed prior to and within 2 to 6 months following the conversion from simvastatin. Adherence to therapy was determined by medication refill data.

 Treatment with ezetimibe/simvastatin resulted in significantly greater reductions in LDL compared with rosuvastatin or atorvastatin (37 vs 25 and 26 mg/dL, respectively; P <0.05). Adherence to therapy was 51% of all patients studied. All treatments significantly lowered total cholesterol, high-density lipoprotein, and triglycerides when compared with simvastatin. There was no difference between treatment groups in the number of adverse events.

 At the doses used in this population, ezetimibe/simvastatin resulted in greater LDL reductions than rosuvastatin or atorvastatin. The clinical impact of these differences is as yet undetermined.

	In a Veterans Administration population, low-density lipoprotein (LDL)-lowering in patients switched from generic simvastatin was greater with ezetimibe/simvastatin than atorvastatin or rosuvastatin without any difference in side effects. Adherence to therapy was only 51% and had a marked effect on the efficacy of LDL lowering. Thus:

		The greatest effect on LDL lowering is achieved using combined statin and cholesterol absorption inhibition.

Efficacy of switching statin therapy from generic simvastatin was examined in a VA population. Ezetimibe/simvastatin was more potent than atorvastatin or rosuvastatin in lowering LDL.

August 2011

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