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For-Profit And Not-For-Profit Health Plans Participating In Medicaid

Abstract

 
The proliferation of for-profit health plans has heightened concerns about quality of care, particularly with respect to Medicaid. We undertook this study to compare for-profit and not-for-profit health plans that participate in Medicaid, examining processes of care and the organizational characteristics related to utilization management, financial incentives, and quality of care. Our findings demonstrate that for-profit and not-for-profit plans appear to be more similar than dissimilar in many areas of management, although for-profit plans are more likely to use aggressive utilization review and have slightly less developed quality management systems. On balance, these findings should reassure critics of for-profit health care.

In recent years the proliferation of for-profit plans has exacerbated these concerns. Whereas fewer than 30 percent of health maintenance organizations (HMOs) were for-profit in 1983, by 1998 more than two-thirds were for-profit.⁴ Critics of for-profit medicine have argued repeatedly that fiduciary responsibility to shareholders (that is, maximizing profitability) and high-quality care are incompatible. Anecdotal reports abound in the popular press about poorer care provided by for-profit health plans, and there have been problems with for-profit health plans in Medicaid in the past. For instance, in an expansion of the MediCal program in the 1970s, newly formed not-for-profit health plans, which were often controlled by for-profit entities, were embroiled in scandals related to fraudulent marketing practices, inadequate capital, and substandard care.⁵

Notwithstanding these occurrences in the past, some observers argue that all health plans are sensitive to economic constraints and that the more flexible capital structure of for-profit health plans facilitates the provision of high-quality services.⁶ For-profit plans may have more resources available to develop their information systems and the quality management infrastructure necessary for providing high-quality care. Indeed, for-profit entities operate in most sectors of our economy without reducing the quality of their services or products.

Despite the importance of these issues, virtually no data exist to show how for-profit health plans actually differ from not-for-profit plans on critically important aspects of health care delivery. Specifically, we still know very little about how for-profit and nonprofit health plans differ in the way they manage utilization and assure quality of care or how they differ in the financial incentives designed to constrain medical services or increase quality of care provided by member physicians. In this study we report on a national survey of health plans serving the Medicaid managed care market.

Data And Methods

Top Data And Methods Study Results Discussion NOTES

 
Survey sample and procedures. We developed a detailed self-report questionnaire that was administered to health plan representatives between September 1997 and April 1998. Details of the questionnaire design and administration as well as results pertaining to quality management by commercial health plans and those that serve predominantly the Medicaid population are reported elsewhere.⁷

Briefly, through previous research and published reports, we identified thirty-four states, including the District of Columbia, that enrolled Medicaid beneficiaries in comprehensive prepaid managed care plans as of 30 June 1996. We then randomly selected, proportional to total Medicaid enrollment, eleven of these states (Arizona, California, Connecticut, Pennsylvania, Florida, Maryland, Tennessee, Oregon, Washington, Michigan, and Illinois) and the District of Columbia. All health plans providing prepaid general medical care to Medicaid beneficiaries during June 1997 (the reference period for the study) were eligible to participate in the survey. We excluded primary care case management (PCCM) plans, specialized HMOs that focused on mental health or other specialized populations, and plans with fewer than 200 Medicaid enrollees.

Using information from state Medicaid agencies, we identified a health plan contact—generally the medical director, chief executive officer (CEO), or director of quality management—to complete the survey. We gave respondents the option of scheduling a structured telephone interview or completing the written survey independently, an option that allowed them to gather information from colleagues. We reviewed completed surveys and made follow-up calls to query missing or confusing responses.

Survey questionnaire. The survey instrument, designed for closed-ended responses, first elicited descriptive information on plans’ organizational characteristics, including total and Medicaid enrollment, relationship of the Medicaid product to commercial products, years in operation, ownership, use of gatekeepers, categories of Medicaid beneficiaries enrolled, and profit status. The remainder of the questionnaire reported here included questions on aspects of health care management in which for-profit and not-for-profit health plans seemed likely to differ: strategies to control utilization, use of financial incentives, quality management, credentialing, and information systems. These domains were selected based on a theoretical model of the effects of health care organizations on the quality of care as well as a review of the relevant literature.⁸ In particular, there is evidence to suggest a possible relationship between profit status and utilization review, quality management practices, and the use of financial incentives.⁹

We obtained information about three aspects of utilization review: (1) whether the plan required approval for a specific diagnostic test (magnetic resonance imaging, or MRI, of the head), referral (to an orthopedic surgeon), and surgical procedures (spinal surgery) that are expensive and frequently thought to be discretionary and are thus commonly targeted by health plans; (2) whether the plan allowed direct access for visits to the emergency room and to a gynecologist; and (3) whether the plan collected information and fed it back to providers on use of services, including hospitalizations, emergency room visits, and referrals.

To assess financial incentives, we first asked the principal methods for compensating primary care and specialist physicians and the extent to which health plans adjusted compensation based on financial or nonfinancial (for example, quality and patient satisfaction) measures of performance. We also inquired into the maximum proportion of compensation that was "at risk" in each of these areas and the average proportion of "at-risk" compensation that was actually paid out in each of these areas in the past year.

We next collected information about quality management. We first asked about existing data collection and feedback to providers on complaints, disenrollment, satisfaction, and indicators of access and quality. In the areas of access and quality, we chose measures applicable to the Medicaid population. We primarily asked about specific Health Plan Employer Data and Information Set (HEDIS) measures for quality improvement initiatives because we thought that plans would preferentially target these measures. For each indicator of satisfaction, quality, and access, we then asked if the health plan had "targeted [the area] in a quality improvement program" and whether the health plan had demonstrated improvement.

We next collected information about the composition of the provider network in terms of physician credentialing and requirements for board certification. Although drawing firm conclusions about a plan’s quality on the basis of such information is difficult, many purchasers use this information as an indicator of the quality of care.¹⁰

The final part of the survey inquired about information systems. We first asked whether the plan maintained a complete encounter- or claims-level database and, if so, whether it had used this database to analyze patterns of care for individual providers or groups of providers, specific populations according to either diagnoses or demographic characteristics, or episodes of care. We defined episodes of care as "all of the care that surrounds an acute or chronic illness related to that condition such as all of the visits or hospitalizations related to a single episode of pneumonia." We also asked the extent to which the plan validated the quality of its data and, of particular concern to the Medicaid population, whether their automated systems contained information on the primary language for all enrollees.

Analysis. We compared characteristics of for-profit plans with those of not-for-profit plans. For the purposes of this analysis, we grouped together publicly traded and privately held for-profit plans. Proportions were compared using the chi-square test or the Cochran-Mantel-Hanzel test for categorical variables. We used t-tests to compare continuously valued variables. All results were also examined using multivariable regression to control for other plan characteristics that might be associated with the implementation of specific programs and policies. The independent variables in all of the regressions were plan model type (group/staff or independent practice association/network), size (fewer than 5,000 members), age of plan (under five years), years participating in Medicaid (under five years), local sponsorship (for example, whether the plan was affiliated with a national managed care company), and Medicaid-only. In general, the control variables were related to some of the domains of interest in expected ways. For instance, small and new plans were less likely to have well developed quality assurance programs. None of the statistically insignificant bivariate findings became statistically significant using multivariable analysis. Therefore, we present the results of bivariate analyses and multivariable analyses of the bivariate associations that were statistically significant.

We examined the distribution of for-profit and not-for-profit health plans across the eleven states because some states might have more intense regulations that could affect our findings, and these states might tend to have a predominance of one type of plan or the other. To test the hypothesis that our findings were due to confounding by state regulations, we repeated our analyses that were statistically significant after restricting the sample to the eight of eleven states with a relatively even distribution of for-profit and not-for-profit plans. Since none of the results changed, we do not present these results.

Study Results

Top Data And Methods Study Results Discussion NOTES

 
Of the 167 health plans initially identified, we excluded thirteen. Seven plans were not providing prepaid care to Medicaid beneficiaries, four had not yet started enrolling Medicaid participants or had low Medicaid enrollment (under 200 enrollees) during the reference time for the study, and two were specialized (in this case, aimed exclusively at children). Of the remaining 154 plans, we obtained responses from 130 (84 percent). The number of eligible plans per state ranged from four to thirty-one (mean, 12.5), and response rates by state varied from 67 percent to 100 percent. For-profit and not-for-profit health plans were relatively evenly distributed across the eleven states, with only three states having one-third or less of their health plans in the smaller of the two categories. The District of Columbia had all for-profit plans, while Pennsylvania was dominated by for-profit plans and Michigan, by not-for-profit plans.

Of the 130 plans surveyed, sixty-six were for-profit and sixty-four were not-for-profit (Exhibit 1). The 130 plans enrolled a total of 26.5 million members with 5.0 million Medicaid enrollees, representing approximately 33 percent of total Medicaid managed care enrollment at the time of the reference period, and 40 percent of prepaid managed care enrollees (after excluding PCCM and "other" plans as classified by the Health Care Financing Administration).¹¹

Utilization management. Exhibit 3 displays data on the rules and regulations that health plans use to control use of services (utilization management or review). Ninety-five percent of for-profit health plans and 89 percent of not-for-profit plans used a gatekeeper model, in which patients were required to obtain authorization from a primary care physician before obtaining services such as specialty care or diagnostic tests. For-profit plans, however, were more likely to require additional review for certain selected services. On average, for-profit plans required approval for 2.2 (±0.9) of the three items about which we inquired; not-for-profit plans required approval for 1.6 (±1.2) (p < .01). These differences persisted in multivariate models controlling for size, age of plan, model type, Medicaid only or not, and local sponsorship.

In the other areas of utilization management we considered, for-profit and not-for-profit plans were more comparable. Similar proportions of plans allowed direct access to gynecologists and emergency rooms, and similar proportions were collecting and disseminating data on hospitalizations, emergency rooms, and referrals.

Quality management. Exhibit 4 shows the extent to which health plans used performance measures on selected items of particular relevance to the Medicaid population to improve the quality of care. Most plans, both for-profit and not-for-profit, collected quality information in the six areas we considered, although for-profit plans were less likely to feed such information back to physicians or physician groups. For instance, while 80 percent of not-for-profit plans and 82 percent of for-profit plans collected information on the proportion of women receiving prenatal care in the first trimester, 52 percent of not-for-profit plans fed this information back to providers, as compared with just 33 percent of for-profit plans (p < .05). In addition, while plans typically were unable to demonstrate quality improvement, not-for-profit plans were much more likely to have demonstrated improvement in the care of diabetics (22 percent versus 9 percent, p < .05). Not surprisingly, not-for-profit plans were also more likely to collect and feed back information on diabetes performance, suggesting a possible mechanism for this improved care. With one exception (collection of information on diabetics receiving a glyco-hemoglobin test, p = .10), all of these results were unchanged after other plan characteristics were controlled for.

Finally, for-profit health plans less commonly required board certification for participating participating primary care physicians, although these differences were not statistically significant (Exhibit 5). Consequently, for-profit plans reported that 75 percent of their Medicaid primary care physicians were board certified, as compared with 79 percent for not-forprofit plans (p = n.s.).

Discussion

Top Data And Methods Study Results Discussion NOTES

 
With a paucity of information, many remain concerned about the possibility of lower quality care in for-profit health plans. Minnesota now requires that health plans be not-for-profit, and a recent ballot initiative in Massachusetts that would have temporarily banned for-profit conversions of health plans was only narrowly defeated.¹² Our data suggest that for-profit and not-for-profit health plans are similar in their management practices and capabilities, and there appear to be only subtle differences in their quality and utilization management practices. Clearly, this is an important area that deserves further investigation, but the findings of this study do not seem to support policies that would ban for-profit ownership of health plans.

Despite the overall similarity between for-profit and not-for-profit plans, we did find some aspects of utilization and quality management on which plans appear to differ. For-profit plans more frequently require health plan review of diagnostic tests, referrals, and procedures. They also have a higher proportion of rejected preauthorization requests (5.5 percent versus 3.4 percent), although the magnitude of the differences appears to be small. Not-for-profit plans make greater use of performance feedback in quality management. While not-for-profit plans do not report improved performance across the board, they do appear to have more success in managing diabetes. These findings are consistent with our prior hypotheses and suggest that differences in profit status may translate into slightly different approaches to health care management.

This study is the largest published study to date of health plan practices. We know of two previous studies of differences in the quality of care provided by for-profit and not-for-profit health plans. David Himmelstein and colleagues found that for-profit plans provide lower-quality care as measured by HEDIS scores.¹³ Their findings are consistent with some of the results we observed on health plans’ quality management practices, although the disparities by profit status that they noted seem more prominent than those apparent from our survey. In a national study of elderly Medicare beneficiaries enrolled in managed care plans, Bruce Landon and colleagues found that for-profit health plans received significantly worse scores on patients’ assessments of their experiences with the plan. It is conceivable that these findings reflect the differences we note in administrative review and its attendant burden on patients.¹⁴

Study limitations. Our study has several important limitations. The data we collected on incentives were limited to information available to health plan representatives. Thus, we collected information on the magnitude of health plan payments "at risk" but lack data on how payments to medical groups were split among individual doctors. The size of the group splitting up the payment and the formulas used are critical in understanding the magnitude of incentives for individual physicians. In addition, we did not differentiate between different types of capitation (for example, full versus primary care services only), so there still might have been differences in the use of more aggressive types of capitation. Aswith almost all surveys, too, we rely on self-reports from plan representatives rather than more objective audits of what is actually done. In addition, similar policies reported by different plans might be implemented differently, and some could be systematically better. Respondents also might have been more likely to respond positively to questions that concerned desirable aspects of managed care. However, this particular limitation should not affect our comparative findings because it applies equally to both for-profit and not-for-profit health plans.

There are wide variations across states in Medicaid contracting specifications and in the regulations that address quality management.¹⁵ These regulations could bias our results. For-profit and not-for-profit plans were relatively evenly distributed across eight of the eleven states in our study. Our analyses of the patterns in these states suggest that it is unlikely that our few statistically significant findings are an artifact of state regulations. These regulations could also bias our study against finding a difference if the health plans lacked discretion in the areas into which we inquired. We reviewed the relevant regulations in the study states. Only rarely were there precise regulations directed at the specific areas in our inquiry. Lastly, in some instances there may be questions about the connections between the management practices we report, the use of medical services they are designed to affect, and health care outcomes. However, all of the structural and process indices we chose have substantial face validity in relation to constraining utilization or improving quality of care.¹⁶

Our survey of health plans serving the Medicaid market demonstrates that, overall, for-profit and not-for-profit health plans are similar, although there are some differences in our findings on utilization and quality management that lend support to the notion that the financial incentives inherent in profit status affect the way health care is managed. Further study is warranted to describe further whether and how management differences are translated into differing patterns of care and health outcomes and to determine the extent to which any of the few differences we found are meaningful, given the extent of the similarities.

Editor's Notes

 
Bruce Landon is an instructor in medicine and health care policy at Harvard Medical School and on staff at Beth Israel Deaconess Medical Center. Arnold Epstein is the John H. Foster Professor and chair, Department of Health Policy and Management, Harvard School of Public Health, and on staff at Brigham and Women’s Hospital.

This work was supported by a grant from the Commonwealth Fund. The authors are indebted to Laurie Felland, Christie Herring, Kiri Ozturk, Naama Ende, and Tal Halpern for assistance with health plan interviews; to Jeffrey Schwartz for assistance in sample development; to Deborah Collins for assistance in the preparation of this manuscript; and to Barbara McNeil and Paul D. Cleary for comments on an earlier version of this manuscript.

NOTES

Top Data And Methods Study Results Discussion NOTES

 

1. D.U. Himmelstein et al., "Quality of Care in Investor-Owned versus Not-for-Profit HMOs," Journal of the American Medical Association 282, no. 2 (1999): 159–163; J. Gabel, "Ten Ways HMOs Have Changed during the 1990s," Health Affairs (May/June 1997): 134–145; M. Angell and J.P. Kassirer, "Quality and the Medical Market-place—Following Elephants," New England Journal of Medicine 335, no. 12 (1996): 883–885; and P.M. Nudelman and L.M. Andrews, "The Value Added of Not-for-Profit Health Plans," New England Journal of Medicine 334, no. 16 (1996): 1057–1059.
2. Health Care Financing Administration, <www.hcfa.gov/medicaid/omc1999.htm> (2 April 2001).
3. B.E. Landon and A.M. Epstein, "Quality Management Practices in Medicaid Managed Care: A National Survey of ‘Medicaid’; and Commercial Health Plans Participating in the Medicaid Program," Journal of the American Medical Association 282, no. 18 (1999): 1769–1775.
4. Inter Study Competitive Edge 7.1 (1999).
5. B.H. Gray, "External Accountability and Problems of Fraud and Abuse," in The Profit Motive and Patient Care (Cambridge, Mass.: Twentieth-Century Fund, 1991).
6. M.M. Hasan, "Let’s End the Nonprofit Charade," New England Journal of Medicine 334, no. 16 (1996): 1055–1057.
7. Landon and Epstein, "Quality Management Practices in Medicaid Managed Care."
8. See, for example, R.H. Miller and H.S. Luft, "Managed Care Plan Performance since 1980: A Literature Analysis," Journal of the American Medical Association 271, no. 19 (1994): 1512–1519; B.E. Landon, I.M. Wilson, and P.D. Cleary, "A Conceptual Model of the Effects of Health Care Organizations Organizations on the Quality of Medical Care," Journal of the American Medical Association 279, no. 3 (1998): 1377–1382; and R.A. Dudley et al., "The Impact of Financial Incentives on Quality of Health Care," Milbank Quarterly 76, no. 4 (1998): 649–686.
9. M.V. Pauly, A.L. Hillman, and J. Kerstein, "Managing Physician Incentives in Managed Care: The Role of For-Profit Ownership," Medical Care 28, no. 11 (1990): 1013–1024; Himmelstein et al., "Quality of Care"; and M. Schlesinger, B. Gray, and E. Bradley, "Charity and Community: The Role of Nonprofit Ownership in a Managed Health Care System," Journal of Health Politics, Policy and Law 21, no. 4 (1996): 697–751.
10. R. Tamblyn et al., "Association between Licensing Examination Scores and Resource Use and Quality of Care in Primary Care Practice," Journal of the American Medical Association 280, no. 11 (1998): 989–995; and P.G. Ramsey et al., "Predictive Validity of Certification by the American Board of Internal Medicine," Annals of Internal Medicine 110, no. 9 (1989): 719–726.
11. <www.hcfa.gov/medicaid/plansum7.htm>.
12. R. Mishra, "Election 2000/Question 5; Health Care Initiative Apparently Defeated—Ad Drive Erodes Initial Support," Boston Globe, 8 November 2000, B3.
13. Himmelstein et al., "Quality of Care."
14. B.E. Landon et al., "Health Plan Characteristics and Consumers’ Assessments of Quality," Health Affairs (Mar/Apr 2001): 274–286.
15. S. Rosenbaum et al., Negotiating the New Health System, 2d ed. (March 1998), <www.gwu.edu/~chsrp> (2 April 2001).
16. R.H. Palmer et al., "What Makes Quality Assurance Effective? Results from a Randomized, Controlled Trial in Sixteen Primary Care Group Practices," Medical Care 34, no. 9 (1996): SS29–SS39; M.W. Rich et al., "A Multidisciplinary Intervention to Prevent the Readmission of Elderly Patients with Congestive Heart Failure," New England Journal of Medicine 333, no. 18 (1995): 1190–1195; J.A. West et al., "A Comprehensive Management System for Heart Failure Improves Clinical Outcomes and Reduces Medical Resource Utilization," American Journal of Cardiology 79, no. 1 (1997): 58–63; L.M. Baldwin et al., "The Effect of Expanding Medicaid Prenatal Services on Birth Outcomes," American Journal of Public Health 88, no. 11 (1998): 1623–1629; D.A. Buchner et al., "Effects of an Asthma Management Program on the Asthmatic Member: Patient-Centered Results of a Two-Year Study in a Managed Care Organization," American Journal of Managed Care 4, no. 9 (1998): 1288–1297; and T.S. Thompson, "What Have HMOs Learned about Clinical Prevention Services? An Examination of the Experience at Group Health Cooperative of Puget Sound," Milbank Quarterly 74, no. 4 (1996): 469–509.

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