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Quality Of Care

HMO Plan Performance Update: An Analysis Of The Literature, 1997–2001

Abstract

 
This paper synthesizes results from peer-reviewed literature published from 1997 to mid-2001, on various dimensions of health maintenance organization (HMO) plan performance. Results from seventy-nine studies suggest that both types of plans provide roughly comparable quality of care, while HMOs lower use of hospital and other expensive resources somewhat. At the same time, HMO enrollees report worse results on many measures of access to care and lower levels of satisfaction, compared with non-HMO enrollees. Quality-of-care results in particular are heterogeneous, which suggests that quality is not uniform—that it varies widely among providers, plans (HMO and non-HMO), and geographic areas.

We also review evidence on HMOs’ relative performance in the areas of access, satisfaction, prevention, and health care use and spending. We summarize findings on the effects that increasing HMO market share could have on community-wide measures including prevention, access, premiums, and spending. We also speculate on why we observed the pattern of results that we did and on the implications of recent developments for HMO plan performance in the future.

Study Methods

Top Study Methods Study Results Discussion Concluding Comments NOTES

 
Literature analyses of HMO performance can be controversial. Unlike meta-analyses of randomized controlled trials with clear interventions, endpoints, and tightly defined protocols, studies of HMO performance rarely involve randomization of subjects, and the interventions, endpoints, settings, and measures are highly variable. Thus, it is difficult to simply "add" results together. Furthermore, whereas in a meta-analysis of controlled trials of similar patients it can make sense to give much more weight to a study with a larger sample size, it does not necessarily make sense to give proportional weight in a literature analysis to a study that happens to have many results, all of which may be affected by subtle issues of study design, the specific plans under investigation, or the regional or chronological setting of the study. On the other hand, a "one study, one result" rule would ignore the fact that some studies contain far more information than others do. For example, a study that assesses quality differences for six different diseases conveys more information than does one examining just one disease.

Thus, we explore various dimensions or categories of performance (utilization, satisfaction, quality, and so on), and studies can contribute observations to one or more dimension. Sometimes a study will address different diseases or conditions, and these will each be treated as separate observations. Other times, however, multiple measures are lumped within a single observation. For example, nine different measures of access to care in the same study would be assessed together. Thus, there may be multiple results assigned to a given observation, and these results may differ with respect to their level of statistical significance and even the direction of the effect. Our classification approach attempts to capture this variability.

In the quality category, the assessment of findings is even more complicated—and more important—as they have substantial policy implications. The additional complication arises from the fact that it is not always clear what measures should be used. For example, is a lower rate of certain interventions an indicator of poor quality if there is no clear evidence in the literature that outcomes are worse? Is a patient’s assessment of "quality" quality or satisfaction? (We consider it to be the latter.) More generally, the heterogeneity of the health system, of diseases and conditions that can be studied, of quality of data available, of quality of methods used, and of measures for each disease or condition means that there are alternative ways to summarize and score results from published articles.

Consequently, we provide some detail on how we selected articles, produced observations, scored results, and generated subanalyses. Our goal is to make our methods as transparent as possible. We use the following terminology: Study results refer to (sometimes many) specific comparisons reported on in an article (but not yet summarized by us); a finding is our assessment of those study results for a category of performance.

Article selection. We used several methods to identify articles that potentially met our criteria. (1) We conducted Medline searches, using the following keywords: [(managed care) or HMO or (health maintenance organization) or prepaid) and (indemnity) or (preferred provider organization) or PPO or PPOs or fee-for-service or (traditional insurance) or (non-HMO) or (regular Medicare)] or (HMO market share) or (HMO market penetration) or (managed care market penetration). This identified more than 75 percent of the articles. (2) We conducted article-by-article reviews of the journals with the most comparisons in previous literature analyses, including Health Affairs, Health Services Research, Inquiry, Journal of the American Medical Association, and Medical Care. (3) We examined references cited in more recently published articles. (4) We examined references accumulated by the authors for other purposes.

We included articles that met the following criteria: (1) Article was published in a peer-reviewed journal in 1997 to June 2001. (2) Study included HMO enrollees—in most cases without PPO enrollees, but in some cases combined with PPO enrollees (we called the HMO/PPO combination "managed care"); as a result, we did not include one study of PPOs only, or three studies of utilization management for indemnity enrollees who did not have to see physicians that were part of a network or organization that contracted with the health plan. (3) Article focused on plans that provided coverage for most medical services—so we excluded articles on workers’ compensation, managed behavioral health carve-outs, and Medicaid plans that were restricted to primary care case management. We also excluded numerous studies that focused on HMOs’ effects on physicians. (4) Article included a reasonable contemporaneous comparison group, with a reasonable attempt to statistically adjust for differences between the HMO and non-HMO groups; we also included one pre/post study on TennCare, a Medicaid systemwide change, in which researchers attempted to statistically adjust for (the small) differences between managed care populations before and after the change.³

Among articles excluded were those in which the comparison group came mostly or completely from a different geographic area, was selected in a manner somewhat different from the HMO group, or likely had different clinical data quality from the HMO group. In each instance, differences in performance could be attributed to such factors rather than to the HMO. We also excluded articles that did not rely on detailed clinical data when there was potential for sizable differences in unmeasured clinical characteristics. In all, we reviewed dozens of articles that contained some valuable information but did not meet our criteria for inclusion in this comparison.⁴

Categories of study findings. We created several categories of findings: quality, prevention, access, satisfaction, utilization (different types), spending, and premiums. An article could contribute more than one finding if it produced evidence for more than one category of performance (for example, quality, prevention, and utilization); different diseases and conditions; different types of health plans or delivery systems (for example, group-model HMOs and [separately] independent practice association [IPA]–model HMOs); different geographic areas, where HMO performance in each area was analyzed separately (for example, one study produced three findings for quality of care: for northern California, for the Los Angeles region, and for southern California other than LA); and Medicare and (separately) non-Medicare beneficiaries in the same area (this produces two findings).⁵ Conversely, two or more articles from the same underlying study would be combined to contribute one finding for the same category, population, and disease or condition if the articles used different measures for the same concept or used data for adjacent time periods.⁶ We did not create separate findings where one set of results was a subset of another (for example, one article reported results for quality for coronary article bypass graft [CABG] surgery in southern Florida, whereas another reported on all of Florida).⁷

Thus, for each study a finding summarized the specific results for each performance category. Some findings simply reflected the sole result for the performance category. In many cases, however, the finding summarized multiple results (for example, a study of adverse maternal outcomes included maternal death, cardiac arrest, excessive blood loss, anesthesia complications, lacerations and trauma to perineum, and eclampsia).

Scoring. We attempted to score each finding based on the direction and statistical significance of the study results. We created the following spectrum of findings, from those most favorable to those least favorable to HMOs: (1) F s: favorable to HMOs and statistically significant (compared with non-HMO plans); (2) F s, ns: favorable to HMOs with favorable significant and nonsignificant evidence and (if any) nonsignificant unfavorable evidence; (3) F/M s, ns: mixed evidence, with more statistically significant favorable than unfavorable results; (4) F ns: favorable with only nonsignificant evidence; (5) Mixed: evidence for HMO and non-HMO enrollees that had both favorable and unfavorable nonsignificant results and/or that had an equal number of favorable and unfavorable statistically significant results; (6) Same: evidence that was reported as being "similar" (not statistically different) but no data (or direction of differences) were presented in the tables or text, or evidence that had a tie in performance, or had findings with nonsignificantly different results that were no more than 5 percent different from each other (for example, satisfaction rates of 68 percent and 65 percent would be considered equivalent, if that difference was nonsignificant). For findings that were unfavorable to HMOs, we created the mirror-image of the favorable scores: UF ns; UF/M s, ns; UF s, ns; and UF s. Generally, we focus our discussion on findings with the first three and last three scores—that is, those findings with statistically significant evidence that was predominantly favorable or predominantly unfavorable to HMO plans, compared with non-HMO arrangements.

We also created more detailed findings for subcategories of quality performance—one finding each for mortality outcomes, morbidity outcomes, and process measures that are indicative of quality—to see whether or not HMO versus non-HMO comparisons differed by type of quality measure. For example, if a study had one mortality result, multiple morbidity outcome results, and multiple process-of-care quality results, we created three detailed findings, one for each type of quality measure, using the same scoring method described above. We included a finding in mortality outcomes if the study measured either actual mortality or HMO enrollees’ use of hospitals or surgeons with higher- or lower-than-average (or median) mortality. To further examine patterns of findings when data were sufficient, we examined subcategories of diseases or location.

In our prior literature analyses, the Medical Outcomes Study and the Medicare Tax Equity and Fiscal Responsibility Act (TEFRA) evaluation contributed a disproportionately large number of findings, because they were large, comprehensive studies of multiple domains of performance. The largest study this time, the Community Tracking Study (CTS), contributed nine findings, or less than 8 percent of the total, for seven different categories of performance. For CTS comparisons by type of enrollee, we took results from the most recent summary of results, which could use more accurate enrollee insurance status information than did three prior CTS analyses.⁸

Study Results

Top Study Methods Study Results Discussion Concluding Comments NOTES

 
We developed 141 findings from 79 articles. All but six findings were based on at least some data from 1990 forward.

Quality. Quality-of-care findings for HMO plans were roughly comparable to those for non-HMO plans (Exhibit 1). Of forty-seven findings from thirty-seven articles, fourteen were predominantly favorable with respect to HMOs and fifteen were predominantly unfavorable.⁹

The pattern of findings was more favorable to HMOs in California than elsewhere. Of fourteen California findings, seven were predominantly favorable to HMOs, and three were predominantly unfavorable.

Only two studies reported separate results for group- and IPA/network-model HMO performance compared with non-HMO plans. One showed favorable findings for the group-model and no difference for the non-group-model HMOs, relative to PPO/indemnity plans.¹³ The other found that both types of HMOs had nonsignificant findings compared with non-HMO plans.¹⁴ Another study suggested more favorable group-model HMO performance relative to that of IPA/network-model HMOs but did not make a direct comparison.¹⁵ Only six other findings had a clearly identified type of HMO plan (four findings for group models, two for IPA/networks)—too few studies to permit any generalizations about performance differences among HMO models.¹⁶ There was even less information on plan ownership (for-profit versus not-for-profit)—again making generalizations impossible.

The overall pattern of findings changed little when we compared HMO versus non-HMO performance using seventy-three findings categorized by mortality and morbidity outcomes and quality-of-care process measures (Exhibit 3). Overall, sixteen of these were favorable to HMOs, sixteen were unfavorable, and forty-one showed no clear differences. Of the twenty-seven mortality findings, five were clearly favorable to HMOs and seven were clearly unfavorable, while of the sixteen morbidity findings, two were clearly favorable to HMOs and two were clearly unfavorable. The thirty process-measure findings included nine that were predominantly favorable and seven that were predominantly unfavorable to HMOs. Overall, the pattern of findings for quality of care in this literature analysis is similar to that in our previous reviews, which showed roughly comparable quality performance in HMOs and non-HMOs.

Satisfaction. Satisfaction findings were consistently unfavorable to HMOs (Exhibit 5). Of the eleven findings from nine studies, eight were predominantly unfavorable to HMOs and none were predominantly favorable.¹⁸ One "same" finding compared HMO/PPO enrollees with indemnity enrollees.¹⁹ At the same time, satisfaction was fairly high among enrollees in all plan types in most studies.

In our two past analyses of literature on enrollee satisfaction, there was clear evidence of a trade-off for HMO enrollees: greater satisfaction with financial aspects of their plan than in FFS, along with less satisfaction with nonfinancial plan attributes. However, for this analysis only one study provided direct evidence on satisfaction with costs in an HMO plan, making it impossible to determine whether such a trade-off persists.

Most studies of satisfaction did not compare performance among types of HMO plans. However, the one study that did make multiple comparisons showed that in the Boston area IPA/network enrollees were somewhat more satisfied than group-model enrollees were: Among nine specific satisfaction result comparisons, two were predominantly favorable and four were predominantly unfavorable to group-model HMOs.²¹ Group- and IPA/network-model HMO enrollees were much more satisfied than were staff-model HMO enrollees. Also, one study showed that satisfaction with different types of plans (HMO and non-HMO alike) is lower when there is no choice of plans, compared to having a choice.²²

Prevention. Findings on prevention (mostly cancer screening) were consistently favorable to HMOs (Exhibit 6). Of the ten findings from eight studies, HMOs had seven clearly favorable findings and no unfavorable findings.²³ These results for prevention are very similar to those in our 1994 literature analysis.

Use and spending. Ambulatory care use. Although measures or reporting of ambulatory care use varied among the ten findings from nine studies, overall there appeared to be few differences. Three studies found no discernible difference in the number of HMO and non-HMO ambulatory care visits per enrollee.²⁴ Two studies found no significant differences in the percentage of enrollees with at least one visit.²⁵ Three studies examined the percentage of enrollees with at least one physician visit and the number of visits per user but did not test for differences in numbers of visits per enrollee: Of those, two found higher likelihood of some use for HMO enrollees but no difference in number of visits for users; another found no difference for either type of measure.²⁶ For specialist use, one study found significantly lower likelihood of a specialist visit among HMO enrollees, whereas another found no difference.²⁷ One finding on overall ambulatory care resource use showed lower utilization for HMO compared with non-HMO enrollees.²⁸

Hospital admissions. There was little evidence of differences in hospital admission rates for HMOs compared with non-HMOs, based on eight findings from eight studies.²⁹

Hospital length-of-stay. Of ten findings from ten studies, five showed statistically significantly shorter HMO hospital lengths-of-stay, ranging from 4.4 percent to 13.9 percent lower.³⁰ None of the other five findings showed discernible differences in length-of-stay (Exhibit 7).³¹

Several explanations are possible for the major difference in findings for the first two studies, which have large national samples. One is that HMOs might affect use of hospitals more for the elderly Medicare population (which has relatively high use, on average) than for a younger commercial population (which has relatively low use, on average). Another is the well-documented favorable selection experienced by Medicare risk-contract HMOs.

Hospital charges per admission. The one study that reported on hospital charges per admission showed that HMO enrollees incurred significantly lower charges than did non-HMO enrollees.³⁵ The one study on hospital-related expenditures per enrollee showed no significant differences.³⁶

Use of other expensive resources. Of fifteen findings from thirteen studies, eight showed predominantly lower use of more costly resources in HMOs than in non-HMOs, while none showed significantly higher use (Exhibit 8).³⁷ Other expensive resources included use of posthospital facilities (such as a rehabilitation hospital rather than a nursing home), neurology consultations and wards, emergency departments, cataract extractions, ambulances, and services in an intensive care unit (ICU). Excluding findings on use of emergency department and emergency rooms, seven of eight findings showed predominantly lower use of expensive services in HMOs compared with non-HMOs.

Summary of use and cost findings. Overall, HMOs appeared to use fewer resources. Although there was no clear pattern in the findings for hospital admissions, lengths-of-stay tended to be somewhat shorter for HMO enrollees: The combination of the two patterns of findings suggests less hospital use per enrollee. The only study explicitly measuring hospital days per enrollee confirmed that implied finding.⁴⁰ There were no clear differences in physician visits, but there was clearly less use of expensive resources in HMOs than in non-HMOs.

The pattern of findings for physician visits (no clear differences among plans) and use of expensive resources (less use for HMO versus non-HMO plans) are similar to those in our 1994 and 1997 literature analyses. The pattern of findings for hospital use (shorter lengths-of-stay but no clear pattern for hospital admissions or use per enrollee) falls in between those for our two prior analyses. In the 1994 analysis there were clear indications of less hospital use—somewhat lower hospital admissions (albeit not large differences) and both shorter lengths-of-stay and fewer hospital days per enrollee—for HMOs. In the 1997 analysis there was no clear pattern for hospital use.

Given that managed care grew rapidly to contain the rate of increase of health care spending, the lack of clear evidence about hospital utilization warrants comment. There are several potential explanations: Among them, HMOs may create incentives for FFS plans to contain hospital use, including shorter lengths-of-stay, to be competitive. On the Medicare side, the diagnosis-related group (DRG) system of payment creates incentives for shorter lengths-of-stay. It can be argued that while comprehensive disease management could reduce hospital admissions, it requires consistent, proactive care; the inconsistent use of disease management programs in HMOs may account for the lack of clearly lower admissions in HMOs compared with non-HMOs.

Studies with both quality and utilization outcomes. Fewer than a third of the studies with quality findings (eleven of thirty-six) also had findings with some measure of utilization. According to the stereotypical positions in the managed care debate, the anti-HMO side would argue that HMOs lower utilization at the expense of quality, and the pro-HMO side would argue that HMOs lower utilization with no change, or an improvement, in quality. Of the eleven studies, four support the first position and two support the latter.⁴¹ Five findings support neither "pure" stereotype, as they show no discernible difference in utilization between HMOs and non-HMOs; of those, two showed relatively higher HMO quality, one showed relatively lower HMO quality, and two showed similar quality of care.⁴² That is, five findings showed lower HMO quality with the same or lower utilization, while four findings showed higher HMO quality with the same or lower utilization.

Communitywide effects associated with market penetration. Fourteen findings provide evidence on the association of various outcomes at the community level with higher HMO or HMO/PPO market penetration. Although causality can be difficult to assess, these associations (or effects) may be due either to the direct effect of HMOs or HMOs/PPOs on their enrollees or to the indirect "spillover" effects of HMOs on non-HMOs or on uncompensated care. The reverse causality could be involved if HMOs are attracted to areas in which these communitywide differences are under way or already in place. Some of the studies attempt to address this issue of causality using various econometric techniques.⁴³

Generally, the findings are in the expected directions: Higher HMO or HMO/PPO penetration rates are associated with less access; more prevention; less use of expensive resources; and lower employer health plan premiums, Medicare FFS expenditures, and hospital cost growth.

Access. Three findings on access indicated predominantly unfavorable managed care effects. Charity care hours provided per week by physicians was negatively associated with a higher percentage of managed care (HMO/PPO) revenues in the physician practice.⁴⁴ Uncompensated care provided by not-for-profit hospitals was negatively associated with greater Medicaid managed care presence in a state; this is an unfavorable finding if one assumes that charity care as a percentage of uncompensated care would remain the same or decline, although it may also indicate that there is less need because the state provides more Medicaid coverage.⁴⁵ The percentage of uninsured low-income persons having a usual source of care or ambulatory care visits was negatively associated with a higher percentage of Medicaid managed care in the state; the percentage of uninsured low-income persons with ambulatory care visits was negatively associated with high overall managed care (HMO/PPO) penetration.⁴⁶ Other findings on the association between access, outcomes, and HMO or HMO/PPO market penetration were mixed (for insured low-income persons), statistically insignificant, or apparently unfavorable to HMOs but not tested.⁴⁷

Prevention. One finding showed that the percentage of FFS-covered women adhering to breast cancer screening guidelines for mammograms was positively associated with a higher level of HMO market penetration.⁴⁸

Use of more costly resources. One finding showed lower per capita use of magnetic resonance imaging (MRI) in communities with higher HMO penetration.⁴⁹

Premiums. One finding showed that lower health plan costs for employers were associated with high levels of HMO market penetration, as a result of both lower HMO than non-HMO premiums and lower non-HMO premiums.⁵⁰ A different type of finding showed no evidence of cost shifting by HMOs from Medicare to commercial premiums.⁵¹

Spending. Two related findings for the 1986–1990 and 1990–1994 periods showed slightly lower (but still statistically significant) Medicare Parts A and B FFS expenditures associated with higher HMO market penetration.⁵² Two other findings on managed care market penetration and hospital cost growth showed somewhat similar associations. High HMO and PPO penetration was associated with reductions in hospital cost growth in highly competitive hospital markets, with the HMO effect being approximately double that of PPOs.⁵³ Another showed that hospital cost inflation (spending growth) between 1985 and 1993 in six of eight years was negatively associated with high levels of HMO market penetration—in all, lowering absolute hospital spending levels by 7.8 percent by 1993.⁵⁴

Discussion

Top Study Methods Study Results Discussion Concluding Comments NOTES

 
This literature analysis produced results similar to those in our two previous analyses. Compared with non-HMOs, HMOs had roughly comparable quality of care, more prevention activities, less use of hospital days and other expensive resources, and lower access and satisfaction ratings.

What is noteworthy is the greater depth of studies on quality of care meeting our criteria—thirty-six over the four-and-a-half-year period, compared with fifteen in the prior three-year period—which permitted a better assessment of quality of care in the different types of plans. This increase reflects the greater importance of HMOs in the health care system (which meant more HMO-related data), more interest among researchers in conducting the comparisons, and greater interest in quality on the part of funding agencies.

At the same time, the eight studies or so per year on quality of care is a very small number in the context of an exceptionally heterogeneous health care system with hundreds of large HMO plans and delivery systems having different payment methods to physician organizations and individual physicians; different utilization management, prevention, and disease management programs; and dozens of conditions and diseases for which interesting and useful analyses could be conducted. Given that heterogeneity, an increase in the number of studies by a magnitude of ten or even one hundred would be needed to understand the extent of, and reasons for, true differences in plan performance in HMOs and non-HMOs. Many times more findings still would be needed to help consumers to determine the quality of care in their geographic area.

One study on quality of cancer care exemplifies the heterogeneity in health plan and delivery system performance.⁵⁵ We counted one overall result (HMO mixed/favorable) for data pooled across eight HMO versus non-HMO comparisons. Yet that study produced evidence for each HMO versus non-HMO comparison, for two measures of quality of breast cancer treatment. If each of the eight HMO comparisons had been a separate finding, they would show highly varied findings: three predominantly favorable and two predominantly unfavorable findings, and three more with nonsignificant results. What we need to know is not simply the "counts of findings" but why there is such variability across HMOs.

Study limitations. In addition to the relatively small number of studies, numerous issues force one to be cautious about any generalizations about plan performance. The following are but a few examples.

Selection bias within the studies. In a majority of findings with direct HMO versus non-HMO comparisons, HMO enrollees either were younger or had a pattern of somewhat fewer comorbidities. In general, the studies we included attempted to control for such differences, but such controls may be inadequate, biasing findings in favor of HMO plans.

Selection of research topic bias. This is a far greater concern than is the issue of publication bias. Research topics are not proposed (or funded) at random. What gets examined depends on data availability and on researchers’ and funding agencies’ interest in the topic. Researchers might choose topics to highlight (or test) the apparent strengths or weaknesses of HMOs—which is certainly possible in an environment with heated feelings for and against HMOs.

Misclassification of plan types. Recent research indicates that a large percentage of enrollees do not know which type of plan they are in. In one study more than four-fifths of persons in FFS plans incorrectly identified themselves as being in managed care.⁵⁶ Methods for reliably determining health plan status varied greatly among studies, and some studies did not ask additional questions or use statistical matching techniques to improve the reliability of the data. Moreover, many studies relied on hospital administrative databases, in which the reliability of health plan information is unclear.

Creation and scoring of findings. For a literature synthesis such as this, any method to create and score findings will have shortcomings, the result of trade-offs necessary to generate "bottom-line" results. For example, we did not (and could not) assign weights to reflect the relative importance of one indicator over another in the many cases where several study results had to be combined to produce a "finding."

Responding to an earlier critique. After our last literature review, Kip Sullivan argued that our past findings were biased in favor of HMOs because we did not adjust for the fact that HMOs tend to provide more comprehensive coverage than non-HMO plans do.⁵⁷ Adjust for those differences, the argument goes, and HMO findings would be much less favorable. This argument is flawed because it ignores the fact that plans are selected on the basis of a "bundle" of characteristics or attributes, not just one. In general, HMOs tend to have more-comprehensive coverage (that is, fewer price constraints on demand), combined with more nonprice constraints—narrower networks and other nonprice attempts (gatekeepers and prior authorizations) to limit specialist visits and expensive services. Non-HMO plans tend to have less comprehensive coverage (that is, more price constraints on demand) but fewer nonprice constraints. Sullivan’s proposal holds constant only one part of the "bundle" coverage, ignoring the other. FFS plans with comprehensive coverage and few nonprice constraints on demand have high utilization, high premiums, and few insured persons. Although the Canadian-style single-payer FFS system has few price restrictions, it too must constrain demand—through overall budgets, long-range resource planning, and queuing.

Also flawed is an additional argument that the apparent comparability of quality is because Medicare, as a result of inadequate risk-adjustment methods, overpays HMOs, which can therefore offer better coverage (such as outpatient prescription drugs), leading to better outcomes than would have been the case without the overpayment. Implicitly, HMO quality is as good as it appears only because HMOs use more resources than FFS plans use.

There is evidence that Medicare overpaid Medicare HMOs by approximately 6–7 percent, according to two estimates.⁵⁸ However, the implication with respect to quality is flawed, since it ignores the fact that many FFS Medicare beneficiaries, employers, or Medicaid pay extra for supplemental insurance coverage and that beneficiaries also incur copayments, deductibles, and other out-of-pocket expenses. These payments add substantially more resources for FFS than for HMO enrollees. As a result, while FFS Medicare beneficiaries may use fewer Medicare-financed dollars (risk-adjusted) than their HMO counterparts use, they almost certainly use more real resources in toto.

In fact, if quality is comparable for HMO and non-HMO plans, then many HMO enrollees who have a choice among plans seem willing to accept lower satisfaction for lower out-of-pocket payments. Based on the findings from the articles reviewed here and in the past, the trade-off overall does not appear to be one of lower quality of care for lower out-of-pocket payments. We note, however, that not all enrollees have a choice of plans, and this may be a source of some of the backlash against managed care.

Concluding Comments

Top Study Methods Study Results Discussion Concluding Comments NOTES

 
Our findings suggest that HMOs and non-HMOs provide roughly comparable quality of care, while HMOs lower the use of hospital and other expensive resources. At the same time, HMOs reduce many measures of access to care and are associated with lower levels of enrollee satisfaction, compared with non-HMOs. Quality-of-care research results, however, are particularly heterogeneous, which suggests that quality varies greatly among providers, plans (HMO and non-HMO), and geographic areas.

Managed care (both HMOs and PPOs) expanded rapidly in the early 1980s in response to rapid health care inflation; this expansion was accompanied by public-sector cost containment measures, including the implementation of DRGs and the resource-based relative value scale (RBRVS) for physician payment in Medicare. These were efforts to contain the ever-growing health care share of gross domestic product. Not stated was the implicit trade-off—that something in terms of quality of care, satisfaction, or access to care might have to be given up in exchange for cost containment. Recent evidence indicates that, overall, the tradeoff has not been as severe as some had feared—HMOs have led to lower costs, and while access and satisfaction seem to have suffered, quality of care has been comparable for all types of enrollees combined. At the same time, most (but not all) HMOs have not accomplished what their proponents had promised: changing clinical practice processes and improving quality of care relative to the existing system, while containing costs for both purchasers and consumers.

In part, whether or not HMOs could achieve this promise could not really be tested, because the developments that some HMO proponents had hoped for generally have not yet been put in place. These include the following: (1) Purchasers and plans would have to hold plans and provider organizations accountable for defined populations and set quality standards, require performance measurement, reward high performance organizations, and risk-adjust payment rates to compensate for the resulting migration of sicker patients to organizations with higher performance; (2) consumers would have to be educated about performance scores so that they could respond to reported quality measures; and (3) provider organizations would have to implement new information technology (IT)—in particular, electronic medical records—that would enable them to measure and report performance to consumers and purchasers, generate data needed to risk-adjust payment rates, and reengineer clinical processes to improve quality. While these developments could improve all care, including in the non-HMO sector, it is easier to create accountability with the defined populations of the HMO sector.

Although such developments have not been widespread, some important changes are taking place. First, there is some movement in the direction of having purchasers and plans reward quality performance—for example, the Leapfrog Group’s efforts to set standards, and California HMOs’ "pay-for-performance" proposal. Second, consumers are increasing their health care knowledge, thanks in part to the Internet. This understanding and the potential for more gains in the future in turn make it more possible for consumers to demand more information and to comprehend and act upon comparable quality information from health plans and providers—when it is made available. Third, developments over the past decade in the IT industry in general, and health IT industry specifically, mean that implementation of advanced clinical information systems, especially electronic medical record systems, is much more possible now than ever before.

The consistently mixed quality-of-care results for HMO versus non-HMO plans over the past two decades suggests that for HMOs to meet the vision of their advocates and as a whole outperform PPO and indemnity plan quality of care, nothing less than a systematic revamping of health care information systems, incentives, and clinical processes may be required. It remains to be seen whether such a revamping will occur. If it does not, HMOs will likely be but a footnote in the history of U.S. health care. If it does occur, then we still will have to see if HMOs not only improve care for their own enrollees but also raise the standards for all. Unfortunately, the jury is still out on whether this vision can be achieved.

Editor's Notes

 
Robert Miller is associate professor of health economics in residence at the Institute for Health and Aging, Institute for Health Policy Studies, and Department of Social and Behavioral Sciences at the University of California, San Francisco (UCSF). Hal Luft is the Caldwell B. Esselstyn Professor of Health Policy and Health Economics and directs the Institute for Health Policy Studies at UCSF.

This research was funded by the Robert Wood Johnson Foundation. An earlier version was presented at the Council on the Economic Impact of Health System Change, Eighth Princeton Conference: The Future of Managed Care, held in Princeton, New Jersey, in May 2001. The authors received helpful comments on the earlier version from conference participants and from fellows and faculty at the Institute for Health Policy Studies and Institute for Health and Aging Writing Seminar.

NOTES

Top Study Methods Study Results Discussion Concluding Comments NOTES

 

1. 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[Abstract]; and R.H. Miller and H.S. Luft, "Does Managed Care Lead to Better or Worse Quality of Care?" Health Affairs (Sep/Oct 1997): 7–25.
2. D.B. Bernard and D.J. Shulkin, "The Media vs. Managed Health Care: Are We Seeing a Full Court Press?" Archives of Internal Medicine 158, no. 19 (1998): 2109–2111.[Abstract/Free Full Text]
3. W.A. Ray et al., "Perinatal Outcomes following Implementation of TennCare," Journal of the American Medical Association 279, no. 4 (1998): 314–316.[Abstract/Free Full Text]
4. A listing of studies we considered but did not include is available from Robert Miller, millerr{at}itsa.ucsf.edu.
5. Regarding different types of plans or delivery systems, see, for example, A. Lee-Feldstein et al., "The Relationship of HMOs, Health Insurance, and Delivery Systems to Breast Cancer Outcomes," Medical Care 38, no. 7 (2000): 705–718. [Medline]Regarding different geographic areas, see, for example, M. Chernew, D. Scanlon, and R. Hayward, "Insurance Type and Choice of Hospital for Coronary Artery Bypass Graft Surgery," Health Services Research 33, no. 3, part 1 (1998): 447–466. [Medline]The exception was G. Riley et al., "Stage at Diagnosis and Treatment Patterns among Older Women with Breast Cancer: An HMO and Fee for-Service Comparison," Journal of the American Medical Association 281, no. 8 (1999): 720–726, whose eight separate findings of breast cancer results in different regions would have accounted for about 17 percent of the quality findings. [Abstract/Free Full Text]Regarding Medicare and non-Medicare beneficiaries, see, for example, R.G. Roetzheim et al., "Effects of Health Insurance and Race on Breast Carcinoma Treatments and Outcomes," Cancer 89, no. 11 (2000): 2202–2213.[Medline]
6. Regarding use of different measures, one article, D.M. Oleske et al., "A Comparison of Capitated and Fee-for-Service Medicaid Reimbursement Methods on Pregnancy Outcomes," Health Services Research 33, no. 1 (1998): 55–73, reported on the odds of Medicaid mothers’ having a low-birthweight baby in California[Medline]; another article, D.M. Oleske et al., "Effect of Medicaid Managed Care on Pregnancy Complications," Obstetrics and Gynecology 95, no. 1 (2000): 6–13, reported on the odds of pregnancy complications, for the same population and time period. [Abstract/Free Full Text]Regarding use of data for adjacent time periods, see L.C. Baker, "The Effect of HMOs on Fee-for-Service Health Care Expenditures: Evidence from Medicare," Journal of Health Economics 16, no. 4 (1997): 453–481[Medline]; and L.C. Baker, "Association of Managed Care Market Share and Health Expenditures for Fee-for-Service Medicare Patients," Journal of the American Medical Association 281, no. 5 (1999): 432–437.[Abstract/Free Full Text]
7. J.J. Escarce, J.A. Shea, and W. Chen, "Segmentation of Hospital Markets: Where Do HMO Enrollees Get Care?" Health Affairs (Nov/Dec 1997): 181–192; and J. Escarce et al., "Health Maintenance Organizations and Hospital Quality for Coronary Artery Bypass Surgery," Medical Care Research and Review 56, no. 3 (1999): 340–362; discussion, 363–372.[Abstract/Free Full Text]
8. J.D. Reschovsky, P. Kemper, and H. Tu, "Does Type of Health Insurance Affect Health Care Use and Assessments of Care among the Privately Insured?" Health Services Research 35, no. 1, part 2 (2000): 219–237[Medline]; T. Lake, "Do HMOs Make a Difference? Consumer Assessments of Health Care," Inquiry 36, no. 4 (1999): 411–418[Medline]; J.D. Reschovsky, "Do HMOs Make a Difference? Access to Health Care," Inquiry 36, no. 4 (1999): 390–399[Medline]; and H.T. Tu, P. Kemper, and H.J. Wong, "Do HMOs Make a Difference? Use of Health Services," Inquiry 36, no. 4 (1999): 400–410.[Medline]
9. Chernew et al., "Insurance Type and Choice of Hospital";; L.C. Erickson et al., "The Relationship between Managed Care Insurance and Use of Lower-Mortality Hospitals for CABG Surgery," Journal of the American Medical Association 283, no. 15 (19 April 2000): 1976–1982[Abstract/Free Full Text]; L.C. Erickson et al., "The Impact of Managed Care Insurance on Use of Lower-Mortality Hospitals by Children Undergoing Cardiac Surgery in California," Pediatrics 105, no. 6 (June 2000): 1271–1278[Abstract/Free Full Text]; Escarce et al., "Health Maintenance Organizations and Hospital Quality";; N.R. Every et al., "Influence of Insurance Type on the Use of Procedures, Medications, and Hospital Outcome in Patients with Unstable Angina: Results from the GUARANTEE Registry (Global Unstable Angina Registry and Treatment Evaluation)," Journal of the American College of Cardiology 32, no. 2 (1998): 387–392[Abstract/Free Full Text]; B. Experton et al., "How Does Managed Care Manage the Frail Elderly? The Case of Hospital Readmissions in Fee-for-Service versus HMO Systems," American Journal of Preventive Medicine 16, no. 3 (1999): 163–172[Medline]; E. Guadagnoli et al., "Appropriateness of Coronary Angiography after Myocardial Infarction among Medicare Beneficiaries: Managed Care versus Fee for Service," New England Journal of Medicine 343, no. 20 (2000): 1460–1466[Abstract/Free Full Text]; J. Hadley and J.M. Mitchell, "Breast Cancer Treatment Choice and Mastectomy Length of Stay: A Comparison of HMO and Other Privately Insured Women," Inquiry 34, no. 4 (1997a): 288–301[Medline]; J. Holtzman, Q. Chen, and R. Kane, "The Effect of HMO Status on the Outcomes of Home-Care after Hospitalization in a Medicare Population," Journal of the American Geriatrics Society 46, no. 5 (1998): 629–634[Medline]; K.J. Kelleher et al., "Insurance Status and Recognition of Psychosocial Problems: A Report from the Pediatric Research in Office Settings and the Ambulatory Sentinel Practice Networks," Archives of Pediatrics and Adolescent Medicine 151, no. 11 (1997): 1109–1115[Abstract]; S. Kreindel et al., "Health Insurance Coverage and Outcome following Acute Myocardial Infarction. A Community-Wide Perspective," Archives of Internal Medicine 157, no. 7 (1997): 758–762[Abstract]; Lee-Feldstein et al., "The Relationship of HMOs, Health Insurance, and Delivery Systems";; A. Levinson and F. Ullman, "Medicaid Managed Care and Infant Health," Journal of Health Economics 17, no. 3 (1998): 351–368[Medline]; D. McCormick et al., "Differences in Discharge Medication after Acute Myocardial Infarction in Patients with HMO and Fee-for- Service Medical Insurance," Journal of General Internal Medicine 14, no. 2 (1999): 73–81[Medline]; R.M. Merrill et al., "Survival and Treatment for Colorectal Cancer Medicare Patients in Two Group/Staff Health Maintenance Organizations and the Fee-for-Service Setting," Medical Care Research and Review 56, no. 2 (1999): 177–196[Abstract]; D.B. Mukamel, A.S. Murthy, and D.L. Weimer, "Racial Differences in Access to High-Quality Cardiac Surgeons," American Journal of Public Health 90, no. 11 (2000): 1774–1777[Abstract/Free Full Text]; H. Ni, D.J. Nauman, and R.E. Hershberger, "Managed Care and Outcomes of Hospitalization among Elderly Patients with Congestive Heart Failure," Archives of Internal Medicine 158, no. 11 (1998): 1231–1236[Abstract/Free Full Text]; T.E. Obst, E. Nauenberg, and G.M. Buck, "Maternal Health Insurance Coverage as a Determinant of Obstetrical Anesthesia Care," Journal of Health Care for the Poor and Underserved 12, no. 2 (2001): 177–191[Medline]; Oleske et al., "A Comparison of Capitated and Fee-for-Service Medicaid Reimbursement Methods on Pregnancy Outcomes";; Oleske et al., "Effect of Medicaid Managed Care on Pregnancy Complications";; E.F. Philbin and T.G. DiSalvo, "Managed Care for Congestive Heart Failure: Influence of Payer Status on Process of Care, Resource Utilization, and Short- Term Outcomes," American Heart Journal 136, no. 3 (1998): 553–561[Medline]; H.A. Picken et al., "Insurance Type and the Transportation to Emergency Departments of Patients with Acute Cardiac Ischemia: The ACI-TIPI Trial Insurance Study," American Journal of Managed Care 4, no. 6 (1998): 821–827[Medline]; A.L. Potosky et al., "Breast Cancer Survival and Treatment in Health Maintenance Organization and Fee-for-Service Settings," Journal of the National Cancer Institute 89, no. 22 (1997): 1683–1691[Abstract/Free Full Text]; A.L. Potosky et al., "Prostate Cancer Treatment and Ten-Year Survival among Group/Staff HMO and Fee-for-Service Medicare Patients," Health Services Research 34, no. 2 (1999): 525–546[Medline]; Ray et al., "Perinatal Outcomes following Implementation of TennCare";; S.M. Retchin et al., "Perioperative Management of Colon Cancer under Medicare Risk Programs," Archives of Internal Medicine 157, no. 16 (1997): 1878–1884[Abstract]; S.M. Retchin et al., "Outcomes of Stroke Patients in Medicare Fee for Service and Managed Care," Journal of the American Medical Association 278, no. 2 (1997): 119–125[Abstract]; Riley et al., "Stage at Diagnosis and Treatment Patterns";; R.G. Roetzheim et al., "Effects of Health Insurance and Race on Early Detection of Cancer," Journal of the National Cancer Institute 91, no. 16 (1999): 1409–1415[Abstract/Free Full Text]; R.G. Roetzheim et al., "Effects of Health Insurance and Race on Colorectal Cancer Treatments and Outcomes," American Journal of Public Health 90, no. 11 (2000): 1746–1754[Abstract/Free Full Text]; Roetzheim et al., "Effects of Health Insurance and Race on Breast Carcinoma Treatments and Outcomes";; M. Sada et al., "Influence of Payor on Use of Invasive Cardiac Procedures and Patient Outcome after Myocardial Infarction in the United States: Participants in the National Registry of Myocardial Infarction," Journal of the American College of Cardiology 31, no. 7 (1998): 1474–1480[Abstract/Free Full Text]; R.M. Schwartz et al., "Permanent Presence of Managed Care and Outcome of Critically Ill Infants," Pediatric Clinics of North America 45, no. 3 (1998): 635–650[Medline]; M.F. Shapiro et al., "Variations in the Care of HIV-Infected Adults in the United States: Results from the HIV Cost and Services Utilization Study," Journal of the American Medical Association 281, no. 24 (1999): 2305[Abstract/Free Full Text]; M.A. Smith et al., "HMO Membership and Patient Age and the Use of Specialty Care for Hospitalized Patients with Acute Stroke: The Minnesota Stroke Survey," Medical Care 37, no. 12 (1999): 1186–1198[Medline]; S.B. Soumerai et al., "Timeliness and Quality of Care for Elderly Patients with Acute Myocardial Infarction under Health Maintenance Organization vs. Fee-for-Service Insurance," Archives of Internal Medicine 159, no. 17 (1999): 2013–2020[Abstract/Free Full Text]; and J. Spetz, M.W. Smith, and S.F. Ennis, "Physician Incentives and the Timing of Cesarean Sections: Evidence from California," Medical Care 39, no. 6 (2001): 536–550.[Medline]
10. Miller and Luft, "Does Managed Care Lead to Better or Worse Quality?"
11. The stroke studies were Retchin et al., "Outcomes of Stroke Patients"; and Smith et al., "HMO Membership and Patient Age." The frail elder studies were Experton et al., "How Does Managed Care Manage the Frail Elderly?"; and Holtzman et al., "The Effect of HMO Status." The unfavorable studies were Experton et al., "How Does Managed Care Manage the Frail Elderly?"; and Smith et al., "HMO Membership and Patient Age."
12. Medicare findings unfavorable to HMOs were from Erickson et al., "The Impact of Managed Care Insurance on Use of Lower-Mortality Hospitals";; Escarce et al., "Health Maintenance Organizations and Hospital Quality";; Experton et al., "How Does Managed Care Manage the Frail Elderly?" Guadagnoli et al., "Appropriateness of Coronary Angiography after Myocardial Infarction";; Ni et al., "Managed Care and Outcomes of Hospitalization";; Potosky et al., "Prostate Cancer Treatment and Ten-Year Survival";; Roetzheim et al., "Effects of Health Insurance and Race on Early Detection of Cancer"; and Roetzheim et al., "Effects of Health Insurance and Race on Colorectal Cancer Treatments and Outcomes." Medicare findings favorable to HMOs were from Potosky et al., "Breast Cancer Survival and Treatment";; Riley et al., "Stage at Diagnosis and Treatment Patterns"; and Soumerai et al., "Timeliness and Quality of Care." Medicare findings with no difference were from Holtzman et al., "The Effect of HMO Status";; Merrill et al., "Survival and Treatment for Colorectal Cancer Medicare Patients";; Retchin et al., "Outcomes of Stroke Patients";; Roetzheim et al., "Effects of Health Insurance and Race on Breast Carcinoma Treatments and Outcomes"; and Roetzheim et al., "Effects of Health Insurance and Race on Early Detection of Cancer."
13. Spetz et al., "Physician Incentives."
14. Lee-Feldstein et al., "The Relationship of HMOs, Health Insurance, and Delivery Systems."
15. Chernew et al., "Insurance Type and Choice of Hospital."
16. The four findings for group models were from Merrill et al., "Survival and Treatment for Colorectal Cancer Medicare Patients";; Potosky et al., "Breast Cancer Survival and Treatment"; and Potosky et al., "Prostate Cancer Treatment and Ten-Year Survival." The two findings for IPA/network models were from Experton et al., "How Does Managed Care Manage the Frail Elderly?"; and Picken et al., "Insurance Type and the Transportation to Emergency Departments."
17. Chernew et al., "Insurance Type and Choice of Hospital";; D. DeLia, J.C. Cantor, and D. Sandman, "Medicaid Managed Care in New York City: Recent Performance and Coming Challenges," American Journal of Public Health 91, no. 3 (2001): 458–460[Abstract/Free Full Text]; W.A. Leigh et al., "Managed Care in Three States: Experiences of Low-Income African Americans and Hispanics," Inquiry 36, no. 3 (1999): 318–331[Medline]; S.K. Long and T.A. Coughlin, "Impacts of Medicaid Managed Care on Children," Health Services Research 36, no. 1, Pt. 1 (2001): 7–23[Medline]; P.W. Newacheck et al., "The Impact of Managed Care on Children’s Access, Satisfaction, Use, and Quality of Care," Health Services Research 36, no. 2 (2001): 315–334[Medline]; D.L. Pina, "Medicaid Beneficiaries’ Experiences in HMO and Fee-for-Service Health Care," Journal of Health Care for the Poor and Underserved 9, no. 4 (1998): 433–448[Medline]; Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?";; H.H. Schauffler and S.A. Chapman, "Health Promotion and Managed Care: Surveys of California’s Health Plans and Population," American Journal of Preventive Medicine 14, no. 3 (1998): 161–167[Medline]; and L. Shi, "Type of Health Insurance and the Quality of Primary Care Experience," American Journal of Public Health 90, no. 12 (2000): 1848–1855.[Abstract/Free Full Text]
18. S.A. Flocke, K.C. Stange, and S.J. Zyzanski, "The Impact of Insurance Type and Forced Discontinuity on the Delivery of Primary Care," Journal of Family Practice 45, no. 2 (1997): 129–135[Medline]; A.A. Gawande et al., "Does Dissatisfaction with Health Plans Stem from Having No Choices?" Health Affairs (Sep/Oct 1998): 184–194; Long and Coughlin, "Impacts of Medicaid Managed Care on Children";; Newacheck et al., "The Impact of Managed Care";; Pina, "Medicaid Beneficiaries’ Experiences";; Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?";; D.G. Safran et al., "Organizational and Financial Characteristics of Health Plans: Are They Related to Primary Care Performance?" Archives of Internal Medicine 160, no. 1 (2000): 69–76[Abstract/Free Full Text]; Shi, "Type of Health Insurance and the Quality of Primary Care Experience"; and C.G. Tudor, G. Riley, and M. Ingber, "Satisfaction with Care: Do Medicare HMOs Make a Difference?" Health Affairs (Mar/Apr 1998): 165–176.
19. Flocke et al., "The Impact of Insurance Type and Forced Discontinuity."
20. Tudor et al., "Satisfaction with Care";; Safranet al., "Organizational and Financial Characteristics"; and Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"
21. Safran et al., "Organizational and Financial Characteristics."
22. Gawande et al., "Does Dissatisfaction with Health Plans Stem from Having No Choices?"
23. E. Alessandrini et al., "Effects of Medicaid Managed Care on Quality: Childhood Immunizations," Pediatrics 107, no. 6 (2001): 1335–1342[Abstract/Free Full Text]; O. Carrasquillo, R.A. Lantigua, and S. Shea, "Preventive Services among Medicare Beneficiaries with Supplemental Coverage versus HMO Enrollees, Medicaid Recipients, and Elders with No Additional Coverage," Medical Care 39, no. 6 (2001): 616–626[Medline]; N.P. Gordon, T.G. Rundall, and L. Parker, "Type of Health Care Coverage and the Likelihood of Being Screened for Cancer," Medical Care 36, no. 5 (1998): 636–645[Medline]; Newacheck et al., "The Impact of Managed Care";; K.A. Phillips et al., "Factors Associated with Women’s Adherence to Mammography Screening Guidelines," Health Services Research 33, no. 1 (1998): 29–53[Medline]; A.L. Potosky et al., "The Association between Health Care Coverage and the Use of Cancer Screening Tests: Results from the 1992 National Health Interview Survey," Medical Care 36, no. 3 (1998): 257–270[Medline]; Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"; and R.M. Weinick and K.M. Beauregard, "Women’s Use of Preventive Screening Services: A Comparison of HMO versus Fee-for-Service Enrollees," Medical Care Research and Review 54, no. 2 (1997): 176–199.[Abstract/Free Full Text]
24. S. Christensen and J. Shinogle, "Effects of Supplemental Coverage on Use of Services by Medicare Enrollees," Health Care Financing Review 19, no. 2 supp. (1997): 5–17, following 218[Medline]; E.C. Nelson et al., "A Longitudinal Study of Hospitalization Rates for Patients with Chronic Disease: Results from the Medical Outcomes Study," Health Services Research 32, no. 6 (1998): 759–774[Medline]; and Shapiro et al., "Variations in the Care of HIV-Infected Adults."
25. DeLia et al., "Medicaid Managed Care in New York City"; and Long and Coughlin, "Impacts of Medicaid Managed Care on Children."
26. T. Fama and A. Bernstein, "A Comparison of Physician and Hospital Use among the Nonelderly Covered by HMOs and Indemnity Insurance," Medical Care Research and Review 54, no. 2 (1997): 239–254[Abstract/Free Full Text]; Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"; and Newacheck et al., "The Impact of Managed Care."
27. Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"; and Long and Coughlin, "Impacts of Medicaid Managed Care on Children."
28. A.B. Flood et al., "How Do HMOs Achieve Savings? The Effectiveness of One Organization’s Strategies," Health Services Research 33, no. 1 (1998): 79–99.[Medline]
29. DeLia et al., "Medicaid Managed Care in New York City";; B. Experton et al., "The Impact of Payor/Provider Type on Health Care Use and Expenditures among the Frail Elderly," American Journal of Public Health 87, no. 2 (1997): 210–216[Abstract/Free Full Text]; Fama and Bernstein, "A Comparison of Physician and Hospital Use among the Nonelderly";; Long and Coughlin, "Impacts of Medicaid Managed Care on Children;"; Nelson et al., "A Longitudinal Study of Hospitalization Rates";; Newacheck et al., "The Impact of Managed Care";; Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"; and Shapiro et al., "Variations in the Care of HIV-Infected Adults."
30. Hadley and Mitchell, "Breast Cancer Treatment Choice";; Holtzman et al., "The Effect of HMO Status";; Ni et al., "Managed Care and Outcomes of Hospitalization";; Philbin and DiSalvo, "Managed Care for Congestive Heart Failure";; K.G. Volpp and M.K. Bundorf, "Consumer Protection and the HMO Backlash: Are HMOs to Blame for Drive-Through Deliveries?" Inquiry 36, no. 1 (1999): 101–109.[Medline]
31. Every et al., "Influence of Insurance Type";; Experton et al., "The Impact of Payor/Provider Type";; S. Kreindel et al., "Health Insurance Coverage and Outcome following";; Newacheck et al., "The Impact of Managed Care"; and Sada et al., "Influence of Payor on Use of Invasive Cardiac Procedures."
32. Christensen and Shinogle, "Effects of Supplemental Coverage."
33. Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"; and Tu et al., "Do HMOs Make a Difference?" Note that the CTS tested differences in the percentage of enrollees with at least one admission and number of nights of stay given an admission, but not total hospital days per enrollee.
34. Experton et al., "The Impact of Payor/Provider Type."
35. Philbin and DiSalvo, "Managed Care for Congestive Heart Failure."
36. Experton et al., "The Impact of Payor/Provider Type."
37. C. Fong, "The Influence of Insurance Status on Nonurgent Pediatric Visits to the Emergency Department," Academic Emergency Medicine 6, no. 7 (1999): 744–748[Medline]; B. Friedman and C. Steiner, "Does Managed Care Affect the Supply and Use of ICU Services?" Inquiry 36, no. 1 (1999): 68–77[Medline]; C.L. Goldzweig et al., "Variations in Cataract Extraction Rates in Medicare Prepaid and Fee-for-Service Settings," Journal of the American Medical Association 277, no. 22 (1997): 1765–1768[Abstract]; Hadley and Mitchell, "Breast Cancer Treatment Choice";; S.D. Ramsey, A.L. Hillman, and M.V. Pauly, "The Effects of Health Insurance on Access to New Medical Technologies," International Journal of Technology Assessment in Health Care 13, no. 2 (1997): 357–367[Medline]; Sada et al., "Influence of Payor on Use of Invasive Cardiac Procedures";; Smith et al., "HMO Membership and Patient Age";; DeLia et al., "Medicaid Managed Care in New York City";; Long and Coughlin, "Impacts of Medicaid Managed Care on Children";; Newacheck et al., "The Impact of Managed Care";; Picken et al., "Insurance Type and the Transportation to Emergency Departments";; Reschovsky et al., "Does Type of Health Insurance Affect Health Care Use?"; and Shapiro et al., "Variations in the Care of HIV-Infected Adults."
38. J.E. Kralewski et al., "The Effects of Medical Group Practice and Physician Payment Methods on Costs of Care," Health Services Research 35, no. 3 (2000): 591–613.[Medline]
39. E. Yelin et al., "A National Study of Medical Care Expenditures for Musculoskeletal Conditions: The Impact of Health Insurance and Managed Care," A