The study reports noteworthy findings on the effect of insurance coverage under HMO plans. The results strongly suggest a pattern in which the growth of managed care has been associated with fewer preventable admissions for private HMO enrollees. The findings identify HMO enrollees under commercial plans as less likely to be admitted for preventable conditions, possibly as a result of a higher level of primary and preventive care that HMOs may provide. These findings indicate that HMO penetration might reduce preventable admissions relative to other admissions. Further tests showed that this result was generally true across racial groups.
Unlike private HMO enrollees, we found distinctly different admission patterns in response to managed care among adult Medicaid beneficiaries. In fact, admission patterns for Medicaid patients under managed care were not different from their fee-for-service counterparts. This finding is in agreement with other studies on adults (e.g., Coughlin and Long 2000
) where no significant difference in access between managed care and FFS Medicaid enrollees was found. Studies also suggested that Medicaid HMO enrollees may actually face greater access barriers than their FFS counterparts (e.g., Porell 2001
). This was found true in Pennsylvania, which showed a significantly higher likelihood of preventable admissions among MMC enrollees compared with Medicaid FFS.
The findings from our study support the current evidence (e.g., Lillie-Blanton and Lyons 1998
; Institute of Medicine 2000
) that Medicaid managed care appears to have major differences from commercial managed care in terms of access to primary care. The difference may exist irrespective of the differential health status between the two groups. Although the data did not permit us to sufficiently control for the differences in the underlying health status of different populations, we focus our comparisons on within-group differences, for example, Medicaid FFS versus Medicaid HMO, and private FFS versus private HMO, which have similar health status. The main attempt to capture potential differences in health status among population groups in this study was the Medstat severity index, based on serious comorbidities and age within diagnostic groups. This index has been used in a number of published articles with hospital administrative data. In addition, our analysis included race and median county income, which may also capture some of the differences in health status, combined with other determinants of the use of primary and preventive services.
We also explored whether differences in health status within Medicaid (between FFS and HMO) patients could bias our results. A primary reason for such differences could be the eligibility categories (SSI versus TANF), which could not be included in this study because of lack of data. However, the difference in health status was not found likely to bias the relative rates of preventable versus marker admissions. If admission per enrollee is a measure of health status, further analysis (data available from authors) did not reveal any marked difference between preventable and marker admission rates per enrollee in two enrollment categories (FFS and HMO). Additionally, we tested interactions of severity (RDSCALE) with Medicaid FFS and Medicaid HMO enrollment. There was no clear indication that patients admitted for preventable conditions with higher severity were more likely to be Medicaid FFS enrollees than Medicaid HMO patients relative to marker admissions, as the two odds ratios had very close values.
Selection bias is another issue that often challenges the researchers in a comparison of HMOs with FFS. Because we focused on within-group differences, Medicaid FFS versus Medicaid HMO and private FFS versus private HMO, and selection bias may occur among both Medicaid HMO and private HMO patients, our conclusions should not be affected. Moreover, the direction of effect of unmeasured severity bias is counter to the results shown. Health maintenance organizations usually have favorable selection, so selection bias would tend to make HMOs seem more effective.
Selection bias is usually a more important issue in states with voluntary Medicaid HMO enrollment. Except Tennessee, all three other states had a combination of mandatory and voluntary programs. It was not possible to know from hospital discharge records which beneficiaries were subject to mandatory managed care in these states. The expected bias due to the inclusion of voluntary enrollees is that the Medicaid managed care would seem to reduce hospital admissions due to selection of healthier enrollees. This bias would be opposite to the findings. We tried to control for selection bias with a larger number of indicators: RDSCALE, source of admission, teaching status of admitting hospital, and distance traveled for hospitalization.
Another source of potential bias could be found in our inability to correctly identify Medicaid patients who were previously uninsured. This could have a disproportionate effect on Medicaid FFS because most patients who would transition from uninsured to Medicaid at the time of admission might enter into Medicaid fee-for-service. It is likely that the bias could be more important for patients admitted for marker conditions because these are mostly urgent admissions. However, while some of the preventable conditions are flare-ups of chronic conditions, many are also acute infections or other problems that were not promptly treated and required an urgent admission (e.g., bacterial pneumonia, cellulitis, urinary tract infection, dehydration, and so on). Further analysis of enrollment data (available from authors) suggests that the marker admission rate per enrollee for Medicaid FFS versus Medicaid HMO was no greater than the corresponding ratio for preventable admissions in these two enrollment categories.
Several other sensitivity tests were done in our study where several variables, including admission from emergency rooms, transfer admissions, teaching hospital, and distance were dropped due to the likelihood of association with marker admissions, and are not adequately representing causes of admission. These exclusions did not cause any change in our major findings.
To summarize, the study shows that while HMOs were associated with fewer preventable admissions in the privately insured population, there was no such association found among the Medicaid population. There could be various explanations for this, several of them cited in other studies (Institute of Medicine 2000
; Nawacheck, Hughes, and Studdard 1996
; Lillie-Blanton and Laveist 1996
; Rosenbaum and Shin 1998
). These include the poorer health status of these beneficiaries, their more diverse need, lack of choice, and dependence on nonmedical services. The demands placed on managed care may be far greater within Medicaid as plans treat more chronically ill and severely disabled individuals and provide a far broader range of services to patients with large unmet needs (Zuckerman, Evans, and Holahan 1997
; Weinberger, Oddone, and Henderson 1996
). From a provider perspective, lack of experience with Medicaid populations and low payment rates could act as access barriers. Unlike most commercial enrollees, Medicaid clients do not typically have continuous enrollment in a plan throughout the year. This intermittent eligibility is a common issue in Medicaid managed care and could lead to administrative complexity and costs for provider and plans (Hurley and Wallin 1998