This study explores the reasons for the observed differences in hospitalizations between Medicaid and private-pay residents in NHs. Our findings demonstrate that both within-facility and across-facility variations account for the difference in hospitalizations between Medicaid and private-pay residents in NYS facilities. All NHs, except those that are FP and bed-hold ineligible, seem to make differential hospitalization decisions for their Medicaid and private-pay residents. The magnitude of this within-facility difference varies with facility ownership status and bed-hold eligibility. For example, the within-facility disparity is greater in FP than NFP facilities eligible for Medicaid bed-hold, but not among those where a bed-hold policy does not apply. Among the NFP facilities bed-hold policy does not seem to have the expected impact. These findings suggest that FP facilities may behave differently than NFP, perhaps because they might be more sensitive to financial incentives. NFP facilities may be more heterogeneous and incorporate different goals into their objective functions (Cohen & Spector, 1996
; Ettner, 1993
; O'Neill, Harrington, Kitchener, & Saliba, 2003
; Scanlon, 1980
; Spector, et al., 1998
). Moreover, we find that residents in most NHs with a higher concentration of Medicaid residents are more likely to be hospitalized, regardless of their payer status.
These findings suggest that NHs’ hospitalization decisions may be affected by financial factors. The incremental hospitalization events induced by such financial incentives are likely to be “unnecessary” since these hospitalization decisions are not based on residents’ health conditions or their treatment preferences. This appears to be particularly true when we compare hospitalizations rates by payer within the same facility. In principle, all residents in the same facility should have the same level of resources available to them and hence, unless we have been unable to sufficiently control for differences in the clinical risk or treatment preferences between Medicaid and private pay patients (see further discussion below), there is no reason to expect a differential hospitalization pattern.
Our findings are not consistent with previous studies that found no within facility differences in quality of care between Medicaid and private- pay residents, which have suggested that quality of care is a common good in NHs (Grabowski, Gruber, et al., 2008
; McKay, 1989
; Troyer, 2004
). However, these studies focused on different outcomes. For example, Grabowski and colleagues have examined quality indicators such as the prevalence of physical restraints, pain and pressure ulcers, measures that are directly affected by care provided by the frontline staff. It seems reasonable that frontline staff will provide similar quality of daily care (e.g. turning the residents to prevent pressure ulcers) to residents regardless of their payer status. However, hospitalization decisions are not directly made by the frontline staff. In addition, in contrast to the care delivered to residents every day, hospitalization decisions are more sporadic and more directly affected by financial resources and incentives (especially under a generous bed-hold policy). Furthermore, there is no standard definition as to what should be considered an “appropriate hospitalization”. While quality measures used in the above cited study are well defined, widely used, and published in the Centers for Medicare and Medicaid Services (CMS) quality report cards, there are no such indicators for hospitalizations. Because of this, while reports of poor quality of care may potentially hurt NHs’ profits (i.e. attractiveness to private-pay residents), hospitalization rates may not have such an effect.
Consistent with previous studies (Intrator, et al., 2007
; Intrator, et al., 2009
), we find that Medicaid bed-hold policy might provide an incentive for NHs to hospitalize residents, specifically Medicaid residents in FP facilities. However, it may not be practical to simply repeal the Medicaid bed-hold policy to reduce the burden of unnecessary hospitalizations associated with this policy. For Medicaid residents bed-hold policy has been associated with continuity of care (Intrator, et al., 2009
). Without a bed-hold policy, Medicaid residents may not be able to return to their original NHs following discharged from the hospital. Such disruption of care could lead to unfavorable health outcomes for these residents (Intrator, et al., 2009
; Nohigren, 2004
) and maybe undesirable as a policy option for Medicaid. Moreover, the potential savings from hospitalizations associated with repealing bed-hold policies would largely benefit Medicare. Given the separation of Medicaid and Medicare funding mechanisms, state Medicaid programs do not have the financial incentive to repeal their bed-hold policies.
Since the main objective of a bed-hold policy is to ensure continuity of care, it should ideally only be applied to facilities with very high occupancy rates. In NHs with low occupancy rates it may not be necessary to hold a bed since there is no shortage of empty beds to which a Medicaid resident may be re-admitted following a hospital stay. In fact, NYS raised the occupancy rate requirement for its Medicaid bed-hold policy from 95% to 97% in 2009. This literally excludes most facilities from eligibility for Medicaid bed-hold payments in NYS. It will be interesting to re-investigate hospitalization rates in New York State after this change. This would offer guidance to other states who may be contemplating changes to their bed-hold policies.
Recently, the Centers for Medicare and Medicaid Services (CMS) embarked on a pay-for-performance (P4P) demonstration, which provides incentive payments to NHs based on their quality performance, including a measure based on hospitalizations rates (Barondess, 2008
). CMS expects savings due to the anticipated reductions in hospitalization rates. However, concerns about the impact of the P4P program have also been raised, including the potential for deepening the existing Medicare and Medicaid payment silos. For example, NHs that improve their care management strategies to avoid unnecessary hospitalizations may save Medicare dollars, while increasing the cost of care to Medicaid by making daily routine care more costly (Briesacher, Field, Baril, & Gurwitz, 2008
The Evercare model has been associated with fewer hospitalization events among certain groups of the elderly (Kane, Keckhafer, Flood, Bershadsky, & Siadaty, 2003
). Through dual capitation, this model somewhat eases the financial tensions between Medicaid and Medicare. Extending such a model to the majority of NH residents may further help to reduce hospitalization rates for Medicaid residents. Indeed, Evercare may be a plausible way to reduce avoidable hospitalization events since the costs incurred by saving Medicare costs are born by Medicare. However, there are also potential issues with this approach. In absence of a clear definition of intensive care that qualifies for Medicare reimbursement, NHs may have an incentive to provide unnecessarily intensive care in order to receive a higher Medicare rate (Grabowski, 2007
As to payer-related across-facility variations in hospitalizations, facilities with a higher proportion of Medicaid residents are likely to have fewer resources (Mor, et al., 2004
), and, therefore, may not be able to provide intensive onsite care in the first place. For these facilities, policy interventions such as P4P may not be effective since these facilities may need additional funding to bring them up to par in order to compete with other facilities. However, it may be less feasible to simply increase the Medicaid payment rates, considering states’ current fiscal deficits and the financial conflicts between Medicare and Medicaid. Moreover, the assumption that a higher Medicaid reimbursement rate may reduce hospitalization rates is based on the supposition that NHs are willing to invest in the clinical services necessary for the provision of intensive care onsite if they are better funded. If the profits of hospitalizing a resident are higher than providing onsite care (especially under a generous bed-hold policy), NHs may still be inclined to hospitalize their residents, even under a higher Medicaid reimbursement rate.
Several limitations of the study must be acknowledged. First, we may not be able to capture the occurrence of all acute events as their availability is only as good as the data set we have. However, we assume that the incidence of acute conditions is similar for Medicaid and private-pay residents, conditional on their health status at the beginning of the observation period. If this assumption is violated, the differences in hospitalizations between Medicaid and private-pay residents could also be attributed to unequal quality of care delivered to Medicaid and private-pay residents. However, this is not very likely as other studies have not found any systematic differences in quality of daily care by payer within a facility (Grabowski, Gruber, et al., 2008
; Troyer, 2004
). Second, although we have controlled for individuals’ treatment preferences and a very long and exhaustive list of their health conditions, we may still not have captured all residents’ heath conditions or their treatment preferences, and thus have biased estimations of the effect of payer source. If Medicaid residents are systematically different from private-pay residents in an unobserved way that make them more susceptible to hospitalization (e.g. unobserved heterogeneity of health conditions or their preferences), the difference in hospitalizations between Medicaid and private-pay residents could be caused by these unobserved factors rather than their payer status. Future studies that examine the within-facility differences across states with different bed-hold policies may provide more evidence because the differences in unobserved heterogeneities between Medicaid and private-pay residents may be less likely to correlate with different state Medicaid bed-hold policies. Third, we do not consider multiple hospitalizations and deaths in NHs in our main analysis. However, we do not think this limitation seriously undermines the findings of this study. For any individual, multiple hospitalization events are likely to be highly correlated. We have conducted a sub-analysis among those who have multiple hospitalization events, and find Medicaid residents are more likely to be hospitalized multiple times than their private-pay counterparts. Further, under the null hypothesis (NHs treat Medicaid and private-pay residents the same), there should be no systematic difference in the distribution of the number of hospitalizations or deaths for Medicaid and private-pay residents, controlling for health conditions. The likelihood of death in NHs will be directly affected by the hospitalization decisions. In other words, the differences in the distribution of deaths or the number of hospitalizations are directly linked with the rejection of the hypotheses. Fourth, this study focuses on the overall hospitalizations rather than non-discretionary or discretionary hospitalization admissions because there is no clear definition of what should be considered as discretionary/non-discretionary hospitalization admissions, and our data do not provide us with a sufficient sample if we only focus on a small subset of hospitalization admissions with relatively high agreement for the distinction of discretionary / non-discretionary hospitalizations( e.g. acute myocardial infarction). Finally, our study only focuses on New York State, which is unique as it has the highest Medicaid reimbursement rate in the country and a very generous bed-hold policy.
In conclusion, we find unequal hospitalization risks between Medicaid and private-pay residents in New York State NHs. Furthermore, we find evidence suggesting that financial incentives may motivate consideration of payer source in hospitalization decisions. Future research should examine whether such variations hold across states with different levels of Medicaid payment and bed-hold policies. Findings from such research would offer additional insights on these complex relationships and may help guide Medicaid and Medicare policies that influence these decisions.