|
Article Excerpt
Hospitalization of nursing home residents is prevalent throughout the U.S., but varies considerably both within and between states (Intrator and Mor 2004; Intrator, Zinn, and Mor 2004). Over 15 percent of long-stay nursing home residents are hospitalized within a given 6-month period (Intrator, Zinn, and Mor 2004). Hospitalizations are costly and put residents at risk for iatrogenic disease and delirium (Ouslander, Weinberg, and Phillips 2000). In addition to resident characteristics and severity of illness, facility, and market characteristics are associated with the likelihood of hospitalization of nursing home residents (Intrator, Zinn, and Mor 2004). Although hospitalization rates vary across states, even when controlling for facility and market factors, there has been little systematic study of the influence of state Medicaid nursing home policies on these rates.
Over 60 percent of nursing home resident care, and an even higher percentage of long-stay resident care, is paid for by states' Medicaid programs that differ considerably in the generosity and method of payment (Harrington et al. 1999; Grabowski et al. 2004). States have broad discretion to set the daily Medicaid nursing home payment rate (Wiener and Stevenson 1998). States' nursing home policies have been shown to be associated with quality measures (Grabowski, Angelelli, and Mor 2004; Zhang and Grabowski 2004), expenditures (Harrington and Swan 1987), and access to services (Ettner 1993).
In response to less generous Medicaid payments, nursing homes appear to reduce staffing (Cohen and Spector 1996; Grabowski 2001a, b; Grabowski, Angelelli, and Mor 2004; Intrator et al. 2005) and the use of nurse practitioners or physician assistants (NP/PAs; Intrator et al. 2005). In facilities with inadequate staffing, temporary acute conditions are more likely to occur, and less likely to be well managed, typically necessitating hospitalization (Ackermann and Kemle 1998; Intrator, Castle, and Mor 1999; Reuben et al. 1999; Intrator and Mor 2004; Intrator, Zinn, and Mor 2004). Yet, there has been insufficient research on the direct relationship between state Medicaid nursing home policies and hospitalizations. In the only published study of this issue, Intrator and Mor used 1993 data from nursing homes in 10 states and showed that a $10 Medicaid payment rate higher than the average Medicaid rate across states ($100) was associated with a 9 percent lower odds of hospitalization (Intrator and Mor 2004).
Bed-hold policies pay nursing homes to reserve the bed of acutely hospitalized residents, and vary across states in the proportion of the average Medicaid daily rate paid for bed-hold, and the number of days covered. Some states also require a minimum facility occupancy rate to qualify for bed-hold payments. The goal of bed-hold is to provide a continuous place of residence for the nursing home resident. In the absence of a bed-hold policy, some residents may refuse hospitalization to avoid loss of their bed (Nohlgren 2004). On the other hand, if the marginal profit associated with the Medicaid bed-hold payment is greater than the marginal profit associated with nursing home Medicaid payment for continued care in the nursing home, then bed-hold introduces a financial incentive to hospitalize nursing home residents. Using the Institutional Population Component of the 1987 National Medical Expenditures Survey, Freiman and Murtaugh (1993) found a positive, but statistically insignificant association between the presence of a state bed-hold policy and nursing home hospitalization.
In this paper, we used national data from 2000 to analyze the association between state Medicaid policies and the probability of acute hospitalization from the nursing home setting, using multilevel multinomial response models controlling for death and for resident, facility, and market factors that may influence hospitalization.
METHODS
Data Sources
We merged data from mandated assessments of nursing home residents, Medicare claims and eligibility files, annual nursing home certification surveys, county-level market measures, and state-level policies collected via our own survey. All data pertain to the study year, 2000.
The minimum data set (MDS) resident assessment instrument, in use in nursing homes since 1991, has nearly 400 data items, including cognitive functioning, physical functioning, diagnoses, health conditions, and more, which provide information on resident case-mix acuity. The Centers for Medicare and Medicaid Services (CMS) mandates that all residents treated in a federally certified nursing home for at least 14 days be assessed quarterly, at admission, readmission, discharge, and when a significant change in health status occurs (Morris et al. 1990, 1997). We used MDS data from CMS's MDS Repository from all 48 contiguous U.S. states (excluding Hawaii, Alaska, and the District of Columbia because they are either remote or have political constraints beyond those of the other states). MDS data were merged with Medicare eligibility files for the same time period to determine cohort eligibility, and with inpatient claims to determine inpatient hospital utilization.
Facility characteristics were obtained from the On-line Survey of Certification and Reporting (OSCAR) annual report closest to July 1, 2000. OSCAR provides information on nursing home structure (proprietary status, number of beds, hospital affiliation, etc.), staffing, resident case mix, and service availability. The many studies that have used the OSCAR data provide evidence of its validity (Weech-Maldonado, Neff, and Mor 2003; Zinn et al. 2003; Feng et al. 2005; Intrator et al. 2005).
Nursing home markets are frequently defined as counties because of patterns of funding and patient origin (Joskow 1980; Nyman 1985; Zinn 1994; Banaszak Holl, Zinn, and Mor 1996). Although this may be a suboptimal approximation (Zwanziger, Mukamel, and Indridason 2002), aggregate data based on other geographic market definitions are not readily available. We used the Area Resource File, a county-level database containing socioeconomic data, as well as availability of medical professionals and services, to control for market heterogeneity in supply and demand for nursing home services (Stambler 1988).
We collected data on state policies via a comprehensive survey of state nursing home policies and used states' average daily Medicaid nursing home payment and bed-hold policies from 2000 (Grabowski et al. 2004).
Cohort Definition
Given differences in urban and rural nursing home markets, we excluded rural nursing homes because they are more isolated, and their hospitalization patterns, including the response to state policies, may be influenced by external resource constraints, such as travel distance, beyond those found in urban settings (Zwanziger, Mukamel, and Indridason 2002). We also excluded 145 (1.5 percent) nursing homes with fewer than 20 beds because we believe their incentives for operation would be very different than those of larger facilities, and, based on information in the OSCAR, we observed that they cater to very select populations.
We limited our analysis to long-stay nursing home residents. Residents recently admitted for short-stay rehabilitation and skilled nursing following a hospitalization may be more likely to be readmitted to the hospital due to medical instability associated with their initial hospitalization (Gillen...
|
