In this section we present descriptive statistics on 2011 NED2 voucher users, extending our knowledge about them from the process analysis. Using linked survey and administrative data, we describe these individuals and compare them with non-users on a variety of demographic, functional, health, and institutional-related characteristics.
1. Method for Identifying NED2 Voucher Users
Using HUD administrative data, we identified 139 voucher users across the five PHAs included in the analysis sample (Table III.2). Generally, the number of voucher users identified in the HUD data in a particular PHA was lower than the count collected by TAC. The exception was Baltimore City, for which we identified two more voucher users than there were vouchers leased. This may have been due to voucher turnover; if a NED2 participant was reinstitutionalized or died, the voucher was made available for reissue. Alternatively, the difference might be attributed to differences in the timing of the two data sources. TAC data collection may have occurred at any point in December 2011 and HUD administrative data identified users through the end of the month. People who leased vouchers later in the month may have been missed by TAC but identified by HUD.
|TABLE III.2. Counts of NED2 Voucher Users in HUD and Matched MDS-HUD Data|
|NED2 PHA|| 2011 NED2 Voucher Users
| 2011 NED2 Voucher Users Identified
in MDS Treatment Area Facilities
|Baltimore County, MD||13||10|
|Baltimore City, MD||28||27|
|SOURCES: HUD administrative data and MDS.|
We used HUD administrative data to identify NED2 voucher users in the MDS, linking the two data sources using Social Security numbers or last name, gender, and date of birth. Of the 139 voucher users in the HUD data, 130 were successfully matched to records in the MDS. Some of those not identified in the MDS may have resided in institutions other than nursing facilities (for example, ICFs-ID; see above) before voucher use, or information in the HUD administrative data or MDS may have been missing or incorrect. We focused only on the voucher users who resided in nursing facilities in a treatment area during the intervention period.27 Accordingly, we excluded people reported to have been discharged from nursing facilities before NED2 vouchers were made available.28 Finally, we excluded two voucher users based on institutional length of stay.29 After these exclusions, our sample consisted of 116 voucher users.
2. Characteristics of NED2 Voucher Users
To learn more about NED2 voucher users, we compared users to non-users ages 62 years and under who resided in treatment area nursing facilities during the intervention period (Table III.3). Non-users were further divided into two categories: those who made transitions to the community and those who did not. The latter group included people who had died, remained in nursing facilities, moved to different nursing facilities, or moved to acute care or other facilities. It is clear that vouchers users differed substantially from both those who made transitions without vouchers and those who did not make transitions.
A comparison of voucher users to people who made transitions to the community without the use of vouchers is suggestive of the extent to which the vouchers were being used by people who were different from those who would make transitions without such assistance. The two groups differed in terms of several demographic characteristics. For example, voucher users were 14 percentage points less likely to be female than non-users who made transitions. The gender gap was evident in all three states but particularly pronounced in Cincinnati (Appendix Table B.1). There is no obvious explanation for the difference. Voucher users were also less likely to be married than non-users who made transitions (9 percent compared to 25 percent), a difference again reflected in statistics for all three states. Voucher users may have lacked informal and financial support that, for others, was provided by spouses.
|TABLE III.3. Characteristics of NED2 Voucher Users Relative to Other Nursing Facility Residents Ages 62 and Under (%)|
| NED2 Voucher Users
(N = 116)
| People Who Made Transitions
Without NED2 Vouchers
(N = 4,804)
|People Who Did
Not Make Transitions
(N = 4,307)
|Condition: renal disease||11.2||9.9||8.6|
|Able to make self understood||95.7||92.5*||60.4***|
|Walk in room--independentk||42.2||24.2***||13.4***|
|Walk in corridor--independentk||36.2||20.8***||10.9***|
|Locomotion on unit--independentk||69.0||32.5***||21.1***|
|Locomotion off unit--independentk||63.8||30.5***||18.6***|
|Days in nursing facility||378.7||52.6***||648.2***|
|Medicaid eligible only||63.8||20.3||37.5|
|Medicare eligible only||3.4||18.5||7.5|
|No Medicaid or Medicare||5.2||43.6***||16.2|
|Entered nursing facility from other facility||88.8||92.0||87.2|
|Does not intend to make transition||0.9||4.5||24.0|
|Intends to make transition||31.0||76.1||22.8|
|Transition intent missing||68.1||19.4***||53.2***|
|SOURCE: HUD administrative data linked to MDS.
NOTES: Chi square tests of significance were conducted on Medicaid/Medicare status and intent to make transition; two-sample t-tests for significance were conducted on all other variables.
*Indicates characteristic is statistically different from that of NED2 voucher users at the 10% level.
On average, voucher users had fewer functional limitations than non-users who made transitions to the community. This pattern appeared in every site. We would expect that, all else equal, nursing facility residents with the fewest functional limitations would be the most likely to make transitions, as it is generally easier to set up community care plans for those who have the fewest needs for assistance with daily activities. Accordingly, this could suggest that functional status was not the primary barrier to independent living faced by voucher users.
NED2 voucher users also differed from those who made transitions without vouchers in terms of health insurance coverage. Voucher users were more likely than non-users to be Medicaid-eligible (91 percent were Medicaid-only or had dual Medicaid/Medicare coverage) and less likely to be without public insurance (only 5 percent were without Medicaid or Medicare coverage). This partly reflects the fact that most voucher users were recruited through MFP, which is only available to people eligible for Medicaid. Indeed, all voucher users in our sample from Baltimore and Cincinnati were eligible for Medicaid. In contrast, less than half of non-users who made transitions to the community had Medicaid coverage (38 percent), and 44 percent lacked Medicaid or Medicare coverage. It seems likely that those without Medicaid or Medicare who made transitions to the community had significant financial support from private insurance, their families, or their own assets.
Of those who later made transitions to the community, with or without the use of a voucher, very few indicated they did not intend to do so when they first entered a nursing home. Despite this similarity, the average NED2 voucher user resided in a nursing facility for almost a year longer than the average person who made a transition without a voucher (379 days versus 53 days).
Although in some respects voucher users were more similar to those who made transitions without vouchers than to those who did not make transitions (in terms, for example, of functional limitations and intention to make transitions), in others (demographic characteristics, insurance coverage, and length of stay) they were more similar to those who did not make transitions. These comparisons suggest voucher users tended to be people who wanted to live in the community and, like others who made transitions, had relatively modest functional limitations, but may have faced other significant challenges such as limited social supports or problems finding a home to which they might return.