Non-Elderly Disabled Category 2 Housing Choice Voucher Program: An Implementation and Impact Analysis. Notes

01/01/2014

  1. NED HCVs are not new; previous NED vouchers did not, however, exclusively target NED individuals living in institutions, as does NED2. Additionally, the NED2 HCV program is not the first in which HUD has established set-aside vouchers for a special population. Similar targeted voucher programs exist for the homeless veteran population (the HUD-Veterans Affairs Supportive Housing program) and families and youth involved in the child welfare system (the Family Unification Program).

  2. Funding for this program originated in the Omnibus Appropriations Act of 2009 (Public Law 111-8), which made available $30 million for incremental Section 8 HCVs for NED families.

  3. In addition to nursing facilities, the definition of an institution includes intermediate care facilities and specialized institutions that care for the developmentally disabled or mentally ill.

  4. "Leasing" of vouchers refers to a voucher being used to sign a lease on a housing unit with rent subsidized by the voucher.

  5. Section IV.B.f of the HUD NOFA informed PHAs that the number of vouchers requested in their applications should reflect the expected need over a 12-month period. A subsequent letter to the PHAs from HUD further reinforced the expectation that "all vouchers are leased within 12 months from the effective date of the Annual Contributions Contract increment."

  6. Among the five states were three in which PHAs received NED2 vouchers: California, New Jersey, and Washington. The remaining two states were recipients of NED Category 1 vouchers, which are not the focus of this report.

  7. HUD's HCV income eligibility requirements are defined under Title 24 of the Code of Federal Regulations, 982.201(b)(1).

  8. Eligible institutions include Medicaid-funded institutions, such as nursing facilities and intermediate care facilities for the developmentally disabled or mentally ill, and non-Medicaid-funded institutions, such as private or public psychiatric facilities that have state-funded dedicated resources, such as fromOlmstead or U.S. Department of Justice settlements.

  9. This figure is based on data self-reported by all 28 PHAs to TAC; see the methodology section for further details and limitations of this data set and the data collection process.

  10. New Jersey operates a single, statewide housing agency consisting of regional and local field offices. Vouchers awarded to the New Jersey Department of Community Affairs could be used anywhere within the state. Because this PHA operates differently than all other PHAs awarded vouchers, we excluded it from certain segments of the evaluation.

  11. These self-reported data were not precise, as updates may have been provided by different staff during each phone conversation, questions were not necessarily posed identically for each PHA, and TAC had no way to validate the information provided. The interactions were, however, the only source of data that provided approximate numbers of vouchers issued or leased at various points in time across all PHAs. Although PHAs were required to track voucher status and provide information on voucher recipients to HUD through the Public and Indian Housing Information Center (PIC) system, those data were not readily available for all 13 PHAs included in this analysis, or for the four points in time we included so we could understand the implementation process.

  12. The MFP program team was the state or local HHS partner in seven of the eight states in this analysis. The exception was Massachusetts, which did not have an operational state MFP program until late 2011, after the NED2 program began. In that state, the PHA partnered with the state HHS Community Support Programs division.

  13. Representatives from the PHAs in Pasadena, California, Lucas County, Ohio, and Tacoma, Washington, could not be reached for participation in these discussions.

  14. Reporting 70 percent in issued or leased status, Pasadena would seem to have had the more impressive start; however, almost all of these vouchers were reported as issued, not leased.

  15. The consent decree required the Housing Authority of Baltimore City to create 1,850 new housing opportunities for non-elderly persons with disabilities, including 1,350 Section 8 rental subsidy vouchers (850 tenant-based vouchers and 500 project-based vouchers), as well as the development of fully accessible public housing units. These types of Olmstead or U.S. Department of Justice lawsuits have not been uncommon in recent years, and the settlements, which often mandate transitions of institutionalized individuals to the community, have resulted in stronger relationships between housing and Medicaid staff in many states.

  16. Portability refers to the ability of a voucher holder to move from the jurisdiction of his or her receiving housing agency to that of another housing agency. Unless otherwise specified by HUD in the voucher program rules, each PHA is permitted to establish its own rules governing portability. See below for further details.

  17. The MDS contains information from the Resident Assessment Instrument, a federally mandated clinical assessment performed on all Medicare and Medicaid beneficiaries residing in nursing facilities. Section Q of this assessment addresses whether the resident would like to explore the possibility of going back into the community.

  18. HUD provides PHAs with a HCV Guidebook, detailed regulations, and issue-specific notices, which detail how to provide for reasonable accommodation requests under all HCV programs.

  19. Unless otherwise specified in program regulations, if a PHA allows a voucher to be transferred ("ported") to another PHA, the receiving PHA has the choice of billing the initial PHA for any assistance provided to the porting individual or of absorbing the individual into its own program. If the receiving PHA elects to absorb the individual, the initial PHA is left with an unused voucher. Several PHAs regarded this as a disincentive to port and hoped that HUD would have established a "no absorption" policy in the governing regulations.

  20. Austin is grouped here because of its relatively low lease rate of 67 percent in summer 2012. The site did not, however, report all the barriers noted by the other three sites listed. Also unlike the others, Austin reported strong lines of communication between the MFP and PHA staff. And although referral activities were not coordinated by a statewide housing specialist, and porting was not permitted, these were not noted as significant barriers to leasing by site staff. Instead, Austin's tight rental market was cited as a major barrier to leasing.

  21. See footnote number 19 for a definition of "absorption".

  22. As described in more detail in Section C, individuals were deemed "unlikely" to use vouchers in a two step process. First, we excluded nursing facility residents with characteristics exhibited by none of the voucher users. Second, we created propensity scores and excluded non-voucher users who were outside the range of scores predicted for voucher users. This method excludes individuals based on a combination of characteristics.

  23. Compared with the MDS, alternative data sources with information on nursing home residents' characteristics are incomplete and/or even less timely. For example, Medicaid Statistical Information System (MSIS) data contain information on patient characteristics, nursing facility admissions, and discharges and could have served as an alternative or supplement to the MDS. There are reporting delays of MSIS data for many states, however, some of which only have data available through September 2010.

  24. Because the MDS is only administered to current nursing facility residents, we could not rely exclusively on MDS 3.0, as it would exclude former residents who left facilities before October 2010 and skew the composition of the pre-intervention (April 1 to December 31, 2010) sample relative to the intervention (April 1 to December 31, 2011) sample. We used both MDS versions for the pre-intervention sample but only the MDS 3.0 for the intervention sample.

  25. We also linked the NPI to the Medicaid Analytic eXtract Provider Characteristics file but were unable to identify as many NED2 voucher users residing in treatment area PHAs as we did using NPPES data.

  26. We also eliminated two PHAs (New Jersey Department of Community Affairs and Lynn Housing Authority in Massachusetts) from the analysis because they made vouchers available statewide, which precluded the construction of within-state comparison groups. Even though 12 NED2 vouchers were awarded to the MD-DHCD and were available statewide, we were able to identify comparison regions for the two PHAs in Maryland by excluding regions in which a majority of those vouchers were used. Of the 11 MD-DHCD voucher recipients included in HUD data, three did not have zip codes recorded, and seven of the eight with zip codes resided in rural areas (most along the Eastern Shore of Maryland); one was in Frederick, Maryland. These areas were not used as comparison areas.

  27. No HUD administrative data system matches PHAs to clearly defined geographic areas. For our analysis, we determined which zip codes corresponded to a given treatment area. A few voucher users (one in Cincinnati, three in Snohomish, and four in Tacoma) resided in nursing facilities outside of treatment areas. HUD regulations did not require people applying for the NED2 vouchers to have lived in the PHA issuing the vouchers while they were institutionalized; applicants just had to say they wanted to live in that area after leaving an institution. We did not expand our definition of treatment areas to include outside areas in which voucher users resided, as doing so would have reduced our ability to detect impacts of any given size.

  28. We excluded four voucher users (one in Baltimore County, two in Cincinnati, and one in Tacoma) who were discharged from nursing facilities before NED2 vouchers were available.

  29. Two voucher users, one in Baltimore County and one in Baltimore City, were reported to have resided in nursing facilities for six or fewer days (according to MDS data) at the time they leased their vouchers, which is inconsistent with the process for voucher assignment and uptake.

  30. Although Longview, Washington, and Lucas, Ohio, are in the same states as other PHAs analyzed in this report, we did not include either area in our analysis. HUD administrative data did not include any 2011 NED2 participants in Longview, Washington, and although nine participants from Lucas, Ohio, were in the HUD data, inclusion of a region with a small number of voucher users would have led to a disproportionately large increase in the treatment sample, substantially reducing statistical power.

  31. As discussed later, given a fixed number of vouchers in a treatment area, the smaller the sample of potential users in the area, the more likely the estimation methodology would detect an impact of given size.

  32. As a sensitivity test, we estimated a specification for the Washington sample that included only those who were Medicaid eligible and had resided in nursing facilities for more than 90 days. As explained below, the results did not change substantially.

  33. Specifically, control variables included demographic characteristics (gender, age, age squared, race, and marital status), sensory ability (vision, hearing), functional characteristics (up to four different levels of functioning in the following categories: ability to make self understood, bed mobility, transfer ability, walk in room, walk in corridor, locomotion on unit, locomotion off unit, dressing, eating, toilet use, personal hygiene, and bathing), presence of health conditions (heart-related diseases, infection, metabolic conditions, musculoskeletal conditions, cognitive conditions, diseases affecting motor skills, neurological conditions, psychological conditions, cancer, and renal disease), and institutional characteristics (days in nursing facility, days in nursing facility squared, Medicaid and Medicare coverage, type of residence before current stay, and intent to transition).

  34. Beneficiary-level control variables included demographic characteristics (gender, age, age squared, race, and marital status), sensory ability (vision, hearing), functional characteristics (up to four different levels of functioning in the following categories: ability to make self understood, bed mobility, transfer ability, walk in room, walk in corridor, locomotion on unit, locomotion off unit, dressing, eating, toilet use, personal hygiene, and bathing), presence of health conditions (heart-related diseases, infection, metabolic conditions, musculoskeletal conditions, cognitive conditions, diseases affecting motor skills, neurological conditions, psychological conditions, cancer, and renal disease), and institutional characteristics (days in nursing facility, days in nursing facility squared, Medicaid and Medicare coverage, type of residence before current stay, and intent to transition).

  35. Results from all logit models, including coefficient estimates, are provided in Appendix C, Tables C.1-C.5.

  36. We also estimated a linear probability model to assess the sensitivity of the findings to the empirical specification. A linear probability model is an ordinary least squares model with a binary outcome. The estimated impacts from the linear probability were not substantively different from the results from the logit model.

  37. An additional ten voucher users were excluded from the model of Medicaid eligibles who resided in nursing facilities for 90 or more days. The alternate model for Washington included 36 voucher users and an analytical treatment sample of 216 observations. The maximum potential impact was 16.7 percentage points.

  38. HUD's application requirements specified that PHAs identify a local HHS/MFP transition agency that would provide service coordination to voucher recipients but did not require evidence of coordination or a commitment to partnership through, for example, confirmation by an HHS/MFP agency director.

  39. An estimated 259 individuals used NED2 vouchers through the end of 2012 in the five PHAs analyzed. Of the 259 NED2 voucher users, at least 188 can be linked to the 2011 MDS and resided in a nursing facility in a designated treatment area before transition. The latter figure represents a 62 percent increase over the number (116) who had used their vouchers by the end of 2011. It is likely that an even higher proportion of voucher users would be linked to the 2012 MDS data.

  40. Several sites in particular are promising candidates for inclusion in a study using 2012 data. For example, although only nine vouchers were leased in both the Pasadena, California and Lucas County, Ohio sites in 2011, by the end of the next year, 25 and 44 vouchers had been leased in each site, respectively. Similarly, although only 11 vouchers were leased in the Austin, Texas site through the end of 2011, by the end of 2012, 31 vouchers had been leased. However, it is uncertain how many of the voucher users link to the MDS data.

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