To the extent they attempted to track individual outcome data, states focused on short-term outcomes. Obtaining longer-term outcomes on applicants' quality of life would require either a longitudinal survey of applicants to observe changes over time in their income, housing status, and health and health care status, or that a case manager have a sufficiently long-term relationship with the applicant to record such outcomes in a management information system. Lack of resources precludes the former, and the latter is not typically characteristic of case management among homeless populations. Thus, in this section we describe the data case study states had available on short-term outcomes pertaining to the disposition of SSI/SSDI applications and associated data on contributions of application outcomes to financial benefits to states and service delivery systems. The data are not necessarily consistent with those used to select the case study states, as described in Chapter 1, because they pertain to a different time period and are reported directly by states (rather than through the TA contractor). We also discuss in this section examples of the institutionalization and proliferation of SOAR practices and procedures that can be used to assess more system-level outcomes of the initiative.
Pennsylvania. Data collected by the organization that manages all SOAR activities in Philadelphia (i.e., the local lead and organization that supplies the in-state trainers) indicate that the SSI/SSDI approval rate has been higher after SOAR than it had been before. The organization uses a spreadsheet to track all applications submitted by in-state training participants (including members of its own staff and case managers from partner CBOs) on behalf of homeless clients. The vast majority of applications to date have been submitted by staff within the organization rather than case managers from partner CBOs. However, among the 50 SOAR applications submitted in the first year of SOAR operations in Philadelphia, 49 were approved, and one was denied. Nine months into the second year, 41 out of 47 applications submitted were approved, one was denied, and 5 were still pending. This organization had been providing SSI/SSDI benefit assistance to clients before SOAR using strategies substantially less intensive than those inherent in the SOAR model. Prior to implementing SOAR, the organization had experienced a 50 to 60 percent approval rate on the SSI/SSDI applications it submitted on behalf of clients (as reported anecdotally by staff). While the organization does not track application processing time, staff report that DDS decisions on SOAR applications are often made within 10 days. The organization's goal for the future is shifting the proportion of applications submitted by its own staff and by case managers from partner CBOs so that the latter outweighs the former.
Utah. In Utah, the State Department of Workforce Services (DWS) maintains data on all SSI/SSDI applications submitted by their own case managers on behalf of homeless clients. They are not representative of all SOAR applications filed in the state because they do not capture applications submitted by case managers in CBOs who received SSTR training early in the initiative. The data indicate that in 2008, of the 412 SSI applications submitted during the year, 338 (82 percent) were approved and 203 of those (49 percent overall) were approved upon initial application. In comparison, the approval rate for all SSI/SSDI applications in Utah as reported by DDS was 44 percent in 2008. Average time between application submission and initial approval was 3.6 months after SOAR compared to 15 months before SOAR.
Massachusetts. Data that the state DDS tracked on the outcomes of SOAR applications indicated that both the number of SOAR applications filed statewide and the application approval rate were low in the early phase of the initiative. Over a two-year period from 2007 through 2008, 138 applications SOAR were filed and about one-quarter were approved. The number of SOAR applications was low, in part because SOAR did not initially take hold well on the ground level and case managers did not submit a large volume of applications, and because difficulties tracking SOAR applications within DDS led to some applications going uncounted. In state fiscal year 2009, PATH funds were designated to support six SSI/SSDI benefit specialists housed in the state's sole PATH contractor. Since then, the PATH contractor has assumed responsibility for tracking outcomes SSI/SSDI application outcomes submitted by the benefit specialists on behalf of homeless individuals. While the benefit specialists did not receive formal SSTR training, they received the training manuals and use strategies consistent with the SOAR model. Data are maintained in a spreadsheet and indicate that designating staff whose sole responsibility is SSI/SSDI benefit assistance has facilitated an increase in application submissions, though it is too early to assess the effect on the application approval rate. As of February 2009, decisions were made in 141 (51 percent) of the 275 applications that the specialists had submitted between June 2008 and February 2009 and that 70 of those 141 applications (50 percent) were approved; the remainder were denied or in appeal. Among approved applications for which data on both the date of application and approval existed, average time between application and approval was 90.5 days (or about three months).
Virginia. Outcome data for the Tidewater area in Virginia are maintained by DDS and based on a flag for SOAR on applications. They indicate that SOAR was at its strongest in 20052006, when the allowance rate was 52 percent. In April 2006, at the peak of SOAR, average DDS analyst decision time for a SOAR application was 34 days, and the average total time from application to SSA award was 52.6 days. Unfortunately, no comparison data on processing time for all applications was available. In 2006 the state team lead took a new position and SOAR was without leadership for some time. In addition, there was substantial local staff turnover at that time. In 20062007, the allowance rate dropped to 25 percent and in 20072008 to 24 percent. The allowance rate for 20082009 to date is 29 percent.
Ohio and New Jersey. Stakeholders in Ohio and New Jersey were unable to report any information on outcomes as there is no sustained effort to collect data in these states. In both states, the number of applications submitted is likely extremely low as the lack of attention to outcomes is due to a general lack of focus on SOAR.
As noted in Chapter I, facilitating access to SSI/SSDI among homeless individuals can also lead to outcomes that financially benefit the state or service delivery systems. SSA may enter into agreements under which states or local governments are reimbursed for basic needs assistance, such as General Assistance, provided during the period that an eligible individual's SSI application for benefits was pending. Currently, 39 states have interim assistance reimbursement agreements with SSA (http://www.ssa.gov/OACT/ssir/SSI09/). In addition, medical providers may recover from Medicaid the costs of uncompensated care they provided to individuals who enroll in the program. Providers are able to recover all costs incurred while the application was pending as well as during a retroactive period of three months prior to the effective filing date. As of the time of our site visits, none of the case study states had attempted to track whether and how much providers had been reimbursed by Medicaid, but several had data regarding recoupment of General Assistance expenditures from SSA.
In Massachusetts, the state recovers Emergency Aid to Elders, Disabled, and Children (EAEDC) dollars when individuals are approved for SSI. EAEDC is a Massachusetts state-funded program that provides cash and medical assistance to needy families and individuals who are not receiving TANF, SSI, or other similar benefits that is, it is the state's General Assistance program. The state maintains cost recovery information on all EAEDC recipients who were awarded SSI, but does not distinguish between homeless versus non-homeless recipients. In fiscal year 2008, the state had recovered $12,326,520 from SSA in EAEDC. The state has little incentive to track cost recovery information specifically for homeless EAEDC recipients or to market SOAR as a major cost recovery mechanism because of the EAEDC payment structure. Individuals receive $92 per month in EAEDC when they are in shelters but $363 per month when they live in the community, so there is more financial incentive to recover EAEDC costs for individuals who are housed.
In Utah, DWS tracks in an Excel spreadsheet the number of SOAR clients statewide who have been approved for SSI/SSDI as well as the number of months they were on General Assistance prior to approval. In 2008, DWS recovered about $800,000 from SSA for General Assistance payments made on behalf of these clients.
SOAR has helped engender systemic changes in communities that will remain in place even if all SOAR-specific activities in the state were to cease. In some states, for instance, SOAR has contributed to an institutionalization of agency roles regarding benefits acquisition. In Utah, DWS created a team of specialists charged with helping General Assistance clients in the most populous regions of the state apply for SSI and Medicaid. Other states have incorporated the concept of benefits assistance (and specifically SOAR) into their 10-year plan to end homelessness. And, SOAR has contributed to the development of personal and organizational relationships that can transcend a breakdown in agency- or system-level activity related to the initiative. Specifically, in many localities there is more interaction than there has ever been between SSA/DDS staff and CBO staff who work directly with applicants who are homeless. These and other changes that have occurred in communities in relation to SOAR are described in more detail in Chapter V.
Another measure of the institutionalization of SOAR practices and principles is the extent to which states are using SOAR as a springboard for developing related initiatives for other low-income populations. At the time of our site visit, Pennsylvania was in the process of exploring the possibility of expanding the SOAR model to work with single people on cash assistance and with Temporary Assistance for Needy Families (TANF) parents. The concept was motivated by a DPW-sponsored analysis which merged TANF caseload and HMIS data. The analysis indicated that 30 percent of TANF families in which someone had a disability also had a history of homelessness. Ohio was also in the process of expanding SOAR's reach to a broader population. The Ohio Benefit Bank (OBB) is the state's online screening and application tool through which public assistance applicants can learn about programs for which they are eligible and begin the application process. At a single location, clients can access information about and applications for public benefits such as food stamps, TANF, health care coverage, home energy assistance, and child care subsidies. At the time of our site visit, the OBB was undergoing an upgrade. In addition to many other elements, the state was considering integrating the SSI application process and components of the SOAR approach into the new version. Staff in 10 communities across the state will be trained (using components of the SSTR curriculum) to assist clients with the electronic application.
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