FHA’s Hospital Mortgage Insurance Program generally serves the segment  of the market consisting of hospitals that are too risky to obtain private  bond insurance but are strong enough to pass FHA’s underwriting tests. FHA uses many of the same techniques that private insurers use to monitor  insured hospitals. Agencies Coordinate Key Activities, but FHA Does Not Track Most Performance Measures

FHA and HHS coordinate key activities, including screening applicants,  underwriting loans, and monitoring insured hospitals. Program Guidance Is Not Up to Date

FHA’s primary guidance for its hospital mortgage insurance program has  not been updated in over 20 years and does not reflect changes to the  program over that time. This trend may pose a risk to the program. HUD’s model incorporates factors and assumptions about how loans will  perform, including estimated claim and recovery rates, which are  consistent with OMB guidance. However, HUD’s model  does not explicitly consider the potential impacts of prepayment penalties  or restrictions when estimating prepayments, or the debt-service coverage  ratios of hospitals at the time of loan origination. According to OMB officials, the  use of this artificial default accounts for the risk that exists due to the low  number of large size loans insured, potential changes in Medicare or  Medicaid reimbursement rates, and the geographic concentration of the  program in New York, which make the program vulnerable to regional  economic conditions. Figure 9 shows changes in the  credit subsidy rate from 1992 to 2005. FHA’s process for reviewing applications for mortgage insurance, while  somewhat lengthier and involving more steps compared with those of  private bond insurers, appears to be a reasonable response to the generally  riskier nature of the applicants. Although it represents a relatively small part of HUD’s GI/SRI fund, the  hospital program insures multimillion dollar loans that currently total  nearly $5 billion. Specifically, the agency agreed  to develop appropriate performance measures and implement data  collection procedures to evaluate both program and contract  administration;  with the need to consolidate updated eligibility requirements, policies,  and procedures into an updated handbook, and stated its intention to  have the handbook finalized by the end of 2006;  to develop a formal strategy to geographically diversify its portfolio of  insured hospitals, including such elements as the processes, skills,  technologies, and various resources that will be used to reach  diversification goals; and  to explore the value of explicitly factoring additional information, such  as prepayment penalties and the initial debt-service coverage ratio of  hospitals as they enter the program, during its annual review of cash  flow modeling techniques for the hospital program. Objectives, Scope, and Methodology

Our objectives were to review (1) the design and management of the  program, as compared with private insurance; (2) the nature and  management of the relationship between the Department of Housing and  Urban Development (HUD) and the Department of Health and Human  Services (HHS) in implementing the program; (3) the financial implications  of the program to the General Insurance/Special Risk Insurance (GI/SRI)  fund, including risk posed by program and market trends; and (4) how HUD  estimates the annual credit subsidy for the program, including the factors  and assumptions used.
Why GAO Did This Study

Under its Hospital Mortgage Insurance Program, the Department of Housing and Urban Development's (HUD) Federal Housing Administration (FHA) insures nearly $5 billion in mortgage loans for the renovation or construction of hospitals that would otherwise have difficulty accessing capital. In response to a requirement in the 2005 Consolidated Appropriations Conference Report, GAO examined (1) the design and management of the program, as compared with private insurance, (2) the nature and management of the relationship between HUD and the Department of Health and Human Services (HHS) in implementing the program, (3) the financial implications of the program to the General Insurance/Special Risk Insurance (GI/SRI) fund, including risk posed by program and market trends, and (4) how HUD estimates the annual credit subsidy for the program, including the factors and assumptions used.

What GAO Found

The Hospital Mortgage Insurance Program insures the mortgages of hospitals that are generally riskier than those that can obtain private bond insurance. While FHA's process for reviewing mortgage insurance applications includes more steps and generally takes longer, the agency monitors active loans with many of the same techniques that private bond insurers use. Under a Memorandum of Agreement, FHA and HHS work together in a variety of ways to review mortgage insurance applications and monitor active loans. However, FHA does not collect data to assess program performance against most performance measures specified in the memorandum, some of which are not objective. Further, FHA has not kept its program handbook of policies and procedures for applicants, lenders, and others up-to-date. The hospital program is small compared with other programs in the GI/SRI fund, and the losses from claims have been relatively low. Despite the program's relatively small size, some program and market trends may pose risks. For example, 61 percent of the program's total insured, outstanding loan amount is concentrated in New York, which makes the program vulnerable to state policies and regional economic conditions. While FHA has goals to diversify the hospital insurance portfolio and has made efforts to do so, it does not have a formal strategy to achieve these goals. To estimate the credit subsidy cost, or program costs, over the life of the outstanding loans insured, HUD uses a model that incorporates factors and assumptions about how loans will perform, including estimated claim and recovery rates, which are consistent with federal guidance. However, HUD's model does not explicitly consider some factors, such as the potential impacts of prepayment penalties or restrictions, which according to some economic studies, are important in modeling default risk.