Poorly Performing Nursing Homes: Special Focus Facilities Are Often Improving, but CMS's Program Could Be Strengthened
Published: 2010-03-19T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: CMS established the Special Focus Facility (SFF) Program in 1998 to help address poor nursing home performance. States select a subset of homes as SFFs from a list of the 15 poorest performing homes in each state, but the program is limited to 136 homes nationwide because of resource constraints. CMS guidance directs states to survey SFFs twice as frequently as other homes and to propose more robust enforcement, including termination, for SFFs that fail to improve within about 18 months. GAO was asked to (1) determine the factors states consider in selecting SFFs and how SFFs differed from other nursing homes, (2) evaluate CMS regional office and state adherence to program guidance and the program's impact on homes' performance, and (3) identify other strategies that have been used to improve poorly performing homes. In general, GAO's analysis used CMS data from 2005 through 2009 on SFFs and other homes as well as interviews with officials in 14 states selected based on the number of SFFs in each state and other factors.
section_title: What GAO Found
paragraphs: When selecting SFFs from the candidate list, state officials considered factors other than rank on that list, such as their own knowledge of each candidate's circumstances. For example, state officials might not select a nursing home as an SFF if the home had a new owner they perceived as committed to addressing the home's quality problems. GAO found that states selected SFFs from among the five worst-ranked candidates about 57 percent of the time from January 2006 through February 2009. State discretion in selecting SFFs is key not only because of states' familiarity with each candidate's circumstances but because the list has limitations. Some officials from the 14 states that GAO interviewed noted that candidate lists included current SFFs, resulting in an insufficient number of homes from which to select new SFFs. The characteristics of SFFs differed from those of other nursing homes in terms of organization type and the number of beds and residents. For example, SFFs were more likely than other homes to be chain affiliated and for-profit and to have more beds and more total residents. GAO found that some states did not consistently follow CMS's basic SFF Program requirements. When CMS began monitoring SFF survey frequency in fiscal year 2008, 8 states did not conduct twice as many surveys for SFFs as required--a significant improvement compared to 26 states in the previous fiscal year. GAO also found that CMS's enforcement guidance is vague and results in inconsistent interpretations. For example, one SFF was assessed no civil money penalties (CMP) even though it was cited for consecutive deficiencies that could have resulted in fines of up to $825 per day of noncompliance while a home with a similar compliance history was assessed CMPs that increased from $300 to $600 per day of noncompliance. Most SFFs did eventually graduate, but not all met CMS's graduation criteria, and some SFFs remained in the program well beyond CMS's expected 18-month time frame for improvement. For example, 17 percent of active SFFs as of February 2009 had been in the program for 25 months or longer--some since 2005. However, most graduates showed significant improvement while in the program but some failed to sustain that improved performance after graduation. CMS and states have used a variety of additional strategies to help address care problems identified at SFFs and other nursing homes. For example, a few CMS regional offices have negotiated agreements requiring SFFs to take specific actions, such as hiring quality improvement consultants. In addition, each year one SFF per state can volunteer to work with an organization under contract with CMS to deal more directly with the root causes of poor quality. Some states have adopted their own quality improvement strategies that offer assistance to both poorly performing and other homes, including on-site technical assistance from nurse consultants or monthly training opportunities for nursing home staff on the most frequently cited care problems. Further, one state charges homes for the cost of additional surveys that it conducts under a program that resembles the SFF Program.

section_title: Letter
paragraphs: The nation’s 1.4 million nursing home residents are a highly vulnerable  population of elderly and disabled individuals who rely on nursing homes  to provide high-quality care. The Centers for Medicare & Medicaid  Services (CMS) contracts with state survey agencies to conduct  inspections, known as standard surveys, and complaint investigations to  determine whether nursing homes are complying with federal quality  standards. Nursing homes must meet those standards to participate in  Medicare and Medicaid. Our prior reports have found that some nursing  homes are chronically noncompliant; that is, they have been cited  repeatedly by state survey agencies for serious deficiencies such as  residents having preventable pressure sores that harmed them or put them  at risk of death or serious injury. In 1998, CMS developed the Special  Focus Facility (SFF) Program to monitor two poorly performing nursing  homes per state, as one way to address issues of chronic noncompliance  and improve the performance of these nursing homes. CMS’s program  guidance directs states to conduct more extensive oversight of SFFs and  the agency’s regional offices to monitor state implementation of the SFF  Program. CMS expanded the program’s size in 2005 to 136 SFFs and up to  6 per state—less than 1 percent of the nation’s roughly 16,000 nursing  homes—and since then has issued additional guidance to states regarding  the operation of the SFF Program. The agency has not further expanded  the SFF Program, with officials citing resource constraints.
You expressed interest in CMS’s efforts to influence the performance of  poorly performing nursing homes. Our August 2009 report estimated the  number and characteristics of homes in the United States that could be  considered the most poorly performing. We found that (1) about 580   (4 percent) of the nation’s nursing homes could be considered the most  poorly performing and (2) the homes selected as SFFs are not necessarily  the most poorly performing homes in the nation but rather are among the  poorest performers in each state. To improve the targeting of scarce  resources, we recommended that the Administrator of CMS consider an  alternative approach for allocating the 136 SFFs across states by placing  more emphasis on the relative performance of homes nationally rather  than on a state-by-state basis, which could result in some states having  only one or not any SFFs and other states having more than they are  currently allocated. In response, CMS noted that it would evaluate a hybrid  approach that would assign some SFFs using homes’ performance in each  state and other SFFs on their relative national ranking.
In this report, we examined the operation of the SFF Program.  Specifically, we (1) determined the factors states consider in selecting  homes for the SFF Program and how such homes differ from other nursing  homes; (2) evaluated the extent to which the CMS regional offices and  states followed CMS guidance in implementing the SFF Program and the  program’s impact on homes’ performance; and (3) identified other  strategies that have been employed to improve the performance of poorly  performing homes, including SFFs. You also asked us to provide  information on the financial performance of SFFs, which can be found in  appendix I.
To determine the factors that states consider in selecting SFFs and how  such homes differ from other nursing homes, we analyzed (1) the scores  for all nursing homes as determined by CMS in January 2009 using a  methodology it employs for the SFF Program as well as the rank for all  homes added to the program from January 2006 through February 2009  using that same methodology, (2) deficiencies and revisit dates associated  with standard surveys conducted in 2008 and deficiencies from complaint  investigations conducted in the year prior to the 2008 standard survey  from CMS’s On-Line Survey, Certification, and Reporting system (OSCAR),  and (3) other CMS data, which describe nursing home characteristics as of  December 2008 and January 2009. For the data analyses throughout this  report on SFFs, we used a CMS list of homes that were placed in the SFF  Program from January 2005 through February 2009. We limited our  analysis to the period 2005 through 2009 because in late 2004 CMS  announced significant changes to strengthen the SFF Program, which  became effective in 2005.
To determine the extent to which its regional offices and states followed  CMS’s SFF Program guidance and the program’s impact on homes’  performance, we analyzed CMS data on (1) survey dates and deficiencies  as reported in OSCAR; (2) sanctions for SFFs, SFF candidates, and all  other nursing homes using CMS’s Automated Survey Processing  Environment Enforcement Manager (AEM) for calendar years 2006  through 2008; (3) dates SFFs were placed in and left the program through  termination or graduation; (4) homes that terminated from Medicare and  Medicaid as reported in the Provider of Service file dated December 2008;  and (5) scores of nursing homes from December 2005 through January  2009, which CMS determined using its SFF methodology. In addition, we  used OSCAR deficiency data to identify SFFs that had serious deficiencies  on consecutive standard surveys and reviewed enforcement reports that  summarize data from AEM which we obtained for these homes from  regional offices.
To determine what other strategies have been employed to improve the  quality of care provided by poorly performing nursing homes, including  SFFs, we reviewed (1) Systems Improvement Agreements (SIA) between  CMS and some SFFs, which require the homes to take specific steps to  address quality of care problems; (2) quality of care Corporate Integrity  Agreements (CIA) between the Department of Health and Human Services  (HHS) Office of Inspector General (OIG) and nursing home corporations,  which are intended to bring about quality improvements across the  corporations’ homes; and (3) the Nursing Homes in Need (NHIN) initiative,  an element of CMS’s August 1, 2008, through July 31, 2011, contract with  Quality Improvement Organizations (QIO) that requires QIOs to work with  a limited number of homes, generally SFFs, to improve the care delivered  to residents.
Our three objectives were informed by interviewing officials from CMS’s  Survey and Certification Group, which we refer to as CMS’s central office,  all 10 of its regional offices, and 14 state survey agencies. CMS’s central  office is responsible for the SFF Program and for oversight of the 10 CMS  regional offices, which in turn monitor states’ nursing home oversight  activities and their implementation of the SFF Program. In our interviews,  we asked regional offices and states about their implementation of the  SFF Program and other topics, such as whether states offer additional  activities that may improve the performance of SFFs and other nursing  homes. We also interviewed officials from (1) CMS’s Office of Clinical  Standards and Quality, the office responsible for oversight of the QIO  contract; (2) the HHS OIG; and (3) an official with an independent  monitoring association that assists HHS OIG in the monitoring of nursing  home quality of care CIAs. In addition, we reviewed our prior reports and  CMS’s guidance to states on nursing home oversight activities and the SFF  Program and analyzed information available at CMS’s Providing Data  Quickly Web site, which produces a variety of reports using data collected  by CMS to oversee providers of Medicare and Medicaid services. For a  more detailed discussion of our scope and methodology, see appendix II.  To ensure the reliability of the various data we analyzed, we interviewed  CMS officials, reviewed CMS documentation, conducted electronic testing  to identify obvious errors, and traced a selection of records to another  CMS reporting system. Based on these activities, we determined that CMS  data were sufficiently reliable for our analysis.
We conducted this performance audit from December 2008 through March  2010 in accordance with generally accepted government auditing  standards. Those standards require that we plan and perform the audit to  obtain sufficient, appropriate evidence to provide a reasonable basis for  our findings and conclusions based on our audit objectives. We believe  that the evidence obtained provides a reasonable basis for our findings  and conclusions based on our audit objectives.
subsections: section_title: Background
paragraphs: Titles XVIII and XIX of the Social Security Act establish minimum  standards that all nursing homes must meet to participate in the Medicare  and Medicaid programs, respectively. Provisions added by the Omnibus  Budget Reconciliation Act of 1987 focused the standards on the quality of  care actually provided by a home. To encourage improvement at nursing  homes that demonstrate chronic noncompliance with these quality of care  standards, CMS initiated the SFF Program in 1998 and subsequently  expanded and strengthened the program in December 2004.
subsections: section_title: Ensuring Compliance with Federal Quality of Care Standards
paragraphs: To assess whether nursing homes meet federal quality of care standards,  state survey agencies conduct standard surveys, which occur on average  once a year, and complaint investigations as needed. A standard survey  involves a comprehensive assessment of federal quality standards.  In  contrast, complaint investigations generally focus on a specific allegation  regarding resident care or safety made by a resident, family member, or  nursing home staff member. Deficiencies identified during either standard  surveys or complaint investigations are classified in 1 of 12 categories  labeled A through L according to their scope (i.e., the number of residents  potentially or actually affected) and severity (i.e., the potential for or  occurrence of harm to residents). (See table 1.) An A-level deficiency is  the least serious and is isolated in scope, while an L-level deficiency is the  most serious and is widespread throughout the nursing home. Nursing  homes with deficiencies at the A, B, or C levels are considered to be in  substantial compliance with quality standards; homes with D-level or  higher deficiencies are considered noncompliant. For most deficiencies, a  home is required to prepare a plan of correction, and, depending on the  severity of the deficiency, surveyors may conduct a revisit to ensure that  the nursing home has implemented its plan and corrected the deficiency.
section_title: Federal Enforcement
paragraphs: Nursing homes that fail to meet federal quality standards may be subject to  federal enforcement actions known as sanctions. Sanctions can affect a  home’s revenues and therefore provide financial incentives to return to  and maintain compliance. Enforcement of nursing home quality of care  standards is a shared federal-state responsibility. In general, sanctions are  (1) initially proposed by the state based on a cited deficiency, (2) reviewed  and imposed by CMS regional offices, and (3) implemented—that is, put  into effect—by the same CMS regional office. Homes may have an  opportunity to correct deficiencies after the imposition of a sanction,  which can result in the sanction being rescinded, that is, not implemented.  At state and regional office discretion, sanctions may be imposed  immediately without giving homes an opportunity to correct deficiencies  after a required notice period. Sanctions are generally reserved for  serious deficiencies—those at the G through L levels—that constitute  actual harm and immediate jeopardy to residents.
Sanctions include fines known as civil money penalties (CMP), denial of  payment for new Medicare or Medicaid admissions (DPNA), and  termination from the Medicare and Medicaid programs. Overall, two  sanctions—CMPs and DPNAs—accounted for about 75 percent of federal  sanctions from 2005 through 2008, while terminations were less than   1 percent. By statute, DPNA and termination are mandatory sanctions in  certain circumstances, but discretionary DPNA and termination may also  be imposed.
CMP. Unlike most other sanctions, CMPs require no notice period; in  addition, they can be applied retroactively to the first date of  noncompliance. CMPs may be either per day or per instance. CMS  regulations specify a per day CMP range from $50 to $10,000 for each day a  home is noncompliant—from $50 to $3,000 for nonimmediate jeopardy  and $3,050 to $10,000 for immediate jeopardy. Per instance CMPs range  from $1,000 to $10,000 per episode of noncompliance. In 2007, CMS issued  guidance to states and regional offices to encourage consistency in CMP  amounts.
DPNA. A DPNA denies a home payments for new admissions until  deficiencies are corrected. A DPNA is required by statute within 3 months  of the end of a survey if, for example, a home fails to correct deficiencies  and return to compliance. In contrast, discretionary DNPAs can go into  effect much sooner—after a 15-day notice period, which is shortened to   2 days in the case of immediate jeopardy. Unlike CMPs, DPNAs cannot  be imposed retroactively.
Termination. CMS can terminate a nursing home by implementing either  a mandatory or a discretionary termination. Mandatory termination is  required by regulation if within 23 days of the end of a survey a home fails  to correct immediate jeopardy deficiencies or within 6 months if it fails to  correct nonimmediate jeopardy deficiencies. CMS may also impose  discretionary terminations in situations other than those specified above,  which require the same notice period applicable to discretionary DPNAs.
In addition, nursing homes can and do terminate voluntarily, which may be  related to the fact that the home is at risk of involuntary termination.
section_title: The SFF Program
paragraphs: The objective of the SFF Program is to decrease the number of  persistently poorly performing nursing homes by focusing more attention  on a small number of nursing homes in each state with a record of poor  quality performance. Since the program’s inception, CMS has changed the  SFF Program’s scope and methodology to enhance the agency’s goal of  improving nursing home performance.
subsections: section_title: CMS’s SFF Methodology and Selection of SFFs
paragraphs: CMS uses its SFF methodology to identify a list of the 15 worst performing  nursing homes in each state. The SFF methodology assigns points to  deficiencies on standard surveys and complaint investigations, and to  revisits associated with deficiencies cited on standard surveys.19, 20 More  points are assigned to deficiencies that are higher in scope and severity,  and additional points are assigned to deficiencies classified as substandard  quality of care (SQC). (See table 2.) For every nursing home, CMS sums  the points associated with the deficiencies (including SQC) and the  revisits to create a cycle score for each of the last three cycles. CMS then  creates the total score by weighting the more recent cycle scores more  heavily. Nursing homes with the highest number of points are the worst  performing homes.
To avoid potential double-counting, deficiencies that appear on complaint surveys  conducted within 15 days of a standard survey (either prior to or after the standard survey)  are counted only once. If the scope or severity differs on the two surveys, the highest scope  and severity combination is used.
From 1999 to 2004, the SFF methodology assigned a different number of points to  deficiencies using only about 1 year of deficiency data. In 2005, CMS altered the number of  points assigned to deficiencies and based a nursing home’s numeric score on about 3 years  of deficiency data, weighted equally. In 2007, CMS removed fire safety deficiencies from  the SFF methodology, to provide an increased focus on quality of care deficiencies.
CMS refers to the resulting list of the 15-worst performing homes in each  state as the SFF candidate list. The list is generally distributed quarterly to  CMS’s regional offices, which then distribute it to states as necessary.  Except for Alaska, each state and the District of Columbia have between  one and six SFFs at any time, depending on the total number of nursing  homes in the state. (See fig. 1.) If there is an opening in the state’s  program because an SFF has graduated from the program or been  terminated from Medicare and Medicaid, the state selects a new SFF from  its candidate list. CMS allows states discretion in determining which of the  candidates to choose for the program, and the CMS regional office  concurs with the states’ selections.
In addition to specifying that states select SFFs from a list of candidate  nursing homes, figure 2 shows that CMS’s guidance to states on the  operation of the SFF Program includes two other key requirements:    States are instructed to increase scrutiny of SFFs in the following ways:    Survey frequency. States provide additional scrutiny of SFFs by  conducting two surveys per fiscal year for each SFF, which is twice as  frequent as at other nursing homes. CMS measures each state’s  compliance with this requirement annually through state performance  reviews. The state performance reviews emphasize three aspects of  the survey program: survey timeliness, survey quality, and the  enforcement and remedy of problems found during surveys. If a  regional office determines that a state has not conducted two surveys  for every SFF allotted to the state per fiscal year, the state must  develop a corrective action plan.
Enforcement. States are required to impose sanctions that increase in  severity and are more immediate when SFFs do not improve. For  example, a state should propose a CMP or a DPNA with the minimum  notice period.
After three standard surveys (approximately 18 months) in the SFF  Program, one of the following three outcomes are expected:    Graduation. States determine if the SFF is eligible to “graduate” from  the program by meeting CMS’s criteria for improved performance: two  consecutive standard surveys and any intervening complaint  investigations must have no deficiencies at the F level or higher. In  addition, an SFF cannot have a deficiency higher than the F level on  the fire safety portion of its most recent standard survey.
Retention. States keep the SFF in the program if it does not meet the  graduation criteria but is showing improvement.
Termination. States recommend that the SFF be terminated from  participation in Medicare and Medicaid if it fails to make significant  progress.
CMS made several key changes to the SFF Program in 2007 and 2008 to  increase both provider and public awareness of the program. In 2007, CMS  began requiring states to notify the governing bodies, owners, operators,  and administrators that a facility had been designated an SFF. CMS also  issued a press release in 2007 listing those SFFs that had failed to  significantly improve their care; previously, the identity of SFFs was not  provided to the public. In an effort to increase transparency, CMS added  the identity of all SFFs to its Nursing Home Compare Web site during 2008.  That same year, information on the SFF methodology and on SFFs, such  as those that failed to significantly improve their care after about one  survey, was added to CMS’s Web site.
In 2008, CMS also added ratings from its Five-Star Quality Rating System  to its Nursing Home Compare Web site to further assist consumers in  judging nursing home quality. Every home in the United States is rated  from one star (much below average) to five stars (much above average).
The Five-Star System provides an overall quality rating based on individual  ratings for three separate components: (1) health inspections— deficiencies cited on standard surveys and any associated revisits and  complaint investigations; (2) nursing home staffing levels; and (3) quality  of care measures, which are computed using data submitted to CMS by  nursing homes on their residents’ health, physical functioning, mental  status, and general well-being. SFFs can have high ratings on any one of  the three components, but their overall rating is capped at three stars.  However, as of February 2009, no SFFs had a five star rating in the health  inspection component of the Five-Star System.
section_title: States Considered Factors Other Than Rank When Selecting SFFs, Which Were More Likely to Be Chain Affiliated and For-Profit Than Other Nursing Homes
paragraphs: When selecting SFFs from the candidate list, state officials considered  factors other than rank, such as their own knowledge of each candidate’s  circumstances. Such discretion is key not only because of states’  familiarity with each candidate’s circumstances but also because the list  has limitations. The characteristics of SFFs differed from those of other  nursing homes in terms of the homes’ organization type and the number of  beds and residents. For example, SFFs were more likely than other homes  to be chain affiliated and for-profit and to have more beds and more total  residents.
subsections: section_title: States Exercise Discretion When Selecting SFFs by Considering Factors Such as Surveyor Workload or Nursing Home Ownership
paragraphs: Although rank and score play an important role in the selection of SFFs,  the states we interviewed consider additional factors when making their  selections, including the candidate’s compliance and enforcement history,  state surveyor workload, nursing home ownership, and financial concerns.  We found that a majority of states selected SFFs from among their five  worst performers. While the first-ranked candidate (the worst performing  home) was selected about 17 percent of the time from January 2006  through February 2009, about 57 percent of SFFs selected during that  period were among the five worst-ranked candidates.
Compliance and enforcement history. Most states we interviewed  specified that they review the details of a nursing home’s overall  compliance with federal quality standards. For example, a state might  review the scope and severity level, type, and repetitiveness of deficiencies  for candidates it considers. When reviewing a nursing home’s history, a  few states indicated that they are likely to select candidates with more  recent poor performance, which is also reflected in the SFF score  beginning in 2008. In addition, some states we interviewed review and take  into consideration a nursing home’s enforcement history, such as any  CMPs or DPNAs imposed for noncompliance with federal standards.
State surveyor workload. Some states we interviewed avoid  concentrating SFFs in the same district in their state due to the additional  workload associated with the SFF Program. For example, California tries  to distribute SFFs geographically so that no state district office has more  than one SFF at a time. To help accomplish this, the California state  survey agency meets with the district offices to review the candidate list.
Nursing home ownership. Some states we interviewed consider the  nursing home’s ownership, including any recent changes or knowledge of  other homes owned by the same chain. State officials explained that a  recent change of ownership could influence their SFF selection. For  example, if state officials are aware of a history of problems with the new  owner, they may select the home for the SFF Program in order to  scrutinize it more closely; on the other hand, they may not select a home if  they perceive that the new owner has a good reputation, which would give  the new owner adequate time to correct quality problems.
Financial concerns. Officials from three of the states we interviewed said  they might consider any known financial concerns when making an SFF  selection. In addition, regional offices told us that they may learn about  nursing homes’ financial difficulties on an ad-hoc basis, such as through  resident and staff complaints about inadequate services or the home’s  inability to meet its payroll or through a home’s request to delay or reduce  payments from CMPs due to financial hardship.
section_title: Limitations in the Candidate List Highlight the Necessity for States’ Discretion
paragraphs: The majority of state officials we interviewed told us that CMS’s candidate  list accurately identifies poorly performing nursing homes in each state,  such as those homes that habitually cycle in and out of compliance with  federal nursing home standards; however, we found that certain  limitations in the list highlight the importance of states’ discretion in  selecting SFFs. First, because of lag times between when surveys are  conducted and when the results are reflected on the SFF candidate list,  some states and regions found that the candidate list may not reflect a  home’s most recent survey. Consequently, some candidates could appear  to have a better or worse score than reflected in the most recent survey, or  homes may be included or excluded inappropriately from the list. Second,  some states told us that the candidate list does not provide them with a  sufficient number of nursing homes from which to select new SFFs.  Specifically, the list includes current SFFs if they are still ranked among  the worst 15 homes in the state, which narrows the state’s selection  possibilities. Officials from Indiana, Illinois, and California, which are  allocated 4, 5, and 6 SFFs, respectively, explained that having existing  SFFs on their list left them with fewer than 15 nursing homes to consider  for the program.
Moreover, we found additional limitations to the list, including  considerable variation in SFF candidate scores, that further highlight the  importance of states’ discretion. As noted in our August 2009 report, the  candidate list identifies poorly performing nursing homes in each state but  does not necessarily identify the most poorly performing nursing homes in  the nation. This limitation becomes apparent when comparing SFF  scores for nursing homes on the candidate list both across and within  states. As a result of the variation across states, some candidates may have  the worst score in their state and yet not score among the worst homes in  the nation. In addition, wide variation in candidates’ scores is also found  within individual states. For example, on the January 2009 candidate list,  the score of the worst home in Tennessee was about 1,512. However, all  SFF candidates in each of 22 states had lower scores than the 15th worst  candidate in Tennessee, which had a score of about 253. (See fig. 3.)
section_title: SFFs Were More Likely to Be Chain Affiliated and For-Profit Than Other Nursing Homes
paragraphs: SFFs differed from other nursing homes not only in terms of their  compliance history but also in terms of other key characteristics. We  compared deficiencies from the 59 SFFs that (1) were added to the SFF  Program in 2008 and (2) had a standard survey that occurred prior to their  entry into the program to deficiencies from other homes that had a  standard survey conducted in 2008. We included in this analysis  deficiencies from complaint investigations that occurred in the year prior  to the 2008 standard survey and revisits associated with the standard  survey. Consistent with the SFF methodology, we found that, on average,  these 59 SFFs had both a greater number of D- through L-level  deficiencies, including more at each scope and severity level, and a greater  number of deficiencies cited on standard surveys and complaint  investigations than other nursing homes. For example, SFFs had, on  average, 5.5 times more actual harm deficiencies and 19 times more  immediate jeopardy deficiencies. In addition, these SFFs had, on average,  a greater number of revisits. (See table 3.)
Additional key characteristics of SFFs also differentiated them from other  nursing homes. Comparing the characteristics of 133 homes in the SFF  Program as of February 2009 to those of other homes, we found that they  differed in terms of type of organization and participation in Medicare and  Medicaid, the number of beds and residents, nurse staffing levels, and  ratings on CMS’s Five-Star System. (See app. III.)
Type of organization and participation in Medicare and Medicaid. A  higher percentage of SFFs were part of a chain organization, for-profit  organization, or both. For example, about 55 percent of SFFs were for- profit and chain affiliated, compared to about 42 percent of other nursing  homes. Furthermore, fewer SFFs participated in Medicaid only compared  to other nursing homes—about 2 percent and about 5 percent,  respectively.
Beds and residents. On average, SFFs had more beds and total residents,  but a lower occupancy rate, than other nursing homes. Specifically, SFFs  averaged approximately 131 beds and 104 residents—about a 79 percent  occupancy rate; other nursing homes had approximately 106 beds and   90 residents—about an 85 percent occupancy rate. SFFs also had a greater  share of Medicaid patients on average than other nursing homes—  71 percent compared to 60 percent.
Nurse staffing. SFFs had fewer registered nurse hours per resident-day  as a share of total hours per resident-day—about 9.0 percent compared to  about 9.9 percent for other nursing homes.
CMS’s Five-Star System. SFFs were much more likely than other  nursing homes to be ranked lower on the overall quality rating and health  inspection component rating of the Five-Star System. Specifically, about  74 percent of SFFs received one star on the overall quality rating, and  about 93 percent received one star on the health inspection component of  the rating. In comparison, about 22 percent of other nursing homes  received one star on the overall quality rating, and about 19 percent  received one star on the health inspection component.
section_title: State and Regional Office Adherence to SFF Program Guidance Was Uneven, but Most SFFs Improved Their Performance While in the Program
paragraphs: We found that some states did not consistently follow CMS’s basic SFF  Program requirements, such as surveying SFFs twice a year. We also  found that CMS’s enforcement guidance is vague and results in  inconsistent interpretations. Most SFFs did eventually graduate, not all  met CMS’s graduation criteria, and some remained in the program well  beyond CMS’s 18-month time frame for improvement. However, most  SFFs improved their performance while in the program, although many  graduates failed to sustain their performance.
subsections: section_title: Some States Did Not Meet CMS’s Requirement to Survey SFFs Twice a Year
paragraphs: Some states did not meet CMS’s requirement to conduct standard surveys  of SFFs twice a year. While states improved their compliance with this  requirement in fiscal year 2008—8 states did not conduct two surveys for  SFFs, compared to 26 states in the previous fiscal year—some SFFs were  still not receiving increased scrutiny through additional standard surveys,  a fundamental component of the program. In addition, 18 states had at  least one SFF that had more than 10 months between surveys from  calendar year 2005 through 2008. Further, between January 2005 and  February 2009, 15 states did not survey at least one of their SFFs within  the first 7 months that the home was in the program.
A CMS official told us the agency was aware that states were not always  conducting two surveys per fiscal year for SFFs. In fiscal year 2007, CMS  began measuring states’ adherence to this requirement as part of its annual  state performance reviews. CMS required seven states that did not meet  this standard in fiscal year 2008 to complete corrective action plans.
section_title: CMS’s Enforcement Guidance Is Vague and Results in Inconsistent Interpretations
paragraphs: CMS’s SFF Program guidance on enforcement, under which states and  regions must impose more robust enforcement on SFFs that do not  demonstrate significant improvement, is vague and open to  interpretations. According to CMS, “more robust” is intended to mean that  homes with continued noncompliance should receive sanctions that both  increase in severity and are immediate; that is, homes should not be  provided with an opportunity to correct deficiencies before the sanction  goes into effect. CMS guidance also allows states discretion in  determining significant improvement, and therefore which homes receive  more robust enforcement and which do not. In our interviews with CMS’s  central office, an official stated that CMS’s SFF enforcement guidance  could be more specific and noted that CMS plans to release descriptive  guidance explaining exactly how states and regions should apply more  robust enforcement. In addition, we found that officials in the regional  offices and states we interviewed had inconsistent interpretations of the  guidance. For example, some officials told us that when determining  sanctions, they treat SFFs no differently than they would any poorly  performing nursing home. For other officials, there was little consensus on  the most appropriate sanctions for SFFs—CMPs, or other sanctions, such  as discretionary DPNAs or discretionary termination.
Despite the existence of SFF Program enforcement guidance, we found  that SFFs were not necessarily more likely to be subject to CMPs and  DPNAs—the most frequently cited sanctions—than SFF candidates, which  are also poorly performing nursing homes. For example, about 28 percent  of SFFs had at least one CMP implemented in 2008, compared to about   34 percent of candidates in the same year. In addition, the rates of  implemented CMPs and DPNAs decreased for SFFs relative to candidates  from 2006 to 2008, while the rates of other nursing homes remained low.  (See fig. 4.) We found similar trends in the average CMP values; for  example, SFF candidates received the highest average per day CMPs in  2008—approximately $4,262 per day—compared to approximately $3,969  for SFFs and $1,990 for other nursing homes. However, it is unclear if  improvement in SFFs’ performance could explain the higher rates and  average values we observed for SFF candidates compared to SFFs.
Our review of the detailed enforcement histories of six SFFs with  consecutive noncompliance cycles at the G level or higher found that the  sanctions imposed by regions and states on the homes ranged in terms of  their immediacy and severity. For example, in three out of seven  noncompliance cycles with G-level or higher deficiencies, one SFF was  allowed an opportunity to correct its deficiencies before sanctions could  go into effect. Still, this same SFF had sanctions of increasing severity  imposed with each successive recurrence of noncompliance at the   G level—the state and regional office increased CMPs from $300 per day of  noncompliance to $600 per day of noncompliance. Conversely, anot SFF was assessed no CMPs, even though it had a similar history of  consecutive noncompliance cycles that could have resulted in CMPs  ranging from $300 to $825 per day of noncompliance, suggesting that  CMS’s monitoring of enforcement is insufficient. However, both of these  SFFs had immediate sanctions imposed; that is, the state and regional  offices imposed discretionary rather than mandatory DPNAs and  terminations. Discretionary DPNAs and terminations provide nursing  homes with a shorter opportunity to correct deficiencies before the  sanction goes into effect compared to mandatory DPNAs and  terminations. Despite this shorter correction period, both of these SFFs  were typically able to correct their deficiencies and avoid these sanctions.
section_title: Most SFFs Did Eventually Graduate, but States and me CMS Regions Kept So SFFs in the Program beyond the Program’s Expecte Frame
paragraphs: Although most SFFs eventually graduated, CMS regions and states often  chose to keep SFFs in the program beyond the 18-month time frame. Mor homes have graduated from the SFF Program than were terminated, but  some graduates did not meet CMS’s criteria. States we interviewed  indicated that some SFFs were able to improve their performance while  others lingered in the program for various reasons, including not  improving enough to meet the graduation criteria nor performing poorly  enough to terminate from Medicare and Medicaid. As a result, other  nursing homes whose performance may have been worse could not be  selected for the program.
Of the 355 nursing homes placed in the SFF Program from Janua through February 2009, 181 graduated (51 percent) and 41 were  terminated (12 percent). CMS terminated 21 SFFs involuntarily, and 20 left the program voluntarily. We found that nursing homes sharing the  same physical location as 13 of the 41 SFFs that terminated have since  been certified to participate in Medicare or Medicaid again. However, at  least 24 of the 181 SFF graduates did not actually meet elements  of CMS’s  graduation criteria—two consecutive standard surveys and any  intervening complaint investigations with no deficiencies at the F level or higher; 15 of these 24 SFFs should not have graduated because they had  deficiencies at the F level or higher. For example, a Florida SFF had four  deficiencies at the F level on the two standard surveys that occurred prior  to its graduation.
We found that CMS’s regions and states often chose to keep SFFs in the  program instead of terminating them, even though CMS’s SFF Program  guidance establishes the expectation that SFFs will be terminated from  Medicare and Medicaid if they fail to make significant progress after being  in the program for 18 months. The fact that some homes did not gradu ate  or terminate after being in the program for 18 months prevented other nursing homes whose perf selected for the program.  ormance may have been worse from being    SFFs added to the program from 2005 through 2007. Of the 254  homes that became SFFs during this time frame, 102 (40 p the program for 25 months or more as of February 2009.
Active SFFs. Of the 133 active SFFs as of February 2009, 23 (17 per cent) were in the program f program or 25 months or more, and 11 had been in the   since 2005.
However, the length of time that SFFs spent in the program before  graduating or terminating has decreased since 2005. (See fig. 5.) For  example, as of the end of February 2009, SFFs added to the program in  2005 graduated on average after 28 months, compared to an average of 20  and 13 months  for SFFs that were added to the program in 2006 and 2007,  respectively.
Some CMS regions and states we interviewed offered several reasons that  might help to explain why they chose to keep some SFFs in the program  beyond 18 months. First, nursing homes may not improve enough to meet  CMS’s criteria for graduation, nor be performing poorly enough to  terminate from Medicare and Medicaid. Second, closing a nursing home  requires the state to transfer residents to another nursing home, and some  residents with special care needs—such as children or those that have  behavioral health issues—may be difficult to relocate. Third, if the SFF  recently had a change in ownership, it may have the potential to improve  and therefore should not be terminated: new management or capital  investment in a poorly performing nursing home may bring about needed  changes in quality. For example, officials in CMS’s New York regional  office described a case in which all three reasons influenced their decision  to allow a nursing home to remain in the program for over 45 months.  The home    had initially demonstrated improvement until two consecutive surveys  resulted in deficiencies at the F level or higher,   had a behavioral health population that was large, making it difficult to  place them in other homes, and    experienced two changes of ownership while in the SFF Program. The  most recent owners invested millions of dollars to improve the physical  environment at the facility and hired a nurse consultant.
Regional office officials indicated that a more recent survey had shown  improvement with no deficiencies higher than the D level, which they  attributed to the investments made by the most recent owner.
Conversely, some SFFs were able to improve enough to graduate in less  than 19 months. Our analysis shows that between 2005 and February 2009,  32 states graduated at least one facility in less than 19 months. According  to some state and regional office officials we interviewed, such SFFs  showed improvement after being selected for the program because of  factors such as the home’s ability to establish stable leadership, a  willingness to adopt new improvements, or the hiring of outside  consultants. Some state and regional office officials indicated that homes  might be able to graduate earlier if the graduation criteria were less  stringent. For example, one regional office and one state did not think that  F-level deficiencies in kitchen sanitation should prevent homes from  graduating. Two regions suggested that a more appropriate graduation  criterion would be to allow homes with F-level deficiencies to graduate as  long as the deficiencies were not in SQC areas, rather than the current  criterion of no F-level or higher deficiencies. We found that 27 percent of  the 328 SFFs (90 homes) had at least one instance where one or more F- level deficiency prevented them from graduating and over half of those  SFFs (54 homes) had F-level deficiencies in kitchen sanitation.
Beginning in 2007, CMS introduced two program changes that may  contribute to a decline in the amount of time that SFFs remain in the  program. For example, CMS began identifying SFFs on its Nursing Home  Compare Web site each month. The majority of CMS regional offices and  states we interviewed believed CMS’s identification of SFFs had a positive  impact on the SFF Program because of the media and public attention.  Florida indicated that there had been little concern by providers about  being in the SFF Program until SFFs were publicly identified. An  additional factor may also have influenced the amount of time SFFs  remain in the program. As noted earlier, CMS began requiring states to  formally notify homes in 2007 that they had been placed in the program,  including each home’s governing body, owner, operator, and  administrator. Michigan has applied a more aggressive notification policy  since 2005, sending a notification letter to each SFF candidate explaining  that they are at risk of being selected as an SFF if they fail to address  performance problems. A copy of the letter is also sent to the owner and  operator of the nursing home the first time the home appears on CMS’s  candidate list. The Michigan official we interviewed believed that this  notification policy has motivated the state’s SFF candidates to improve. In  December 2008, the state of Missouri also began notifying SFF candidates  that they were at risk of being selected as SFFs.
section_title: Most SFFs Improved, but Some Graduates Failed to Sustain Their Performance
paragraphs: While in the program, most SFFs improved their performance, but some  failed to sustain their improved performance after graduation. The scores  of SFF graduates showed a statistically significant improvement when  compared to their scores before entering the program, as did the scores of  active SFFs, but to a lesser degree than graduates. Officials from some  CMS regions and states told us that the SFF Program was helping nursing  homes to improve their performance, but others were unsure of the  program’s effectiveness. For example, officials from New York, which  graduated 8 of 13 SFFs from January 2005 to February 2009, told us that  more frequent surveys and the state’s presence at the facilities had a  positive effect on the behavior of SFFs. Conversely, officials in Alabama,  which graduated 2 of 5 SFFs in the same period, believed that it was  difficult to say whether the program had improved nursing home  performance. Alabama officials noted that while the program had  motivated a few of the states’ SFFs to take a closer look at their  operations, SFFs did not always understand the consequences that might  result for failing to improve their performance.
Despite the improvement in scores, we also found that 75 (50 percent) of  the 149 graduates from calendar years 2005 through 2008 that had a  standard or complaint survey after graduation received at least one F-level  or greater deficiency after graduation, which would have prevented their  graduation had they still been SFFs. For example, one graduate had one  F-level deficiency, two G-level deficiencies, and two J-level deficiencies on  its first standard survey after graduating. A smaller subset of these 149  SFF graduates—22 homes (15 percent)—received at least one J- through  L-level deficiency (immediate jeopardy) on either a standard or a  complaint survey after they graduated.
section_title: Other Quality Improvement Strategies to Assist SFFs Have Merit, and Some Could Inform CMS Efforts
paragraphs: While the core of the SFF Program is more frequent surveys and stringent  enforcement, CMS and others have adopted a variety of other quality  improvement strategies to help address care problems identified at SFFs  and other nursing homes; both the HHS OIG and state strategies hold  potential lessons that could help inform CMS’s efforts. Through Systems  Improvement Agreements (SIA) and the Nursing Homes in Need (NHIN)  initiative, CMS has attempted to deal more directly with the root causes of  poor quality in a limited number of SFFs. In contrast to CMS’s focus on  individual facilities, the HHS OIG has identified corporations that own  poorly performing homes and negotiated Corporate Integrity Agreements  (CIA) to bring about quality improvements across the homes in the  corporation. States have adopted quality improvement strategies that  sometimes resemble CMS’s efforts but that may also be offered to homes  that have not exhibited performance problems.
subsections: section_title: SIAs and the NHIN Initiative Hold Promise, but the Use of Such Interventions Has Been Limited
paragraphs: While both SIAs and the NHIN initiative have the potential to help SFFs  improve the quality of care provided to residents, their use has been  limited. More than 2 years after the first SIA was implemented, CMS’s  central office has not yet collected and shared information about this  intervention with its 10 regional offices. Moreover, the measures used by  CMS to monitor the impact of the NHIN initiative are inconsistent with  those used to measure whether an SFF is improving.
Systems Improvement Agreements with SFFs. SIAs are agreements  between CMS and SFFs that identify concrete actions that the homes are  required to take, generally within a specific time, in order to avoid  termination and to improve and maintain quality. CMS did not develop the  first SIA with an SFF until 2007—9 years after the creation of the SFF  Program. Overall, four CMS regional offices have negotiated a total of 10  SIAs. SFFs that agreed to SIAs retained their SFF designation and were  still subject to more frequent surveys than other homes.
SIAs share some common requirements and sometimes describe similar  elements using different terminology. SIAs may differ because regional  offices attempt to craft agreements that reflect each SFF’s particular  circumstances or the specific regional office goals for the home. Common  SIA elements include    hiring an independent consultant to provide technical assistance with  quality improvement activities at the home; requiring the consultant to identify solutions to issues that were  preventing the SFF from attaining or maintaining compliance, often  referred to as a root-cause analysis, and to develop an action plan to  address quality problems; and   providing periodic reports prepared by either the consultant or the home  to the regional office on the status of actions or recommendations to  improve quality.
Two of the SIAs required the SFFs to commit funds ranging from $850,000  to $956,000 for the improvement of clinical care systems or facility capital  improvements. For example, one SIA required the SFF to dedicate  $956,000, primarily for capital improvements such as a new roof and a  heating and cooling system but also to go into an escrow fund to pay for  quality improvements consistent with the consultant’s root-cause analysis  and action plan.
In general, regional offices have used SIAs as an alternative to terminating  homes that had been in the program for 18 months. Five of the 10 homes  with SIAs had been in the SFF Program from 27 to 42 months when they  signed SIAs. (See app. IV for a chronological summary of all SIAs as of  August 2009.) One regional office negotiated an SIA to avoid bed shortages  that would have resulted had the SFF been terminated from Medicare and  Medicaid. Another SFF at risk of termination had recently undergone a  change in ownership, and the new owner had made substantial clinical  and capital improvements. With 6 of the 10 SIAs, Dallas is the only regional  office with an SIA that has established specific criteria for the use of the  agreements. Any SFF that has failed to graduate from the SFF Program in  18 months and that has no deficiencies above the F level is given one last  chance by signing an SIA. Dallas regional office officials stressed that in  applying these criteria they have also begun to assess the SFF’s  commitment to improve through the SIA process.
Whether or not the agreements result in improved nursing home  performance, they have the potential to address the problem of homes that  linger in the SFF Program for years. Although three of the regional offices  with SIAs indicated that SIAs were effective, the Dallas regional office  thought it was too early to say because the future performance of the  homes was unknown.
Four homes met the terms of their SIAs and graduated from the SFF  Program. As of August 2009, one of these homes was above average  according to CMS’s Five-Star System, and three were below or much  below average.
Two homes were terminated, one for failing to meet terms of the SIA. The  other home voluntarily left the Medicare and Medicaid programs before  CMS could terminate it.
Two homes are still SFFs even though the SIAs have ended. These homes  were rated as below and much below average in August 2009.
Two homes are still subject to the terms of their SIAs, and both were rated  as much below average in August 2009.
Although the first SIA was implemented more than 2 years ago, CMS  central office officials told us they had not yet disseminated information to  the regions describing the elements that should be part of SIAs or  catalogued any lessons learned from their use. We found that most SIAs  were initiated by regional offices with limited CMS central office  involvement and varying levels of state involvement. As of May 2009,  CMS’s central office was not aware of some SIAs that we identified in an  interview with officials in the Dallas regional office. According to officials  at three of the six regional offices that have not used SIAs, they prefer  other agreements to improve and maintain quality, including agreements  between state licensing authorities and SFFs. Of the three remaining  regional offices, two indicated they would be likely to develop an SIA  when they have facilities deemed appropriate and the other had not heard  of SIAs.
Nursing Homes in Need Initiative. The technical assistance provided  by QIOs to a limited number of nursing homes (one per year per state)  from August 1, 2008, through July 31, 2011, under the NHIN initiative  resembles the actions outlined in SIAs. For example, QIOs are required  to conduct an on-site assessment of each home to identify the underlyin causes of poor quality of care, prepare a root-cause analysis based on  those findings, and develop an action plan to address the home’s  problems. Given the voluntary nature of the QIO program, SFFs must  agree to work with QIOs; however, CMS did direct QIOs to contact SFFs  recommended by state survey agencies instead of relying on homes to  request QIO assistance. According to CMS, 44 QIOs assisted one SFF per  state from August 2008 through July 2009, the first year of the NHIN  initiative, and the remaining 6 QIOs assisted other homes, including SFF  candidates. CMS told us that these states’ QIOs were not working with  SFFs for various reasons, such as the SFFs were already showing  improvement. Officials from a majority of the states we interviewed  thought it would be beneficial for QIOs to work with every SFF instead of  just one per state per year.
In addition to the small number of SFFs that participate each year of the  contract, the initiative’s effectiveness is also limited by the misalignment  between the measures CMS uses to monitor the effect of QIO assistance  and those used to measure whether an SFF is improving. Specifically, CMS  monitors the improvement in two quality of care measures to determine  the effect of QIO assistance during the initiative—the percentage of long- term residents of a facility who were either physically restrained or were  high risk and had pressure ulcers. An alternative approach would be to  use the measures that CMS uses to evaluate whether homes in the SFF  Program are improving, that is, the number or scope and severity of  deficiency citations. CMS officials responsible for the QIO program  indicated that they were aware of this discrepancy and would consider  alternative methods for measuring QIO performance.
section_title: HHS OIG’s Experience with Quality of Care CIAs Is Relevant to CMS Activities to Address Poor Quality at SFFs and Other Nursing Homes
paragraphs: CMS officials told us that SIAs are not modeled on the HHS OIG quality of  care CIAs—corporate-level interventions to address quality problems— and CMS and HHS OIG officials have indicated that they have had  preliminary discussions regarding SIAs. SIAs and CIAs are similar in that  they are intended to improve and maintain the quality of participating  facilities in lieu of termination or exclusion, respectively, but quality of  care CIAs are more commonplace, have been in use since 2000, and are  generally in effect for longer periods. According to a 2009 HHS OIG  report, by June 2008, 35 nursing home corporations had entered into such  agreements, which are generally in effect for 3 to 5 years. In its report,  HHS OIG examined 15 of these nursing home corporations under quality  of care CIAs, which collectively operated 1,104 nursing homes as of  December 31, 2006. Both SIAs and quality of care CIAs require homes or  corporations to seek outside technical assistance to identify changes that  will help address quality problems. In addition, quality of care CIAs may  require corporations to take other actions to help improve quality, such as  the establishment of corporate-level compliance officers, quality assurance  committees, and quality assurance monitoring committees. The HHS OIG  requires the corporations to hire an independent entity, or monitor, to  assess the quality assurance and quality improvement systems in place in  the corporations’ homes. According to an official with one such entity,  staff members are embedded in the nursing home corporation to help  ensure that planned quality improvements are actually implemented. In  addition, the corporations must provide the HHS OIG with a list of all  homes that belong to the same corporation at the beginning of the CIA and  update the HHS OIG with information on the homes bought and sold; the  independent quality monitor commonly contracts with a data analysis  organization, subject to HHS OIG approval, to analyze state survey results  and quality of care measures across the homes in the corporation. The  2009 HHS OIG report evaluated the extent to which required quality of  care structures and processes were implemented through CIAs. Based on  its review of 15 such CIAs, the OIG found that all 15 corporations had  enhanced their quality of care structures and processes while subject to  these agreements. As of September 2008, an HHS OIG official was aware  of three corporations with quality of care CIAs that had homes that were  also in the SFF Program, and two of these SFFs had SIAs. However, there  is little coordination between CMS and the HHS OIG to determine whether  there is overlap among homes with these agreements.
The HHS OIG’s experience with quality of care CIAs is relevant and may  contain lessons that could improve the effectiveness of CMS’s efforts to  deal with poorly performing nursing homes even though CMS central  office officials told us that the agency’s relationship is with the individual  home and not the parent company. Thus, we found that some regional  offices do interact with corporations. One SIA we reviewed was signed by  the Vice President of Clinical Services of a large nursing home chain.  Moreover, officials from two regional offices told us that they are aware of  and monitor problems at chains operating in their regions, such as by  conducting federal monitoring surveys at homes belonging to a problem  chain. In fact, one of these regions indicated that CMS’s central office  had directed closer scrutiny of certain nursing home corporations in the  past. Officials from two regions provided a concrete example of their  interactions with officials from one corporation. These two regions  noticed that several homes with compliance problems had a common  name, and one regional office determined through a Google search that  the homes were part of the same chain; this chain operated almost 50  homes in five states, and some of this chain’s homes were SFFs. In one  instance, regional office officials met with the chief executive officer and  regional operations manager to discuss an improvement plan for one of  the chain’s homes after this home became an SFF. In another instance,  officers from the same chain approached a regional office. Ultimately, the  chain developed a quality improvement plan intended to cover all of its  facilities across three CMS regions; however, regional office officials did  not consider this plan to be an SIA because it did not provide for  enforcement.
section_title: Some States Have Also Adopted Nursing Home Quality Improvement Strategies That Are Relevant to CMS’s Efforts to Address SFF Quality Problems
paragraphs: Officials from the majority of the 14 states we interviewed detailed  strategies they use to promote quality improvement in nursing homes,  including poorly performing homes. Their strategies have incorporated a  range of activities, such as having nurse monitors visit all nursing homes,  training nursing home staff on clinical best practices, conducting  expedited or more frequent surveys of nursing homes with performance  problems, and hiring consultants to provide technical assistance to homes.  These activities can be voluntary, and some states target certain poorly  performing nursing homes for participation. According to some states, the  SFF Program is more effective when combined with state-based quality  improvement activities, which may make it difficult to determine whether  performance improvements are attributable to the SFF Program or to state  activities. Officials from three states described the following noteworthy  quality activities:    Florida. Florida law requires the state agency to survey nursing homes  with serious performance problems more frequently (every 6 months for   2 years). Such homes must pay a fine of $6,000 in installments over the   2-year period to cover the expenses associated with the additional  surveys. As of August 2008, state officials told us that 26 nursing homes,  including 3 SFFs, met these criteria.
Missouri. The state’s Quality Improvement Program for Missouri’s Long  Term Care Facilities offers a voluntary nurse consultant program that  provides in-person, on-site technical assistance for nursing homes deemed  to be at risk. While any nursing home in the state can ask to participate in  the program, the state also determines which homes it deems eligible to  participate and has included SFFs in this determination since July 2008.  As of October 2008, 85 nursing homes were targeted for program  participation because the state deemed them to be at risk.
Arkansas. Arkansas’s Innovative Performance Program, which began in  August 2005, provides most nursing homes with (1) monthly training  opportunities, covering a variety of topics for nursing home staff, such as  the top 10 most frequently cited deficiencies or clinical best practices; and  (2) intensive reviews of a home’s operations to help identify and correct  systemic problems and put controls in place to ensure the changes are  implemented. Under its contract with the Arkansas Office of Long Term  Care, the state’s QIO administers this voluntary program and helps identify  the homes most in need of assistance. As of September 2009, 141 nursing  homes were participating in the program, including 5 of 6 SFFs.
section_title: Conclusions
paragraphs: Improving the performance of poorly performing nursing homes through  efforts such as the SFF Program is essential to protecting highly  vulnerable elderly and disabled residents. Paradoxically, we found that  many SFFs improved their performance and graduated from the program  even though some may not always have been surveyed as frequently as  required or subjected to more robust enforcement—actions called for in  CMS SFF Program guidance to states and regional offices. Important  program changes made by CMS since 2004, such as the 2007 decisions to  publicly report the names of SFFs and ensure that owners and boards of  directors are explicitly informed of their facility’s SFF status, have given  homes additional incentives to improve their performance. The  effectiveness of the SFF Program could be further improved if CMS  implemented our August 2009 recommendation to target scarce resources  by placing more emphasis on the worst homes nationally rather than on  the worst homes in each state.
We found that state discretion in selecting SFFs is a key element of the  program, but that limitations in the candidate list restrict that discretion.  For example, homes that are selected as SFFs remain on each state’s list  of 15 candidates, giving states with six SFFs, such as California and Texas,  fewer options when homes graduate from the program or are terminated,  compared to states with only one or two SFFs. Moreover, at least two  states—Michigan and Missouri—have expanded on CMS’s public  disclosure strategy in an attempt to influence the performance of SFF  candidates by informing them that they are at risk of being selected as an  SFF if they fail to address performance problems.
CMS’s guidance to states regarding enforcement for SFFs is vague and  interpreted inconsistently by regional offices and states. We found that for  six SFFs with consecutive noncompliance, severe deficiencies did not  consistently result in more severe or immediate sanctions. For example,  one SFF received no civil money penalties even though it was cited for  consecutive deficiencies that could have resulted in fines ranging from  $300 to $825 per day of noncompliance, while a home with a similar  compliance history received CMPs that increased from $300 to $600 per  day of noncompliance, suggesting that CMS’s monitoring of enforcement is  insufficient.
The significant percentage of SFFs that remained in the program for  considerably longer than CMS’s 18-month time frame for improved  performance or termination is troubling because it prevents other poorly  performing nursing homes from receiving enhanced attention by becoming  SFFs since the program is limited by resources to 136 at a time. For a  limited number of homes that failed to show improvement or where  termination was seen as an option of last resort, 4 of CMS’s 10 regional  offices have negotiated agreements requiring homes to address quality  problems. Although the first SIA was implemented over 2 years ago, CMS  has not disseminated information to the regional offices describing the  elements that should be part of SIAs, or catalogued any lessons learned  from their use. It is probably too early to evaluate the longer-term  effectiveness of SIAs, but they do have the potential to address the  problem of homes that linger in the program for extended periods.
Other efforts also have the potential to help address performance  problems at poorly performing nursing homes, and some may hold lessons  for improving the operation of the SFF Program.
Nursing Homes in Need Initiative. QIOs are employing interventions  similar to those used in SIAs at poorly performing nursing homes,  primarily SFFs, at the rate of one home per state each year for 3 years.  However, the QIO measures used to monitor the effect of QIO assistance  are inconsistent with the measures CMS uses to evaluate whether SFFs  are improving.
Corporate Integrity Agreements. The HHS OIG has considerable  experience negotiating legal agreements with corporations that own  poorly performing nursing homes, agreements that also employ more  direct interventions to address quality problems across the homes in a  chain. Currently, there is little coordination between CMS and the HHS  OIG, even though we found that some regional offices also work with  chain corporate offices and a few homes were subject to both SIAs and  CIAs.
State Quality Improvement Initiatives. Some states have adopted  quality improvement strategies to address problems at poorly performing  homes. For example, Florida requires homes with serious performance  problems to pay $6,000 to cover the costs associated with more frequent  surveys over a 2-year period. Although SFFs and other poorly performing  nursing homes that frequently harm residents or place them in immediate  jeopardy increase survey costs, CMS does not currently have the authority  to charge them for additional survey activities. Charging such a fee could  improve the linkage between the costs associated with more frequent  surveys and the nursing homes that give rise to these costs.
section_title: Recommendations for Executive Action
paragraphs: To increase the SFF Program’s effectiveness in helping to address quality  of care problems at poorly performing nursing homes, we recommend that  the Administrator of CMS take the following five actions:    Expand the SFF Program’s public disclosure strategy by directing states to  notify nursing homes that have been identified as SFF Program candidates  that they are at risk of being selected as an SFF.
Revise the SFF candidate list by removing homes that states have selected  as SFFs and including additional homes so that states with a large number  of SFFs have a full complement of candidates to choose from each time  they select a new SFF.
Ensure that states impose more stringent enforcement, such as higher  CMPs or termination; clarify SFF Program guidance regarding appropriate  sanctions; and monitor SFF sanctions more closely.
Provide CMS regional offices with a description of the elements that  should be part of SIAs and catalogue any lessons learned from their use.
Coordinate more systematically with the HHS OIG regarding its  experiences with CIAs.
To offset the additional costs imposed by SFFs and create incentives for  poorly performing nursing homes to improve resident care more quickly,  we recommend that the Administrator of CMS seek legislative authority to  charge SFFs for the costs associated with conducting additional surveys.
section_title: Agency Comments and Our Evaluation
paragraphs: We obtained written comments on our draft report from HHS, which are  reprinted in appendix V. HHS noted its commitment to further  strengthening the SFF Program and indicated that our report would help  to further improve what could work better and reaffirm what is already  working well. HHS agreed fully with four of our six recommendations,  agreed in principle with a fifth recommendation, and indicated that it  would take a sixth recommendation under advisement.
In its comments, HHS reported on additional analyses it had conducted,  which found that in comparing SFF graduates to candidates, (1) a higher  percentage of graduates had no deficiencies at the F-level or higher both   6 months and 12 months after graduation from the program, and (2) an  average of 21.5 months and 15.6 months, respectively, elapsed before   50 percent of the homes in either group had an F-level or higher  deficiency. HHS concluded that while these analyses did not suggest that  SFF graduates had transformed into high-quality nursing homes, they did  indicate that the greater efforts made by SFF graduates had some lasting  and positive effects on quality of care. Despite the improvements  demonstrated by SFFs, HHS expressed concern about those SFF  graduates that relapse into a pattern of serious deficiencies. HHS noted  that it will re-examine the 18-month time frame for SFFs to demonstrate  improved performance given our finding that a significant percentage of  SFFs remain in the program beyond 18 months.
HHS fully concurred with the following four recommendations:   (1) directing states to notify SFF candidates that they are at risk of being  selected for the SFF Program; (2) clarifying SFF Program guidance on  appropriate sanctions and monitoring SFF sanctions more closely;   (3) providing CMS regional offices with a description of the elements of an  SIA and cataloguing lessons learned from their use; and (4) coordinating  more systematically with the HHS OIG regarding its experiences with  CIAs. In addition, HHS agreed in principle with our recommendation that  CMS revise the SFF candidate list by removing homes that have already  been selected as SFFs and including additional homes so that states have a  full complement of candidates from which to choose; however, HHS said  that CMS will operationalize the recommendation in a different manner by  sizably increasing the SFF candidate list for most states. If implemented,  CMS’s proposed approach would address our recommendation. Finally,  HHS indicated it would take under advisement our recommendation that  the Administrator of CMS seek legislative authority to charge SFFs for the  costs associated with conducting additional surveys.
HHS also provided technical comments, which we incorporated as  appropriate. We also provided excerpts of the report to the HHS OIG and  the three state survey agencies whose specific quality improvement  strategies we described in the report—Arkansas, Florida, and Missouri— and incorporated technical comments from those agencies as appropriate.
As we agreed with your offices, unless you publicly announce the contents  of this report earlier, we plan no further distribution of it until 30 days  from the date of this letter. At that time, we will send copies to the  Administrator of the Centers for Medicare & Medicaid Services and  appropriate congressional committees. The report also is available at no  charge on the GAO Web site at http://www.gao.gov.
If you or your staff have any questions about this report, please contact me  at (202) 512-7114 or at dickenj@gao.gov. Contact points for our Offices of  Congressional Relations and Public Affairs may be found on the last page  of this report. GAO staff who made key contributions to this report are  listed in appendix VI.
section_title: Appendix I: Special Focus Facility Financial Performance
paragraphs: This appendix addresses your interest in the financial performance of  Special Focus Facilities (SFF). Officials from the Centers for Medicare &  Medicaid Services’s (CMS) central office told us that they do not attempt  to determine whether poor financial performance contributed to the poor  quality of care provided by SFFs. However, three of the four regional  offices we interviewed did not believe that poor financial performance  was more common for SFFs than for other nursing homes. An official from  the remaining regional office did not comment because he told us the  office assesses only quality of care. Regional offices told us that they may  learn about homes’ financial problems on an ad hoc basis. For example,  they might learn that a home failed to meet payroll, that lenders were  unwilling to extend credit to a home, or that a resident’s complaint, such  as a low building temperature or limited food supply, might indicate  financial problems. In addition, regional offices are made aware of  potential financial problems when a home requests a delay or reduction in  payment on civil money penalties (CMP) based on poor financial  condition. CMS guidance provides a suggested list of sources for  information to determine if a CMP should be delayed or reduced due to a  home’s financial condition, but does not indicate how the regional office  should make this determination. Furthermore, two regional offices told us  that requests for delayed or reduced CMPs are rare.
CMS’s central office also has access to another source of financial  information—annual Medicare cost reports, which nursing homes  receiving Medicare payments are required to submit to Medicare  Administrative Contractors. However, according to the Medicare Payment  Advisory Commission (MedPAC), the financial information provided in  these reports has several limitations for assessing total financial  performance of nursing homes. For example, the cost reports do not  follow the format of standard audited financial statements or receive  serious audit attention. Despite these limitations, the Medicare  Administrative Contractor we interviewed, which processes Medicare  claims in addition to receiving Medicare cost reports, told us that it could  conduct a financial analysis of nursing homes if CMS were to request and  fund this activity, but noted that it would first want to verify their  information.
We did identify two entities that have initiatives that collect information  about nursing home financial performance. First, Virginia passed  legislation on health care data reporting in 1996, which resulted in the  state’s contracting with Virginia Health Information to report both nursing  home financial information and an assessment of homes’ efficiency and  productivity, among other information, on its Web site. The financial  information that providers, including nursing homes, are required to file  annually includes details about revenue, expenses, and assets. This  information is summarized from either certified audited financial  statements or, if the nursing home is part of a publicly held company,  unconsolidated unaudited financial statements submitted by the home.  Second, the Department of Housing and Urban Development (HUD)  classifies the financial performance of all facilities that participate in the  Section 232 Mortgage Insurance for Residential Care Facilities program.  According to HUD officials, 12 SFFs as of June 2009 had insured  mortgages and the officials classified 8 of them as financially troubled  based on various criteria, such as the home making a late mortgage  payment or concerns about the home’s ability to make future mortgage  payments.
section_title: Appendix II: Scope and Methodology
paragraphs: This appendix provides additional details regarding our scope and  methodology.
State interviews. We selected a nongeneralizable sample of 14 states to  interview based on a combination of factors, including: (1) the number of  SFFs allocated to the state, (2) the inclusion of at least one state from each  CMS region, (3) states that had many homes with high SFF scores, (4) the  number of SFFs that either graduated from the program or were  terminated from Medicare and Medicaid for failing to improve their  performance, (5) the use of Systems Improvement Agreements, and (6) the  existence of state ranking methodologies. We interviewed officials from  the following 14 states: Alabama, Arkansas, California, Colorado,  Connecticut, Florida, Illinois, Indiana, Massachusetts, Missouri, New York,  Pennsylvania, Texas, and Washington.
SFF candidate lists. CMS provided us with 16 SFF candidate lists  generated from December 2005 to January 2009, which contain the score  and rank of all nursing homes using CMS’s SFF methodology. Since 2006,  CMS has issued candidate lists quarterly, but it generates additional lists  when necessary.
To determine the factors that states considered in selecting SFFs from  January 2006 through February 2009, we determined the rank of each  home on the candidate list that was generated before, but closest to, the  date of that home’s selection for the program.
To determine the factors that states considered in selecting SFFs, we  analyzed the scores of SFF candidates from CMS’s January 2009 candidate  list.
To determine the SFF Program’s impact on homes’ performance, we  analyzed the scores for each of the three cycles provided on CMS’s  candidate lists from December 2005 to January 2009 by calculating state  average indexed scores. We then created a mean indexed score for all SFF  graduates for three points in time—before the home entered the program,  while the home was in the program, and after graduation—and compared  them to each other. For SFFs that were active in the program as of  February 2009, we also compared the mean indexed score before the  home entered the program to the mean indexed score while the home was  in the program.
OSCAR survey and deficiency data. We conducted several analyses  using data from CMS’s On-Line Survey, Certification, and Reporting  system (OSCAR) for standard surveys and complaint investigations  generally conducted between January 2005 and July 31, 2009. We analyzed  survey dates, deficiencies cited on standard surveys and complaint  investigations, and any revisits associated with the standard surveys. To be  consistent with the SFF methodology and avoid potential double-counting,  we did not include deficiencies that also appeared on complaint surveys  conducted within 15 days of a standard survey (either prior to or after the  standard survey).
To determine how SFFs differ from other nursing homes, we calculated  the average number of deficiencies and revisits for certain SFFs compared  to other nursing homes. We identified SFFs that were added to the SFF  Program in 2008 and that also had a 2008 standard survey prior to their  entry into the program. We compared these SFFs to other homes that had  a standard survey conducted in 2008. Our analysis included deficiencies  identified during the 2008 standard survey, deficiencies from complaint  investigations that occurred in the year prior to the 2008 standard survey,  and revisits associated with the standard survey.
To determine whether states followed CMS’s guidance to survey SFFs  twice a year, we analyzed the dates of the standard surveys conducted  while nursing homes were in the SFF Program. We determined the number  of surveys that should have been conducted each year by multiplying the  state’s SFF allotment by two. We then summed the number of SFF surveys  conducted by each state for fiscal years 2007 and 2008 and determined if  the number of surveys conducted was fewer than the total number of  surveys that should have been conducted. In addition, we calculated the  number of states that did not survey at least one of their SFFs within the  first 7 months after the home entered the program and that had at least  one SFF with more than 10 months between surveys from calendar year  2005 through 2008.
To determine whether CMS regional offices and the states followed the  agency’s SFF Program graduation criteria, we analyzed survey dates and  data on deficiencies from standard surveys and complaint investigations.  We determined which SFFs did not graduate appropriately because   (1) states conducted standard surveys zero or only one time while the  home was in the SFF Program; (2) the home had deficiencies at the F level  or higher on the two standard surveys preceding their graduation; or   (3) the home had deficiencies at the F level or higher on any complaint  surveys that occurred from the two standard surveys preceding their  graduation through the date of their graduation.
To determine if SFFs had F-level deficiencies that may have contributed to  the length of time they were in the SFF Program, we determined the  number of SFFs that had various combinations of standard and complaint  surveys that resulted in deficiencies at the F level and lower.
To determine the program’s impact on SFF graduates, we analyzed  deficiencies from standard and complaint surveys for SFFs after they  graduated from the program. Specifically, we determined the number of  SFFs that after graduation had F-level or higher deficiencies on any  survey, F-level or higher deficiencies on consecutive standard surveys, and  immediate jeopardy deficiencies.
Nursing home enforcement. To determine whether CMS regional offices  and states followed the agency’s SFF Program enforcement guidance, we  first identified homes that were SFFs as of January 1, 2007, and that had  two consecutive standard surveys, both of which cited at least one G-level  or higher deficiency; we then analyzed Nursing Home Enforcement  History reports and Nursing Home Enforcement Case Profiles for these  homes that we obtained from the regional offices and which summarize  data from CMS’s Automated Survey Processing Environment Enforcement  Manager (AEM).  In addition, we analyzed AEM data on CMPs and denials  of payment for new Medicare or Medicaid admissions (DPNA) that were in  effect for calendar years 2006 through 2008 for each of three categories of  nursing homes—SFFs, SFF candidates, and other nursing homes. We  determined the percentage of homes in each category that had at least one  CMP or DPNA by year. In addition, we calculated mean CMP amounts (per  day and per instance) by home type and year by summing each home’s  CMPs for the year. For SFFs, we included only sanctions that occurred  while the home was in the SFF Program. SFF candidates were those  homes ranked as among the worst 15 homes per state based on the CMS  candidate lists for that same year.
Termination. To determine the number of SFFs that were terminated— voluntarily or involuntarily—and later became certified to participate in  Medicare or Medicaid again, we analyzed information available from  CMS’s Provider of Service file dated December 2008. To do so, we  identified the addresses of SFFs that terminated, and then we identified  nursing homes that shared the same physical location as the terminated  SFFs and that later began participating in Medicare or Medicaid.
Nursing home characteristics data. To determine how SFFs differ from  other nursing homes, we analyzed CMS data that describe the  characteristics of nursing homes: a December 17, 2008, extract of OSCAR  variables, such as type of organization and number of beds; nurse staffing  hours, which were case-mix adjusted by CMS for use in its Five-Star  Quality Rating System and which were dated January 2009; and nursing  home ratings from the Five-Star System available from Nursing Home  Compare, which were dated December 2008. Following are highlights of  how we analyzed certain characteristics:    Nursing homes self-report their ownership type. We created the ownership  type of for-profit by combining for-profit individual, for-profit partnership,  for-profit corporation, and limited liability corporation; the ownership type  of nonprofit by combining nonprofit corporation, nonprofit church-related,  and nonprofit other; and the ownership type of government by combining  the six government designations (state, county, city, city/county, hospital  district, and federal).
CMS maintains a variable in its data called “multi-nursing home (chain)  ownership,” which is self-reported by nursing homes and which we refer  to as chain affiliation. According to CMS, multi-nursing home chains have  two or more homes under one ownership or operation. We determined the  percentage of nursing homes that were for-profit and chain affiliated,  nonprofit and chain affiliated, or government-owned and chain affiliated  by combining the ownership types described above with CMS’s  designation of multi-nursing home (chain) ownership.
We used the number of beds certified for payment for Medicare and/or  Medicaid to calculate the average number of beds per nursing home.
We calculated the percentage of residents by type (Medicare, Medicaid, or  other) by dividing the number of Medicare, Medicaid, and other patients  by the number of total residents.
We calculated the occupancy rate of nursing homes by dividing the total  number of residents by the number of certified beds.
We analyzed the following case-mix adjusted nurse staffing hours:  registered nurse hours per resident per day; licensed practical nurse and  vocational nurse hours per resident per day; nurse aide hours per resident  per day; and total staffing hours per resident per day. We calculated  registered nurse hours as a share of the total. Unadjusted nurse staffing  hours data are collected by CMS, are self-reported by nursing homes, and  represent staffing levels for a 2-week period prior to the state inspection.  CMS case-mix adjusted the staffing data using the average minutes of  nursing care used to care for residents in a given resource utilization  group category as reflected in the Medicare skilled nursing facility  prospective payment system. CMS acknowledges that the staff hours  collected from nursing homes have certain limitations. In order to increase  the accuracy and comprehensiveness of the staffing data, CMS has been  investigating whether it can use nursing home payroll data to report  staffing levels on Nursing Home Compare.
section_title: Appendix III: Characteristics of Special Focus Facilities and Other Nursing Homes
subsections: section_title: Average number of residents per home (number)
paragraphs: For-profit (individual, partnership, or corporation)
Nonprofit (corporation, church, or other)
Type of staff (average hours per resident-day)
Licensed practical and vocational nurses   Registered nurse hours as a share of total hours (percentage)
Individual entries may not sum to 100 percent because of rounding.
section_title: Appendix IV: Chronological Summary of All 10 Systems Improvement Agreements (SIA)
paragraphs: Appendix IV: Chronological Summary of All  10 Systems Improvement Agreements (SIA)
subsections: section_title: Duration in SFF Program (prior to SIA)
paragraphs: date of SIA Duration of SIA(date graduated/  terminated)
CMS’s Five-Star  System Rating  8 months   Graduated (10/08)  5 months   Graduated (3/08)  24 months   Graduated (4/08)  2 months   Graduated (3/09)  4 months   Terminated (10/08)  6 months   Terminated (3/09)
section_title: Appendix V: Comments from the Department of Health and Human Services
section_title: Appendix VI: GAO Contact and Staff Acknowledgments
subsections: section_title: Acknowledgments
paragraphs: In addition to the contact name above, Walter Ochinko, Assistant Director;  Ramsey Asaly; Daniel Lee; Shannon Legeer; Jessica Morris; Roseanne  Price; Jennifer Rellick; Kathryn Richter; and Jessica Smith made key  contributions to this report.
section_title: Related GAO Products
paragraphs: Nursing Homes: Addressing the Factors Underlying Understatement of  Serious Care Problems Requires Sustained CMS and State Commitment.  GAO-10-70. Washington, D.C.: November 24, 2009.
Nursing Homes: Opportunities Exist to Facilitate the Use of the  Temporary Management Sanction. GAO-10-37R. Washington, D.C.:  November 20, 2009.
Nursing Homes: CMS’s Special Focus Facility Methodology Should Better  Target the Most Poorly Performing Homes, Which Tended to Be Chain  Affiliated and For-Profit. GAO-09-689. Washington, D.C.: August 28, 2009.
Medicare and Medicaid Participating Facilities: CMS Needs to  Reexamine Its Approach for Funding State Oversight of Health Care  Facilities. GAO-09-64. Washington, D.C.: February 13, 2009.
Nursing Homes: Federal Monitoring Surveys Demonstrate Continued  Understatement of Serious Care Problems and CMS Oversight  Weaknesses. GAO-08-517. Washington, D.C.: May 9, 2008.
Nursing Home Reform: Continued Attention Is Needed to Improve  Quality of Care in Small but Significant Share of Homes. GAO-07-794T.  Washington, D.C.: May 2, 2007.
Nursing Homes: Efforts to Strengthen Federal Enforcement Have Not  Deterred Some Homes from Repeatedly Harming Residents. GAO-07-241.  Washington, D.C.: March 26, 2007.
Nursing Homes: Despite Increased Oversight, Challenges Remain in  Ensuring High-Quality Care and Resident Safety. GAO-06-117.  Washington, D.C.: December 28, 2005.
Nursing Home Quality: Prevalence of Serious Problems, While  Declining, Reinforces Importance of Enhanced Oversight. GAO-03-561.  Washington, D.C.: July 15, 2003.
Nursing Homes: Public Reporting of Quality Indicators Has Merit, but  National Implementation Is Premature. GAO-03-187. Washington, D.C.:  October 31, 2002.
Nursing Homes: Federal Efforts to Monitor Resident Assessment Data  Should Complement State Activities. GAO-02-279. Washington, D.C.:  February 15, 2002.
Nursing Homes: Sustained Efforts Are Essential to Realize Potential of  the Quality Initiatives. GAO/HEHS-00-197. Washington, D.C.: September  28, 2000.
Nursing Home Care: Enhanced HCFA Oversight of State Programs  Would Better Ensure Quality. GAO/HEHS-00-6. Washington, D.C.:  November 4, 1999.
Nursing Home Oversight: Industry Examples Do Not Demonstrate That  Regulatory Actions Were Unreasonable. GAO/HEHS-99-154R. Washington,  D.C.: August 13, 1999.
Nursing Homes: Proposal to Enhance Oversight of Poorly Performing  Homes Has Merit. GAO/HEHS-99-157. Washington, D.C.: June 30, 1999.
Nursing Homes: Complaint Investigation Processes Often Inadequate to  Protect Residents. GAO/HEHS-99-80. Washington, D.C.: March 22, 1999.
Nursing Homes: Additional Steps Needed to Strengthen Enforcement   of Federal Quality Standards. GAO/HEHS-99-46. Washington, D.C.:   March 18, 1999.
California Nursing Homes: Care Problems Persist Despite Federal and  State Oversight. GAO/HEHS-98-202. Washington, D.C.: July 27, 1998.