U.S. Department of Health and Human ServicesU.S. Department of Health and Human Services
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This report was prepared under contracts #HHS-100-97-0013 and #HHS-100-00-0023 between the U.S. Department of Health and the University of Colorado. For additional information about this subject, you can visit the DALTCP home page at http://aspe.hhs.gov/_/office_specific/daltcp.cfm or contact the ASPE Project Officer, Susan Polniaszek, at HHS/ASPE/DALTCP, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, D.C. 20201. Her e-mail address is: Susan.Polniaszek@hhs.gov..
The opinions and views expressed in this report are those of the authors. They do not necessarily reflect the views of the Department of Health and Human Services, the contractor or any other funding organization.
Post-acute care (PAC) refers to care received after an acute hospitalization, which is typically provided in skilled nursing facilities (SNFs), inpatient rehabilitation facilities (IRFs), home health (HH) agencies, and/or outpatient (OP) rehabilitation settings. In 2002, approximately one-third of Medicare beneficiaries discharged from hospitals utilized some form of PAC within one day of leaving the hospital. Although care received in different PAC settings varies to some extent, many experts believe that patients with similar care needs may be treated in different PAC settings and that the choice of discharge destination is often driven by factors other than patient characteristics (e.g., availability of beds, physician or family preference, practice patterns).
In an effort to contain rapid growth in Medicare PAC expenditures during the late 1980s to mid-1990s, Congress passed the Balanced Budget Act of 1997 that required the development and implementation of prospective payment systems (PPS) for all types of PAC. The PPSs have been phased in over the past eight years, beginning with SNFs in July 1998, followed by OP hospital care in August 2000, HH agencies in October 2000, and IRFs in January 2002.
This study, funded by the Office of the Assistant Secretary for Planning and Evaluation, had three primary aims, including:
1) To compare quality, outcomes, and costs of PAC episodes involving single and multiple-providers (e.g., IRF care followed by HH care, IRF care followed by OP care) provided to Medicare beneficiaries with stroke after PPS implementation.
Using stroke as a tracer condition, this study examined PAC outcomes and costs for single and multiple-provider episodes of care. Outcomes studied included return to community residence, functional outcomes (including activities of daily living (ADLs), instrumental activities of daily living (IADLs), social/role function, and function related to walking), self-reported health, and satisfaction. Costs included cost to the Medicare program and to beneficiaries. Few prior studies have examined outcomes and costs of multiple-provider episodes, particularly those involving OP rehabilitation care, and no major studies have been conducted subsequent to PPS implementation in all PAC settings. This study, therefore, represents a unique opportunity to explore these various facets of PAC during the post-PPS era.
2) To compare and contrast various quality of care and outcome measures that can be used across PAC settings.
This study explored whether a core set of measures can be identified that captures outcomes and quality of PAC episodes involving both single and multiple-providers. Given the current policy interest in uniform assessment for quality monitoring and comparing outcomes across settings, this research provides invaluable information in moving toward this goal.
3) To examine the effect of PPS implementation on patterns of PAC utilization (including IRF, SNF, and HH agency) for stroke patients.
This objective involved analysis of national claims data to complement the in-depth primary data analysis conducted for the first objective. Recent research on the use of IRF care before and after the implementation of the IRF PPS was conducted by RAND; however, this work was limited to only the early stages of the IRF PPS (the first year of IRF PPS implementation). No studies to date have assessed the effects of PPS in terms of PAC utilization and patterns of care following PPS implementation in all PAC settings. Given the financial incentives that exist under the different PPSs, PAC utilization patterns are likely to be altered, with the potential to influence cost and quality of care.
This study of PAC included a national sample of 88 PAC providers comprised of 35 IRFs, 33 SNFs, and 20 HH agencies in 20 states. Subject eligibility was limited to Medicare beneficiaries admitted to PAC from the hospital for an acute stroke, who were at least 65 years of age and enrolled in the Medicare fee-for-service program rather than managed care. Excluded were individuals who were comatose, those residing in a long-term care facility prior to this stroke, and those without a proxy if cognitively impaired or with severe speech/language impairment. The sample included a total of 674 subjects enrolled between late 2002 and early 2005: 555 whose first admission was to IRF, 62 whose first admission was to SNF, and 57 whose initial admission was to HH.
Patient characteristics analyzed in the study included demographics, and pre-stroke condition in available supports, function, and global health rating. Acute stroke characteristics included stroke characteristics and comorbidities. At the time of admission to PAC, the assessment included cognition, visual neglect, speech/language, function, and depression. Cognition and depression were assessed by direct interview with the patient (or proxy), whereas PAC admission function was obtained from the Minimum Data Set for SNFs, the Inpatient Rehabilitation Facility Patient Assessment Instrument for IRFs, and the Outcome and Assessment Information Set (OASIS) for HH agencies. In addition, a range of facility characteristics and community characteristics were collected.
Outcome and quality measures included: location at 90 days; functional recovery in four domains; recovery in self-rated overall health; and patient/proxy satisfaction. Location measures examined both nursing home vs. community residence and whether the 90-day residence was an equally independent living situation to the setting prior to the stroke. The functional recovery measures included the domains of ADLs, IADLs, ambulation, and social/role function. Function was assessed for multiple activities within each of these domains by an on-site data collector by interview for the baseline period prior to stroke, and by telephone for the 90-day follow-up.
Cost analyses included the costs to Medicare and to beneficiaries for all types of care. These costs were obtained from Part A and Part B claims data. Utilization data were obtained from Medicare claims for services covered by Medicare.
Patterns of Post-Acute Care:
Patient Characteristics:
Outcomes:
Costs and Service Utilization:
National Trends:
Measures:
Declining lengths of stay in the IRF setting and discharge to subsequent PAC providers, resulting in multiple-provider episodes, are natural consequences of the IRF per discharge PPS. That is, the incentive exists to admit patients to IRF, contain costs with a shorter stay in the IRF, and then discharge patients to a second type of PAC provider, which could be a SNF, HH agency, or OP care. This response is similar to declining acute hospital lengths of stay and the increased use of IRF, SNF, and HH care following the implementation of the per discharge acute hospital PPS. As per discharge payments for IRF care are readjusted based on length of stay trends, savings in IRF payments may help to offset the costs of the additional care in subsequent providers. However, the impact on quality of care, outcomes, and costs as a result of this discontinuity is important to monitor.
For the diagnosis of stroke, the increased use of IRFs and decline in use of SNFs immediately following the hospitalization suggests that IRFs have an increasing incentive to admit stroke patients under PPS, which may be accompanied by a decreased incentive in SNFs for admitting stroke patients. This could occur because payment rates for stroke patients in IRFs are among the most profitable based on the case mix groups and because other policies such as the 75 percent rule may encourage IRFs to admit patients with diagnoses such as stroke. SNFs may have difficulty covering the costs of the therapy services for stroke patients requiring substantial rehabilitation (which is the case for many stroke patients discharged directly from the hospital). Because the highest Resource Utilization Group rehabilitation category includes patients with 12 hours of therapy per week, and under PPS SNFs have no incentive to provide more than 12 hours of therapy per week, patients requiring more therapy are likely to be admitted to IRFs.
The HH PPS includes a substantial payment rate increase if ten therapy visits are provided; however, there is no payment incentive to admit patients who require any more than ten therapy visits. In combination, the PPS could result in greater differences in the patients admitted to each PAC provider from the hospital because of their need for and ability to tolerate therapy.
For the subgroup of stroke patients discharged to IRF and subsequently a SNF (about 25 percent of discharges to IRF from hospital), substitution with patients discharged directly to SNFs appears to exist. The major difference was that the IRF–>SNF episodes were almost twice as likely in communities with high IRF use rates and occurred more frequently in urban areas, suggesting differences in practice patterns. Overall, 60 percent of these patients had cognitive impairment, 75 percent had significant functional impairment, and 25 percent met strict criteria for depression. Nevertheless, outcomes were comparable between the IRF–>SNF group and those admitted directly to SNFs, whereas costs were 2-3 times higher for IRF–>SNF patients. From a policy perspective, if these individuals can be identified upon acute hospital discharge, then direct discharge to SNF would be more cost-effective. One way to encourage more cost-effective care would be to pay IRFs at a reduced payment rate equivalent to the SNF level of care for IRF days in cases when the patient is ultimately discharged to a SNF. A similar policy is currently in place whereby Medicare pays IRFs a lower rate for patients with stays of less than four days. Under this scenario, even if patients were to receive a very brief trial of rehabilitation in an IRF, as soon as it is apparent they require longer term, less intense rehabilitation, they would be discharged to a SNF.
The cost-effectiveness of OP services subsequent to IRF care was very apparent in this study. Stroke patients who received OP care subsequent to an IRF stay had better outcomes, received more therapy visits, and at lower cost to Medicare relative to patients discharged to HH agencies subsequent to an IRF stay. The comparability between these HH patients and OP patients raises questions about why some patients are considered "homebound" and others are not. While most of the patients receiving more HH or OP care following IRF may meet the relatively loose definition of "homebound," OP services were more likely to be used by stroke patients with higher incomes. Not surprisingly, the IRF–>OP pattern resulted in higher beneficiary costs because of the larger coinsurance. Reducing the cost to beneficiaries by reducing the OP coinsurance might increase the utilization of OP services relative to home care services following the IRF stay, which would be offset by fewer patients using higher cost HH services. Even if more patients in total were to use OP services (i.e., those previously discharged home with no further care), total cost would not be impacted for such patients due to the costs of Medicare services (increased hospitalizations and subsequent PAC services) that would have been needed by these patients if they had not received OP care. The difficulty in paying the coinsurance associated with OP service and the potential lack of reliable transportation may encourage people to use the more expensive HH care rather than OP services. From a policy perspective, we need to begin to recognize the important role of OP care in PAC used either immediately following the acute stay or subsequent to other PAC providers. It may offer the most cost-effective benefit for patients in many circumstances.
A uniform set of core measures is required to assess PAC outcomes for patients admitted to single or multiple PAC settings. The current setting-specific assessment tools cannot be used for this purpose because they use different elements, only some of which can be cross-walked, and have different follow-up intervals, making it impossible to compare change over fixed time periods. For outcome measurement, a baseline time point and a fixed follow-up point are required, regardless of the number of PAC providers that are utilized by a patient. An ideal baseline is pre-morbid function so that one can determine the extent to which prior function was recovered, and 90 days represents a follow-up point at which most PAC is completed. Functional measures across a range of domains, such as ADL, IADL, ambulation, and social/role function, are critical to assess because they are unique functional dimensions that recover at different rates. Changes in residence and global health ratings from baseline to 90 days are excellent general markers of rehabilitation success.
From this national study of PAC prospective payment between late 2002 and early 2005, we observed major changes in patterns of PAC utilization for stroke patients. Overall, providers were strongly responding to the PPS incentives. Substitution between patients directly discharged to SNFs and those discharged to SNF following IRF, and between patients discharged to OP following IRF and discharged to HH following IRF, showed that cost-effectiveness of PAC may be improved through changes in incentives. Continued collection of uniform outcome and cost data is essential if we intend to maximize opportunities for improving PAC provided to Medicare beneficiaries.
Post-acute care (PAC) refers to care received after an acute hospitalization, which is typically provided in skilled nursing facilities (SNFs), inpatient rehabilitation facilities (IRFs), home health (HH) care, and/or outpatient (OP) rehabilitation care. SNFs are nursing homes that are certified by the Centers for Medicare & Medicaid Services (CMS) to provide Medicare-reimbursable skilled nursing services on an inpatient basis. They consist of both hospital-based and freestanding facilities, and nearly 80 percent of their Medicare admissions receive physical, occupational, and/or speech therapy.1 IRFs are hospitals that provide intensive inpatient rehabilitation care; they are required to have a certain proportion of their patients require intensive rehabilitation for one of 13 broad medical conditions, one of which is stroke. IRFs are also characterized by much greater physician presence, particularly from rehabilitation specialists. HH care is provided to Medicare beneficiaries who are homebound (unable to leave their residence without considerable and taxing effort) and require intermittent or part-time skilled nursing care and therapy services. Hospital OP rehabilitation care generally consists of therapy and physician services of physical medicine and rehabilitation services.
In 2002, approximately one-third of Medicare beneficiaries discharged from hospitals utilized some form of PAC within one day of leaving the hospital.2 Although care received in different PAC settings varies to some extent as described above, many experts believe that patients with similar care needs may be treated in different PAC settings and that the choice of discharge destination is often driven by factors other than patient characteristics (e.g., availability of beds, physician or family preference, practice patterns). This issue is further discussed in Section C.
In an effort to contain the rapid growth in Medicare PAC expenditures during the late 1980s to mid 1990s, Congress passed the Balanced Budget Act of 1997 that required the development and implementation of prospective payment systems (PPSs) for all types of PAC. The PPSs have been phased in over the past seven years, beginning with SNFs in July 1998, followed by OP hospital care in August 2000, HH in October 2000, and IRFs in January 2002.
1. Reimbursement Under PPS
Under a PPS, instead of being tied to an individual provider’s cost of delivering services, fixed payments are established in advance of the service delivery and vary only by regional wage differences. This fixed payment is based on patient characteristics, called case mix, which determines the average resources required to meet the patient’s service needs. The case mix is determined by an assessment in each PAC setting. The payment algorithm and payment units for each PAC setting are different. The units of payment may be for the service, the day, an episode of care, or the entire stay. Brief descriptions of the PPS for each of the four PAC settings follow.
SNF PPS: Under the PPS for SNFs, facilities are paid a predetermined rate for each day of care based on the patient’s service needs, including all nursing, therapy, and ancillary services. Patients are assigned to 44 groups, referred to as resource utilization groups, version III (RUG-III), which are intended to classify patients according to their needs for nursing and therapy care. Assessments at five, 14, 30, 60, and 90-day intervals are based on the Minimum Data Set (MDS) patient assessment (which is further described in Section E). Medicare payment rates for each of the groups consist of three components: (1) a fixed amount for routine administrative expenses; (2) a variable amount based on intensity of nursing care required; and (3) a variable amount based on intensity of therapy services required. CMS recently revised the RUG-III classification system, increasing the number of RUG groups from 44 to 53. For beneficiaries needing skilled care following a hospital stay of at least three days, Medicare covers a maximum of 100 days of SNF care per episode of illness. The first 20 days of care are covered at 100 percent, and for the 21st through 100th day, the beneficiary is responsible for coinsurance equal to one-eighth of the inpatient hospital deductible per day. In 2006, the SNF coinsurance rate was $119 per day.3
IRF PPS: The IRF PPS pays facilities a predetermined rate per discharge for the entire stay based on the patient’s condition (diagnoses, functional and cognitive status, and age). Stays are categorized into one of 385 case mix groups (CMGs), which are derived based on information collected through the Inpatient Rehabilitation Facility Patient Assessment Instrument (IRF-PAI), which is described in more detail in Section E. Medicare coverage for IRF care is handled like other inpatient hospital stays in that Medicare beneficiaries are required to pay daily copayments that begin on the 61st day of the stay. They are not required to make copayments for the first 60 days after an inpatient hospital deductible that in 2006 was $952. The Medicare inpatient hospital benefit covers 90 days per episode, with a 60-day lifetime reserve (which the beneficiary may elect to use after the 90th day). The coinsurance for the 61st-90th day of care is a per day charge equal to one-fourth of the inpatient hospital deductible, and the coinsurance for 60 lifetime reserve days is equal to one-half of the inpatient hospital deductible. In 2006, the inpatient hospital coinsurance rate for days 61-90 was $238 per day, and for the lifetime reserve days, the coinsurance rate was $476 per day.3
HH PPS: Several years prior to implementation of PPS in HH, an interim payment system (IPS) was established to constrain per visit Medicare payments until the HH PPS was implemented. The PPS for HH pays agencies a predetermined rate for each 60-day episode of HH care. The payment rates are determined by the patient’s condition and anticipated service use, based on the Outcome and Assessment Information Set (OASIS), which is further discussed in Section E. In instances when fewer than five HH visits are provided, agencies are paid on a per visit (rather than per episode) basis. Patients receiving five or more visits are allocated to one of 80 home health resource groups (HHRGs), which are determined by diagnosis, functional capacity, and service use information gathered through the OASIS. HH episodes that require at least ten therapy visits receive substantially higher payments than those not meeting the threshold. Medicare Beneficiaries are not required to make copayments or pay coinsurance for HH services.
Hospital Outpatient PPS: The hospital OP PPS is established as a fee schedule that sets payment rates for individual services and procedures. Services and procedures are grouped into 570 ambulatory payment classifications (APCs). This PPS payment unit is based on services provided rather than patient case mix. As with the grouping systems under the previously described PPSs, however, each APC consists of services that are clinically similar and require comparable resources. Under Medicare, the coinsurance amount for OP care is determined by the APCs. Over the past several years, there has been substantial pressure to reduce coinsurance in the OP PPS to a target of 20 percent.4, 5, 6, 7 OP therapy services are excluded from the APCs and are covered by a fee schedule in which Medicare covers 80 percent and the beneficiary is responsible for 20 percent, which is paid out-of-pocket or from supplemental insurance. Therapy services require a physician order, a specific treatment plan, and must be provided by skilled, qualified providers. No limits exist for provision of therapy services in OP hospitals; however, an annual limit of $1,740 exists for combined OP physical therapy (PT) and speech therapy (ST) with a $1,740 limit for occupational therapy (OT) when services are provided outside a hospital in the year 2006 (certain exceptions to this policy are allowed). The caps on OP therapy services were originally implemented in 1999. However, moratoriums on enforcing the caps have delayed final implementation until 2006. The exception process to the caps allows Medicare beneficiaries meeting certain conditions to receive therapy above the caps.
2. Incentives and Preliminary Evidence of Changes Under PPS
Different types of payment systems (per discharge, per day, per episode, per service) create different financial incentives for the provision of care, often resulting in variation in practices and utilization across PAC settings.
SNF PPS: Under a per diem payment system, financial incentives exist to increase the number days over which service is provided. In their 2003 Medicare Data Book, the Medicare Payment Advisory Commission (MedPAC) indicated that the average length of stay in SNFs decreased by more than five days from 1996 to 1998 (prior to SNF PPS implementation), but progressively increased by approximately one day per year during the early years of the SNF PPS (between 1998 and 2001) -- providing initial evidence in support of the notion that the per diem SNF PPS provides an incentive for longer SNF stays.8
A study by Hutt et al. assessed the impact of the SNF PPS on the amount of therapy provided and community discharge rates in a six state demonstration of the SNF PPS in comparison to non-participating states.9 Under the SNF PPS demonstration, facilities were reimbursed using the RUG-III system, which assigns patients to one of seven “hierarchies.” The rehabilitation hierarchy, in which the payments are generally the highest, requires that patients receive therapy, and payments are determined by the quantity of therapy provided, the number of therapy specialties provided, and the patient’s functional status. Therefore, there is an incentive in the SNF PPS to provide therapy and to provide the amount of therapy that places patients in the most profitable groups. However, there is no incentive to provide more therapy than the minimum required to qualify for that payment group. Hutt and colleagues found that patients with the highest levels of function in participating sites received approximately 40 percent more therapy during the PPS demonstration than they had prior to the demonstration, while the volume of therapy received by similar patients in the non-participating sites remained constant. Interestingly, they found that the more intense levels of therapy in participating states were not associated with improved community discharge rates.
Further evidence of SNFs’ changing practices under the PPS was provided in an August 2002 Report to Congress by the General Accounting Office (GAO), which examined the mix of patients treated and Medicare services received across and within payment groups. The report’s findings indicated that two years after implementation of the SNF PPS: (1) the mix of SNF patients across categories of payment groups had shifted; and (2) the majority of patients in rehabilitation groups received less therapy than in early 1999 (shortly after implementation of the SNF PPS).10
IRF PPS: Per discharge payment systems (such as the one implemented under the IRF PPS) provide a fixed payment per patient discharge regardless of the patient’s length of stay. Therefore, under a per discharge payment system, it is in the provider’s best financial interest to discharge patients as quickly as possible, limiting the cost of services provided. Even prior to IRF PPS implementation Ottenbacher et al. found a significant decrease in IRF length of stay between 1994 and 2001 for patients within five impairment groups: stroke, brain dysfunction, spinal cord dysfunction, other neurologic conditions, and orthopedic conditions.11 Recent research by RAND Health examining the early stages of IRF PPS implementation found a decline in average IRF length of stay of 13 percent between 1999 and 2002, and 5.8 percent between 2001 to 2002.12, 13 This research also found that the rate of decline in length of stay varied across hospitals, with those with relatively long lengths of stay in 1999 having greater percentage declines between 1999 and 2002.
HH PPS: Prior to implementation of the HH PPS, an IPS was implemented in HH agencies that applied reimbursement caps to the previously established fee-for-service (FFS) system. Unlike the HH PPS, the IPS did not include outlier payments for high cost patients, and incentives existed for HH agencies to admit patients needing fewer, less expensive visits.14 Research by McCall et al. examining Medicare HH utilization and spending before and after implementation of the IPS for HH revealed a dramatic decrease in use of HH services following IPS implementation (i.e., 55 percent and 52 percent drop in visits and payments, respectively).15 Overall, the proportion of beneficiaries using HH services following the IPS implementation dropped by more than one-fifth and many HH agencies closed their doors. The HH PPS replaced the IPS in October 2000. Given that the HH PPS pays a fixed rate per 60-day episode regardless of the number of visits (as long as the episode includes at least five visits), an incentive exists for providers to reduce the number of visits provided. However, the additional payment associated with HH episodes consisting of ten or more therapy visits provides a strong incentive for provision of ten and no more than ten therapy visits. According to the MedPAC, the average number of HH visits and minutes per episode and have decreased (by 47 percent and 37 percent, respectively) between 1997 and 2002, but the amount of therapy delivered as proportion of those visits has increased by 17 percent.2
Changing Patterns of Care and Use of Multiple-Provider Episodes: Due to the substantial changes in Medicare PAC reimbursement under PPS and the varying incentives under each system, interest has grown in whether PAC utilization patterns have changed subsequent to PPS implementation. A recent study by Direct Research LLC, which compared episodes of PAC use in 1996 (prior to implementation of any PAC PPS) and 2001 (after PPS implementation in SNFs and HH) found that the number episodes involving HH only decreased by 46 percent; whereas episodes involving only SNF care increased by 28 percent and those involving care by long-term care hospitals (LTCHs), IRFs, or psychiatric hospitals increased by 33 percent.16 Episodes consisting of SNF care followed by HH care decreased by 13 percent, and those involving other combinations of providers increased by 17 percent.
Another study by McCall et al. examined patterns of PAC utilization for Medicare beneficiaries with stroke, chronic obstructive pulmonary disease (COPD), heart failure, hip fracture, and diabetes during the period when the HH IPS was in effect and the SNF PPS was being instituted.17 They found substantial changes in patterns of PAC, with use of IRFs increasing and use of HH services falling as both an initial PAC setting and a subsequent setting following initial treatment in an institutional setting.
Earlier research by Liu et al. in 1999 revealed that prior to implementation of PAC PPS, 51 percent of PAC patients used HH care only, 26 percent used SNF care only, 4 percent used IRF care only, and 19 percent used more than one PAC setting.18 Now that PPS has been implemented in all PAC settings, further research is needed to examine the effects of these new systems on PAC utilization and patterns of care.
Given the varying incentives under the PPSs for different PAC settings, one might expect that the number of PAC episodes consisting of more than one provider would increase, especially when ownership or contractual relationships play a role (e.g., when an IRF, SNF, and/or HH agency fall under the same ownership, which is sometimes the case for hospital-based PAC facilities). Few studies to date have directly addressed this issue. The previously mentioned study by Direct Research LLC found a decrease in episodes involving SNF care followed by HH care, but an increase in other types of multiple-provider episodes.16 A study by Coleman et al., the goal of which was to describe patterns of post-hospital care transitions from 1997-1998, found 46 distinct types of care patterns during the 30 days following acute hospital discharge, 61 percent of which were limited to a single transfer, 18 percent of which involved two transfers, and 13 percent of which involved three or more transfers -- with an additional 8 percent that resulted in death.19 Concerns have been raised regarding the potential negative effects of poorly executed transitions between health care settings, with patient safety issues and medication errors of particular concern.20, 21 Further investigation is needed to determine the impacts of PAC PPS on the occurrence of multiple-provider episodes, as well as the outcomes associated with multiple care transitions within a PAC episode.
Evidence suggested that prior to PPS at least some degree of overlap existed in the characteristics of patients treated across SNFs and IRFs, with controversy over the overlap between HH agency and institutional PAC. Work by Kramer et al. involving a database of 518 hip fracture patients and 485 stroke patients treated in SNFs or IRFs utilized propensity score methodology to predict placement into SNFs vs. IRFs by stratifying on the probability of assignment to one type of PAC setting.22 Kramer et al. found a number of overall differences between patients treated in IRFs and in SNFs; on average, IRF patients had more functional independence upon admission, better pre-morbid function, better cognitive function, and were more likely to have an able and willing caregiver than SNF patients. However, stratification for probability of SNF placement using propensity scores demonstrated that certain patient subgroups were treated in both settings, whereas other subgroups were treated predominately in one setting or the other. For example, hip fracture patients with caregivers and good physical and cognitive function were represented in both SNFs and IRFs, whereas hip fracture patients with no caregiver, and particularly those with cognitive impairment, were prevalent in SNFs and extremely rare in IRFs. Stroke patients who had no caregivers and lower cognitive function were found only in SNFs, whereas stroke patients who had caregivers and higher cognitive function were prevalent in both settings, although more so in IRFs. Both hip fracture and stroke patients in IRFs were more likely to participate in social and recreational activities than patients in SNFs. Through this stratification process, five variables were found to determine the strata for hip fracture: availability of a caregiver, cognition, participation in social and recreational activities, functional independence, and pre-morbid walking ability. Three of these variables -- availability of a caregiver, cognition, and participation in social and recreational activities -- determined the strata for stroke. Given the differences between the two settings, these covariates could be considered critical for inclusion in any model controlling for selection bias between SNFs and IRFs.
Research by Neu, Harrison, and Heilbrunn of RAND explored utilization rates across different health service market areas to determine whether market areas with unusually high utilization of one type of PAC setting demonstrate relatively low utilization of other types of PAC settings. These authors found some evidence for substitution between SNF and HH care, an effect that was more pronounced for certain diagnoses than for others.23 Less consistent evidence of substitution patterns was found through this research for care involving IRFs. Early work by Kramer et al. comparing nursing home and HH case mix found pronounced differences in functional and cognitive ability between Medicare patients treated in the two settings, with nursing home patients much more likely to be functionally dependent.24
In a later study of PAC utilization, Gage found that use of different PAC settings varies to a great extent by geographic region, and the potential for substitution among settings varies by diagnosis.25 Similarly, research by Bronskill et al. examined the extent to which factors beyond patient characteristics contribute to variation in post-acute service use in elderly Medicare patients with acute myocardial infarction.26 After controlling for patient and hospital characteristics, researchers found that for-profit ownership of the acute hospital and the provision of HH services through the acute hospital or a subsidiary significantly predicted the use of PAC services, suggesting that the organizational structure of hospitals can influence the patterns of PAC service use for clinically similar patients.
Kane et al. found substantial geographic variation in both the overall level of PAC use and the patterns of PAC, which the authors believe are likely to reflect differences in PAC availability and practice styles across regions.27 Similary, Lee, Huber, and Stason found wide geographic variation in the use of different PAC settings for stroke rehabilitation, indicating substantial variation in treatment practices and substitution between different PAC rehabilitation settings across different geographic regions.28 Research by Liu et al. found that SNF and HH care may substitute for one another under certain circumstances.29 Data sources included: the Medicare Current Beneficiary Survey, which contained data on patient characteristics; Medicare claims, which included data on SNF and HH service use; and data from various sources on market area characteristics. They found that older patients and those with a history of Alzheimer’s disease were more likely to use SNFs than HH, and that patients with emphysema were more likely to use HH than SNFs. They also found that patients with a second source of health insurance (Medicaid or supplemental insurance) were more likely to use SNFs than HH, and that use of SNF care increased as SNF and IRF bed availability increased.
Taken together, these findings suggest that factors other than patients’ clinical characteristics -- such as geographic location, acute hospital ownership type, PAC provision through the acute hospital, availability of PAC services, and insurance coverage -- often played a role in determining the setting in which PAC was provided prior to PPS. In the pre-PPS era there was evidence of substitution among IRFs and SNFs for some subgroups of patients, but controlling for the patient characteristics that differed across these settings (such as cognition, pre-morbid function, and social support) was critical in any comparisons. The overlap between HH and institutional PAC was less clear, and patient characteristics beyond diagnosis seemed to be strongly associated with placement. The extent of substitution in the post-PPS era remains to be seen.
In recent years, studies have compared outcomes and costs of PAC services received in different settings. Among the outcomes most commonly examined are mortality, physical function, rehospitalization, and return to community. Because care for certain clinical conditions such as stroke, hip fracture, and joint replacements is frequently provided in various PAC settings, these conditions are most frequently examined in research comparing outcomes and costs across sites of PAC. These studies all attempt to take advantage of the natural variation that exists in PAC treatment settings; however, they all struggle with the challenge of selection bias by setting, which confounds the comparisons. Thus, the strength of the evidence generated by these studies should be considered in the context of the overall design, the covariates that are investigated, and the analysis methods. Furthermore, none of the work to date takes into consideration the multiple-providers that contribute to PAC outcomes; rather, they focus only on the initial treatment setting.
1. Stroke
A retrospective study of 331 patients from an IRF and 97 from a SNF by Keith et al. found that IRF treatment resulted in greater functional improvement and a somewhat higher likelihood of discharge to community than treatment in a SNF.30 However, the study had significant limitations in that 5 percent of the SNF group and 14 percent of the IRF group were admitted from a setting other than the hospital (including other PAC settings), SNF patients had 4.5 fewer days since their stroke upon admission to PAC, and the authors controlled only for demographic variables and amount of therapy in this comparison. Two measures of cost-effectiveness (charges per successful discharge to the community and charges per one-point gain in functional improvement on the Functional Independence Measure, or FIM) revealed SNF care to be a more cost-effective option than IRF care.
The aforementioned 1997 study by Kramer et al. in 92 sites found that stroke patients treated in IRFs had better outcomes at six months in terms of both community residence and function than those treated in SNFs, but at a much higher cost.22 This study used an extensive primary database including pre-stroke function, social situation, stroke severity, and even uniform readings of CT/MRI studies.
In a study of 487 stroke patients from three cities discharged to home without HH (n=160), HH (n=125), SNF (n=123) and IRF (n=79), Chen et al. found that stroke patients discharged to HH showed more improvement in activity of daily living (ADL) function than those discharged to IRF, SNF, or home without home care at six weeks, six months, and one year post-discharge.31 In addition, they found that patients discharged to IRFs demonstrated more functional improvement at these time points than patients discharged to SNFs. Data sources included patient and family interviews, hospital medical records, and Medicare billings. To adjust for selection bias across the various PAC settings, Chen et al. employed a two-stage instrumental variable estimation method. They also found that costs for patients receiving HH were considerably lower than those receiving care in an institutional setting (SNF or IRF).
A study by Kane et al. using the same data source found that stroke patients receiving PAC in SNFs had higher mortality rates at six weeks, six months, and one year than those in IRFs or HH, and that stroke patients discharged to HH had lower rehospitalization rates at one year than those discharged to SNFs or IRFs.32 Independent variables examined came from interviews, the Medicare Denominator File, and medical records; they included patient characteristics such as functional independence, living arrangements, cognitive status, and informal supports, as well as various case mix variables to adjust for stroke severity.
2. Hip Fracture
Over the years, studies of outcomes and costs for hip fracture patients treated in different PAC settings have yielded mixed results. The previously mentioned study by Kramer et al. found comparable outcomes in both SNFs and IRFs, with IRF care at a substantially higher cost.22 A study conducted by Deutsch et al. involving clinical data review of 29,793 Medicare FFS beneficiaries who received treatment for hip fracture in 1996 or 1997 found that SNF-based rehabilitation was a less costly alternative to IRF care, yielding similar or better improvement in motor functional status and community discharge outcomes in most areas assessed.33 This study examined a number of covariates including motor and cognitive function, time from fracture to PAC admission, type of hip fracture repair, pre-hospital living arrangements, and geographic location, but did not include caregiver support or participation in social or recreational activities. The potential for sample selection bias was examined using propensity scores.
Other research suggests that SNFs may not be the best setting for provision of PAC for hip fracture patients. Kane et al. found that hip fracture patients treated in HH or IRFs had significantly more functional improvement than those treated in SNFs at six weeks, six months, and one year.32 Independent variables examined included patient characteristics such as pre-morbid and PAC discharge functional independence, living arrangements, self-reported pre-morbid health status, cognitive status, and informal supports, as well as various case mix variables to adjust for stroke severity. However, pre-fracture walking ability and participation in activities, two covariates that Kramer et al. found to be critical, were not included.
In a study of 42 hip fracture patients admitted to IRF and 34 admitted to SNF from one hospital, Munin and colleagues found that hip fracture patients receiving IRF care were more likely to regain 95 percent of their pre-fracture function by 12 weeks post-hospital discharge than patients receiving SNF care.34 IRF patients were also more likely than SNF patients to be discharged home, and SNF patients were more likely than IRF patients to be discharged to a nursing home. Covariates examined included depression, cognition, medical complexity, pre-fracture motor function, delirium, participation during rehabilitation, and social support. This study suffered from serious risks of selection bias in that SNF patients were more cognitively impaired, had worse social supports, had worse function immediately post-fracture, and 12.5 percent were admitted from personal care homes in contrast to 5 percent of IRF patients. Whether there was actual overlap between groups is uncertain, and if there was overlap, the author’s ability to adjust for selection differences with these small samples is doubtful.
3. Joint Replacement
In a large-scale comparison of Medicare spending and outcomes for all elderly beneficiaries who underwent hip or knee replacements (with no preceding hip fracture) and were discharged from an acute hospital between January 2002 and June 2003, Beeuwkes Buntin et al. found no differences in mortality between patients across different sites of PAC.35 However, using an instrumental variable approach they found that patients receiving care in IRFs and SNFs were more likely than HH patients to be institutionalized 120 days after their initial hospitalization. They also found that Medicare payments for PAC episodes in IRFs and SNFs were far higher than for those receiving HH care, with IRF payments being the highest of the three. Data sources included Medicare claims, MDS and IRF-PAI patient assessment data, cost report and provider of service (POS) data, and hospital discharge records. Independent variables assessed included such items as individual predictors (e.g., age, gender, race, place of residence), clinical predictors (comorbidities and complexities derived from hospital discharge records), discharging hospital characteristics (e.g., size, teaching status, ownership status, Medicare patient percentage), PAC availability (distance from patient’s home to the closest provider and number of PAC providers within a specified radius around the patient’s home), and functional status (using a measure similar to the Barthel Index derived from the MDS and IRF-PAI). Important covariates such as availability of a caregiver, cognition, participation in activities, and pre-morbid walking ability were not included.
The Medicare, Medicaid, and State Children’s Health Insurance Program Benefits Improvement and Protection Act of 2000 mandated the Secretary of Health and Human Services to report, by January 1, 2005, on the development of health and functional assessments for various Medicare beneficiaries using PAC and other specified services. The legislation specified that information across providers be readily comparable and that only information necessary to meet program objectives be collected. The Secretary was also required to make recommendations regarding use of patient assessment instruments for payment purposes.
Currently, Medicare requires that patients be evaluated in three of the four PAC settings discussed in this chapter using different patient assessment instruments. The MDS is used in SNFs, the IRF-PAI is used in IRFs, and the OASIS is used in HH. Currently, no assessment instrument is required for patients receiving OP rehabilitation care. These assessment tools differ in terms of the elements they assess, their assessment periods, and their rating scales. A recent empirical comparison of the MDS, IRF-PAI, OASIS and the physical function scale of the Short-Form-36 (an assessment sometimes used with ambulatory care populations) revealed differences between and limitations within each of the instruments in terms of their content, breadth of coverage, and measurement precision.36 In addition, the tools were designed to achieve different objectives (e.g., care planning, quality measurement, outcome monitoring, and patient classification) -- differences that limit their comparability for measuring quality of care.
In their June 2005 Report to Congress, MedPAC recommended that data elements be identified for use by CMS in establishing payments and evaluation of patient outcomes across PAC settings, asserting that the data elements “predict resource use; capture relevant clinical data; be reliable, valid, and well accepted; and minimize the burden to providers and CMS.”2 The Institute of Medicine also recommends that “the Federal Government accelerate, expand, and coordinate its use of standardized performance measurement and reporting to improve health care quality,” and that current performance measurement mechanisms within and across government programs be replaced by standardized measurement and reporting mechanisms.37 In working toward these goals, it will be necessary to determine the core outcome measures that accurately and reliably measure quality of care and outcomes both within and across PAC settings.
Under the Deficit Reduction Act of 2005, Congress required that CMS explore costs and outcomes across different PAC settings and episodes. This demonstration will involve examination of the use of a comprehensive assessment tool at hospital discharge to determine appropriate PAC placement.
This study has three primary aims:
1. Compare Quality, Outcomes, and Medicare Costs of PAC Episodes Involving Single and Multiple-Providers for Medicare Beneficiaries with Stroke after PPS Implementation
Using stroke as a tracer condition, this study examines PAC outcomes and costs for single and multiple-provider episodes of care lasting 90 days after discharge from the hospital. Outcomes studied include mortality, rehospitalization, return to community residence, and functional outcomes (including ADLs, instrumental activities of daily living (IADLs), social/role function, and function related to walking). Few prior studies have examined quality and outcomes of multiple-provider episodes, particularly those involving OP rehabilitation care, and none have done so subsequent to PPS implementation in all PAC settings. This study, therefore, represents a unique opportunity to explore these various facets of PAC during the post-PPS era.
2. Compare and Contrast Various Quality of Care and Outcome Measures that Can be Used Across PAC Settings
This study explores whether a core set of measures can be identified that captures outcomes and quality of PAC episodes involving both single and multiple-providers. Given the current policy interest in identifying a uniform assessment for quality monitoring and payment purposes, this research will provide invaluable information in moving toward this goal.
3. Examine the Effect of PPS Implementation on Patterns of PAC Utilization for Stroke Patients
As previously discussed, the implementation of four different PPSs for PAC services has recently occurred. No studies to date have assessed the effects of PPS on PAC utilization and patterns of care following PPS implementation using recent data. Given the financial incentives that exist under the different PPSs and the way providers respond to these incentives over time, the findings of this study on such issues should prove to be particularly policy relevant.
DataPRO Team. Skilled nursing facilities prospective payment system quality medical review Data Analysis Pro: Final Report for CMS Contract 500-99-CO01, Attachment J-19. 2002.
Medicare Payment Advisory Commission. Report to the Congress: issues in a modernized Medicare program. Chapter 5: Payment for post-acute care. 2005.
Medicare Learning Network. Medlearn matters: information for Medicare providers. Update to Medicare deductible, coinsurance, and premium rates for 2006. MM4132. November 4, 2005. Centers for Medicare & Medicaid Services.
Center for Medicare Education. Medicare Outpatient Prospective Payment System. Issue Brief 2003; 4(1).
Centers for Medicare & Medicaid Services. Medicare announces payment rates and policy changes for hospital outpatient services in 2006. Beneficiary coinsurance rates continue to fall. Medicare News 2005.
Medicare Payment Advisory Commission. Report to the Congress: Medicare payment policy. Chapter 9: Reducing beneficiary coinsurance under the hospital outpatient prospective payment system. 2001; 141-151. Washington, DC: MedPAC.
MedPAC. Medicare basics: Outpatient therapy services. December 28, 2005. Washington, DC: MedPAC.
Medicare Payment Advisory Commission. A data book: healthcare spending and the Medicare program. Section 8: Post-acute care. 2003.
Hutt E, Ecord M, Eilersten TB, Frederickson E, Kowalsky JC, Kramer AM. Prospective payment for nursing homes increased therapy provision without improving community discharge rates. J Am Geriatr Soc 2001; 49: 1071-1079.
General Accounting Office. Skilled nursing facilities: providers have responded to Medicare payment system by changing practices. GAO-02-841. 2002. Washington, DC.
Ottenbacher KJ, Smith PM, Illig SB, Linn RT, Ostir GV, Granger CV. Trends in length of stay, living setting, functional outcome, and mortality following medical rehabilitation. JAMA 2004; 292(14): 1687-1695.
Beeuwkes Buntin M, Carter GM, Hayden O, Hoverman C, Paddock SM, Wynn BO. Inpatient rehabilitation facility care use before and after implementation of the IRF prospective payment system. 2006. RAND Health.
Paddock SM, Escarce JJ, Hayden O, Beeuwkes Buntin M. Changes in patient severity following implementation of the inpatient rehabilitation facility prospective payment system. 2006. RAND Health.
Medicare Payment Advisory Commission. Report to the Congress: Medicare payment policy. Section 2D: Assessing payment adequacy and updating payments for home health services. 2003. Washington, DC: MedPAC.
McCall N, Komisar HL, Petersons A, Moore S. Medicare home health before and after the BBA. Health Aff 2001; 20(3): 189-198.
Medicare Payment Advisory Commission. Report to Congress: variation and innovation in Medicare. Chapter 5: Monitoring post-acute care. 2003.
McCall N, Korb J, Petersons A, Moore S. Reforming Medicare payment: early effects of the 1997 balanced budget act on postacute care. Milbank Q 2003; 81(2): 277-303.
Liu K, Gage B, Harvell J, Stevenson D, Brennan N. Medicare’s post-acute benefit: background, trends, and issues to be faced. For contract #HHS-100-97-0010. 1999. The Urban Institute [Available http://aspe.hhs.gov/daltcp/reports/mpacb.htm]
Coleman EA, Min S, Chomiak A, Kramer AM. Posthospital care transitions: patterns, complications, and risk identification. Health Serv Res 2004; 39(5): 1449-1465.
Coleman EA, Berenson RA. Lost in transition: challenges and opportunities for improving the quality of transitional care. Ann Intern Med 2004; 141(7): 533-536.
Moore C, Wisnivesky J, Williams S, McGinn T. Medical errors related to discontinuity of care from an inpatient to an outpatient setting. J Gen Intern Med 2003; 18: 646-651.
Kramer AM, Steiner JF, Schlenker RE, Eilertsen TB, Hrincevich CA, Tropea DA, et al. Outcomes and costs after hip fracture and stroke: a comparison of rehabilitation settings. JAMA 1997; 277(5): 396-404.
Neu CR, Harrison SC, Heilbrunn JZ. Medicare patients and postacute care: who goes where? 1989; 1-83. Santa Monica, CA: The RAND Corporation.
Kramer AM, Shaughnessy PW, Pettigrew ML. Cost-effectiveness implications based on a comparison of nursing home and home health case mix. Health Serv Res 1985; 20(4): 387-405.
Gage B. Impact of the BBA on post-acute utilization. Health Care Fin Rev 1999; 20(4): 103.
Bronskill SE, Normand ST, McNeil BJ. Post-acute service use following acute myocardial infarction in the elderly. Health Care Fin Rev 2002; 24(2): 77-93.
Kane RL, Wen-Chieh L, Blewett LA. Geographic variation in the use of post-acute care. Health Serv Res 2002; 37(3): 667-682.
Lee AJ, Huber JH, Stason WB. Poststroke rehabilitation in older Americans. The Medicare experience. Med Care 1996; 34(8): 811-825.
Liu K, Wissoker D, Rimes C. Determinants and costs of post-acute care use of Medicare SNFs and HHAs. Inquiry 1998; 35(1): 49-61.
Keith RA, Wilson DB, Gutierrez P. Acute and subacute rehabilitation for stroke: a comparison. Arch Phys Med Rehabil 1995; 76(6): 495-500.
Chen Q, Kane RL, Finch MD. The cost-effectiveness of post-acute care for elderly Medicare Beneficiaries. Inquiry 2000; 37: 359-375.
Kane RL, Chen Q, Finch M, Blewett L, Burns R, Moskowitz M. Functional outcomes of posthospital care for stroke and hip fracture patients under Medicare. J Am Geriatr Soc 1998; 46: 1525-1533.
Deutsch A, Granger CV, Fiedler RC, DeJong G, Kane RL, Ottenbacher KJ, et al. Outcomes and reimbursement of inpatient rehabilitation facilities and subacute rehabilitation programs for Medicare beneficiaries with hip fracture. Med Care 2005; 43(9): 892-901.
Munin MC, Seligman K, Dew MA, Quear T, Skidmore ER, Gruen G, et al. Effect of rehabilitation site on functional recovery after hip fracture. Arch Phys Med Rehabil 2005; 86: 367-372.
Beeuwkes Buntin M, Deb P, Escarce J, Hoverman C, Paddock S, Sood N. Comparison of Medicare spending and outcomes for beneficiaries with lower extremity joint replacements. A study conducted by RAND Health for the Medicare Payment Advisory Commission. June 2005.
Jette AM, Haley SM, Ni P. Comparison of functional status tools used in post-acute care. Health Care Fin Rev 2003; 24(3): 13-24.
Institute of Medicine. Leadership by example: coordinating government roles in improving health care quality. 2005. National Academies Press.
MedPAC reported in 2005 that one-third of the Medicare beneficiaries discharged from the hospital used at least one day of PAC services. As described in Chapter 1, CMS has recently implemented PPSs for each of the PAC settings that are intended to curtail the rapid increase in the expenditures for PAC. While all PAC settings offer the rehabilitation needed by persons who have had a stroke, the assessment used, services provided, and incentives from the PPSs differ widely across PAC settings. To explore the role of various PAC settings for stroke patients, this study addressed the three primary objectives as described below.
Compare Quality, Outcomes, and Medicare Costs of PAC Episodes Involving Single and Multiple-Providers for Medicare Beneficiaries with Stroke after PPS Implementation. The first step in this analysis was to describe the patterns of stroke care provided to elderly Medicare beneficiaries from admission to an IRF, SNF, or HH agency until 90 days after admission. The characteristics of patients admitted to each setting and to the major multiple-provider PAC episodes were then compared to determine the potential for substitution among providers. Further analyses were conducted that found similarities in characteristics between patients receiving care in IRFs followed by HH agency and IRFs followed by OP care, and between patients admitted directly to SNFs and those admitted to IRFs followed by SNFs. These similarities suggest possible substitution of PAC settings. Outcomes and costs of care were then compared for each of these pairs.
Compare and Contrast Various Quality of Care and Outcome Measures that Can Be Used Across PAC Settings. Because of the lack of uniformity in assessment items and time periods across PAC instruments, we relied on a large-scale primary data collection effort to evaluate core measures. These core measures within 90 days of admission to PAC included: residence in the community; functional recovery in ADLs, IADLs, ambulation, and social/role function; global self-reported health; and satisfaction. We developed indices for the four functional domains and examined the likelihood of recovery in each. We used all of these measures in comparisons across episodes of PAC.
Examine the Effect of PPS Implementation on Patterns of PAC Utilization for Stroke Patients. We examined the effect of PPS implementation on patterns of PAC utilization by studying the population of Medicare stroke patients from 1998 to 2004. Medicare Provider and Analysis Review (MedPAR) data provided records for every inpatient stay that were linked into 90-day episodes of PAC. We analyzed trends in various aspects of PAC utilization including: discharge destination, length of stay, and distribution of stroke patients among providers. Examination of geographic differences was also performed. Finally, regression models of the likelihood of selected discharge destinations reinforced the trends observed, using the limited case mix adjustment data available from the PAC data.
This chapter describes sampling methods for PAC settings and patients, data and data collection, and the analysis variables. Details on the statistical methods used to address the three objectives can be found in the relevant chapters to avoid confusion on the methods employed to address each objective.
1. Provider Selection and Recruitment
The study objectives relate to PAC for Medicare FFS beneficiaries who were hospitalized for a stroke and subsequently received PAC services in differing patterns of care. The primary settings of PAC reviewed for this study were IRFs, SNFs, and HH agencies. For the purposes of estimating the size of the universe of providers and patients for IRFs and HH agencies, we used 1999 Medicare Part A claims data files constructed by the Research Data Assistance Center. These files excluded providers with ten or fewer beneficiaries in order to preserve provider confidentiality. For SNFs, we used a more refined national claims-based file designed specifically for tracking SNF care (DataPRO) from which providers with ten or fewer stays were also excluded.1
The primary stratifier for sampling in this study was provider type. However, the number of providers for each provider type is unbalanced and the patient loads for patients with stroke differ among provider types. To maximize the similarities of selected subjects across provider types for comparison purposes, while assuring a representative mix of facilities within the operational and budgetary limitations of the project, we conducted a secondary explicit stratification on two other factors. First, providers were stratified on whether they were located in a community with low or high use of IRFs. For each community (defined as CMSA, MSA, or state-specific non-MSA), we estimated the ratio of IRF admissions relative to acute care hospitalizations for Medicare patients. This ratio was inversely related to the SNF admission/acute care hospital ratio (correlation -0.29; P<0.001). Stratifying on this ratio at 0.040 (4 percent of Medicare acute hospital stays admitted to IRF), approximately 62 percent of SNF patients and 29 percent of IRF patients were treated in low rehabilitation hospital use communities, whereas 38 percent of SNF patients and 71 percent of IRF patients were treated in high rehabilitation hospital use communities. By sampling in proportion to these two strata, more SNF patients were included from areas where fewer patients were admitted to IRFs and more IRF patients were enrolled from communities where fewer patients were admitted to SNFs. This stratification helped to ensure that both SNF and IRF patients were sampled from the same community, which improved the precision in the estimates.
A secondary explicit stratification was based on statewide availability of community-based services, which has a substantial influence on one of the primary outcomes for comparing the different modalities -- rate of community residence at 90 days after admission to PAC. States that were above the median on residential care beds per capita and below the median on nursing facility beds per capita were classified as high on community-based services and those with the inverse were classified as low. Thus, states that had high numbers of licensed assisted living facility beds and other types of residential care per capita and low numbers of nursing home beds per capita were high on community-based services. In the nine states that were either above or below the median for both of these criteria, the number of Medicaid recipients per thousand beneficiaries enrolled in a statewide home-based services waiver program was used to classify the state, recognizing that this was not a perfect classification method because these programs vary in their use and coverage across states. Facilities were then assigned a value of this stratifier based on the state in which they were located.
Only providers with a history of admitting at least 12 stroke patients per year were included in the study sample to reduce the project resources and burden that would be required to enroll facilities with a low volume of such Medicare admissions. Within each of the sampling cells, we initially selected the desired number of facilities using a probability-proportionate-to-size sampling technique so that larger facilities of the same type were given a higher probability of selection than the smaller ones of that type. A stratified sample of each type of facility (IRF, SNF, HH agency) was selected from the national census of Medicare facilities. Although this method resulted in a sample that was more likely to include large facilities, concerns about bias were tempered in that we did not believe that outcomes and quality would be tied systematically to facility size across facility types.
Each of the initial sampled facilities was contacted for enrollment in the study. Recruitment was performed through phone calls and written communication with facilities by research staff who continued to pursue each facility until a definite acceptance or refusal was proffered. Participating facilities were asked to complete a facility questionnaire to verify the address and contact information of the facility, as well as to obtain further information regarding the volume of Medicare stroke patients the facility admitted on a yearly basis and the names and telephone numbers of staff members who could serve as the facility’s data collector. We asked each facility to provide the contact information for at least one data collector. With the increased attention to protecting patient health information, many facilities required approval from internal Institutional Review Boards (IRBs). In those facilities, research staff proceeded to complete the requested forms in order to comply with the review process. With the need for IRB approval and the need to find and train data collectors who met the study standards, several months elapsed between initial contact and the first screened patient in some facilities. While an effort was made to enroll each of the facilities, there may be some non-response bias based on those not enrolled. However, we do not believe that responsiveness was tied to a facility’s predilection for secondary PAC, making it unlikely to create significant bias in our results.
A second stratified sample of IRFs and four additional stratified samples of SNFs were created using the methodology described above, as investigators determined a need to expand the number of enrolled facilities. Table 2.1 describes the facilities that participated in the study. A total of 88 facilities participated, comprised of 35 IRFs, 33 SNFs, and 20 HH agencies in 20 states. For the 12 SNFs that screened patients but did not enroll any subjects, participation lasted an average of 11 months. For the seven HH agencies that screened patients but did not enroll any subjects, participation lasted an average of 12 months.
| TABLE 2.1: Characteristics of Participating Post-Acute Care Facilities | |||
|---|---|---|---|
| IRF | SNF | HH Agency | |
| Participating Facilities | 35 | 33 | 20 |
| Facilities that Enrolled at Least One Subject | 35 | 21 | 13 |
| Medicare Admissions Mean (Std Deviation) | 652 (587) | 266 (167) | 2,291 (2,944) |
| Strokes Treated Prior Year Mean (Std Deviation) | 122 (121) | 18 (12) | 118 (196) |
| Ownership n (percent) | |||
| For-Profit | 5 (14%) | 11 (52%) | 2 (15%) |
| Non-Profit | 24 (69%) | 9 (43%) | 11 (85%) |
| Government | 6 (17%) | 1 (5%) | 0 (0%) |
| Total Enrolled Subjects | 555 | 62 | 57 |
| Subjects Per Facility Mean (Std Deviation) | 15.9 (14.4) | 3.0 (3.8) | 4.4 (4.6) |
| Range | 1 - 48 | 1 - 17 | 1 - 15 |
2. Subject Selection and Recruitment
Using a screening form, the on-site data collector reviewed records of all new stroke admissions to identify stroke patients who were eligible for the study. Subject eligibility was limited to Medicare beneficiaries admitted to PAC for an acute stroke (either first or recurrent), with the diagnoses based on ICD-9 codes (study codes and their descriptions can be found in Appendix A as part of the screening form that the data collectors filled out on each potential subject) and confirmed by chart review. Hospitalization for an acute stroke must have occurred within the 30 days prior to PAC admission without an intervening PAC episode. Subjects had to be at least 65 years of age and if cognitively impaired, or with severe speech and language impairment (for example, aphasia), must have had an able and willing caregiver/proxy available for interview. Because we targeted post-acute rehabilitation, we excluded individuals who were not able to receive therapy, were comatose, or resided in a long-term nursing facility prior to their acute stroke.
| FIGURE 2.1: Sample Selection |
 |
Figure 2.1 provides a breakdown of sample selection for screened patients at all PAC providers. Data collectors identified 3,630 hospital admissions for stroke admitted to a participating PAC provider. Confirming the diagnosis of stroke and admission to the PAC setting within 30 days of the hospitalization left a total of 3,175 cases to represent the population of stroke survivors in PAC settings of interest. Approximately 31 percent of confirmed stroke patients receiving care in the study facilities were under 65 years of age and were eliminated from the study. Our population of interest included only Medicare patients who were subject to PPS (non-HMO) for whom the study facility was the first PAC admission for that stroke, eliminating approximately 30 percent of elderly stroke patients. These patients were then subject to exclusionary criteria necessary to acquire accurate data for our study and to focus on rehabilitation care. The exclusionary criteria included: not receiving therapy, non-English speaking, comatose, nursing home resident prior to hospitalization, and no identifiable proxy. One-hundred fifty-seven (157) patients (10 percent) were excluded, leaving 1,390 eligible for our study.
| TABLE 2.2: Exclusions and Eligibility Criteria by Provider Type | ||||||
|---|---|---|---|---|---|---|
| IRF | SNF | HH agency | ||||
| n | % | n | % | n | % | |
| Confirmed Stroke Casesa | 2,335 | 73.5% | 377 | 11.9% | 463 | 14.6% |
| Exclusions:b | ||||||
| Age <65 | 814 | 34.9% | 61 | 16.2% | 103 | 22.2% |
| Prior PAC | 110 | 4.7% | 64 | 17.0% | 182 | 39.3% |
| HMO | 215 | 9.2% | 64 | 17.0% | 58 | 12.5% |
| Any of Above Exclusions | 1,128 | 48.3% | 183 | 48.5% | 317 | 68.5% |
| >65/FFS/First PACc | 1,207 | 100.0% | 194 | 100.0% | 146 | 100.0% |
| Eligibility Criteria:d | ||||||
| Receiving therapy | 2 | 0.2% | 14 | 7.2% | 10 | 6.8% |
| English speaking | 60 | 5.0% | 5 | 2.6% | 5 | 3.4% |
| Not Comatose | 4 | 0.3% | 9 | 4.6% | 0 | 0.0% |
| Not nursing home resident prior | 19 | 1.6% | 17 | 8.8% | 8 | 5.5% |
| Had a proxy (if needed) | 13 | 1.1% | 1 | 0.0% | 0 | 0.0% |
| Any of Above | 96 | 8.0% | 39 | 20.1% | 22 | 15.1% |
| Remaining Eligible Cases | 1,111 | 92.0% | 155 | 79.9% | 124 | 84.9% |
| Enrollede | 555 | 50.0% | 62 | 40.0% | 57 | 46.0% |
|
||||||
One-hundred sixteen (116) patients (8.3 percent) of the cases eligible for our study were randomly eliminated to moderate burden when too many patients were admitted in a single week. The remaining eligible patients were contacted by the data collector for recruitment into the study and to schedule an interview. Twenty-five percent (25 percent) of the approached patients refused, and of the remaining patients, 5.3 percent died or were discharged before data collection was conducted. Two-hundred twenty-nine (229) patients were not enrolled largely because the data collector could not complete the interview within the 7-10 day interval since admission due to issues with the data collector or patient schedule. The final sample for the study was 674 patients. Of these, claims data were matched for 642 patients, so analyses requiring claims data were on this slightly smaller sample.
Of the 3,175 cases with a confirmed stroke and hospitalized in 30 days, the majority were admitted to IRFs (74 percent), with the remainder split almost evenly between SNFs and HH agencies (Table 2.2). Despite attempts to enroll the highest volume SNFs and HH agencies into the study, the 33 SNFs admitted an average of 11.4 stroke patients (0.9 per screening month) during the study period and the 20 HH agencies admitted an average of 23.1 stroke patients (1.9 per screening month), in contrast to 66.7 stroke patients admitted per IRF for the 35 IRFs (4.9 per screening month).
| TABLE 2.3: Characteristics of Participating Stroke Post-Acute Care Patients | |
|---|---|
| Demographic | % (n) |
| Age | |
| 65 - 74 | 34.1% (230) |
| 75 - 84 | 46.6% (314) |
| 85+ | 19.3% (130) |
| Mean (Std Deviation) | 77.7% (7.1) |
| Female | 55.6% (375) |
| Marital Status | |
| Married | 46.7% (313) |
| Widowed | 43.2% (290) |
| Divorced | 7.0% (47) |
| Separated | 0.9% (6) |
| Never Married | 2.2% (15) |
| Race and Ethnicity | |
| American Indian | 1.0% (7) |
| Asian | 0.6% (4) |
| Black | 8.2% (55) |
| White | 86.7% (584) |
| Hispanic | 2.8% (19) |
| Other race | 0.7% (5) |
| Years of Education: Mean (Std Deviation) | 12.1 (3.3) |
The percent of total confirmed subjects who were excluded for age less than 65 years, received PAC services in a prior setting, or an HMO payer was highest in HH agencies (68.5 percent). The major reason for exclusion in HH was prior PAC (39 percent). Just less than half (48.5 percent) of SNF patients were excluded due to any of the three exclusion criteria. IRF patients were excluded largely due to age <65 (35 percent). The volume of stroke admissions, particularly FFS with no prior PAC stay, was so low that 12 of 33 SNFs and 7 of 20 HH agencies did not have a single patient who met these study criteria. This problem was compounded by the 20 percent of SNF patients and 15 percent of HH patients who were ineligible largely because they were not receiving therapy or had been residing in a nursing home. Thus, relatively few FFS Medicare stroke patients meeting study criteria were admitted directly from the hospital to participating SNFs and HH agencies.
Patient characteristics are described in Table 2.3. Participants were predominantly between 75-84 years of age, and roughly 56 percent were female. Most participants were married (47 percent) or widowed (43 percent), and the vast majority were White (87 percent).
Data were acquired from three sources: (1) patient (or proxy) report from interviews conducted after PAC admission; (2) follow-up patient (or proxy) report from interviews conducted 90 days post-PAC admission; and (3) Medicare claims and electronic clinical data (i.e., MDS, OASIS or IRF-PAI) for the period from the index hospitalization to 90 days post-PAC admission for all study subjects. The 90-day time interval for follow-up was chosen because functional outcomes following stroke have largely peaked at 90 days, and because the intent of this study was to attribute differences in outcomes to the PAC episode. Longer periods of follow-up make attribution of outcomes to the PAC episode more difficult, and may overlap with subsequent PAC episodes because of the high rehospitalization rates associated with stroke.
Although similar in many respects, the admission and 90-day follow-up instruments were designed separately and for different purposes. The admission instrument was designed for administration within 7-10 days of PAC admission; it assessed baseline function (ADL, IADL, ambulation, and social/role function) during the week prior to hospitalization, as well as current mental health (depression and cognition). The follow-up instrument was designed for administration 90 days after PAC admission; it assessed the same functional measures, as well as residence, and some measures of satisfaction including satisfaction with care, adequacy of patient/family education, and degree of patient/family involvement in care. The admission and follow-up survey instruments are presented in Appendix B. Medicare secondary data used in the study included electronic clinical data from patient assessments completed in each of the PAC settings that report assessments of patient condition and Medicare data from both Part A and Part B claims. Each of these data sources is explained in greater detail below.
1. Admission Interview
Data Collectors and Training: Admission interviews were conducted by facility data collectors who were skilled personnel consisting of licensed nurses, physical therapists, occupational therapists, or social workers. All on-site data collectors participated in a telephone training session prior to beginning data collection at their respective facilities. The training session covered the following areas: (1) study goals and objectives; (2) patient screening and sampling procedures; (3) study protocols and instruments; (4) protocols for locating and interviewing proxy respondents; (5) general interviewing techniques; and (6) safeguarding data and confidentiality guidelines. Prior to the training session, each data collector received a training manual, which included general information about the study and study objectives, all instruments and protocols, as well as training modules that highlighted the various phases of data collection: screening and sampling; initial patient contact; consent; and data collection. In addition to the formal training session, each data collector completed one or more mock interviews with research staff before performing his/her first interview for the study. All specific questions about the instruments or interpretations of responses were addressed by research staff via a series of memos, with copies sent to all data collectors to help ensure that they were able to apply the protocols and procedures uniformly.
Administration: The admission interview was administered within 7-10 days of the study participant’s admission to PAC. Subjects were interviewed face-to-face, either in the PAC facility for inpatients, or at home for HH patients. Efforts were made to accommodate patient preferences as to time of interview. If, during the screening process, it was found that the patient had aphasia or severe dysarthria, data collectors located and contacted a proxy, advised him/her of the study, and asked him/her to participate in the study on the patient’s behalf. Additionally, proxies were used in cases where the patient was not able to understand or give consent -- either in the data collector’s initial contact, or if the patient’s score was less than 17 on the Mini-Mental State Exam (MMSE)2 during the administration of the admission interview, indicating severe cognitive dysfunction that may have impaired a subject’s capacity to consent to participate in the study. Further, if in the data collector’s determination the patient appeared too fatigued, confused, or agitated to complete the interview, the data collector discontinued the interview with the patient and attempted to contact a proxy. Proxies were identified according to the following priorities: (1) legal guardian, if one was assigned; (2) close relative who lived with the patient, such as spouse, son, daughter, sister, brother, or “significant other;” (3) close friend/companion who lived with the patient; (4) close relative/friend who lived in the same area, and was in frequent (at least weekly) contact with the patient. In all cases, preference was given to individuals who were most familiar with the patient’s health and health care use. Overall, of the 674 study subjects, 463 were patient and 211 were proxy interviews. Completed interviews were submitted to research staff on a weekly basis.
Data Review: For ongoing management, each on-site data collector was assigned to a supervisor who maintained weekly contact and reviewed all admission interviews received for consistency and accuracy, addressing any data quality concerns with the data collector in a timely fashion and asking for corrections or clarifications when needed. The supervisor was also available on a daily basis to respond to any questions or issues encountered by the data collector. Upon receipt, data collector supervisors reviewed hardcopy baseline instruments for completeness and to ensure that the interviewer instructions were correctly followed. If a critical item was missing, a call was made to the on-site data collector to retrieve the missing data and reinforce the need to provide complete information. Once the editing process was completed and callbacks were made to retrieve critical data items, the documents were entered by trained staff. Each document was data entered a second time to reduce the number of entry errors, and at completion of data entry the two databases were compared. Inconsistencies between the databases were minimal, and differences were subsequently reviewed and corrected.
2. Follow-Up Interview
Follow-Up Interview Administration: The follow-up interviews were conducted by research staff, which included a core of supervisors and interviewers experienced in interviewing the frail elderly. We used contact information provided by the subject for themselves and two other persons who would be likely to know the whereabouts of the subject. During the follow-up interview, responses were entered directly into a telephone interview database with forms designed uniquely for this study. Because our goal was to conduct the follow-up interviews approximately 90 days after PAC admission, interviewers made an initial attempt to contact each patient 80-85 days after his or her PAC admission, and completed the follow-up interview no later than 115 days after PAC admission. Interviewers accommodated subjects’ schedules as much as possible, completing interviews in the evenings or weekends when requested.
The interview began with a brief competency assessment comprised of a series of simple questions (name, address, reason for hospitalization). Based on the patient’s or proxy’s responses, telephone data collectors determined whether the patient/proxy understood the questions being asked of him/her. If, in the data collector’s determination, the responses seemed incoherent or illogical, he or she discontinued the interview and asked to speak with a proxy (as defined by the priorities specified above). If at any time during the telephone interview, the respondent seemed too fatigued, confused, or agitated to complete the interview, data collectors either offered to schedule the remainder of the interview at another time (in cases of fatigue) or contacted a proxy to complete the remainder of the interview (in cases of confusion or agitation).
Follow-Up Interview Response Rates: We were able to complete follow-up interviews with 87 percent of those subjects alive at 90 days. There were 39 subjects (5.8 percent) who died between admission and 90 days, 30 (4.4 percent) who could not be located, 39 (5.8 percent) who refused, eight who were unable to complete the interview (1.2 percent), and five (<1 percent) cases for which there was a data collector error. This left 553 cases for which a 90-day follow-up interview was conducted. Of these cases, 483 (87 percent) were conducted with the original respondent (70 or 13 percent were completed with a different respondent). Also, there were 318 cases that were conducted with the patient at both the baseline and 90-day period, 58 cases with patient at baseline and proxy at 90 days, four cases with proxy at baseline and patient at 90 days, and 173 cases with a proxy at both time points. For the 173 proxy-proxy combinations, 165 kept the same proxy across time points (eight changed).
Data Review: The database was periodically reviewed for consistency, with unusual responses examined and corrections applied. Follow-up interview responses were also compared to baseline interview responses to flag subjects with unlikely recovery patterns, and responses were dropped when concerns about their accuracy arose. As an example, if a patient was unable to walk 20 feet before the stroke based on the admission interview, and then had no difficulty walking 20/50/300 feet at 90 days, this would be considered unlikely. For such cases, the suspicious items were set to missing for analysis purposes.
3. Medicare Secondary Data
We requested claims data and electronic clinical data (MDS, OASIS, and IRF-PAI) for all study subjects from the beginning of the data collection period to 90 days after the last subject was enrolled in the study. We also requested national MedPAR discharge data for the years 1998-2004 on all stroke discharges and POS files for PAC providers. These secondary data sources provided additional covariates, as well as outcome, cost, and utilization measures.</