This report examines Medicare beneficiary episodes of post-acute care (PAC). The importance of understanding beneficiary patterns of cost and use of post-acute services is particularly critical given recent estimates from MedPAC that 2007 spending on PAC was over $45 billion dollars (MedPAC, 2008). Numerous studies have focused on the costs and use of individual services in the Medicare program, including numbers of users, program costs per user, and the factors associated with those costs and use. But few have viewed these patterns across an episode.
Policymakers are calling for greater attention to beneficiary episodes of care in order to understand patterns in service use across PAC providers within the current setting-based payment systems. Examining an episode-based approach allows one to consider the related sets of services that beneficiaries need to treat a condition, or set of conditions. Understanding these related services is critical to facilitating efficiency and improvements in health care quality across the continuum of care. Our work shows that over a third (35.2 percent) of all beneficiaries discharged from acute hospitals go on to use other services. Of those who do, almost 80.0 percent are discharged to either skilled nursing facilities (SNF, 41.1 percent) or sent home with home health services (HHA, 37.4 percent). Another 9.0 percent are discharged to outpatient therapy services (OP). The remaining 10-12.0 percent are leaving the hospital for continued services at a specialized hospital, such as an acute-level inpatient rehabilitation facility (IRF, 10.3 percent) or long term care hospital (LTCH, 2.0 percent).
Understanding these service patterns and the factors that explain them is critical for assessing whether Medicare beneficiaries have access to appropriate services while ensuring that Medicare covers the most cost-effective options with the public Trust Funds. This research examines the relative importance of these different services and how their use varies by individual beneficiary characteristics, such as medical conditions, and the local availability of service options. The work presented here examines episodes of care that can answer questions such as how do individual costs vary by type of health condition and severity of illness? How are institutional, community-based, and physician services tied together for different types of patients?
An episode of care in this work begins when a beneficiary is admitted for an index acute hospital stay in 2006 following a 60-day period without acute hospital or PAC use (HHA, LTCH, IRF, SNF, or OP) and includes all claims until a 60-day gap in acute or PAC service use. The 60-day gap in service use is consistent with Medicare rules on the "spell of illness" definition which applies to SNFs and inpatient hospitals. According to Medicare's definition, a spell of illness includes all readmission and skilled nursing facility service use until a 60-day period without readmission or skilled nursing facility use1. The 60-day period is also consistent with the home health 60-day episode definition.2
The episode definition assumes that services following the index acute admission are related to the original hospitalization and allows us to look at the patterns of care for individual beneficiaries until a 60-day gap in services. This approach differs from many studies of chronic illness trajectories which examine only service use associated with treating a particular condition. By including all claims within these windows of time, we are able to assign claims to episodes when it may not be clear by examining diagnoses codes alone that claims are related. For example, diagnoses codes on inpatient rehabilitation claims are often coded as rehabilitation though they may be related to an episode that initiated in an inpatient acute hospital with a diagnosis of stroke. Our time based approach to constructing episodes allows us to link related claims that may not have similar diagnoses.
Using a person-level approach to defining an episode of care allows us to consider people, their related service use, and the factors that predict cost and utilization. Defining related services lets us consider the effect of comorbidities and severity of illness in explaining total beneficiary costs and use variation, rather than examining services treating a specific condition as though each service were independent of the patient's complicating conditions. This work builds on studies of state and regional variations in Medicare expenditures per service (MedPAC, 2008; Wennberg, Fisher, et al, 2003; Gage, Moon, and Chi, 1999) and looks at the total program costs per patient across an episode of care, similar to past work by this team (Gage, 1999; Gage, Morley, Spain, and Ingber, 2007).
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Section 1 Background
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Few medical services are used in isolation, with the exception of physician services. Typically, patients requiring treatment in a hospital also need related follow-up services, with at least their physician, and often with home health, skilled nursing facility, or outpatient services. These services may be considered related as they are part of the beneficiary's treatment for the original illness requiring hospital admission. Yet, little work examines the relative use of these services across an episode of care.
The one exception is with the chronically ill populations, where policymakers and insurers recognize these populations use multiple services and have tried to focus case management and other practices on coordinating care for these populations. These efforts typically focus on physician services and their role in managing costs, use, and outcomes for these high use populations. Some have also begun including hospital use in these studies as research has shown that the higher cost chronically ill populations often have inpatient admissions associated with physician services. Yet, few studies effectively consider the post-hospital services; an oversight as they account for a substantial share of both the chronically ill and other beneficiary's total episode of care costs. They also may be key to controlling adverse outcomes and reducing avoidable hospitalizations.
This study focuses on all Medicare beneficiaries (chronic and acute care populations) with a hospital admission in 2006 following 60 days without acute or PAC use. Beneficiaries are assigned to a condition-group based on the DRG recorded on the acute hospital claim. In examining episodes of care, we consider the range of services that may be related to treating this condition. Beneficiaries are assigned to a group based on the DRG on the index acute hospital claim. This allows us to characterize a beneficiary's use of services based on the initial reason for admission though diagnoses on subsequent claims may differ from the diagnoses on the index claim.
Second, this study examines the effects of organizational relationships on the likelihood of using different types of services. While medical conditions are hypothesized to be the most significant predictor of service use, the availability of substitute services is also an important factor (Gage, 1999; Gage et al, 2007; Gage, Morley, and Green, 2006; Bewkes-Buntin, 2005). Understanding not only the availability, but the effect of financial or other types of relationships is important for considering future policy options, including mechanisms for bundling payments across an episode of care.
This report analyzes variations in costs and utilization patterns for Medicare beneficiaries in different parts of the country. The analyses control for case-mix differences, both the primary conditions and the types and severity of comorbid conditions. The analyses also control for differences in resources in each state as we consider the factors that predict the type of post-hospital care, level of care, costs of care, and outcomes.
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Section 2 Data and Methods
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Multiple data sources are used to construct episodes of care, identify organizational relationships, and examine local supply variation. Episodes begin with an index hospitalization3 and continue through discharges to inpatient rehabilitation hospitals, long term acute care hospitals, skilled nursing facilities, home health agencies, and outpatient therapy services.4 Costs and use of physicians and other practitioners, hospice, and durable medical supplies during the episode are also examined. These patterns of care analyses allow us to study order of services as well as volume and relative probability of service use for different populations or beneficiaries with certain health conditions.
Measures of formal and informal relationships between hospital and post-acute providers also are constructed. Formal relationships are defined by hospital ownership of a subprovider, such as a hospital-based rehabilitation unit or skilled nursing facility. Informal relationships are defined by "co-location" factors such as independently-owned providers being physically within 250 yards of each other, in effect, creating a medical mall or campus. Proximity is important in creating access to services, particularly for someone requiring transportation services, such as an ambulance between settings. Other informal relationships are defined by the presence of a satellite facility within another provider. This satellite may be located within a hospital campus or co-located with other healthcare providers in the community besides the parent facility. We hypothesize that these physically close providers may provide benefits to the acute hospitals despite the lack of formal "ownership" relationships.
Hospitals have an incentive to discharge their cases within the average lengths of stay (ALOS) window used to set their payment rates in order to avoid losses on a particular case. Having a post-acute provider nearby allows this discharge to occur at the earliest time possible. Further, each post-acute provider has their own payment system in which the patient may be viewed as "profitable" or not. If a hospital owns the post-acute provider, they may encourage the PAC site to admit the patient if the anticipated hospital "savings" or reduced losses are greater than the anticipated PAC losses. For some cases, discharge to the PAC may be a win-win situation where the hospital limits its costs and the PAC payment rate is profitable for that patient.5
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Section 3 Results
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Geographic Distribution of Post Acute Care Providers. The availability of PAC services varies widely across the nation. Skilled nursing facilities and home health agencies are available in every state, although certain states, such as Texas, California, Florida, Ohio, and Illinois have particularly high numbers of PAC providers compared to other states. In addition to looking at the number of PAC providers, it is important to consider the number of beneficiaries that they serve. After controlling for number of residents, states including Louisiana have a high supply of providers per beneficiary population. States with the highest supply of IRF beds per beneficiary included the District of Columbia (2.66 beds per 1,000 beneficiaries), Louisiana (2.09 beds per 1,000 beneficiaries), Arkansas (1.82 beds per 1,000 beneficiaries), and Texas (1.53 beds per 1,000 beneficiaries). The states with the highest supply of SNF beds per beneficiary population included North Dakota (62.69 beds per 1,000 beneficiaries), Iowa (59.98 beds per 1,000 beneficiaries), and Louisiana (57.66 beds per 1,000 beneficiaries). The two states with the highest number of LTCH beds per beneficiary included Massachusetts (3.92 beds per 1,000 beneficiaries) and Louisiana (3.08 beds per 1,000 beneficiaries). Services were less available in some of the rural states. Maryland had the fewest IRF beds per beneficiary, Alaska had the fewest SNF beds per beneficiary, and seven states had no LTCH beds (Montana, New Hampshire, Alaska, Iowa, Maine, Vermont, and Oregon). The majority of LTCHs, SNFs, and HHAs are free-standing, or not owned by an acute hospital. The majority of IRFs, on the other hand, tend to be hospital-based units (Table 3-1 and Table 3-2).
Organizational Relationships. Organizational relationships were another area we examined in this work. In looking at the discharges from acute hospitals to first site of PAC, we found that organizational relationships between the acute hospital and the PAC provider varied significantly depending on the type of PAC provider used. For example, in 2006, over 83.0 percent of discharges to LTCHs were to freestanding providers compared to 47.3 percent of discharges to freestanding IRFs. This difference reflects the differences in supply of each type of provider (Section 3.1.3, Table 3-3). We also examined the role of organizational relationships further in the multivariate models to explain variations in episode costs and use (Section 3.9). Acute hospitals that have a subprovider, such as a hospital-based rehabilitation unit or skilled nursing facility unit or which own a home health agency or have a co-located LTCH, had longer length acute stays. However, the availability of these services was not significantly associated with the probability of using PAC. In other words, the PAC providers appeared to be located by hospitals treating longer-stay, possibly sicker populations. But this did not affect whether a patient used PAC, all else equal, such as their severity of illness and precipitating conditions.
Post-Acute Care Episodes. Using the episode definition in our analysis, about 15.0 percent of all beneficiaries had at least one index admission to an acute hospital in 2006.6 Of these, 35.2 percent were discharged to a post-acute site of care for further treatment. Skilled nursing facilities were the most common discharge destination for PAC users (41.1 percent of all PAC users), followed by home with home health care (37.4 percent). Inpatient rehabilitation hospitals and hospital outpatient therapy providers accounted for 10.3 percent and 9.1 percent, respectively of first sites following hospital discharge. LTCHs are the least commonly used PAC provider; only 2.0 percent of all PAC users were discharged to LTCHs (Section 3.2, Table 3-4 and Section 3.7, Figure 3-2).
Type of Condition. The importance of PAC services varies by type of condition being treated in the acute hospital. The most frequent acute hospital admission in 2006 was in DRG 544: Major Joint Replacement or Reattachment of Lower Extremity.7 This DRG represents over 5.0 percent of all hospital discharges in 2006, and 87.0 percent of beneficiaries with this discharge go on to use PAC services. The next most common acute DRGs by volume for PAC users are DRG 089: Simple Pneumonia and DRG 127: Heart Failure and Shock. While these two DRGs account for high numbers of acute admissions, beneficiaries with these conditions are much less likely to use PAC; only one-third of each of these cases will be discharged to PAC. Still, because of the high number of admissions in these categories, the DRGs rank 3rd and 4th in terms of the highest PAC volume (Section 3.3, Table 3-6 and Table 3-7).
Most PAC admissions can be stratified by whether they need PAC for treating medical conditions or functional impairments. Among the medical conditions, such as pneumonia, septicemia, and other infections, beneficiaries are likely to be discharged to SNFs or HHAs where these conditions rank high in the frequency of admissions. Beneficiaries discharged after joint replacements and back problems are much more likely to be discharged to rehabilitation hospitals and skilled nursing facilities. LTCHs are more likely to admit the more medically complex cases whereas IRF patients need to be healthy enough to sustain 3 hours of therapy per day, on average (Table 3-7).
Severity of Illness. Severity of illness typically distinguishes between PAC site of care, all else equal. LTCH admissions tend to have higher severity ratings, whether on the APR-DRG (severity level 3 or 4) or MS-DRG system, whereas SNF and HHA admissions tend to be in severity groups 2 or 3. IRF and outpatient admissions tend to be in severity groups 1 or 2. These differences reflect the expected variation in medical severity for each level of care (Section 3.4, Table 3-8).
Comorbid conditions, as measured by Hierarchical Condition Categories (HCCs), are another indicator of severity of illness or number of complicating conditions. The HCCs were used in these analyses because they to provide a convenient method for collapsing ICD-9 codes into meaningful disease groupings to identify comorbid or complicating conditions. In these analyses, we counted the number of HCCs per beneficiary, regardless of the reason for acute hospitalization. In looking at mean length of stay and payments in the acute hospital, the general trend is that the mean length of stay and mean payment increase with increasing numbers of HCCs. For example, DRG 014 (Stroke), beneficiaries with one HCC had an episode mean length of stay of 82.6 days and mean episode payments of $23,442, whereas, stroke beneficiaries with five or more HCCs had mean episode length of stays of 108.9 days and mean episode payments of $35,659 (Section 3.5, Table 3-12).
Readmission rates similarly vary by the type of condition. Beneficiaries admitted for diagnoses such as pneumonia or heart failure had higher readmission rates compared to beneficiaries with rehabilitative diagnoses. For example, over 43.0 percent of beneficiaries in DRG 127: Heart Failure & Shock had an acute readmission during their episode compared to only 14.3 percent of beneficiaries in DRG 544: Major Joint Replacement or Reattachment of Lower Extremity (Section 3.4, Table 3-10).
Patterns of Care. Considering the patterns of care in the Medicare program and how the mix of services may vary depending on the patients' complexity and the resources available in their local market area can be invaluable. The pattern analysis tables and figures (Section 3.7, Tables 3-19 to 3-22 and Figures 3-2 to 3-7) help us understand the way services are combined to treat individual patients. Of the 35.2 percent of hospital discharges to PAC, 52.0 percent of them go on to use additional services after the first PAC site. The episode payments and length of stay vary extensively depending by the extent to which higher cost institutional services are part of the episode or longer lasting, ambulatory services, such as home health or outpatient therapy. In the most common first site of PAC (SNFs which admitted 41.0 percent of PAC users), average payment per SNF stay was $8,759. For beneficiaries subsequently discharged to HHA, average payments were an additional $3,544. For beneficiaries discharged from SNF to LTCH, average payments were an additional $29,118. Further, seeing how these patterns varied for medical versus rehabilitation cases was also useful for considering expected care trajectories and costs.
Composition of Total Episode Payments. In Section 3.8 we analyzed the composition of Medicare spending on post-acute care episodes by looking at the proportion of total episode payments attributable to each type of service. The episode composition analyses were performed overall, and by severity level for all DRGs and also for DRGs 089: Simple Pneumonia & Pleurisy and DRG 544: Major Joint Replacement or Reattachment of Lower Extremity. Across all DRGs, the largest share of episode spending is for the index acute admission (34.3 percent) followed by spending on SNFs (17.9 percent). Though payments for beneficiaries using LTCHs are very high, the proportion of total episode spending on LTCH services was only 3.7 percent due to the small number of beneficiaries using this service overall. In looking at the distribution of spending by severity level, we see that the proportion of total episode spending on LTCH services increases with increasing severity. In looking at the distribution of payments for beneficiaries in DRG 089 compared to DRG 544, we see that the proportion of spending for SNF is higher for beneficiaries in DRG 089 compared to those in DRG 544, and that the proportion of spending on index acute admissions and IRF services is higher for beneficiaries in DRG 544 reflecting the use of surgical procedures and frequency of use of rehabilitation services for beneficiaries in this DRG (Section 3.8, Figures 3-8 to 3-16).
Physician Use. We also examined physician use during an episode of care (Section 3.8, Table 3-23). Over 90.2 percent of the beneficiaries in our hospital discharge sample had a physician visit in the hospital. Over 68.0 percent had an inpatient consultation, 60.0 percent had an emergency room visit, and 55.0 percent had an office visit sometime during the episode of PAC. The highest payments were associated with hospital visits (over $1,100). The physician visit patterns also differed between the medical and rehabilitation cases. Medical cases, such as DRG 089: Simple Pneumonia & Pleurisy, were more likely to have seen a physician in the ER and more likely to have a NF visit than the patients in DRG 544: Major Joint Replacement or Reattachment of Lower Extremity which were more likely to have fewer visits of every kind.
In sum, this report provides a great deal of insight on the factors associated with using post-acute care and the types of PAC services used. The leading indicator appears to be the patients' medical conditions and severity of illness although availability of alternative services is also critical to service use.
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Section 4 Discussion
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These analyses provide important information for understanding who uses PAC services, how their likelihood of using PAC services differs by certain characteristics, and which factors are most important in predicting hospital length of stay, probability of PAC use, relative probability of PAC site of care choices, hospital readmission rates, and average episode payments. Age and severity of illness factors were important in all the multivariate models predicting these outcome variables (Section 3.9, Tables 3-24 to 3-27).
In this work, we compare several measures of severity including APR-DRG, MS-DRG and HCCs. The additional contribution of the HCC indicators to the multivariate models flagging comorbid conditions proved quite useful to improving the explanatory power of the models. Greater severity was associated with longer length stay, as expected, regardless of measure used. Severity was also important for explaining the probability of PAC use and the type of PAC service used. Patients with higher severity scores were more likely to use LTCHs, followed by SNFs, then IRFs, and last home health services relative to outpatient therapy services.
Organizational relationships were also important for predicting use. We also found greater likelihood of using a type of PAC if the hospital had a subprovider or co-located PAC provider of that type. For example, multivariate models showed a greater likelihood of using IRFs if the hospital has a subprovider or co-located IRF and a lower likelihood if the hospital had a SNF subprovider, all else equal. Similarly, having a co-located LTCH increased the likelihood of LTCH use while the presence of a SNF or HHA reduced the likelihood of LTCH use, all else equal. And the same is true for the presence of a SNF.
Both these factors (severity and organizational relationships) were also important for predicting readmission rates and average episode payments (Section 3.9, Table 3-27). The probability of readmission increased as severity increased and having a subprovider was negatively associated with readmission rates. Both factors were also statistically significantly associated with episode payments; as severity increased, so did the average payment per episode. Similarly, average episode payments were higher for beneficiaries treated in hospitals with PAC subproviders. This may reflect different resource mixes of the hospitals or reflect higher likelihood of using subproviders where they exist, all else equal.
This work provides an important starting point for predicting beneficiary costliness and outcome variations. Understanding the contributions of better severity and medical complexity measures allows us to refine payment and outcome models. During the coming year, we will be adding data from the Chronic Care Warehouse (CCW) dataset to identify beneficiaries in our 2006 episode file with chronic conditions. Similar to some of the analyses presented in this report, we will look at the patterns of use and expenditures associated with having one or more chronic conditions. This will further allow us to refine the information describing a beneficiary's medical complications and is more comprehensive than our limited application of the HCCs to the index acute admission claims. Second, we will also examine alternative episode definitions including fixed and variable length episodes and episodes initiating in IRF, LTCH, HHA, or outpatient therapy without an index acute hospital admission-so-called community entrants to Medicare post-acute care services. This work will serve as the basis of exploring potential episode-based payment or bundling options and will build on some of the episode composition work presented here.
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