U.S. Department of Health and Human Services
This report was prepared under contract #HHS-100-97-0010 between the U.S. Department of Health and Human Services (HHS), Office of Disability, Aging and Long-Term Care Policy (DALTCP) and The Urban Institute. For additional information about the study, you may visit the DALTCP home page at http://aspe.hhs.gov/daltcp/home.htm or contact the ASPE Project Officer, Jennie Harvell, at HHS/ASPE/DALTCP, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, SW, Washington, DC 20201. Her e-mail address is: Jennie.Harvell@hhs.gov.
The authors thank the following people for helpful comments on earlier drafts of the report: Arlene Bierman, AHQR; John Thomas/Lisa Hines/Carolyn Rimes/Laurence Wilson, HCFA; Joyce Brown-Moore/Ruth Katz/Floyd Brown/Kamal Hijjazi/Henry Krakauer, ASPE.
Understanding the quality of post-acute care is more important and has become more challenging than ever before. The multiple and ongoing changes to Medicare post-acute care payment policies create a dynamic environment in which measuring the effect of service delivery is particularly difficult. The Office of the Assistant Secretary for Planning and Evaluation (ASPE) has implemented a research strategy designed to examine the quality of Medicare post-acute care services (i.e., services provided in rehabilitation hospitals/units, skilled nursing facilities, and home health agencies). Rapidly rising Medicare post-acute care expenditures was one factor driving the interest in post-acute care quality. In addition, the impact that recently enacted payment changes for Medicare post-acute care services may have on the quality of care stimulated increasing interest in measuring the quality of Medicare post-acute care.
As an integral part of ASPEs research strategy, this project sought to identify measures that could be used to determine the quality of post-acute care services. The project identified a mixture of both global and disease-specific outcome and process measures relevant to post-acute care. It focused on measures relevant to patients who, following a hospital stay, receive post-acute care for conditions that required either intense medical or rehabilitation management. The conditions targeted in this study were congestive heart failure, pneumonia, stroke, and back and neck conditions. Through discussions with expert clinicians and researchers and a review of the literature, post-acute care process and outcome measures were identified. They included traditional measures of physical function, utilization, and mental health, as well as measures emphasizing symptom relief, specific therapies and other processes of care, satisfaction, and health-related quality of life, including role resumption.
During the course of this study, it was determined that existing administrative data (including patient assessment instruments) do not contain information needed to adequately measure the quality of care within and across post-acute care settings. While existing data systems include information needed for some of these measures (e.g., utilization and functional measures) many of the measures identified as important in understanding quality of post-acute care are not included in existing administrative data (e.g., mental health, quality of life, satisfaction, and role resumption). In addition, while existing data systems measure functional status (i.e., information that was considered important across all conditions), existing patient assessment instruments measure functional status in different ways and at different times across post-acute care settings. Further, the differences in patient assessment instruments and processes make if difficult to identify whether similar patients are, in fact, treated across different settings, and if so, what are their relative outcomes of care. Finally, patient assessment data is collected only as long as a patient is treated in any particular post-acute care setting. However, many outcomes that the expert clinicians and researchers identified as important may not be present until after the patient is discharged from the post-acute care setting. Thus, while existing data systems may serve a variety of purposes, they were not found to include information needed to measure post-acute care quality and outcomes.
As a result, this project developed four quality assessment instruments, one for each of the targeted conditions. These instruments, which will be used in future research measuring the quality of post-acute care, derives data from hospital and post-acute care medical records and two patient surveys (i.e., one upon admission to post-acute care and the other at a specified point in time following post-acute care admission).
The Office of the Assistant Secretary for Planning and Evaluation (ASPE), within the Department of Health and Human Services (HHS), funded this study to develop quality measures for post-acute care services for similar patients with selected conditions. The conditions targeted in this project were stroke, congestive heart failure (CHF), pneumonia, and back and neck conditions. Under this project, four quality measurement instruments, one for each condition, were developed. Each instrument consists of four parts: a medical and post-acute care chart review, and an initial and follow-up patient survey. The instruments, intended for use in future research, could provide information on the extent of case mix and service overlap across post-acute care settings for patients with one of the four identified conditions and their outcomes following post-acute care.
This report is presented in five chapters. Chapter I, Purpose, provides an overview of the project. Chapter II, Rationale, develops the rationale for conducting this project. This chapter reviews the need to understand post-acute care outcomes in view of the historical trends in post-acute care payment and use, recent changes in post-acute care payment policies and the impact of those changes on quality and access, issues regarding the potential overlap in post-acute care patients and services and the need to understand quality of care across settings if such overlap exists. This chapter also presents what is known about post-acute care quality and outcomes, and concludes with a discussion about why is it important to understand post-acute care quality. Chapter III, Quality Measurement Development, describes how quality measures for selected conditions were identified and selected, and how quality measurement instruments were developed and refined. Chapter IV, Conclusions and Policy Implications, summarizes the quality measures chosen for the selected tracer conditions across post-acute care services and the limitations of existing administrative data (including patient assessment information) in measuring outcomes. The last chapter, Chapter V, Next Steps, briefly describes the next phase of the ASPE research strategy to examine post-acute care quality. In that phase, ASPE is funding a study to examine post-acute care outcomes for stroke patients, which will use the patient assessment instrument developed for stroke under the current project. In addition, Chapter V summarizes work that ASPE is funding to develop a conceptual framework that will specify the objectives of collecting patient health and functional information, review methods used in identifying and collecting patient information, and specify next steps for identifying the patient information needed to achieve objectives and methods for data collection and maintenance. Finally, the Appendices include several background and supporting documents, as referenced throughout this report.
Post-acute care services represent an increasingly important part of the health services used by Medicare beneficiaries. While there is no standardized definition of Medicare post-acute care, for purposes of this report these services are defined as post-hospital services received from a skilled nursing facility (SNF), home health agency (HHA), and/or rehabilitation hospital/unit -- inpatient rehabilitation facilities (IRFs). Medicare expenditures for post-acute care services have increased dramatically, consuming an increasing share of total Medicare expenditures. In response to that trend, legislation was enacted to reduce the amount Medicare pays for post-acute care and change the ways the program pays for these services. These significant changes in payment policy and reductions in amounts Medicare will pay for post-acute care services could have a significant impact on access to and quality of care. There are no studies comparing the outcomes of post-acute care following implementation of these payment policy changes.
Implementation of the new post-acute care payment policies has retained setting specific payment methods and amounts. Such fragmentation may perpetuate inappropriate financial incentives for the admission, transfer, and discharge of patients in post-acute care. It has been presumed that there is considerable overlap in the types of patients treated in and the services provided across post-acute care settings, and thus that such fragmentation in payment policies may not be rational. However, these presumptions are not based in solid evidence. Further, questions have recently been raised about how much overlap really exists in patients and services across post-acute care settings. Some have suggested that, to the extent there was overlap, it has diminished since the implementation of recent payment policy changes.
Medicare expenditures for post-acute care have consumed an increasing share of total Medicare payments. From 1986 to 1996 Medicare payments for post-acute care increased from 3% to 15% of total Medicare expenditures, while Medicare payments for hospital services declined from 61% to 49% of total Medicare payments.1 The shift in Medicare payments from inpatient hospital to post-acute care services is attributed to several factors, including: the implementation of the diagnosis related group (DRG) hospital prospective payment system (PPS) which resulted in patients being discharged quicker sicker from the acute setting to the post-acute arena, technological advances that permitted the delivery of more complex care in downstream post-acute care settings, and Medicare post-acute care coverage and payment policies.1
From 1986 to 1996, Medicare post-acute expenditures increased from $2.5 billion per year to more than $30 billion, growing roughly 25% to 35% per year. The most rapid growth in expenditures was for HHA and SNF care. Contributing to the growth in post-acute care expenditures was the increased numbers of beneficiaries using these types of care, increased utilization of ancillary services (e.g., physical, occupational, and speech therapies, drugs, ventilators, etc.) in SNFs, increased numbers of visits per HHA user, and increased numbers of all types of Medicare certified post-acute care providers.
Approximately 25% of Medicare beneficiaries discharged from a hospital receive post-hospital services in HHAs, SNFs, and/or rehabilitation hospitals/units.2 Approximately 17% of those beneficiaries admitted to a post-acute care setting receive post-acute care from more than one post-acute provider. For some conditions, the proportion is much higher. For example, 65% of Medicare beneficiaries hospitalized for stroke receive post-acute care, and almost 20% of stroke patients receive care from multiple post-acute care providers.
In response to the rapidly rising post-acute care expenditures; the Balanced Budget Act (BBA) of 1997 mandated a change from cost-based reimbursement for post-acute care services to prospective payment in all three post-acute settings. The PPSs for each setting differ. It should be noted that, for certain settings, the statute prescribed most of the design of the particular PPS (e.g., the PPS for SNFs), while for other benefits the design of the PPS was subject to considerable administrative discretion (e.g., rehabilitation hospital PPS). The following briefly describes key design elements of recently enacted payment reforms for post-acute care providers.
SNFs are now reimbursed on a per diem basis using case mix groups called Resource Utilization Groups (RUGs). RUGs categories are based on staff time measurement data. Patients are classified into RUGs categories using data from the Minimum Data Set (MDS) collected by facility staff. SNFs are required to complete the MDS on the following days following admission: days 5, 14, 30, and 60. The BBA limited SNF payment rates to amounts paid for these services in 1995, trended forward, and required that SNFs be transitioned to Federal PPS rates over a three-year period. The Balanced Budget Refinement Act (BBRA) of 1999 increased, at least temporarily, SNF PPS payments, effective April 2000, by 20% for 15 RUGs categories to better account for non-therapy ancillary costs for patients in these categories. The BBRA also permitted SNFs to elect to be immediately paid the full Federal PPS rate (rather than being transitioned over three years to the full Federal PPS rate). The Benefits Improvement and Protection Act (BIPA) of 2000 modified the 20% adjustment in response to the concern that some lower cost categories were being overpaid relative to higher cost categories. In addition, BIPA increased the amount of payments for the nursing component of the SNF PPS rates.a
The BBA required that HHAs be paid a case mix adjusted prospective payment rate. Payment rates were to be limited to amounts that would have been paid in fiscal year 2000 -- reduced by 15% -- had the PPS not been implemented. The BBRA and BIPA delayed the application of the 15% reduction on HHA payments. At this time, the 15% reduction will not be implemented until 2001.a The HHA PPS was effective for all HHAs October 1, 2000 and pays case mix adjusted rates for each 60-day episode of care. Payment rates are established for each case mix group called Home Health Resource Groups (HHRGs) that were derived from the Outcome and Assessment Information Set (OASIS) assessment instrument completed by provider staff upon admission, every 60 days thereafter, and at discharge.
The BBA and BBRA contained legislation requiring Health Care Financing Administration (HCFA) to implement a PPS for IRFs.a The BBA left the rehabilitation PPS design requirements largely unspecified. However, the BBRA required that a per discharge PPS be established for IRFs based, among other criteria, on factors deemed necessary to improve functional independence measure (FIM) and functional related group methodology (a pre-existing, tested IRF payment methodology). As with the SNF PPS, the BBA required that IRFs transition to the new PPS. However, the BIPA included a provision permitting IRFs to elect to be paid the full PPS rate without such transition. The statute required that the IRF PPS reduce amounts that would have been paid to these providers by 2%. In November 2000, HCFA proposed that IRFs be reimbursed on a per episode basis -- based on case mix groups. The case mix groups were based on patient characteristics collected from the FIMs, a patient assessment instrument voluntarily used by many IRFs. HCFA proposed that patients would be assigned to case mix groups based on patient data derived from a new patient assessment instrument, the MDS for Post-Acute Care (MDS-PAC). The proposed rule would implement the PPS beginning in April 2000. However, HCFA has since announced that implementation will be delayed and a new date has yet to be established. The proposed rule would require IRFs to complete the MDS-PAC on days 4, 11, 30, and 60 after admission; and upon discharge. HCFA is in the process of reviewing comments received on the proposed payment and assessment systems.
Each of these payment changes -- i.e., the shift to PPS, the option of being paid a blend of PPS and historic cost-based payment rates or the full Federal PPS amount, increases in payment rates for case mix categories, potential reductions in base payment amounts -- may have an impact on the quality of and access to post-acute care. For example, implementation of the acute care hospital PPS in 1983 had a major impact on hospital and post-acute care. One important impact was that the hospital PPS led to decreased lengths of hospital stay. Between 1980 and 1987, the mean length of a hospital stay decreased approximately 13%, from 9.7 days to 8.4 days.3;4 The discharge of sicker patients earlier in the course of illness5 was associated with increased utilization of post-acute care,4;6 contributing to growth in the use of and expenditures for post-acute care. However, despite shifts in where services were delivered following implementation of the hospital PPS, there was no convincing evidence that the quality of care, as measured by patient outcomes, was significantly affected by the implementation of the hospital PPS, with the exception of premature discharge of patients.7 A potential explanation for stability in outcomes is that hospital services were adequately replaced by post-acute care services.
Nonetheless, it is reasonable to anticipate shifts in who receives post-acute care, the settings in which such services are delivered, and the quality of care following implementation of the recent and significant payment changes for SNFs, HHAs, and rehabilitation hospitals. Anticipating the potential effects of multiple post-acute care payment changes is complex, given different payment systems for each post-acute setting, each implemented and modified at different points in time. Key payment design elements that may uniquely affect quality and access to care include differences in the unit of payment (i.e., per episode versus per diem payments), the basis for calculating payments (e.g., resource use versus patient characteristics), and the different payment rates across settings (particularly for patients with potentially similar conditions). In addition, it is less clear what downstream types of care might be necessary or sufficient to fill in voids or decrements in quality that could occur because of the design of the various post-acute care PPSs. Because the PPSs for SNFs, HHA, and rehabilitation hospitals were first and foremost aimed at reducing post-acute care expenditures by limiting reimbursement to providers, there is widespread concern about adverse effects on access and quality of post-acute care if the payment systems create incentives for providers to change admission, treatment, and discharge practices. For example, in recent reports the Office of the Inspector General indicated that high cost patients may have had difficulties accessing SNF and HHA services as a result of payment changes.8;9 Thus, it is increasingly important to understand and monitor, particularly in view of the recent significant post-acute care payment changes, the extent of overlap in case mix and the quality of care provided in various post-acute care settings.
There is presumed to be significant overlap in the characteristics of patients treated across the three post-acute care settings, as well as overlap in the types and intensity of services provided. In its June 1996 report to Congress, ProPAC reported that distinctions among the services provided in post-acute care settings and the patients served by these providers had blurred.10 ProPAC attributed the increasing similarity in post-acute care services to Medicare payment and coverage policies and changes in technology. As previously mentioned, up until the late 1990s, Medicare paid for post-acute care services using cost-based reimbursement methodologies. Coupled with emerging technologies, such payment policies allowed new services to be delivered in post-acute settings. For example, cost-based payment policies permitted payment of high cost intravenous therapy in the home by HHAs. Further, the essentially unlimited reimbursement for therapies and drugs in SNFs permitted these facilities to deliver a more intense level of care than historically was found in hospitals, including rehabilitation hospitals.
Whether or not there was or continues to be similarities in patients and services across post-acute settings requires further study. Analyses of the characteristics of patients treated across post-acute care settings have typically compared post-acute care use and length of stay by preceding hospital DRG and length of stay. In its 1996 report, ProPAC found that there was significant overlap in the hospital-assigned DRG across [post-acute care] settings.11 However, in this same report, ProPAC concluded that more information is needed that would allow meaningful comparisons of the diagnoses, severity, and functional limitations of beneficiaries in all of these settings.12 At its December 2000 meeting, MedPAC (the Medicare Payment Advisory Commission which replaced ProPAC) members questioned what is actually known about the overlap in patients and services across post-acute care.13 Commission members raised questions about the comparability across post-acute care settings of patients severity of illness (i.e., which is in part a function of the length of preceding hospital stay) and functional status, and questioned how other non-clinical factors such as facility ownership, family support, and patient preferences may affect post-acute care use. In addition, Commission members questioned the comparability of services across post-acute care settings. Specifically, they noted that while similar services may be provided across post-acute care settings, the mix and intensity of those services may differ. In an ASPE sponsored study, Liu et al. found that providers, consumer groups, and others reported that following implementation of the SNF PPS, the similarity (i.e., overlap) in patients treated in and services provided by SNFs and rehabilitation facilities had diminished.14
There is a need for further research that examines the differences and similarities between patients treated by post-acute care providers and the outcomes of this care under the new payment systems. Such information could be used to support the current payment methodologies across post-acute care settings or could provide the foundation for alternative payment approaches. In addition, such research could help provide information on what should be measured in the post-acute care arena to monitor and assure the quality of care.
There is little extant research comparing the care provided by the three types of post-acute providers, patient characteristics associated with receipt of post-acute care in one setting versus another, patient outcomes as they relate to each post-acute setting, or appropriateness of admission of patients to the various post-acute settings. Several studies have compared outcomes of patients with specific diseases treated in different post-acute settings,15;16;17;18 and of a cohort of general medical and surgical patients,19 but there is great need for additional research in this area. In addition, the few extant studies of post-acute care outcomes were conducted before recent changes in payment policy.
Monitoring access to and quality of post-acute care is particularly important, given the reductions in payment and changes to payment policy implemented as a result of the BBA and subsequent legislation. However, each post-acute care setting has its own patient assessment instrument administered at different points during a post-acute care episode. Collecting data at different points in time makes it difficult to compare patient characteristics and outcomes across post-acute settings. In addition, there are significant differences in the data elements contained in existing federally required or proposed patient assessment instruments. For example, in an analysis of the comparability of the MDS, OASIS, MDS-PAC, and FIMs, it was concluded that there are many differences in the conceptualization of [activities of daily living] and disability terms and definitions.20 Further, during the September 2000 meeting, MedPAC staff presented preliminary findings from a study that questioned the utility of current administrative data (including patient assessment data) for measuring access to quality health care.21
Acute care is defined by a discrete event with a beginning and end, whereas chronic care is defined by long-term, ongoing treatment. However, post-acute care refers to the period of care that follows an acute event. For example, acute stroke care involves diagnosis of the type of stroke and extent of neurologic damage, life support and acute interventions such as thrombolytic agents to minimize the extent of brain damage, and intensive monitoring of neurologic signs. Once a stroke victim is stabilized, post-acute care involves continuation of stroke treatments (e.g., anticoagulation); rehabilitation of physical, cognitive, speech and language impairments; prevention of future stroke; and diagnosis and treatment of associated conditions such as depression.22 Patients needing post-acute care may also require ongoing, chronic care, either due to pre-existing conditions or as a result of the severity of the acute event precipitating the need for post-acute care. For example, chronic care of a stroke victim then involves continued management of the underlying diseases related to stroke, such as hypertension, and long-term management of residual impairment and disability.22
Because acute, post-acute, and chronic care represent different phases of illness requiring different types of care, a unique set of quality measures is required for each. Emphasis has been placed on measures of acute care quality, including appropriate process criteria for making the diagnosis and treating the acute phase of illness, as well as outcomes such as mortality.23 Quality measures relating to chronic care include process attributes, such as treating hypertension and arrhythmias to prevent further stroke, and outcomes such as recurrent stroke, rehospitalization for stroke or decline in function and quality of life.24;25 Because post-acute care has historically been part of extended acute hospital stays, quality measures for post-acute care are less well specified. However, post-acute care quality measures must not only encompass elements of acute treatment, but also aspects of care that are unique to the post-acute period (e.g., maximizing recovery of function).
The structures (i.e., settings) where post-acute care is provided are sometimes the same venues that also provide chronic care, such as SNFs and HHAs, but may also be unique (e.g., rehabilitation hospitals). The processes of post-acute care include continued monitoring of acute illness begun in the hospital and a strong emphasis on rehabilitation services such as physical therapy, occupational therapy, and speech therapy aimed at restoring function and quality of life. Outcome measures thus include both avoidance of acute events leading to rehospitalization and/or death, as well as recovery in physical, cognitive, psychological, and social function with the hope of ultimately restoring a persons lifestyle prior to the acute event. This multiplicity of care objectives represents one of the major challenges in quality measurement of post-acute care.
The fact that similar types of care and services may be delivered in different settings depending on the characteristics of the individual and the availability of services in the community, renders comparisons of quality across post-acute settings difficult, in part because each setting may rely on different processes to meet the same objectives. For example, institutional providers (SNFs and rehabilitation hospitals) spend more time treating the individual patient, while home health providers may rely more on training caregivers to provide some services and teaching patients exercises to perform independently. However, while the two institutional providers are paid very different rates, differences in processes of care in these settings are less clear. Both SNFs and rehabilitation hospitals provide the range of therapies. It is poorly understood how the mix and intensity of these services vary across provider types and the impact of these differences on length of post-acute care stays, quality of care, and outcomes.
There are several clinical reasons to be concerned about measuring the quality of post-acute care. First, a critical time window exists during which older persons recover function and the capacity to return to their previous lifestyle in the community following acute illness.15;19 Generally, if this transition does not take place within the first 60-90 days, it will not take place.15 Second, the highest rehospitalization rate occurs in the period shortly after discharge from the hospital.26;27 Third, acute hospital lengths of stay have been continually declining for Medicare beneficiaries, dropping an average of two days over the last decade, and thereby increasing the acuity level of patients at the time they begin post-acute care.5
In addition, substantial variation in the utilization of post-acute care across geographic regions creates additional challenges in understanding the relative outcomes associated with different post-acute care options.28;29;30 Our lack of understanding about the relative effectiveness of post-acute care use creates questions regarding the appropriateness of current payment and coverage policies.29;30 Complicating our ability to evaluate the quality of post-acute care, and determine relationships between post-acute care settings and outcomes, is the fact that a large proportion (17% as of 1996) of Medicare beneficiaries receive post-acute care in more than one setting. Receiving care in multiple settings may jeopardize the quality of care because of the need for clinical information to flow from one provider to another. To the extent needed information is not transmitted to a subsequent provider, services may be replicated or omitted.
In response to these issues, ASPE funded a national project to develop quality measures for post-acute care that could be used in future research. The project strategy was to first specify quality measures that are most relevant to episodes of post-acute care provided in all three settings, based on extensive literature review and expert consensus.
In this project, we identified a set of quality measures for Medicare post-acute care services for four tracer conditions that are prevalent in the Medicare post-acute population: stroke, CHF, pneumonia, and back and neck conditions. Eight conditions were initially selected based on policy considerations,31 such as volume and Medicare utilization criteria (i.e., hospital re-admission rates). These eight conditions were later narrowed to the four tracer conditions based on a framework of clinical criteria,32 the goal of which was to represent different types of illness (chronic vs. acute), different post-acute care settings and services, and different domains of outcome measures. The methods for how the initial eight conditions were selected and how these were narrowed down to the four conditions included in this study are discussed in Appendix A.
Throughout this report, we frequently make reference to the terms quality indicator and quality measure; we often reference these constructs as they relate to outcomes or processes of care. The following definitions clarify the distinction between an indicator and a measure, and between a process and an outcome of care.
Outcome indicator -- Change (e.g., improvement, decline, recovery) in a health status attribute that reflects a patient outcome, but does not require precise quantification of the outcome. Examples of outcome indicators include improvement in global function, decline in pain, and recovery of ambulation/mobility. Use of certain services can also be considered as outcomes.
Outcome measure -- A precise quantification of an outcome indicator. For example, the outcome indicator of improvement in global function can be translated into an outcome measure when a scale such as the SF-36 is used at baseline and follow-up time points. The outcome measure might be the change in total score between baseline and follow-up.
Process indicator -- An attribute of care at the patient level, without specific quantification of the attribute. Examples of process indicators include evaluation of depression, patient education, and use of sedatives/hypnotics.
Process measure -- A precise quantification of a process indicator. For example, the process indicator of evaluation of depression can be translated into a process measure by establishing a set of criteria for determining the circumstances under which a depression evaluation should be conducted, defining the essential features of the evaluation, and rating the extent to which these are met.
Based on initial review of the medical literature and clinical experience, we generated comprehensive lists of potentially useful quality indicators relevant to post-acute care for each of the four conditions. To provide a basic structure for reviewing the indicators, we organized the indicator lists into domains (e.g., functional outcomes, utilization, process). We then convened four panels of health care providers (i.e., one for each of the four targeted conditions) to rate the importance and feasibility of including each indicator on a post-acute care quality assessment instrument. Based on this first round of panel meetings and the quality measures identified by the panel, draft longitudinal quality measurement tools were assembled for each condition using validated measures wherever possible. These draft instruments were then presented to a second expert panel comprised of experts in the field of post-acute care, research methodologists, and researchers with expertise relevant to each condition. Instruments were revised based on this meeting and subsequently pilot tested for feasibility of administration and time studies. Feasibility testing was limited in scope, taking place in two waves using post-acute care facilities recruited in the Denver metropolitan area. Revisions were made to the instruments based on qualitative experience with the instruments gained during the first wave of testing and input from the second expert panel meeting. A second wave of feasibility testing was then conducted, and final revisions were made to the instruments. The final instruments and users manuals produced as the products of this project are the result of the processes described above.
The following sections (Sections B through D) discuss the indicators selected, and instrument development and refinement.
To generate the initial sets of post-acute care quality indicators for each of the four conditions, we conducted an extensive review of the medical literature, which was supplemented by clinical experience. Because our ultimate goal was to compile a comprehensive list of quality indicators relevant to Medicare post-acute care, our goal in selecting these initial sets of indicators was to be as inclusive as possible. Specific determinations as to the degree to which indicators and measures were relevant to a geriatric post-acute population would be made at a later time (both through the expert panels' review and literature review). Similarly, we were less concerned at this stage about the extent to which the indicators we selected would be measurable or feasible to collect; such determinations would be made following the final panel ratings. These lists of quality indicators included both process and outcome indicators. They also included a combination of both global quality indicators (those applicable to all four conditions) and condition/disease-specific quality indicators.
Next, we organized the quality indicators by domain to provide a basic structure for reviewing the indicators. These domains included: physical function outcomes, mental health outcomes, quality of life outcomes, utilization outcomes, physiology outcomes, satisfaction outcomes, and process of care. In order to facilitate review of the indicator lists and to avoid redundancy, each indicator was assigned to only one domain. Though one might reasonably argue that a different domain would be an alternative for a certain indicator, the purpose of the domain structure -- to simplify review -- would be defeated if an indicator were placed in multiple domains. To clarify the types of measures denoted by an indicator and to obtain some review of measures, we also included an illustrative set of potential quality measures corresponding to many of the quality indicators.
Participants on the expert panels were selected according to the following criteria: (1) representative of the three major post-acute settings (SNFs, HHAs, and rehabilitation hospitals); (2) representative of both managed care and fee-for-service settings; (3) national in scope; (4) inclusive of both generalists and specialists; and (5) representative of multiple disciplines (medical doctors, therapists and nurses). Our expert panels were ultimately comprised of a geriatrician, physiatrist, psychiatrist, SNF nurse, HHA nurse, rehabilitation nurse, speech therapist (who participated in the stroke panel meeting only), physical therapist, and a nationally recognized specialist for each of the four clinical conditions. The list of panelists is included in Appendix B.
The expert panel members were mailed background information about the project along with the initial quality indicator rating forms (see sample rating form, Appendix C). The panel members were asked to review the indicators and individually rate them with respect to the importance of each for assessing quality of care for the specified condition. They were asked to review each indicator separately for each condition using the four condition-specific indicator lists. The indicator ratings were based on the following scale:
0 = of negligible value for assessing
quality of care for that condition;
1 = of definite value for assessing quality of care;
2 = extremely important for assessing quality of care.
Reviewers were asked to consider the following criteria to determine the value of each quality indicator: (1) the likelihood that a significant portion of individuals with that condition will experience some change for the outcome indicator; and (2) the sensitivity of the indicator to differences in the quality of care received by individuals between sites. For each condition, reviewers assigned a rating of "2" to only 20 indicators. This provided us with each reviewer's "Top 20" quality indicators for each condition. Panel members were also asked to add indicators to the list and to rate these added indicators as well.
In addition to rating the indicators, panel members were asked to rate the quality measures with which they had experience. The measure ratings were based on the following scale:
R = recommended;
NR = not recommended;
Blank = unfamiliar.
Panel members were also asked to add measures to the list and to rate these added measures as well.
After rating the quality indicators and measures according to the above criteria, the panel members returned their completed rating forms. We calculated an average rating for each indicator and then ranked the indicators in descending order by their average ratings. In preparation for the meetings, we presented this information in two ways for each condition. First, we revised the previously distributed quality indicator rating forms that were organized by domain to include the average rating for each indicator. On this form, we indicated those quality measures that were frequently recommended by panel members. We also included all of the quality indicators and measures that were added by panel members. On a second form, we presented the ranked list of quality indicators in descending order of average rating.
The panel meetings took place over a period of two days; one half-day was devoted to discussing each of the four conditions. At the meetings, expert panel members were given the quality indicator rating results and a blank rating form pertaining to the condition under discussion. Panel members were, therefore, aware of the ratings each of the indicators received through the initial panel review. The focus of the panel meetings was on the indicators for which there was the least consensus among the panel members. We selected these more "controversial" indicators for discussion prior to the panel meetings by targeting those with the highest variance in ratings.
During the discussions, panel members often decided to redefine or modify some of the specific indicators for each condition; these modifications are delineated in the expert panel meeting notes (see Appendix D). Within each condition's panel meeting discussion, time was also set aside to discuss the additional indicators previously suggested by panel members, as well as some of the recommended quality measures for various indicators. After the discussion for each condition, panel members were asked to again individually rate the quality indicators a second time, this time by selecting the most important 25 quality indicators for the condition. The 25 selected indicators could include any combination of global and disease-specific indicators from any of the seven domains.
We compiled the panels' final ratings, enumerating the indicators for each condition in descending order based on the number of panel members who selected each (see Appendix E). We further refined this list by eliminating the following: (1) indicators that were not direct measures of post-acute quality, (e.g., cost measures or risk factors); (2) indicators that were incorporated in or similar to other indicators (e.g., single elements of larger scales, or redundant constructs), and (3) indicators that were not feasible to collect or not measurable (e.g., requiring hard to access data sources, or dates that are not readily available). The dropped indicators, and our reasons for dropping each, are included in Appendix E.
Appendix F includes the final list of quality indicators that were selected by at least four panel members; it is organized by global indicators (indicators that were selected by four or more panel members for three or four of the conditions) and disease-specific indicators (indicators that were selected by four or more panel members for only one condition). We used this final list of indicators to develop our post-acute care quality assessment instruments for the four conditions.
Following the expert panel proceedings, we reviewed quality measures corresponding to the panels most highly rated quality indicators and developed quality assessment instruments for post-acute care. The most highly ranked indicators were in the following areas: Health Related Quality of Life (HRQL), physical function, depression, social/role function, pain, satisfaction, utilization, disease-specific symptom management, and performance of key care processes. In reviewing the panels final ratings, it was apparent that emphasis should be placed on global measures of quality applying to all patients served in post-acute care, but selected disease-specific measures were required for each condition.
Complicating uniform quality measurement across post-acute care settings is the fact that all post-acute care settings use, or in the case of IRFs will use different assessment tools that are nationally mandated. The Federal Government requires that the MDS 2.0 (Minimum Data Set, Version 2.0) be used for all patients in Medicare (and Medicaid) certified nursing facilities and the OASIS be used for all skilled patients treated by Medicare HHAs. As previously mentioned, each of the instruments contains its own elements that are generally non-comparable and different assessment time points.
Clinicians and researchers who were expert panel members for this study identified as important outcomes in the measurement of the quality of post-acute care, outcomes that are not captured by existing federally required patient assessment instruments. For example, these tools do not measure whether a setting maximized a patients functioning, prepared him/her to return to and remain in the most independent living environment, and reintegrated him/her into prior lifestyle. Measuring such important outcomes requires input directly from patients or their proxies, as the latter two are subjective and the patients perception of those outcomes is, in fact, the measure of the outcome. In fact, many researchers focused on patient-centered outcomes believe that functional outcomes should derive from patients, as their perception of their function is more important than so-called objective measures of function. Patient-perceived functional capacity captures disability by integrating its relevance to the patient. If a difficulty performing a functional task is not related by a patient, it is likely of little importance or relevance to his or her life and needs. Existing patient assessment instruments use facility staff to measure outcomes, often an registered nurse or therapist, and thereby fail to capture the relevance of individual functional measures to the individual patient. Because the goal of rehabilitation is to restore patients to their previous level of function, capturing their perception of function both before and after an acute event in their terms is essential to measuring quality. Further, the expert panelists indicated that many important outcomes cannot be measured within the time frames over which post-acute services are typically provided in most settings. Given that average lengths of Medicare covered stays in the mid-1990s were approximately 25 days in SNFs and 21 days in rehabilitation hospitals,33 it is not possible to determine whether post-acute care has successfully maximized a patients function, allowing sustained return to the most independent living environment, and reintegration into prior activities and lifestyle. Generally, these outcomes take 60-90 days before they begin to plateau.15;19 In addition, because assessment data is not comparable across settings and whatever data is collected is only collected while the patient is treated by a particular provider type, it is not possible to measure outcomes across episodes of care that include multiple post-acute settings.
During the development of precise measures, data items, and data collection instruments, the limitations of existing data systems for measuring quality across settings were apparent. First, they did not cover many of the important domains and measures determined to be important by the expert panels (e.g., health-related quality of life; role resumption, satisfaction). Second, existing data systems do not use the individual patient as the respondent, but are based exclusively on provider reports. Third, existing instruments do not use uniform time frames that could be compared across settings. Fourth, based on our extensive review of existing patient assessment tools, the elements cannot be rendered comparable from one setting to the next because of differences in data elements, scaling and timing of completion, with the exception of basic demographic variables and an estimate of a Barthel index upon post-acute admission.
In addition to the concerns raised above about the need to assess patient-perceived function, concern also exists about the reliability of provider reported data.34 The primary concern, however, is over validity of provider reports. Based on literature review and expert panel members input, the types of measures that are relevant to post-acute care (e.g., HRQL, mental health and depression, physical and social/role function, satisfaction with care) require patient input. While patient-reported data are necessary for appropriate assessment of the above domains, the validity and reliability of this data may be affected by such factors as social desirability and acquiescent response biases.35 In addition, cognitive impairment, which is relatively common in the Medicare post-acute care populations, further complicates collection of patient-reported data. However, even among cognitively impaired subjects, proxy input on such outcome measures is more likely to reflect the needs and values of patients than provider assessment.
In this section, we provide the rationale for selecting the specific quality measures and data items corresponding to the quality indicators chosen by the expert panels. The selection of measures was guided by several principles. First, the burden of data collection had to be kept to a minimum; shorter versions of questionnaires were chosen whenever feasible. Second, the measures had to be relevant to patient care provided during the post-acute period and relevant to all three provider types, rather than outpatient, acute hospital or long-term care. Third, redundancy within and between measures was to be minimized. Fourth, measures needed to be responsive to the quality of the post-acute care delivered and clinically meaningful change. Finally, where possible, validated and reliable measures were chosen, particularly if they had been evaluated in older, frailer patients and in post-acute settings.
Health Related Quality of Life (HRQL)
The expert panels reached unanimous consensus with regard to the importance of HRQL as a quality measure for post-acute care. Similar to other investigators in this area,14;36;37 we struggled with how to operationalize HRQL as an outcome measure. Lack of a standardized and precise definition in the literature was a major barrier. Other terms, such as general health status and quality of life, refer to similar concepts.38;39;40 The panels discussed the utility of several commonly used and validated HRQL instruments. The three most commonly used instruments considered were the Medical Outcomes Study Short Form-36 (MOS SF-36), the Sickness Impact Profile (SIP) (as well as the SIP for nursing home residents (SIP-NH)), and the Quality of Well Being Scale (QWB).41;42;43;44
The domains encompassed by global health status or HRQL measures such as the MOS SF-36 and the SIP share a high degree of overlap with many of the important quality domains recommended by the panels for inclusion in a quality measurement instrument: physical function, depression, pain, and social/role function. Recognizing this overlap, the question arose as to whether any of these instruments were sufficient in and of themselves as measures for these domains, and whether such an HRQL instrument like the SF-36 would suffice as the entire patient self-report component of the instruments. A number of concerns, however, precluded such an approach. First, these global instruments were not designed for use in older, frailer populations, much less populations receiving post-acute care. Thus, the specific items have varying levels of relevance to the activities and goals of post-acute care. Our concerns about the psychometric performance of these instruments in older populations have been echoed in the medical literature.45;46;47 This is not a criticism of these instruments, but a recognition that we are dealing with an older, frailer population in a period immediately following an acute event that requires a unique measurement strategy.
Furthermore, the level of detail measured by any of the individual HRQL instruments in a given domain is often limited such that some areas are not given the weight that our panels recommended. For example, while these instruments examine depressive symptoms, they do not allow for adequate assessment of whether depression is present. Because depression was rated very high by the panels for three of the four conditions, ability to measure it more precisely seemed important. Similarly, while pain is examined by all of the aforementioned HRQL instruments, most instruments have only one or two pain questions. As a clinical endpoint, two pain questions may not be adequate for conditions where pain may be the dominant symptom (e.g., back and neck).
Based on these concerns, as well as comments received during the panel discussions, we chose quality measures that are specific to each indicator that the clinical panels supported. Rather than use an existing comprehensive health status instrument, we have combined individual measures and indices of physical function, depression, social/role function and pain to create a more detailed patient report instrument in the areas chosen. Collectively, we believe that our instruments capture the essential elements of HRQL described in the medical literature,14 while simultaneously providing the level of detail necessary for the patient population served by post-acute care providers.
Numerous physical function measures were discussed. Represented measures were: the MOS SF-36 physical function scale,41 the FIM score,48 the Barthel Index,49 the Lawton IADL Index,50 the Katz ADL Index,51 the Kane ADL Index,52 and the Basic ADL Index.53;54 Selection of the final measure was guided by the need for adaptation for use in-person or by telephone (the individual may actually be discharged from post-acute care at time of follow-up), knowledge of prior performance in post-acute populations, and most importantly, relevance of question content. Based on these guiding principles, Wolinsky's Basic ADL Index, a five-item measure that incorporates the ADLs of bathing, dressing, toileting, transferring, and walking 20 feet, was selected for inclusion.53;54 This assessment of function focuses on self-reported difficulty in ADL performance, which has direct relevance to the provision of post-acute care. It was originally derived using data from the Longitudinal Study on Aging55 and has been used extensively in large national studies of older persons and patients receiving post-acute care.15;56;57 In these post-acute care studies, serial measurement was conducted at baseline corresponding to premorbid period, three, six, nine and twelve months with both in-person and telephone administration. Similar to prior studies that used this instrument in post-acute care, the outcome measure is the number of ADLs recovered to premorbid disability levels.58
In addition to an assessment of basic ADLs, we have also included questions about recovery of IADL function50 for patients with stroke. The stroke panel strongly advocated for inclusion of IADLs as a responsive measure of the quality of care delivered to persons with stroke. While IADLs are important to the care delivered in the other conditions considered, the burden of additional data collection required limiting inclusion to only those measures identified as essential. In subsequent sections, we further describe efforts to ensure that each instrument is comprised of only those measures of most relevance and significance.
Numerous instruments have been designed for self-assessment of depression in general populations.59;60;61 However, only one instrument has been specifically developed for use in the older population, the Geriatric Depression Scale (GDS).62 The GDS places greater emphasis on affective aspects of depression over somatic symptoms. Assessing depression in older post-acute patients is particularly challenging and the GDS has been employed in prior studies in this population.15;63 A shorter version of the GDS has been validated and used successfully. With half as many items, the shorter 15-item version of the GDS poses much less responder burden with minimal loss of sensitivity and specificity.64 For the purpose of quality assessment in post-acute care, we will measure change in GDS score over time.
These two quality indicators were combined into a single indicator based on the recommendation of the expert panels. The panels believed that change in a measure of social/role function would capture important aspects of functional status not addressed by the traditional measures of function, basic ADLs and IADLs. Though the HRQL instruments noted in earlier sections include items measuring social and role function, the wording and examples in the questions are not always relevant to older post-acute patients and appear not to fully capture the concept as it applies to this patient population or as envisioned by the expert panels.
The Reintegration to Normal Living (RNL) Index65 was recommended by several expert panelists and was selected based on the relevance and wording of the items for the population of interest, the development strategy employed in choosing the items, and its brevity. In addition to acceptable psychometric properties, the RNL has been specifically tested in post-acute populations.65 The authors of the RNL solicited input from three advisory panels made up of patients with chronic illness, healthy persons, health care providers, psychologists and clergyman to ensure broad-based input and representation.66 The final instrument is comprised of eleven items, uses a visual analog scale for response and can be converted to a 100 point score. Because we foresee the need to administer follow-up interviews by telephone to measure outcomes of post-acute care, we have adapted the visual analog scale for telephone use using a five-point Likert scale. Further, several of the questions are concerned with activities of less relevance to measuring quality in the post-acute population. These questions have been removed from the instruments.
Evaluation of change in pain control was rated highly for back and neck patients. This prompted a search for a validated pain instrument that referred to a time interval relevant to post-acute care (i.e., four weeks or less). Some pain scales we reviewed placed too much emphasis on affective symptoms and thus were redundant with the depression items covered by GDS.67;68 The McGill Pain Instrument69 and the Back Pain Classification Scale69 were evaluated, but were perceived to lack face validity for the population under study. The MOS Pain Measure, which has proven to be valid and reliable in varied populations,70 was selected for these reasons and because it measures both pain severity and the effects of pain on function. In contrast, the Oswestry Low Back Pain Disability Questionnaire only examines the latter.71
The relationship between patient satisfaction and quality of care continues to become more accepted and established among leading methodologists.72;73;74 The literature on patient satisfaction has been historically dominated by the inpatient hospital setting, followed by the outpatient setting as a distant second site of care. No single instrument has been developed for all three of the post-acute sites of interest for this effort. The instruments designed for satisfaction assessment in nursing homes place more emphasis on living arrangements and autonomy pertinent to a long-term care population rather than time-limited rehabilitation pertinent to post-acute patients. Similarly, questions on instruments used in home care are not easily translated to older patients who are not residing in their homes. The most promising of all satisfaction instruments reviewed was developed by researchers at the Rehabilitation Institute of Chicago.75 The main advantage of this instrument stems from the fact that the wording of the individual items allows for administration in all three sites of post-acute care. However, the length of the full instrument limits its utility in our instruments. Fortunately, the individual items have been validated and we have recommended that a representative and relevant sub-group of questions be incorporated into our post-acute care quality measurement instruments. These questions focus on the patients perceptions of the care delivered and how well their needs are being met with respect to returning to independent living.
Uniformly, the panels recommended inclusion of use of emergency services and rehospitalizations during the post-acute episode as indicators of quality of care. In addition, to account for the possibility that a given patient might use more than one type of post-acute care (e.g., SNF followed by home health care), total post-acute utilization was also recommended as a quality measure. Finally, the panelists recommended including, if applicable, the date of death.
The number of disease-specific patient report indicators recommended varied by condition. While these indicators have intuitive appeal, few have been operationalized from the standpoint of quality measurement. In many cases, the disease-specific measures added to the patient report section have not been formally tested. For example, the back and neck panel argued that existing pain and disability instruments did not adequately address change in limb numbness and tingling for patients with back and neck conditions. These symptoms represent important target symptoms that may not be captured under a narrow definition of nociceptive pain. The back and neck instrument has been supplemented with these questions accordingly. Change in symptoms of dyspnea, fatigue and cough for patients with pneumonia were modified from formal instruments.76 For CHF, a validated disease-specific quality of life measurement instrument is included to assess the change in how CHF symptoms affect quality of life over time. The first four items of the Chronic Heart Failure Questionnaire have been included specifically to address control of symptoms.76
Additional Measures for Risk Adjustment
Additional questions were included to account for important differences in case mix when comparing quality across settings of post-acute care. Potential adjusters that could be derived from patient self-report include cognitive status, social support, and demographics. In addition to these potential self-report risk adjusters, we identify other potential risk adjusters in subsequent sections of this report. The Pfieffer Short Portable Mental Status Questionnaire (SPMSQ) has been shown to be both valid and reliable77;78 and was selected as a potential cognitive screen. The SPMSQ was developed to provide a rapid screen (approximately two minutes) for cognitive impairment in older patients and has been used extensively in both community and institutional settings.79;80 The Mini Mental Status Exam (MMSE)81 was also selected as a potential cognitive screen. The MMSE is longer and more strenuous than the SPMSQ, requiring ten minutes and thirty points. The MMSE is more commonly used as a risk adjuster in qualitative research than the SPMSQ and allows finer delineation between different levels of cognitive dysfunction. The MMSE and SPMSQ will also serve as indicators of when a proxy informant may be required for the patient self-report component of the instruments. Social supports and living arrangements will be assessed using selected items from the Older Americans Resource and Services (OARS) instrument.82 Standard demographic data will also be assessed from patient self-report for the purpose of risk adjustment. These characteristics include: age, race, gender, education and marital status.
The process quality measures, both global and disease-specific, were selected by the panels because of an association with high quality care and, in some cases, with defined clinical outcomes (e.g., ACE inhibitor use and mortality in CHF). However, there are some logistical and measurement considerations worth noting. Similar to the patient report symptom measures, some of the indicators rated highly by the panels do not have corresponding validated measures. Other highly rated indicators were not included because measurement was simply not possible (e.g., time to reach clinical stability following pneumonia). Thus, process measures as recommended by the expert panels were incorporated judiciously.
To measure most of the outcome domains specified above (physical function, social/role function, mental health, and satisfaction with care), two separate patient report instruments were created for each of the four conditions: an admission instrument and a follow-up instrument. The admission instruments were designed to be administered within ten days of post-acute care admission to assess baseline function one month prior to hospitalization. Initially, the section on physical functioning included measurement of perceived physical function at the time of the interview, in addition to the existing questions about function one month prior to the hospitalization. However, during pilot testing, we found qualitative difficulties administering the questions related to function at two distinct time periods, with subjects becoming confused. As a result, the baseline patient interview will not be used to assess function at the time of entry into post-acute care because of the difficulties encountered when trying to ask patients or proxies to describe their functional capacity at two separate time points, both one month prior to hospitalization and at the time of post-acute care admission. A tight time interval between admission and completion of the baseline instruments is not required since the questions largely refer to pre-hospitalization function and status, with the exception of mood related questions encompassed in the GDS. The follow-up instruments were designed to be administered at a pre-determined follow-up time point and to assess recovery to baseline function. For CHF and pneumonia, the follow-up time point chosen was 60 days after post-acute care admission; for stroke and back and neck conditions, the follow-up time point chosen was 90 days after post-acute care admission (see discussion in Section D1).
The source of provider reported data will be the medical and post-acute care record. This component is needed to assess specific process measures advocated by the expert panels, and to obtain information about comorbidity for case mix adjustment.
Risk adjustment: The medical record is a valuable source of information to create comorbidity indices for the purpose of case mix adjustment. Indices such as the Charlson Index83 have been used extensively and are relatively simple to construct. The Charlson Index is comprised of a formula that provides a weighting of chronic illnesses. These diagnoses represent major conditions that would normally be represented in an individual patients problem list in the medical record. Additional hospital chart review items to be collected for risk adjustment for patients with pneumonia include evaluation for delirium, blood gas results, abnormal vital signs, and lab parameters.84
In addition, the provider reported component includes information obtained from several formal patient assessment instruments, including the MDS, MDS-PAC and OASIS. In an effort to reduce redundancy, relevant items from the MDS and OASIS (and once implemented, the MDS-PAC) will be abstracted. Additional data for case mix adjustment will also be abstracted from these data sources. Data on patient function at the time of post-acute admission can be obtained from these three sources for risk adjustment. Because all three instruments are required upon post-acute care admission and all three have basic function items that allow estimation of a Barthel Index, data from these can be used sparingly to risk adjust for function at the time of post-acute admission. In particular, physical function items from these instruments can be converted to a comparable Barthel Index. Results from a forthcoming validation study conducted by our research team reveal that the MDS 2.0-based Barthel Index compares favorably to an actual independent Barthel measure. Testing and refinement of the MDS-PAC and OASIS conversions are underway. The conversion codes are provided in Appendix G.
Process measures: In addition, selected process measures recommended by the expert panels would be obtained from the medical and post-acute care records.
Global process measures: With regard to global process quality measures, the panels recommended that regardless of condition or post-acute setting, an evaluation by a licensed physical therapist and occupational therapist are important and essential elements of high quality post-acute care. These were the only two process measures believed to be relevant to all four conditions.
Disease-specific process measures: The disease-specific quality of care processes reflect a wider range of care.
Stroke: For patients with stroke, quality measures include a speech and swallowing evaluation, and management by a multidisciplinary care team. In addition, efforts to educate the patients informal caregivers need to be recorded. For patients who experience a non-hemorrhagic stroke, consideration of anticoagulation must be explicitly documented in patient records. The day the patients stroke occurred relative to initiation of post-acute care will be determined for the purpose of risk adjustment.
CHF: For patients with CHF, those patients with compromised left ventricular function should either be on an ACE inhibitor or have the reason for not using an ACE inhibitor clearly evident in their records. In addition, patients with CHF need to have the frequency of body weight assessment documented in their records as well as an attempt by post-acute care providers to evaluate their medication compliance.
Pneumonia: Patients with pneumonia should have documentation of advance directives discussions and immunization status for influenza and pneumococcal pneumonia. Obtaining blood cultures during the acute course of illness was recommended by the pneumonia panel out of concern that this may be overlooked in patients with pneumonia who are not hospitalized before admission to post-acute care. Distinguishing community-acquired pneumonia from nosocomial with regard to antibiotic selection was also included for its relevance to post-acute care.
Back and Neck Conditions: For patients with back and neck conditions, the expert panel emphasized the importance of use of prescription analgesic medications. From the perspective of quality measurement, it is not always clear to what degree use of prescription medications is associated with quality. The appropriate selection of medication and dosing is often highly tailored to the individual. Instead, a much stronger case could be made for focusing on whether or not pain was systematically assessed and that a plan of care had been devised and documented. Thus, evidence of a revised plan of care designed to optimize pain control would be considered a high quality process of care.
While the data needed to measure the utilization outcomes (e.g., emergency services, rehospitalizations, and multiple post-acute care use) would likely be obtained from claims data for patients treated under the Medicare fee-for-service program, these items are included in the instruments to be certain they are collected for HMO patients.
Once the four draft instruments were compiled, we convened a second expert panel that included content experts, methodologists, providers, and Federal policy officials (see Appendix H). All expert panel members were asked to comment on the relevance and feasibility of the measures, response burden, sampling issues, definitions of an episode of care, and redundancy with other reporting requirements. Content experts (disease specialists) in the four clinical conditions were also asked to comment on the balance between global and disease-specific measures, the feasibility of constructing a summary performance measure, and risk adjustment. Methodologists, including those with experience in post-acute care quality measurement, were asked to comment on the feasibility of administering the measures, the scaling (i.e., floor and ceiling effects), responsiveness of measures, and risk adjustment.
Prior to the in-person panel meeting, we convened three separate conference calls with disease specialists in the areas of CHF, pneumonia, and back and neck conditions. (Note: We did not convene a separate conference call for stroke because the stroke specialist was present at the in-person panel meeting.) Among the issues discussed during the specialist calls were disease-specific measures, post-acute care episode length, and case mix adjustment. Notes from the three specialist calls are included in Appendix I. One especially significant outcome of the specialist calls was the decision to narrow the back and neck condition down to the more specific condition of lumbar spinal stenosis. The back and neck specialist strongly recommended using lumbar spinal stenosis as a tracer condition for this study because it is a relatively prevalent condition that will yield a more homogeneous patient sample. Therefore, throughout the remainder of this report, we will refer to the former back and neck condition as lumbar spinal stenosis.
For the in-person panel meeting, we compiled a series of key questions (see Appendix J) related to issues such as post-acute care episode length, measure feasibility and responsiveness, response burden, and case mix adjustment, which served as a guide for panel discussion. Following are some highlights of the panels recommendations.
With respect to physical function particularly as it relates to stroke outcomes, panel members recommended including a more thorough assessment of higher order function (i.e., IADLs) in addition to basic ADL function, which would allow better discrimination between patients with varying degrees of functional ability as well as recovery of higher level functions following stroke.
In defining an episode of post-acute care, (the interval between admission and follow-up assessments), the panels objective was to recommend an episode that would allow enough time for most disease-specific outcomes to have occurred, while not encountering any new post-acute care episodes. Panel members therefore recommended a 60-day follow-up for CHF and pneumonia, and a 90-day follow-up for stroke and lumbar spinal stenosis.
Panel debate centered around the appropriate assessment of satisfaction. Patient confidentiality may be a concern if assessing satisfaction upon admission, especially if the data collector were affiliated with the post-acute facility; whereas poor patient recollection of the post-acute stay may be a concern if assessing satisfaction at follow-up. Mail-in satisfaction surveys were mentioned as a possible alternative; however, difficulties with low response rate to mail-in surveys remains an issue. Consensus was not reached in this area.
The panel recommended assessing caregiver burden, satisfaction, and patient and caregiver education as outcomes that are reflective of quality of post-acute care.
Certain processes of care that may be difficult to abstract from post-acute care charts might better be assessed through patient interview at follow-up. For many of these measures, such as caregiver/family education and discussion of advance directives, patients perceptions of care processes might be more informative than the facilitys documentation of such processes.
Another issue discussed during the meeting included disease-specific risk adjustment items (e.g., Rankin Score for stroke and renal disease in CHF).
Prior to and concurrent with the second expert panel meeting, we began conducting feasibility tests of the four quality measurement instruments in SNFs, IRFs, and HHAs located in the Denver metropolitan area. We selected facilities based on feedback received from local clinicians regarding volume of admissions and responsiveness of facility staff. Following is a brief summary of the feasibility test issues and findings.
Feasibility testing was conducted in two phases. During the first phase, four SNFs, two HHAs, and two IRFs were enrolled and a social worker or intake person from each facility was asked to identify patients newly admitted with one of the four tracer conditions. Identified patients were subsequently invited to participate and consent was obtained. Interviews, using the instruments developed, were then conducted to determine feasibility of administration of the questions.
In the first phase of piloting, 21 subjects were recruited and interviewed. Of the 21 interviews, 13 were conducted in SNFs, six were conducted in HHAs, and two were conducted in IRFs. Seven of these 21 subjects were admitted to the post-acute facility with pneumonia, five with CHF, two with back and neck conditions, and seven with stroke. Hospital and post-acute care charts were obtained on these subjects and reviewed using the chart review instruments. Revisions were made to the instruments based on insights gained from the first phase of piloting and feedback from the expert panel. A second phase of piloting was then conducted using the newly revised instruments. Four subjects were recruited and interviewed during this phase. Of the four interviews, one was conducted in an SNF, two were conducted in IRFs, and one was conducted in an HHA. One of these four subjects was admitted to the post-acute facility with a back and neck condition and three were admitted with strokes.
During both phases of feasibility testing, ongoing difficulties were encountered in identifying and recruiting patients. Facility staff who were responsible for identifying newly admitted residents for our study indicated on several occasions that there were numerous demands on their time and that they simply did not have the time (or additional staff) necessary to review the facilitys admissions on a regular basis. This issue was of particular concern to staff members in SNFs and HHAs. Although we had been successful with this method of patient recruitment for past studies, many of the facility staff and administrators we spoke with indicated that pressures under PPS had placed increasing demands on their time and available resources.
The time to complete the entire admission interview, after consent was obtained, averaged 25 minutes.
Approximately 13% of eligible subjects declined to participate.
Subjects requiring a proxy were not eligible for the pilot study because we did not have IRB approval to use proxies. (Approximately 17% of subjects were below the mental status cut-off.)
The order of the sections was changed to improve the flow from one section to the next.
The time to complete the telephone follow-up interview averaged 14 minutes, and the response rate was approximately 63%.
Married, Education, and Race
A question about the duration since married/widowed/divorced was deleted because of uncertain relevance to any of the measured outcomes or as a risk stratifier.
The time necessary to complete the MMSE averaged 10 minutes and some subjects appeared to be annoyed or burdened by the questions. The SPMSQ, used on the stroke and lumbar spinal stenosis instruments, appeared to be less burdensome for subjects to complete, eliciting fewer complaints or difficulties. However, the purpose of mental status testing is three-fold: (1) To determine a subjects capacity to consent to participate in the study and understand the described risks and benefits; (2) to identify subjects whose memories are impaired and whose responses to questions about past functional capacity may be inaccurate; and (3) to use as a descriptive variable for the study population and risk adjuster in later data analysis. Given these three needs, the MMSE was retained despite the time necessary for completion.
As mentioned, this section was initially expanded to include measurement of perceived physical function at the time of the interview as well as functioning one month prior to the hospitalization. However, we found qualitative difficulties administering the questions related to function at two distinct time periods, with subjects becoming confused. Thus, function at the time of admission to rehabilitation was dropped from the patient survey, because it can be derived from automated patient data in the form of a cross-walked Barthel Index, for the purposes of risk adjustment. While functional items from automated patient data like the MDS are considered adequate for risk adjustment purposes (for function at the time of post-acute admission), recovery of patient-perceived function is the outcome of interest. Recovery of function requires measurement at a fixed time point across all settings and must be obtained from the patient or proxy, as previously discussed.
IADL measures were included in the final stroke instrument to represent higher levels of function as recommended by the panel. However, IADLs with high non-response rates (e.g., due to gender bias) were excluded based on prior IADL measurement experience at the University of Colorado Health Sciences Center.
Social and Role Function
The Re-integration to Normal Living Scale was difficult to administer in an interview format, although the original instrument was used in this context. In particular, the 5-point scale proved to be too cumbersome for subjects to answer. Secondly, the first-person nature of the questions was awkward to use in an interview format. The following changes were therefore made:
Several questions about role function were deleted prior to the pilot project because they were not relevant to an elderly, post-acute population.
The first-person narrative was changed to a question format (from I moved around my house to were you able to move around your house ).
The present tense of the questions as originally written was changed to past tense for the admission interview to allow measurement of social and role function prior to the index event, in concert with the other baseline measurements.
The answer scale was changed to a yes/no answer, followed by a rating of how bothered the subject is/was by limitations in social/role function if he/she answered no, they were not able to perform a given social/role function.
Throughout the process of altering the Re-integration to Normal Living Scale, a concerted attempt was made to maintain the essence of the questionnaire in terms of measuring subjects function from their perspective, their perceived need to perform a certain function, and how disturbed they are/were by limitations in social and role function.
Pain (Lumbar Spinal Stenosis Instrument Only)
Questions specifically referring to back/neck or limb pain were removed because subjects responses to the general pain questions appeared to be related to back/neck/limb pain and the site-specific questions seemed redundant. In an attempt to shorten the number of pain questions, questions related to numbness were also removed.
The pain instrument was derived from the MOS pain questionnaire. The original instrument uses a 20-point visual analogue scale. With pilot subjects, the 20-point scale was awkward, and a 10-point scale was more familiar to subjects. A 10-point scale was adopted.
The GDS questions were easily administered. Question #9 was difficult for several subjects to answer because at the time of the interview they were in a skilled nursing or rehabilitation facility and were therefore limited in their ability to go out. Therefore, it was decided that this question would be asked only of home health patients.
Two questions regarding the availability of a willing and able caregiver were added to reflect both short-term and long-term social support networks. The original instrument had similar questions, but they proved to be difficult for subjects to answer in their original format, particularly about the time frame of support availability (indefinite, short time, now and then). Some participants answered that all three were true and specified a different person for each. The added questions were adapted from the Longitudinal Study on Aging, but differ in the addition of the two time frames: short and longer term.
Quality of Life (CHF and Pneumonia Instruments)
Questions related to dyspnea were modified. The original questions had a seven-level response ranging from Not at all short of breath to Extremely short of breath. The response scale was modified to a three-level scale because of subjects difficulty responding to the seven-level question. This modification decreases the likelihood of finding the same degree of variability in these questions as well as detecting small amounts of intra-subject change over time. The trade-off between making the questions easier to answer versus decreasing the likelihood of finding change and variability was intended as a discussion point for the expert panel, but there was not ample time to cover this issue. Thus, a decision was made to simplify the questions based on the qualitative experience conducting pilot interviews.
Patient satisfaction with care was ranked very highly by the original expert panel and considered a necessary component of quality measurement for post-acute care. However, measurement of satisfaction presents several challenging issues. First, when should satisfaction be measured? In the original instrument, satisfaction questions were placed in the follow-up telephone interview. This presents a problem because that interview is scheduled to take place 90 days later. Subjects ability to recall the care received 90 days prior may be suspect. Alternatively, measurement of satisfaction early in the post-acute stay via the baseline instrument may reflect satisfaction with acute hospital care, or be too premature for subjects to have formed an opinion. Also, at the baseline interview facility staff will be collecting baseline data, which may bias subjects response to satisfaction questions. We have considered an alternative strategy of giving a written satisfaction survey to subjects and asking them to mail it at the end of their post-acute stay. This strategy is subject to selection bias. Ultimately, we decided to ask three satisfaction questions during the 90-day follow-up telephone interview.
The four instruments were revised on a continuous basis, based on insights gained from both the expert panel meeting and local pilot testing. Although the instruments underwent several rounds of revisions based on these insights, there remain some limitations with their use. First, the reliability and validity of the instruments require further testing. Pilot test sample sizes for both the admission and telephone follow-up interviews were very small. Second, the instruments rely heavily upon patient-reported information. While patient report measures are necessary in researching such domains as health-related quality of life, mental health, depression, social/role function, and satisfaction with care, it may not be feasible to utilize such measures for ongoing quality monitoring purposes. Third, the validity of the satisfaction measures included in these instruments -- as of all health care satisfaction measures -- is subject to factors such as the subjects reluctance to discuss quality of medical care, reduced expectations, unwillingness to complain, and fear of retaliation. In addition, as previously mentioned, the time point (admission, follow-up, or other) at which satisfaction should be assessed is unclear. And finally, although these instruments contain both global and disease-specific components for the four conditions, they are weighted more heavily toward global measures of quality. Although some may argue that more disease-specific measures should be incorporated, the ratings of the expert panel members indicated that more emphasis should be placed on global measures that are relevant to all patients served in post-acute care settings.
Understanding the quality of post-acute care is more important and has become more challenging than ever before. The multiple and ongoing changes to Medicare post-acute care payment policies create a dynamic environment in which measuring the effect of service delivery is particularly difficult. The statute requires new PPSs for each post-acute care provider type. Each PPS varies in terms of key design features such as the unit of payment (per diem, per discharge, every 60 days), classification schemes (e.g., RUGs, HHRGs, and case mix groups), and patient assessment instruments and processes used for patient classification (e.g., MDS, OASIS, and MDS-PAC). Each of these payment schemes is being phased in on different timetables, and each is being modified in different ways and at different times. How such fragmentation will affect the quality and outcomes of post-acute care is difficult to anticipate.
This project identified a mixture of both global and disease-specific measures that are important in measuring outcomes of post-acute care, based on a consensus of clinicians and researchers, and a review of the literature. The study focused on patients who, following a hospital stay, received post-acute care for conditions that required either intense medical or rehabilitation management. The conditions targeted in this study were CHF, pneumonia, stroke, and back and neck (lumbar spinal stenosis). Through discussions with expert clinicians and researchers, and a review of the literature, post-acute care outcome measures were identified that include traditional measures of physical function, utilization, and mental health, and measures emphasizing symptom relief, specific therapies and other processes of care, satisfaction, and health-related quality of life including role resumption.
Based on input from expert clinicians and researchers, and a review of the literature, the project found that existing administrative data do not contain information needed to measure important outcomes within and across post-acute care settings, and across a span of time over which important post-acute care outcomes may mature. While existing data systems include information needed for some of these measures (e.g., utilization and functional measures) many of the measures identified as important in understanding quality of post-acute care are not included in existing administrative data (e.g., mental health, quality of life, satisfaction, and role resumption). In addition, while existing data systems measure functional status (i.e., information that was considered important across all conditions), existing patient assessment instruments measure functional status in different ways and at different times across post-acute care settings. Further, the differences in patient assessment instruments and processes make it difficult to identify whether similar patients are, in fact, treated across different settings, and if so, what are their relative outcomes of care. Finally, patient assessment data is collected only as long as a patient is treated in any particular post-acute care setting. However, many outcomes that the expert clinicians and researchers identified as important may not be present until after the patient is discharged from the post-acute care setting. Thus, while existing data systems may serve a variety of purposes, they were not found to include information needed to measure post-acute care quality and outcomes.
The instruments developed under this study for each of the four tracer conditions are available to others interested in conducting research measuring the outcomes of post-acute care for patients with these conditions.
ASPE has contracted with the University of Colorado Health Sciences Center and Mathematica Policy Research, Inc., to conduct a national study that will utilize the instrument developed for stroke patients to evaluate, in a post-PPS environment, the outcomes and costs of post-acute care provided in SNFs, rehabilitation hospitals and HHAs. This national study of stroke patients is intended to address several questions about Medicare beneficiaries who are discharged from hospitals to post-acute care, including:
What are the demographic and health-related characteristics of patients admitted to post-acute care, including persons who use multiple post-acute providers (e.g., SNF followed by HHA, or IRF followed by HHA)? What are the similarities and differences between patients admitted to the three settings or multiple settings?
What patterns of post-acute provider use are most prevalent for these patients?
What are the health, functional, quality of life, and other outcomes for beneficiaries treated in HHAs, SNFs, IRFs, or in multiple post-acute settings?
Which post-acute setting, or combinations of settings, provides better outcomes and quality of care for similar patients with stroke, after controlling for case mix differences?
How does the mix and intensity of services provided in HHAs, SNFs, IRFs, or in use of multiple post-acute settings compare?
To what extent do Medicare expenditures and costs differ for similar patients treated in different post-acute settings, or combinations of settings?
What core outcome and quality measures are most useful to incorporate into ongoing reporting requirements to monitor the quality of post-acute care for stroke?
This project, funded by ASPE in 1999, will be completed in January 2004.
Liu K, Gage B, Harvell J, Stevenson D, Brennan N. Medicare's post-acute care benefits: background, trends, and issues to be faced. 1999. US Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation. [Full Report]
Gage B. The balanced budget act: implication for post-acute services. 1998. New York, NY, The Commonwealth Fund.
Leibson CL, Naessens JM, Campion ME, Krishan I, Ballard DJ. Trends in elderly hospitalization and readmission rates for a geographically defined population: pre- and post-prospective payment. Journal of the American Geriatrics Society 1991; 39(9):895-904.
Manton KG, Woodbury MA, Vertrees JC, Stallard E. Use of Medicare services before and after introduction of the prospective payment system. Health Services Research 1993; 28(3):269-292.
Shaughnessy PW, Kramer AM. The increased needs of patients in nursing homes and patients receiving home health care. New England Journal of Medicine 1990; 322(1):21-27.
Easton LS, Cogen R, Fulcomer M. Effect of Medicare prospective payment system on a home health agency: changes in patient population and services provided. Applied Nursing Research 1991; 4(3):107-112.
Rubenstein LV, Kahn KL, Reinisch EJ, Sherwood MJ, Rogers WH, Kamberg C et al. Changes in quality of care for five diseases measured by implicit review, 1981 to 1986. JAMA 1990; 264(15):1974-1979.
Office of the Inspector General, Department of Health and Human Services. Early effects of the prospective payment system on access to skilled nursing facilities. OEI-02-99-00400. 1999.
Office of the Inspector General, Department of Health and Human Services. Medicare beneficiary access to home health agencies: 2000. OEI-02-00-00320. 2000.
Prospective Payment Assessment Commission. Medicare and the American health care system: report to the Congress. 91. 1996.
Prospective Payment Assessment Commission. Medicare and the American health care system: report to the Congress. 110. 1996.
Prospective Payment Assessment Commission. Medicare and the American health care system: report to the Congress. 113. 1996.
Medicare Payment Advisory Commission. December 2000 meeting transcript. Medicare Payment Advisory Commission. 2000. Medicare Payment Advisory Commission.
Wilson IB, Cleary PD. Linking clinical variables with health-related quality of life. JAMA 1995; 273(1):59-65.
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.
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. Journal of the American Geriatrics Society 1998; 46:1525-1533.
Anderson C, Rubenach S, Mhurchu CN, Clark M, Spencer C. Home or hospital for stroke rehabilitation? Results of a randomized controlled trial: I: health outcomes at 6 months. Stroke 2000; 31(5):1024-1031.
Anderson C, Mhurchu CN, Rubenach S, Clark M, Spencer C. Home or hospital for stroke rehabilitation? Results of a randomized controlled trial: II: cost minimization analysis at 6 months. Stroke 2000; 31(5):1032-1037.
Johnson MF, Kramer AM, Lin MK, Kowalsky JC, Steiner JF. Outcomes of older persons receiving rehabilitation for medical and surgical conditions compared with hip fracture and stroke. Journal of the American Geriatrics Society 2000; 48(11):1389-1397.
Rogers JC, Gwinn SM, Holm MB. Comparing activities of daily living assessment instruments: FIM, MDS, OASIS, MDS-PAC. Physical and Occupational Therapy in Geriatrics 2001; 18(3):1-25.
Medicare Payment Advisory Commission. September 2000 meeting transcript. Medicare Payment Advisory Commission. 2000. Medicare Payment Advisory Commission.
Gresham GE, Duncan PW, Stason WB. Post-stroke rehabilitation: clinical practice guideline no. 16. 1995. Rockville, MD, Agency for Health Care Policy and Research.
Duncan PW, Jorgensen HS, Wade DT. Outcome measures in acute stroke trials: a systematic review and some recommendations to improve practice. Stroke 2000; 31(6):1429-1438.
Hart RG, Benavente O. Stroke: part I. A clinical update on prevention. American Family Physician 1999; 59(9):2475-2482.
Barnett HJ, Eliasziw M, Meldrum HE. Drugs and surgery in the prevention of ischemic stroke. New England Journal of Medicine 1995; 332(4):238-248.
Barker WH, Zimmer JG, Jackson Hall W, Ruff BC, Freundlich CB, Eggert GM. Rates, patterns, causes and costs of hospitalization of nursing home residents: a population-based study. American Journal of Public Health 1994; 84(10):1615-1620.
Kayser-Jones JS, Wiener CL, Barbaccia JC. Factors contributing to the hospitalization of nursing home residents. Gerontologist 1989; 29(4):502-510.
Gage B. Impact of the BBA on post-acute utilization. Health Care Financing Review 1999; 20(4):103-126.
Lee AJ, Huber JH, Stason WB. Poststroke rehabilitation in older Americans: the Medicare experience. Medical Care 1996; 34(8):811-825.
Lee AJ, Huber JH, Stason WB. Factors contributing to practice variation in post-stroke rehabilitation. Health Services Research 1997; 32(2):197-221.
Liu K, Gage B, Kramer A. Medicare post-acute care quality measurement: selecting and evaluating eight targeted conditions. 1998. Washington, DC, The Urban Institute.
Kramer A, Eilertsen T, Holthaus D, Johnson M, Gage B. Medicare post-acute care quality measurement: selecting the targeted conditions. 1998. Denver, CO, Center on Aging, University of Colorado Health Sciences Center.
Medicare Payment Advisory Commission. Health care spending and the Medicare program: a data book. July 1998 ed. 1998.
Harrington D, Summers PR, Curtis M, Maynard R. Study of the resident assessment information system. 1996. San Francisco, CA, University of California, Department of Social and Behavioral Sciences.
Committee on Improving Quality in Long-Term Care, Institute of Medicine, Department of Health and Human Services. Improving the quality of long-term care. Wunderlich GS, Kohler PO, editors. 2000. Washington, DC, National Academy Press.
Guyatt G, Cook D. Health status, quality of life, and the individual. JAMA 1994; 272(8):630-631.
Frank L, Kleinman L, Kline N, Legro M, Shikiar R, Revicki D. Defining and measuring quality of life in medicine. JAMA 1998; 279(6):429-430.
Guyatt G. Insights and limitations from health-related quality-of-life research. Journal of General Internal Medicine 1997; 12:720-721.
Berlowitz D, Du W, Kazis L, Lewis S. Health-related quality of life of nursing home residents: differences in patient and provider perceptions. Journal of the American Geriatrics Society 1995; 43(7):799-802.
Guyatt G, Feeny D, Patrick D. Measuring health-related quality of life. Annals of Internal Medicine 1993; 118(8):622-629.
Ware JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). Medical Care 1992; 30(6):473-481.
Bergner M, Bobbitt R, Carter W, Gilson B. The sickness impact profile: development and final revision of a health status measure. Medical Care 1981; 19(8):787-805.
Gerety M, Cornell J, Mulrow C, Tuley M, Hazuda H, Lichtenstein M et al. The sickness impact profile for nursing homes. Journals of Gerontology 1994; 49(1):M2-M8.
Kaplan R, Bush J, Berry C. Health status: types of validity and the index of well-being. Health Services Research 1976; 11:478-507.
Stadnyk K, Calder J, Rockwood K. Testing the measurement properties of the short form-36 health survey in a frail elderly population. Journal of Clinical Epidemiology 1998; 51(10):827-835.
Wolinsky FD, Wan GJ, Tierney WM. Changes in the SF-36 in 12 months in a clinical sample of disadvantaged older adults. Medical Care 1998; 36(11):1589-1598.
McHorney C. Measuring and monitoring general health status in elderly persons: practical and methodological issues in using the SF-36 health survey. Geronotologist 1996; 36(5):571-583.
Linacre J, Heinemann A, Wright B, Granger C, Hamilton B. The structure and stability of the functional independence measure. Archives of Physical Medicine and Rehabilitation 1994; 75:127-132.
Mahoney F, Barthel D. Functional evaluation: the Barthel index. Maryland State Medical Journal 1965; 14:61-65.
Lawton M, Brody E. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 1969; 9:179-186.
Katz S, Ford A, Moskowitz R, Jackson B, Jaffe M, Ford A et al. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963; 185:914-919.
Finch M, Kane R, Philp I. Developing a new metric for ADLs. Journal of the American Geriatrics Society 1995; 43(8):877-884.
Wolinsky FD, Johnson RJ. The use of health services by older adults. Journals of Gerontology 1991; 46(6):S345-S357.
Fitzgerald J, Smith D, Martin D, Freedman J, Wolinsky F. Replication of the multidimensionality of activities of daily living. Journals of Gerontology 1993; 48(1):S28-S31.
Fitti J, Kovar M. The supplement on aging to the 1984 national health interview survey. US Government Printing Office, editor. 87-1323. 1987. Washington, DC, US Department of Health and Human Services.
Kramer A. Outcomes for stroke and hip fracture patients in HMO and fee-for-service systems. Presented at Beyond the Waters Edge: Charting the Course of Managed Care for People with Disabilities. St. Michaels, MD. November 1996. [Executive Summary]
Wolinsky FD, Callahan CM, Fitzgerald JF, Johnson RJ. The risk of nursing home placement and subsequent death among older adults. Journals of Gerontology 1992; 47(4):S173-S182.
Kramer AM. Rehabilitation care and outcomes from a patient's perspective. Medical Care 1997; 35(6):JS48-JS57.
Radloff L. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement 1977; 1:385-401.
Hamilton M. A rating scale for depression. Journal of Neurology, Neurosurgery and Psychiatry 1960; 23:56-62.
Beck A, Steer R, Garbin M. Psychometric properties of the Beck depression inventory: twenty-five years of evaluation. Clinical Psychology Review 1988; 8:77-100.
Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M et al. Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research 1983; 17:37-49.
Lesher E, Berryhill J. Validation of the geriatric depression scale-short form among inpatients. Journal of Clinical Psychology 1994; 50:256-260.
Lyness J, Noel T, Cox C, King D, Conwell Y, Cain E. Screening for depression in elderly primary care patients: a comparison of the center for epidemiologic studies-depression scale and the geriatric depression scale. Archives of Internal Medicine 1997; 157:-449.
Wood-Dauphinee S, Williams JI, Opzoomer MA, Marchand B, Spitzer WO. Assessment of global function: the reintegration to normal living index. Archives of Physical Medicine and Rehabilitation 1988; 69:583-590.
Wood-Dauphinee S, Williams JI. Reintegration to normal living as a proxy to quality of life. Journal of Chronic Disability 1987; 40(6):491-499.
Pilowsky I, Bassett D, Barrett R, Petrovic L, Minniti R. The illness behavior assessment schedule: reliability and validity. International Journal of Psychiatry in Medicine 1983; 13:11-28.
Zung WK. A self-rating pain and distress scale. Psychosomatics 1983; 24:887-894.
Melzack R. The McGill pain questionnaire: major properties and scoring methods. Pain 1975; 1:277-299.
Sherbourne C. Pain measures. In: Stewart A, Ware Jr J, editors. Measuring functioning and well-being: the Medical Outcomes Study approach. Durham, NC, Duke University Press; 1992: 220-234.
Fairbank J, Couper J, Davies J, O'Brien J. The Oswestry low back pain disability questionnaire. Physiotherapy 1980; 66(8):271-273.
Cleary P, McNeil B. Patient satisfaction as an indicator of quality care. Inquiry 1988; 25(1):25-36.
Covinsky K, Rosenthal G, Chren M, Justice A, Fortinsky R, Plamer R et al. The relation between health status changes and patient satisfaction in older hospitalized medical patients. Journal of General Internal Medicine 1998; 13(4):223-229.
Nelson E, Hays R, Larson C, Batalden P. The patient judgment system: reliability and validity. QRB: Quality Review Bulletin 1989; 15(6):185-191.
Heinemann A, Bode R, Cichowski K, Kan E. Measuring patient satisfaction with medical rehabilitation. Journal of Rehabilitation Outcomes Measurement 1997; 1(4):52-65.
Guyatt G, Nogradi S, Halcrow S, Singer J, Sullivan M, Fallen E. Development and testing of a new measure of health status for clinical trials in heart failure. Journal of General Internal Medicine 1989; 4:101-107.
Pfeiffer E. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. Journal of the American Geriatrics Society 1975; 23:433-441.
Smyer M, Hofland B, Jonas E. Validity study of the short portable mental status questionnaire for the elderly. Journal of the American Geriatrics Society 1979; 27:263-269.
Lesher E, Whelihan W. Reliability of mental status instruments administered to nursing home residents. Journal of Consulting and Clinical Psychology 1986; 54:726-727.
Pfeiffer E, Johnson T, Chiofolo R. Functional assessment of elderly subjects in four service settings. Journal of the American Geriatrics Society 1981; 29:433-437.
Folstein M, Folstein S, McHugh P. Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 1975; 12(3):189-198.
Multidimensional functional assessment: the OARS methodology. Durham, NC, Duke University Center for the Study of Aging and Human Development. 1978.
Charlson M, Pompei P, Ales K, MacKenzie C. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Disability 1987; 40(5):373-383.
Fine M, Hanusa B, Lave J, Singer D, Stone R, Weissfeld L et al. Comparison of a disease-specific and a generic severity of illness measure for patients with community-acquired pneumonia. Journal of General Internal Medicine 1995; 10:359-368.
This legislation included additional changes to post-acute care payment policy that are not discussed in this report.
|You can advance to: