Executive Summary The Health Care Financing Administration (HCFA) has had a long-term commitment to work towards implementation of a per-episode prospective payment approach for Medicare home health services, and Section 5101(f) of Public Law 105-277, Omnibus Consolidated and Emergency Supplemental Appropriations Act for Fiscal Year 1999, mandates the implementation of such a system by FY2001. HCFA must develop a payment system which promotes provider efficiency while preserving access to services for patients with high care needs. The latter goal is attained by modifying payment amounts based on prospectively-set rates using adjustment factors which reflect the differences in the amount of resources required by patients of different types. This is typically termed case-mix adjustment. The formulation of accurate case-mix adjustment factors requires the ability to estimate the future resource use by each patient or by categories of patients. This document presents findings from a research project intended to develop such a case-mix adjustment model. This Project Previous efforts to develop a model that predicts home health resource use have had less than satisfactory results. This project was designed to improve upon past efforts by: Recruiting a large sample of agencies that could in turn provide a large representative sample of patients for the analysis; Collecting extensive and consistent data on patient, agency, and area characteristics; Collecting more detailed and consistent data on the services provided and resources used. The Agencies and the Patient Cohort. The study design called for recruitment of 90 home health agencies from 8 states, selected for diversity of location, home health practice pattern, distribution of agency type, and fiscal intermediary. A total of 290 agencies volunteered to take part, and a sample of 90 were selected to participate, stratified so as to optimize our ability to generate national estimates of patient distributions from the study. Two providers dropped out of the (voluntary) study before collecting data, so the findings are based on data from 88 participating home health agencies. The patient cohort includes all Medicare fee-for-service patients admitted to participating agencies during the first six months of its participation in the project. This translates roughly to October 1997 through mid-april 1998. Data on Patient Characteristics. The original procurement required the contractor to collect patientlevel data using the OASIS and any other data items deemed necessary for case-mix adjustment. The Outcomes and Assessment Information Set (OASIS) therefore provided the core of the primary data collection protocol used for patient assessment. However, since the OASIS was not intended to provide all of the data elements necessary to adjust prospective payment rates for case-mix differences, supplemental data elements were added. The task of supplementing the OASIS-B dataset was approached with Abt Associates Inc. Home Health Case-Mix Project: Second Interim Report, 9/24/1999 V
much concern over burdening home health agencies with too much data collection. Many of the items selected to augment the OASIS-B were based on the Minimum Data Set for Home Care (MDS-HC) (Morris et al., 1996a; Morris et al., 1996b). Using tested items from a validated instrument was a necessity on the project s expedited time frame, since no time was available for extensive item development, testing and revision. The final supplemented dataset includes 129 items and was named OASIS+. Resource Data. Additional data collection protocols were developed to capture information on the length of time spent by clinicians in the home, on selected services performed, and on events likely to affect the length of the visit. The visit logs were not intended to collect data on ALL activities performed in the home, only those that were likely to affect the length of the visits significantly. Project agencies were directed to collect data on every visit provided to a study cohort patient by each of the six Medicare-covered disciplines (skilled nursing; home health aide; physical, occupational and speech therapy; and medical social work). Estimated resource use for each Medicare-covered visit was calculated by multiplying total minutes by a national average wage for the appropriate discipline. Resource use was then summed over all visits in the relevant segment. This measure of resource use does not represent Medicare payment amounts; rather it is an estimate of the resource cost of time spent in the home. Other Data. In addition to assessments and visit logs, secondary data on cohort patients and agencies have been assembled from secondary sources, including Medicare enrollment files as well as claims for home health and inpatient services. Agencies have also provided information on the staff who serve cohort patients. Finally, data on agencies and the areas in which they operate have been obtained from the Medicare Provider of Service files, as well as the Area Resource File. Descriptive analysis of the agencies and the patient cohort were presented in the First Interim Report (Goldberg, Burstein, Moore et al., 1998). This Report This report summarizes our efforts to create a clinically useful and statistically predictive case-mix model, building on the exploratory analyses presented in the First Interim Report (Goldberg, Burstein, Moore et al, 1998). Chapter 1 reviews the background of the project, the need for a prospective payment system, and the implications of previous research related to patient classification systems and case-mix adjustment for home health. A brief summary of the implementation of the project and the development of the data which supports the analysis used to create the case-mix adjustor are described in Chapter 2. The process of developing the model and a methodological discussion of the measures used to assess its performance is detailed in Chapter 3. Chapter 4 presents the data on the performance of the model overall, and for subgroups of agencies of different types. Finally, Chapter 5 describes future activities under the project. Results of Case-mix Modeling Efforts The case-mix adjustor model which resulted from the project is a straightforward system combining 21 data elements to create easily understandable patient case-mix groupings. These elements are drawn from OASIS assessment items and additional variables that enhance the case-mix adjuster s predictive Abt Associates Inc. Home Health Case-Mix Project: Second Interim Report, 9/24/1999 VI
accuracy. The selection of these items was guided by statistical analysis, review of the literature, and consultation with home health clinicians, government policy experts, and researchers. The data elements measure three basic dimensions: clinical severity factors, functional status factors, and service utilization factors. Each possible value for each data element used in a dimension is given a score based on its observed relationship to home health resource use. Scores were developed through statistical analysis of the participating agencies data. Within each dimension, scores on assessment items are summed, and the resulting total is used to assign a patient to a severity category for that dimension. The case-mix model defines a set of 80 mutually-inclusive groups from all possible combinations of severity categories across the three dimensions (Exhibit A). The process of defining a structure for the case-mix model, and of selecting items for the dimensions, is described in detail in Chapter 3. The process of selecting items for the three case mix dimensions was not limited to statistical criteria for predictive accuracy, but also included qualitative criteria relating to policy objectives, incentives to provide good care, robustness against gaming, apparent item subjectivity, and administrative feasibility. The first case-mix model dimension is the Clinical Severity domain. It includes OASIS items pertaining to the following clinical conditions and risk factors: diagnoses involving orthopedic, neurological, or diabetic conditions; therapies used at home (i.e., intravenous therapy or infusion therapy, parenteral and enteral nutrition); vision status; pain frequency; status of pressure ulcers, stasis ulcers, and surgical wounds; dyspnea; urinary and bowel incontinence; bowel ostomy; and cognitive/behavioral problems, such as impaired decision making and hallucinations. This dimension captures significant indicators of clinical need from several OASIS subdomains, including patient history, sensory status, integumentary status, respiratory status, elimination status, and neuro/emotional/behavioral status. The second case-mix dimension is the Functional Status domain, comprised of six Activities of Daily Living (ADLs): upper and lower body dressing, bathing, toileting, transferring, and locomotion. These items are drawn from the ADL/IADL subdomain of the OASIS assessment instrument. The third case mix dimension is the Service Utilization domain. This dimension includes two kinds of data elements. The first is the patient s pre-admission location in the 14 days preceding admission to home care, taken from the patient history subdomain of OASIS. The second is receipt of home health rehabilitation therapies totaling at least 8 hours during the period of the home health episode itself. The data for this variable will come from the home health agency s service records. Ideally, the case mix system would rely on data elements that do not depend on treatments planned or received; however, we found this measure to be extremely powerful in explaining resource use, even after all other predictive patient characteristics had been included in the model. Defining the variable with a minimum of 8 hours of service was intended to exclude evaluation-only patients and to discourage provider manipulation of the system. In the sample analyzed, only 12% of all cases met this criterion. Including the therapy receipt variable in the case-mix system will also help to preserve access to therapy for patients with significant therapy needs. A summary of the classification algorithm is presented as Exhibit B. The current case-mix model performs well in terms of overall predictive accuracy. It explains 32% of the variation in resource use over a sixty-day episode. The episodes used for development of the model pertained to the first sixty days following admission; however, the model was subsequently tested on a sizable number of observations for subsequent sixty-day periods assembled from the study Abt Associates Inc. Home Health Case-Mix Project: Second Interim Report, 9/24/1999 VII
Exhibit B Summary of the Model Clinical Severity Domain - Clinical Model, >4 visits OASIS Description Value Scoring Item M0230 Primary home care If Orthopedic DG, add 10 to score min = 0-7 diagnosis If Neurological DG, add 19 to score low = 8-16 If Diabetes DG, add 16 to score mod = 17-26 M0250 IV/Infusion/ If box 1, add 15 to score high = 27+ Parenteral/Enteral If box 2, add 20 to score Therapies If box 3, add 24 to score M0390 Vision If box 1 or 2, add 7 to score M0420 Pain If box 2 or 3, add 6 to score M0460 Current pressure ulcer If box 1 or 2, add 15 to score stage If box 3 or 4, add 43 to score M0476 Stasis ulcer If box 3, add 24 to score M0488 Surgical wound If box 2 or 3, add 10 to score M0490 Dyspnea If box 2, 3 or 4, add 5 to score M0530 Urinary incontinence If box 1 or 2, add 8 to score M0540 Bowel incontinence If box 2-5, add 11 to score M0550 Bowel ostomy If box 1 or 2, add 10 to score M0610 Behavioral Problems If box 1-6, add 3 to score Functional Status Domain - Clinical Model, >4 visits OASIS Item Description Value Scoring M0650 (current) Dressing If M0650 = box 1, 2 or 3 Min = 0-4 M0660 (current) or Low = 5-15 M0660 = box 1, 2 or 3 Mod = 16-22 add 4 to score High = 23-35 M0670 (current) Bathing If box 2-5 add 8 to score Max =36+ M0680 (current) Toileting If box 2-4, add 3 to score M0690 (current) Transferring If box 1, add 3 to score If box 2-5, add to 8 score M0700 (current) Locomotion If box 1 or 2, add 6 to score If box 3-5, add 13 to score Service Utilization Domain - Clinical Model, >4 visits Variable Description Value Scoring M0170 line 1 NO Hospital discharge past If box 1 IS BLANK, add 1 Min = 0-2 14 days to score Low = 3 M0170 line 2 or 3 Inpatient rehab or SNF If box 2 or 3, add 2 to discharge past 14 days score Receipt of Therapy 8 or more therapy hours If yes, add 4 to score Mod = 4-6 High= 7 Abt Associates Inc. Home Health Case-Mix Project: Second Interim Report, 9/24/1999 IX
sample. The case-mix model explained approximately 30% of the variance for second sixty day episodes of patients in the cohort. Thus, we found that the explanatory power of the groups is quite similar regardless of whether the episode is the patient s first sixty days following admission or the subsequent sixty days (though most patients were assigned to a different case-mix group in the later period based on their clinical, functional, and service utilization characteristics at the start of that period). This statistical finding suggests that the case-mix model is inherently self-adjusting to changes in patient characteristics that predict resource use over a sequence of sixty-day episodes. As the accumulating data permit, we will test the model s explanatory power on later sixty-day periods. Future Work Future efforts will focus on additional analyses to support HCFA's development of the forthcoming PPS system based on an expanded data set after all projected data are received and the maximum matched sample can be used. In addition, we intend to pursue further refinements to the model, including the creation of customized clinical (and possibly functional) domains for various diagnostic categories in an effort to maximize explanatory power while minimizing the number of end points. Abt Associates Inc. Home Health Case-Mix Project: Second Interim Report, 9/24/1999 X