This study is a cross sectional analysis examining how constellations of HCBS are associated with risk of experiencing an acute inpatient hospitalization among disabled elderly Pennsylvanians. We used logistic regression to estimate the association of hospitalization associated with selected constellations of HCBS. The results are presented as predicted probabilities to facilitate meaningful comparisons of the different services.
Included in this analysis was a reference group of community dwelling elderly people who had applied to receive HCBS but had been deemed ineligible for Medicaid funded HCBS. They are more similar to program users than an aged person in a nursing home or enrolled in Medicaid but not in the 1915(c) waiver. If people using HCBS have a significantly lower risk of hospitalization than people less disabled living in the community and not receiving HCBS, this suggests HCBS is providing some benefit.
The data for this study came from the Pennsylvania Department of Human Services. The unit of observation was the person quarter . The earliest a person can be observed in our data is July of 2014 and the latest a person could be observed in our data is December of 2016. To be counted as receiving HCBS the person needed to be enrolled in the waiver for the whole quarter and receive some HCBS during that quarter. This study used data from both Medicare and Pennsylvania Medicaid concerning a person’s hospitalization experience, enrollment in the Medicaid waiver, their living status, any diagnoses of chronic disease, and the services that person used.
In order to qualify to receive HCBS under Pennsylvania’s 1915(c) waiver, a person must meet eligibility requirements: the individual must have limitations with regards to activities of daily living, he or she must be recommended by a physician to live in a nursing home, and their income must be no greater than 300% of the federal poverty level . Assessment data included was included in this analysis. Two ten point scales were created to measure limitations in all Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL). A zero represented total independence (no limitations) and a ten represented total dependence (completely limited in all tasks). Measurement of cognitive function was limited to presence of a diagnosis of Alzheimer’s disease or related dementia.
The enrollment data had information about the person’s basic demographics including age, rurality, county of residence, gender, race, and ethnicity. We limited the people in our study to people who were dually eligible for Medicare and Medicaid, so the youngest people in this study were 65.
We focused on three specific services that were used most frequently in our data and are important components of all HCBS programs : Personal attendant Services (PAS), Home Delivered Meals, and Adult Day Care. These services are billed on a per encounter basis. PAS was billed in 15 minute increments; we calculated the average minutes per day per quarter. Home delivered meals and adult day care are billed per meal or per day (respectively). Due to the distribution of these data (low prevalence), these were covered to binary measurements, indicating if that person any home delivered meals or adult day care during the person quarter.
This study also used information from Medicare and Medicaid on the number of diagnosed chronic conditions for each person. This information was then converted into a count of chronic conditions to indicate the overall burden of chronic disease.
The outcome of interest was risk for experiencing an acute care inpatient hospitalization. Data on this came both from Medicaid and Medicare claims. This was a binary variable indicating if a person had or had not experienced a hospitalization during that quarter. Our analysis was limited to people who were enrolled in fee for service Medicaid and fee for service Medicare.
We constructed constellations of HCBS based on the services that were used with enough frequency and consistency during the observation period and across the population. The services that met this criteria were home delivered meals, adult day care, and personal assistive services (PAS) also known as attendant care.
The service central to many HCBS programs is personal assistive services (PAS) [19, 20] and 97% of the people in our analysis regularly used some sort of personal assistive services. The amount of PAS used however varied from an average of less than one hour to 24 hours of PAS per day. We decided to define people as being low PAS users, medium PAS users, and high PAS users. We suspected the activities of the caregiver will be different as the caregiver spends more time with the recipient. A caregiver who spends more time with a person may be able to disproportionately devote more hours to activities that could prevent a hospitalization  where as a caregiver who spends less time may need to focus most of his or her time on supporting activities of daily living. Low PAS users were people who used up to four hours of PAS per day or less than half of a work day. Medium PAS users were people who used PAS four to eight hours a day of PAS. High PAS users were people who used more than eight hours of PAS per day. We measured adult day care use and home delivered meal use with binary indicators.
We constructed the constellation of HCBS based on all of the possible combinations of each service. This produced twelve different constellations: 1) Only low levels of PAS, 2) low levels of PAS and adult day care, 3) low levels of PAS and home delivered meals, 4) low levels of PAS, adult day care, and home delivered meals, 5) only medium levels of PAS, 6) medium levels of PAS and adult day care, 7) medium levels of PAS and home delivered meals, 8) medium levels of PAS, adult day care, and home delivered meals, 9) only high levels of PAS, 10) high levels of PAS and adult day care, 11) high levels of PAS and home delivered meals, 12) high levels of PAS, adult day care, and home delivered meals.
This first analysis examined the total number of people and their demographic characteristics in each constellation of HCBS. This analysis also examined the average level of disability experienced by people in each group.
The final analysis was a logistic regression that produced predicted probability of experiencing a hospitalization for people in each HCBS constellation as well as for community dwelling dually eligible people not using Medicaid funded HCBS. The variable of interest was the constellation of HCBS that the person used during that quarter. This variable was a categorical variable with the reference category being those people who applied to receive Medicaid funded HCBS but were deemed ineligible. Other covariates in the model were race, gender, age, rurality, location within the state of Pennsylvania, the person’s level of continence, the person’s ADL and IADL levels, the living situation of the individual (whether the person lived with a child, a spouse, another family member, another person, or alone), the number of diagnosed chronic conditions, and the number of quarters the person had been observed in our data. Since individuals could appear in the data set for multiple quarters, standard errors were clustered at the person level .
Two alternative models were run to further examine the association between risk of hospitalization and constellation of HCBS. The first alternative model run was a model that did not include the community dwelling elderly people and instead used people receiving only low levels of PAS as the reference group for the model. The second alternative specification was a generalized estimating equation that was used to further control for potential problems with heteroscedasticity.