In addition, we ran IPTW
logistic regression models with covariance control to examine CAFS and TAFS as predicted by the two saving indicators identified above.
In our study, 2-Stage adjustments using the multivariable Cox modeling with IPTW
were performed to overcome the limitations of the observational study.
model included baseline age, out-of-pocket drug copay, benefits based copay for brand drugs, Medicare indicator, deductible drug plan indicator, drug benefit business line (e.
Of the matching and weighting strategies, kernel matching and IPTW
had the best reduction in mean standardized difference while retaining nearly all observations from the original sample.
Table 3 shows that after applying IPTWs to the cohorts, the case-mix differences by hospice status observed in the raw data (see Table 1) greatly diminished, confirming the validity of using the IPTW sample.
The adjusted hospice effect estimates derived from the IPTW regression analyses had the same direction as in the unadjusted estimates but quantitatively the effects were more modest, particularly for the long- and short-stay cancer cohorts (Table 4).
The implementation of the IPTW method involves two steps, initial estimation of the probability of hospice enrollment, followed by estimation of the outcome model with a weighted regression where the weights are created using the propensity scores estimated in the first step.
Table 3: Selected Characteristics Adjusted by IPTWs of Hospice and Non-hospice for Long-Stay (>90 Days) and Short-Stay ([less than or equal to] 90 Days) Nursing Home (NH) Residents (% or Mean [+ or -] SD) ([section]) Long-Stay NH Residents Hospice (N=958, Nonhospice Variable 24% (N= 3,077) Sociodemographic Male 27 26 Black 11 10 Other race 7 7 Age group 65-74 years 9 9 75-84 years 32 31 85 years or older 59 60 Additional diagnoses Congestive heart failure 15 15 Chronic obstructive pulmonary 12 12 disease Severe cognitive impairment * 77 78 [greater than or equal to 4 65 66 limitations in ADC ([dagger]) Do-not-resuscitate advanced 29 28 directive Do-not-hospitalize advanced 1 1 directive Environmental Distance from NH to nearest 10.
7) Table 3 presents the estimated hospice effect on end-of-life hospitalization without and with adjustment based on the IPTW weights.
Table 4 presents the detailed results of the model adjusting for all groups of covariates with IPTW weighting adjustment.
Our results found that, indeed, about one quarter of the observed raw hospice effect on hospitalization in the last 30 days of life is eliminated when we use the IPTW method to adjust for selection on observable characteristics (from a RR of 0.