Temporal trends and determinants of palliative care utilization among hospitalized patients with acute myeloid leukemia.

Abstract

e13832 Background: Patients with acute myeloid leukemia (AML) are frequently hospitalized for intensive chemotherapy and treatment-related complications and are at risk for significant physical and psychological burdens. Integrating palliative care enhances symptom management and improves the quality of life for these patients. This study examined temporal trends and predictors of palliative care utilization among hospitalized AML patients. Methods: A retrospective cohort study using the National Inpatient Sample (2016–2020) identified primary AML hospitalizations via ICD-10-CM codes. Patients were categorized by documented palliative care encounters. Trends in palliative care utilization from 2016 to 2020 were examined, and baseline sociodemographic characteristics were summarized. Multivariable logistic regression identified independent predictors of palliative care utilization. Results: Of 33,430 AML hospitalizations, only 14% involved palliative care, with an increase in consultations from 12.5% in 2016 to 16.4% in 2020. The median age of patients receiving palliative care was 66 years (IQR: 53–74), and 54.6% were male. Most patients were non-Hispanic White (73.5%), followed by African American (10.5%) and Hispanic (7.5%). Medicare was the most common payer (39%), followed by private insurance (23.3%) and Medicaid (9.8%). Patients aged ≥75 years were less likely to receive palliative care compared to younger patients (OR = 0.613, 95% CI: 0.563–0.667, p < .001). Males had slightly higher odds of receiving palliative care than females (OR = 1.072, 95% CI: 1.007–1.142, p = .030). Hispanic patients had lower odds of palliative care utilization compared to non-Hispanic Whites (OR = 0.727, 95% CI: 0.590–0.895, p = .003), while Native American patients had higher odds (OR = 2.542, 95% CI: 1.493–4.330, p < .001). Surprisingly, patients with a high comorbidity burden were less likely to receive palliative care than those with fewer comorbidities (OR = 0.476, 95% CI: 0.435–0.521, p < .001). Non-elective admissions were associated with reduced odds of palliative care (OR = 0.251, 95% CI: 0.132–0.475, p < .001). Conversely, hospital stays exceeding five days were linked to increased odds of receiving palliative care (OR = 1.339, 95% CI: 1.244–1.441, p < .001). Regional differences were notable, with higher palliative care utilization in the Northeast compared to the Midwest (OR = 1.264, 95% CI: 1.152–1.388, p < .001). Conclusions: Palliative care remains underutilized among hospitalized AML patients, with notable disparities based on age, race/ethnicity, admission type, comorbidity burden, and geographic region. Efforts should focus on addressing systemic inequities, particularly for vulnerable populations, and enhancing access to palliative care services to ensure equitable and comprehensive care. Factors associated with palliative care utilization among hospitalized patients with acute leukemia. OR (95%CI) P value Age  Less than 70 Reference  70 years and older 0.613 (0.563-0.667) <0.001 Sex  Females Reference  Males 1.072(1.007-1.142) 0.03 Race/Ethnicity  Non-Hispanic White Reference  African American 0.789(0.622-1.001) 0.051  Hispanic 0.727(0.59-0.895) 0.003  Native Americans 2.554(1.493-4.330) <0.001  Others 0.383 (0.302-0.485) <0.001 Insurance type  Medicare Reference  Medicaid 0.985(0.833-1.166) 0.864  Private 0.703(0.593-0.834) <0.001  Other 0.748(0.552-1.012) 0.060 Mode of admission  Elective Reference  Non-elective 0.251(0.132-0.475) <0.001 Hospital region  Midwest Reference  Northwest 1.264(1.162-1.388) <0.001  South 0.905(0.830-0.987) 0.024  West 0.903(0.814-1.002) 0.056 Length of Stay (LOS)  LOS 5 days or less Reference  LOS > 5days 1.339(1.244-1.441) <0.001 Charleston co-morbidity index  Low (0-4) Reference  Medium (5-7) 0.476(0.435-0.521) <0.001  High (>8) 0.785(0.721-0.855) <0.001 OR = odds ratio; CI = confidence intervals; model adjusted for age, gender, race/ethnicity, insurance type, hospital location, Charlson comorbidity index, admission type and length of stay.