End-of-life quality metrics among medicare decedents at minority-serving cancer centers: A retrospective study.

BACKGROUND: We calculated the performance of National Cancer Institute (NCI)/National Comprehensive Cancer Network (NCCN) cancer centers' end-of-life (EOL) quality metrics among minority and white decedents to explore center-attributable sources of EOL disparities. METHODS: We conducted a retrospective cohort study of Medicare beneficiaries with poor-prognosis cancers who died between April 1, 2016 and December 31, 2016 and had any inpatient services in the last 6 months of life. We attributed patients' EOL treatment to the center at which they received the preponderance of EOL inpatient services and calculated eight risk-adjusted metrics of EOL quality (hospice admission ≤3 days before death; chemotherapy last 14 days of life; ≥2 emergency department (ED) visits; intensive care unit (ICU) admission; or life-sustaining treatment last 30 days; hospice referral; palliative care; advance care planning last 6 months). We compared performance between patients across and within centers. RESULTS: Among 126,434 patients, 10,119 received treatment at one of 54 NCI/NCCN centers. In aggregate, performance was worse among minorities for ED visits (10.3% vs 7.4%, P < .01), ICU admissions (32.9% vs 30.4%, P = .03), no hospice referral (39.5% vs 37.0%, P = .03), and life-sustaining treatment (19.4% vs 16.2%, P < .01). Despite high within-center correlation for minority and white metrics (0.61-0.79; P < .01), five metrics demonstrated worse performance as the concentration of minorities increased: ED visits (P = .03), ICU admission (P < .01), no hospice referral (P < .01), and life-sustaining treatments (P < .01). CONCLUSION: EOL quality metrics vary across NCI/NCCN centers. Within center, care was similar for minority and white patients. Minority-serving centers had worse performance on many metrics.

Measuring racial segregation in health system networks using the dissimilarity index.

Racial disparities in the end-of-life treatment of patients are a well observed fact of the U.S. healthcare system. Less is known about how the physicians treating patients at the end-of-life influence the care received. Social networks have been widely used to study interactions with the healthcare system using physician patient-sharing networks. In this paper, we propose an extension of the dissimilarity index (DI), classically used to study geographic racial segregation, to study differences in patient care patterns in the healthcare system. Using the proposed measure, we quantify the unevenness of referrals (sharing) by physicians in a given region by their patients' race and how this relates to the treatments they receive at the end-of-life in a cohort of Medicare fee-for-service patients with Alzheimer's disease and related dementias. We apply the measure nationwide to physician patient-sharing networks, and in a sub-study comparing four regions with similar racial distribution, Washington, DC, Greenville, NC, Columbus, GA, and Meridian, MS. We show that among regions with similar racial distribution, a large dissimilarity index in a region (Washington, DC DI = 0.86 vs. Meridian, MS DI = 0.55), which corresponds to more distinct referral networks for black and white patients by the same physician, is correlated with black patients with Alzheimer's disease and related dementias receiving more aggressive care at the end-of-life (including ICU and ventilator use), and less aggressive quality care (early hospice care).

Medicare Utilization and Spending Among Nurses Compared with the General United States Population.

Background: To better understand health habits in older nurses versus the general population, we sought to determine whether the demographics, health care utilization, and Medicare spending by the Nurses' Health Study (NHS) participants enrolled in Medicare and a matched sample of Medicare beneficiaries meaningfully differed. Materials and Methods: Analytic cohorts included a random 20% sample of Medicare beneficiaries continuously enrolled in fee for service (FFS) Medicare that were propensity matched to the NHS participants continuously enrolled in FFS Medicare in a single year (2012). Matching was based upon preselected demographic factors and health status, using a nearest-neighbor matching algorithm to obtain a 1:1 match without replacement. Healthcare utilization and spending were compared between the two groups; we also stratified findings by number of chronic comorbidities. Results: Similar rates of utilization of primary care and most outpatient services. However, NHS participants had slightly higher rates of cancer screening, specialist care, and inpatient surgery were observed. When stratified by comorbidity status, the largest differences in utilization and spending were found in women with no comorbidity. Conclusions: The modest differences in observed healthcare utilization and spending suggest that older healthcare professionals may access care in fairly similar ways to the general population, and that health status may be a more important determinant of utilization and spending than health profession in older age groups.