Hospice care is medical care provided to terminally ill patients with a life expectancy of 6 months or less. Hospice services include symptom control, pain management, palliative care, and other supportive services such as providing for home equipment or oxygen; however, it does not provide for life-prolonging therapies such as chemotherapy. Although oncologic benchmarks suggest patients should be enrolled in hospice 3 months prior to death, studies show that most hospice referrals are being made too late. These shorter stays in hospice result in increased cost of care especially at the end of life with most patients dying on aggressive treatments in the hospital. Thus, identifying barriers to hospice placement is critical in improving the referral process and enhancing the quality of end-of-life care. This retrospective study collected data on 418 oncologic patients who passed in 2015 and categorized patients based on hospice status at the time of death. Our study found that the demographics between hospice and nonhospice patients were not significantly different. Hospice patients spent a median of 10 days in hospice and 71% (n ¼ 161) of patients were in hospice 30 days or less. Additionally, 56% of patients were in hospice 10 days or less. Increased education for patients and health-care providers along with better utilization of palliative care services and incorporating a nurse navigator to help with transitioning patients to hospice would improve earlier referral to hospice care and enhance patients' quality of life.
ImportanceCancer screening deficits during the first year of the COVID-19 pandemic were found to persist into 2021. Cancer-related deaths over the next decade are projected to increase if these deficits are not addressed.ObjectiveTo assess whether participation in a nationwide quality improvement (QI) collaborative, Return-to-Screening, was associated with restoration of cancer screening.Design, Setting, and ParticipantsAccredited cancer programs electively enrolled in this QI study. Project-specific targets were established on the basis of differences in mean monthly screening test volumes (MTVs) between representative prepandemic (September 2019 and January 2020) and pandemic (September 2020 and January 2021) periods to restore prepandemic volumes and achieve a minimum of 10% increase in MTV. Local QI teams implemented evidence-based screening interventions from June to November 2021 (intervention period), iteratively adjusting interventions according to their MTVs and target. Interrupted time series analyses was used to identify the intervention effect. Data analysis was performed from January to April 2022.ExposuresCollaborative QI support included provision of a Return-to-Screening plan-do-study-act protocol, evidence-based screening interventions, QI education, programmatic coordination, and calculation of screening deficits and targets.Main Outcomes and MeasuresThe primary outcome was the proportion of QI projects reaching target MTV and counterfactual differences in the aggregate number of screening tests across time periods.ResultsOf 859 cancer screening QI projects (452 for breast cancer, 134 for colorectal cancer, 244 for lung cancer, and 29 for cervical cancer) conducted by 786 accredited cancer programs, 676 projects (79%) reached their target MTV. There were no hospital characteristics associated with increased likelihood of reaching target MTV except for disease site (lung vs breast, odds ratio, 2.8; 95% CI, 1.7 to 4.7). During the preintervention period (April to May 2021), there was a decrease in the mean MTV (slope, −13.1 tests per month; 95% CI, −23.1 to −3.2 tests per month). Interventions were associated with a significant immediate (slope, 101.0 tests per month; 95% CI, 49.1 to 153.0 tests per month) and sustained (slope, 36.3 tests per month; 95% CI, 5.3 to 67.3 tests per month) increase in MTVs relative to the preintervention trends. Additional screening tests were performed during the intervention period compared with the prepandemic period (170 748 tests), the pandemic period (210 450 tests), and the preintervention period (722 427 tests).Conclusions and RelevanceIn this QI study, participation in a national Return-to-Screening collaborative with a multifaceted QI intervention was associated with improvements in cancer screening. Future collaborative QI endeavors leveraging accreditation infrastructure may help address other gaps in cancer care.
e21117 Background: Non-small cell lung cancer (NSCLC) is the most prevalent form of lung cancer. Many studies have evaluated the association of social determinants with outcomes in early-stage NSCLC. These studies have shown statistically and clinically significant associations between overall survival (OS) and other social factors (e.g marital status, educational attainment). The aim of our study was to better understand the role of various social determinants of health (SDH) on OS in advanced-stage NSCLC patients in a community oncology practice in Florida. Methods: In this retrospective study, 125 patients with stage III and IV NSCLC were recruited between January 1st, 2014 until December 31st, 2018. We performed both categorical and continuous analyses (Pearson’s chi-square and Kruskal-Wallis test, respectively) to evaluate the association between median OS and several independent variables, including; gender, race, marital status, insurance status, living status, receiving financial assistance (FA), alcohol use, and smoking histories. OS is defined as the date of diagnosis up to the date of death. Other confounders that were analyzed included histology, treatment modality, comorbidities, and performance status of the patients. Results: Of the total study population (n = 125), 60% identified as male with a mean age of 73 years for the study population. The majority of patients (89%) identified as white; 56% were married, and 81% lived with someone. 66% of patients had an HMO insurance plan, and 51% of patients obtained FA to help with treatment care costs. 47% of patients identified as former smokers and 54% denied any alcohol use. The median OS for the patient population was 0.756 years. Chi-square analyses revealed that patients who received FA were more likely to live longer than median OS as opposed to patients that did not receive FA (OR = 2.41, 95% CI [1.18, 4.96], p = 0.050). Kruskal-Wallis analyses demonstrated that patients receiving FA had nearly a two-fold increase in median OS compared to patients without financial assistance (median OS = 1.01 years vs. 0.545 years, respectively; p = 0.013). However, other social determinants evaluated did not have a significant impact on relative OS in advanced-stage NSCLC. Conclusions: Ultimately, our study concludes that receiving FA has a significant association with increased OS in advanced-stage NSCLC patients. This study highlights the importance of reducing the financial burden of advanced-stage NSCLC patients and how FA impacts patient outcomes. Future prospective cohort studies with a larger sample size are warranted to identify other SDH, as well as the underlying mechanisms affecting median OS, in patients with advanced-stage NSCLC.
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