Patient-reported distress at a cancer center during the COVID-19 pandemic (preprint)

Background: Assessments of health-related quality of life (HRQOL) are conducted by health systems to improve patient-centered care. Studies have shown that the COVID-19 pandemic poses unique stressors for patients with cancer. This study investigates change in self-eported global health scores in patients with cancer before and during the COVID-19 pandemic. Methods and Materials: In this single-institution retrospective cohort study, patients who completed the Patient-Reported Outcomes Measurement Information System (PROMIS) at a comprehensive cancer center before and during the COVID-19 pandemic were identified. Surveys were analyzed to assess change in the global mental health (GMH) and global physical health (GPH) scores at different time periods (pre-COVID: 3/1/5/2019-3/15/2020, surge1: 6/17/2020-9/7/2020, valley1: 9/8/2020-11/16/2020, surge2: 11/17/2020-3/2/2021, and valley2: 3/3/2021-6/15/2021). Results: A total of 25,192 surveys among 7,209 patients were included in the study. Mean GMH score for patients before the COVID-19 pandemic (50.57) was similar to those during various periods during the pandemic: surge1 (48.82), valley1 (48.93), surge2 (48.68), valley2 (49.19). Mean GPH score was significantly higher pre-COVID (42.46) than during surge1 (36.88), valley1 (36.90), surge2 (37.33) and valley2 (37.14). During the pandemic, mean GMH (49.00) and GPH (37.37) scores obtained through in-person were similar to mean GMH (48.53) and GPH (36.94) scores obtained through telehealth. Conclusion: At this comprehensive cancer center, patients with cancer reported stable mental health and deteriorating physical health during the COVID-19 pandemic as indicated by the PROMIS survey. Modality of the survey (in-person versus telehealth) did not affect scores.

Changes in Medicaid Enrollment During the COVID-19 Pandemic Across Six States (preprint)

Background: The COVID-19 public health emergency (PHE) has caused extensive job loss and loss of employer-sponsored insurance. State Medicaid programs have experienced a related increase in enrollment during the PHE. However, the composition of enrollment and enrollee changes during the pandemic is unknown. Understanding changes in the Medicaid population during the PHE may inform policy development and identify strategies to meet the rising needs for insurance coverage during public health emergencies. This study aims to examine changes in Medicaid enrollment and population characteristics during the PHE.Methods: A retrospective descriptive study documenting changes in Medicaid new enrollment and disenrollment, and enrollee characteristics between March and October 2020 compared to the same time period in 2019 using Full-state Medicaid populations from six states of a wide geographical region. The primary outcomes were medicaid enrollment and disenrollment during the PHE. New enrollment included persons enrolled in Medicaid between March and October 2020 who were not enrolled in January or February of 2020. Disenrollment included persons who were enrolled in March of 2020 but not enrolled in October 2020.Results: The study included 8.50 million Medicaid enrollees in 2020 and 8.46 million in 2019. Overall, enrollment increased by 13.0% during the PHE compared to 2019, relative enrollment growth of 1.19 million. New enrollment accounted for 24.9% of the relative increase, while the remaining 75.1% was due to disenrollment. A larger proportion of new enrollment in 2020 was among adults aged 27-44 (28.3% vs 23.6%), Hispanics (34.3% vs 32.5%) and in the financial needy (44.0% vs 39.0%) category compared to 2019. Disenrollment included a larger proportion of older adults (26.1% vs 8.1%) and non-Hispanics (70.3% vs 66.4%) than in 2019.Conclusions and Relevance: Medicaid enrollment grew considerably during the PHE, and the majority of enrollment growth was attributed to decreases in disenrollment rather than increases in new enrollment. Our results highlight the impact of COVID-19 on state health programs and can guide federal and state budgetary planning.Funding: This study was supported from the Digital Health CRC (Cooperative Research Centre). The DHCRC is established and supported under the Australian Government’s Cooperative Research Centres Program. Funding for Antonia Chan was provided by the Stanford Medical Scholars Fellowship Program.Declaration of Interest: None to declare.