Predicting Covid-19 infection and death rates among E.U. minority populations in the absence of racially disaggregated data through the use of US data comparisons.

BACKGROUND: The E.U.'s lack of racially disaggregated data impedes the formulation of effective interventions, and crises such as Covid-19 may continue to impact minorities more severely. Our predictive model offers insight into the disparate ways in which Covid-19 has likely impacted E.U. minorities and allows for the inference of differences in Covid-19 infection and death rates between E.U. minority and non-minority populations. METHODS: Data covering Covid-19, social determinants of health and minority status were included from 1 March 2020 to 28 February 2021. A systematic comparison of US and E.U. states enabled the projection of Covid-19 infection and death rates for minorities and non-minorities in E.U. states. RESULTS: The model predicted Covid-19 infection rates with 95-100% accuracy for 23 out of 28 E.U. states. Projections for Covid-19 infection and mortality rates among E.U. minority groups illustrate parallel trends to US rates. CONCLUSIONS: Disparities in Covid-19 infection and death rates by minority status likely exist in patterns similar to those observed in US data. Policy Implications: Collecting data by race/ethnicity in the E.U. would help document health disparities and craft more targeted health interventions and mitigation strategies.

A mixed-methods process evaluation of Family Navigation implementation for autism spectrum disorder.

There is growing interest in Family Navigation as an approach to improving access to care for children with autism spectrum disorder, yet little data exist on the implementation of Family Navigation. The aim of this study was to identify potential failures in implementing Family Navigation for children with autism spectrum disorder, using a failure modes and effects analysis. This mixed-methods study was set within a randomized controlled trial testing the effectiveness of Family Navigation in reducing the time from screening to diagnosis and treatment for autism spectrum disorder across three states. Using standard failure modes and effects analysis methodology, experts in Family Navigation for autism spectrum disorder (n = 9) rated potential failures in implementation on a 10-point scale in three categories: likelihood of the failure occurring, likelihood of not detecting the failure, and severity of failure. Ratings were then used to create a risk priority number for each failure. The failure modes and effects analysis detected five areas for potential "high priority" failures in implementation: (1) setting up community-based services, (2) initial family meeting, (3) training, (4) fidelity monitoring, and (5) attending testing appointments. Reasons for failure included families not receptive, scheduling, and insufficient training time. The process with the highest risk profile was "setting up community-based services." Failure in "attending testing appointment" was rated as the most severe potential failure. A number of potential failures in Family Navigation implementation-along with strategies for mitigation-were identified. These data can guide those working to implement Family Navigation for children with autism spectrum disorder.

Building a navigation system to reduce cancer disparities among urban Black older adults.

BACKGROUND: Although cancer outcomes have improved in recent decades, substantial disparities by race, ethnicity, income, and education persist. Increasingly, patient navigation services are demonstrating success in improving cancer detection, treatment, and care and in reducing cancer health disparities. To advance progress in developing patient navigation programs, extensive descriptions of each component of the program must be made available to researchers and health service providers. OBJECTIVE: We sought to describe the components of a patient navigation program designed to improve cancer screening based on informed decision making on cancer screening and cancer treatment services among predominantly Black older adults in Baltimore City. METHODS: A community-academic participatory approach was used to develop a patient navigation program in Baltimore, Maryland. The components of the patient navigation system included the development of a community academic (advisory) committee (CAC); recruitment and selection of community health workers (CHWs)/navigators and supervisory staff, initial training and continuing education of the CHWs/navigators, and evaluation of CHWs/navigators. The study was approved by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board. CONCLUSIONS: The incorporation of community-based participatory research principles into each facet of this patient navigation program facilitated the attainment of the intervention's objectives. This patient navigation program successfully delivered cancer navigation services to 1,302 urban Black older adults. Appropriately recruited, selected and trained CHWs monitored by an experienced supervisor and investigators are the key elements in a patient navigation program. This model has the potential to be adapted by research and health service providers.