Unequal racial distribution of immunotherapy for late-stage non-small cell lung cancer.

Immunotherapy has increased survival for non-small cell lung cancer (NSCLC), especially for those diagnosed with late-stage disease. However, it is not known if its use is equally distributed across races. We assessed immunotherapy use in 21 098 pathologically confirmed stage IV NSCLC patients according to race in the Surveillance Epidemiology, and End Results-Medicare linked dataset. Multivariable models were conducted to evaluate the independent association of receipt of immunotherapy with race and overall survival according to race. Black patients had statistically significantly lower odds of receiving immunotherapy (adjusted odds ratio = 0.60, 95% confidence interval = 0.44 to 0.80); receipt of immunotherapy was lower in Asian and Hispanic patients but not statistically significant. When immunotherapy was received, survival was similar across races. Immunotherapy for NSCLC is not used equally among races, underscoring the racial disparities that exist in access to the newest cancer treatment. Efforts should be directed toward expanding access to novel, efficacious treatments for advanced stage lung cancer.

A quantitative model to ensure capacity sufficient for timely access to care in a remote patient monitoring program.

INTRODUCTION: Algorithm-enabled remote patient monitoring (RPM) programs pose novel operational challenges. For clinics developing and deploying such programs, no standardized model is available to ensure capacity sufficient for timely access to care. We developed a flexible model and interactive dashboard of capacity planning for whole-population RPM-based care for T1D. METHODS: Data were gathered from a weekly RPM program for 277 paediatric patients with T1D at a paediatric academic medical centre. Through the analysis of 2 years of observational operational data and iterative interviews with the care team, we identified the primary operational, population, and workforce metrics that drive demand for care providers. Based on these metrics, an interactive model was designed to facilitate capacity planning and deployed as a dashboard. RESULTS: The primary population-level drivers of demand are the number of patients in the program, the rate at which patients enrol and graduate from the program, and the average frequency at which patients require a review of their data. The primary modifiable clinic-level drivers of capacity are the number of care providers, the time required to review patient data and contact a patient, and the number of hours each provider allocates to the program each week. At the institution studied, the model identified a variety of practical operational approaches to better match the demand for patient care. CONCLUSION: We designed a generalizable, systematic model for capacity planning for a paediatric endocrinology clinic providing RPM for T1D. We deployed this model as an interactive dashboard and used it to facilitate expansion of a novel care program (4 T Study) for newly diagnosed patients with T1D. This model may facilitate the systematic design of RPM-based care programs.

A model to design financially sustainable algorithm-enabled remote patient monitoring for pediatric type 1 diabetes care.

Introduction: Population-level algorithm-enabled remote patient monitoring (RPM) based on continuous glucose monitor (CGM) data review has been shown to improve clinical outcomes in diabetes patients, especially children. However, existing reimbursement models are geared towards the direct provision of clinic care, not population health management. We developed a financial model to assist pediatric type 1 diabetes (T1D) clinics design financially sustainable RPM programs based on algorithm-enabled review of CGM data. Methods: Data were gathered from a weekly RPM program for 302 pediatric patients with T1D at Lucile Packard Children's Hospital. We created a customizable financial model to calculate the yearly marginal costs and revenues of providing diabetes education. We consider a baseline or status quo scenario and compare it to two different care delivery scenarios, in which routine appointments are supplemented with algorithm-enabled, flexible, message-based contacts delivered according to patient need. We use the model to estimate the minimum reimbursement rate needed for telemedicine contacts to maintain revenue-neutrality and not suffer an adverse impact to the bottom line. Results: The financial model estimates that in both scenarios, an average reimbursement rate of roughly $10.00 USD per telehealth interaction would be sufficient to maintain revenue-neutrality. Algorithm-enabled RPM could potentially be billed for using existing RPM CPT codes and lead to margin expansion. Conclusion: We designed a model which evaluates the financial impact of adopting algorithm-enabled RPM in a pediatric endocrinology clinic serving T1D patients. This model establishes a clear threshold reimbursement value for maintaining revenue-neutrality, as well as an estimate of potential RPM reimbursement revenue which could be billed for. It may serve as a useful financial-planning tool for a pediatric T1D clinic seeking to leverage algorithm-enabled RPM to provide flexible, more timely interventions to its patients.

Large-scale labeling and assessment of sex bias in publicly available expression data.

BACKGROUND: Women are at more than 1.5-fold higher risk for clinically relevant adverse drug events. While this higher prevalence is partially due to gender-related effects, biological sex differences likely also impact drug response. Publicly available gene expression databases provide a unique opportunity for examining drug response at a cellular level. However, missingness and heterogeneity of metadata prevent large-scale identification of drug exposure studies and limit assessments of sex bias. To address this, we trained organism-specific models to infer sample sex from gene expression data, and used entity normalization to map metadata cell line and drug mentions to existing ontologies. Using this method, we inferred sex labels for 450,371 human and 245,107 mouse microarray and RNA-seq samples from refine.bio. RESULTS: Overall, we find slight female bias (52.1%) in human samples and (62.5%) male bias in mouse samples; this corresponds to a majority of mixed sex studies in humans and single sex studies in mice, split between female-only and male-only (25.8% vs. 18.9% in human and 21.6% vs. 31.1% in mouse, respectively). In drug studies, we find limited evidence for sex-sampling bias overall; however, specific categories of drugs, including human cancer and mouse nervous system drugs, are enriched in female-only and male-only studies, respectively. We leverage our expression-based sex labels to further examine the complexity of cell line sex and assess the frequency of metadata sex label misannotations (2-5%). CONCLUSIONS: Our results demonstrate limited overall sex bias, while highlighting high bias in specific subfields and underscoring the importance of including sex labels to better understand the underlying biology. We make our inferred and normalized labels, along with flags for misannotated samples, publicly available to catalyze the routine use of sex as a study variable in future analyses.

Nutrition and Health Improvements After Participation in an Urban Home Garden Program.

OBJECTIVE: To elucidate the perceived health benefits of an urban home gardening and nutritional education program in a population at high cardiometabolic risk. DESIGN: Qualitative data collected via in-depth, semistructured interviews in Spanish or English. SETTING: Community-based program offering supported urban home gardening together with nutrition education in Santa Clara County, CA. PARTICIPANTS: A total of 32 purposively sampled low-income participants in an urban home gardening program. Participants were primarily female (n = 24) and Latino/a (n = 22). PHENOMENON OF INTEREST: Perceptions of the nutrition and health benefits of education-enhanced urban home gardening. ANALYSIS: Bilingual researchers coded transcripts using a hybrid inductive and deductive approach. Two coders double coded at intervals, independently reviewed coding reports, organized content into key themes, and selected exemplary quotations. RESULTS: The most salient perceived impacts were greater food access, increased consumption of fresh produce, a shift toward home cooking, and decreased fast food consumption. Participants attributed these changes to greater affordability, freshness, flavor, and convenience of their garden produce; increased health motivation owing to pride in their gardens; and improved nutritional knowledge. Participants also reported improved physical activity, mental health, and stress management; some reported improved weight and adherence to diabetes-healthy diets. CONCLUSIONS AND IMPLICATIONS: Education-enhanced urban home gardening may facilitate multidimensional nutrition and health improvements in marginalized populations at high cardiometabolic risk.

Marginalization and Community Perception of HIV Care, Treatment, and Support on Mfangano Island, Kenya.

BACKGROUND: In rural sub-Saharan Africa (SSA), the human immunodeficiency virus (HIV)/AIDS pandemic has exerted effects on nearly every aspect of life. Yet despite the pandemic's near ubiquitous impacts, major barriers to HIV care, treatment, and support persist. Compounding the barriers to care is the incredible complexity and diversity of experience across different sociocultural contexts. OBJECTIVES: This exploratory community-based participatory study aimed to generate an explanatory model about how geographic and socioeconomic marginalization shape community perception of HIV care, treatment, and support among rural communities of Mfangano Island, Kenya. METHODS: Twelve focus groups with a total of 105 participants were conducted as a part of a mixed-methods cross-sectional health study. RESULTS: Study findings are organized within an ecological framework with the following themes: readiness at the individual level, social capital at the household level, and collective efficacy at the community level. Potential solutions were also described within this framework; enabling encouragement at the individual level, enhancing productivity at the household level, and addressing underlying socioeconomic inequities at the community level. CONCLUSIONS: HIV-related consequences at the individual, household, and community levels have adversely affected how Mfangano communities respond to the HIV/AIDS epidemic. Community-based strategies are needed to address interrelated inequities at multiple levels. Changing community perception may overcome HIV stigma to enable individual readiness to seek care. Access to care and treatment enhances productivity and hence social capital in HIV-affected households. Addressing socioeconomic inequities at the community level increases access to social and instrumental support and, thus, may decrease risk and vulnerability for HIV/AIDS.

The Kaiser Permanente Clinician Cultural and Linguistic Assessment Initiative: research and development in patient-provider language concordance.

Patient-clinician language concordance is a critical component of the language access equation and is considered the gold standard for communication. As a result of lack of validated testing standards, measures, and tools, Kaiser Permanente developed the Clinician Cultural and Linguistic Assessment Initiative to ensure verifiable linguistic proficiency in clinical encounters and has established a standard level whereby the clinician is deemed to have a qualifying level of proficiency in communicating directly with patients independent of an interpreter. Our benchmarking efforts in language concordance have been rooted with the key aim to identify talented bilingual and bicultural clinician workforce and to establish the systems foundation to coordinate appropriate language services. We share accomplishments, lessons learned, and promising practices to inform future efforts in language concordance.