Modeling geostatistical incomplete spatially correlated survival data with applications to COVID-19 mortality in Ghana.

Survival models which incorporate frailties are common in time-to-event data collected over distinct spatial regions. While incomplete data are unavoidable and a common complication in statistical analysis of spatial survival research, most researchers still ignore the missing data problem. In this paper, we propose a geostatistical modeling approach for incomplete spatially correlated survival data. We achieve this by exploring missingness in outcome, covariates, and spatial locations. In the process, we analyze incomplete spatially-referenced survival data using a Weibull model for the baseline hazard function and correlated log-Gaussian frailties to model spatial correlation. We illustrate the proposed method with simulated data and an application to geo-referenced COVID-19 data from Ghana. There are several disagreements between parameter estimates and credible intervals widths obtained using our proposed approach and complete case analysis. Based on these findings, we argue that our approach provides more reliable parameter estimates and has higher predictive accuracy.

Pharmacist eConsult service for primary care medication optimization and safety.

BACKGROUND: There is a critical need in primary care to proactively prevent, identify, and resolve poor medication-related outcomes. However, more than 80% of primary care practices do not have clinical pharmacists as members of expanded care teams. The emergence of eConsult services in primary care settings presents an opportunity for primary care providers (PCPs) to consult with clinical pharmacists as "on-demand" pharmacotherapy specialists. OBJECTIVES: The objectives were to (1) determine the use of a clinical pharmacist in an existing eConsult network, (2) characterize the use and type of clinical pharmacist eConsults sent by PCPs, and (3) measure the implementation percentage of pharmacist recommendations by PCPs. METHODS: The study was conducted in a federally qualified health center using an existing eConsult platform. A clinical pharmacist was contracted to receive eConsults and was expected to respond within 2 business days. PCPs were introduced to the pharmacist eConsult service through presentations that reviewed the clinical pharmacist's education/training, suitable pharmacist eConsult topics, and workflow for sending a pharmacist eConsult. RESULTS: A total of 57 eConsults containing 123 individual questions were answered. Advanced practice nurses (APRNs) sent 3 times the number of eConsults and individual questions per eConsult compared with physicians (P < 0.0001). Most eConsult questions from APRNs related to adverse drug events/drug interactions (44%), drug or dosage changes to reach therapeutic goals (18%), and renal/hepatic dosage adjustments (13%). However, physician eConsult questions were primarily targeted on patient-specific drug or dosage adjustments (62%) and comprehensive medication regimen reviews (17%). A total of 74% of the pharmacist eConsult responses had at least 50% of the recommendations implemented by PCPs. CONCLUSION: This study revealed the use of a pharmacist eConsult service for medication-related questions in an existing eConsult network for PCPs. As more practices enroll in value-based plans, pharmacist eConsults can improve the quality and safety of prescribing and chronic medication management.

Multiple Imputation for Incomplete Data in Environmental Epidemiology Research.

PURPOSE OF REVIEW: Incomplete data are a common problem in statistical analysis of environmental epidemiological research. However, many researchers still ignore this complication. We evaluate the performance of two commonly used multiple imputation (MI) methods (fully conditional specification and multivariate normal) for handling missing data and compare them to complete case analysis (CCA) method. We further discuss issues that arise when these methods are being used. RECENT FINDINGS: MI is a simulation-based approach to deal with incomplete data. In general, MI will perform better then ad hoc techniques such as CCA. MI is an approach which replaces the missing data with plausible values and allows for additional uncertainty due to the missing information caused by the incomplete data. To illustrate this, we use data of 944 women from the Collaborative Perinatal Project and compare estimates between these methods. The goal is to examine if each of two outcomes, birth-weight and spontaneous abortion, in the data set are associated with mothers' smoking status during pregnancy adjusting for baseline covariates in the model. Results indicate that MI is better suited for handling incomplete data and led to a significant improvement in parameter estimates compared to CCA. The two MI methods produced similar point estimates, but slightly different standard errors.

Texas Adolescent Tobacco and Marketing Surveillance System's Design.

OBJECTIVES: To provide a full methodological description of the design of the wave I and II (6-month follow-up) surveys of the Texas Adolescent Tobacco and Marketing Surveillance System (TATAMS), a longitudinal surveillance study of 6th, 8th, and 10th grade students who attended schools in Bexar, Dallas, Tarrant, Harris, or Travis counties, where the 4 largest cities in Texas (San Antonio, Dallas, Fort Worth, Houston, and Austin, respectively) are located. METHODS: TATAMS used a complex probability design, yielding representative estimates of these students in these counties during the 2014-2015 academic year. Weighted prevalence of the use of tobacco products, drugs and alcohol in wave I, and the percent of: (i) bias, (ii) relative bias, and (iii) relative bias ratio, between waves I and II are estimated. RESULTS: The wave I sample included 79 schools and 3,907 students. The prevalence of current cigarette, e-cigarette and hookah use at wave I was 3.5%, 7.4%, and 2.5%, respectively. Small biases, mostly less than 3.5%, were observed for nonrespondents in wave II. CONCLUSIONS: Even with adaptions to the sampling methodology, the resulting sample adequately represents the target population. Results from TATAMS will have important implications for future tobacco policy in Texas and federal regulation.

Timely Health Service Utilization of Older Foster Youth by Insurance Type.

PURPOSE: To evaluate the impact of a policy change for older foster care youth from a fee-for-service (FFS) Medicaid program to health maintenance organization (HMO) providers on the timeliness of first well-child visits (health care physicals). METHODS: A three-year retrospective study using linked administrative data collected by the Michigan Departments of Human Services and Community Health of 1,657 youth, ages 10-20 years, who were in foster care during the 2009-2012 study period was used to examine the odds of receiving a timely well-child visit within the recommended 30-day time frame controlling for race, age, days from foster care entry to Medicaid enrollment, and number of foster care placements. RESULTS: Youth entering foster care during the HMO period were more likely to receive a timely well-child visit than those in the FFS period (odds ratio, 2.46; 95% confidence interval, 1.84-3.29; p < .0001) and days to the first visit decreased from a median of 62 days for those who entered foster care during the FFS period to 29 days for the HMO period. Among the other factors examined, more than 14 days to Medicaid enrollment, being non-Hispanic black and having five or more placements were negatively associated with receipt of a timely first well-child visit. CONCLUSIONS: Those youth who entered foster care during the HMO period had significantly greater odds of receiving a timely first well-child visit; however, disparities in access to preventive health care remain a concern for minority foster care youth, those who experience delayed Medicaid enrollment and those who experienced multiple placements.