Postpartum diabetes screening among low income women with gestational diabetes in Missouri 2010-2015.

BACKGROUND: Gestational diabetes increases risk for type 2 diabetes seven-fold, creating a large public health burden in a young population. In the US, there are no large registries for tracking postpartum diabetes screening among women in under-resourced communities who face challenges with access to care after pregnancy. Existing data from Medicaid claims is limited as women often lose this coverage within months of delivery. In this study, we aim to leverage data from electronic health records and administrative claims to better assess postpartum diabetes screening rates among low income women. METHODS: A retrospective population of 1078 women with gestational diabetes who delivered between 1/1/2010 and 10/8/2015 was generated by linking electronic health record data from 21 Missouri Federally Qualified Health Centers (FQHCs) with Medicaid administrative claims. Screening rates for diabetes were calculated within 12 weeks and 1 year of delivery. Initial screening after the first postpartum year was also documented. RESULTS: Median age in the final population was 28 (IQR 24-33) years with over-representation of black non-Hispanic and urban women. In the final population, 9.7% of women had a recommended diabetes screening test within 12 weeks and 18.9% were screened within 1 year of delivery. An additional 125 women received recommended screening for the first time beyond 1 year postpartum. The percentage of women who had a postpartum visit (83.9%) and any glucose testing (40.6%) in the first year far exceeded the proportion of women with recommended screening tests. CONCLUSIONS: Linking electronic health record and administrative claims data provides a more complete picture of healthcare follow-up among low income women after gestational diabetes. While screening rates are higher than reported with claims data alone, there are opportunities to improve adherence to screening guidelines in this population.

Assessment of the impact of the COVID-19 pandemic on health services use.

Objectives: The coronavirus disease of 2019 (COVID-19) pandemic declared by the World Health Organization on March 11, 2020 impacted healthcare services with provider and patient cancellations, delays, and patient avoidance or delay of emergency department or urgent care. Limited data exist on the population proportion affected by delayed healthcare, which is important for future healthcare planning efforts. Our objective was to evaluate the impact of the COVID-19 pandemic on healthcare service cancellations or delays and delays/avoidance of emergency/urgent care overall and by population characteristics. Study design: This was a cross-sectional study. Methods: Our sample (n = 2314) was assembled through a phone survey from 8/12/2020-10/27/2020 among non-institutionalized St. Louis County, Missouri, USA residents ≥18 years. We asked about provider and patient-initiated cancellations or delays of appointments and pandemic-associated delays/avoidance of emergency/urgent care overall and by participant characteristics. We calculated weighted prevalence estimates by select resident characteristics. Results: Healthcare services cancellations or delays affected ∼54% (95% CI 50.6%-57.1%) of residents with dental (31.1%, 95% CI 28.1%-34.0%) and primary care (22.1%, 95% CI 19.5%-24.6%) being most common. The highest prevalences were among those who were White, ≥65 years old, female, in fair/poor health, who had health insurance, and who had ≥1 medical condition. Delayed or avoided emergency/urgent care impacted ∼23% (95% CI 19.9%-25.4%) of residents with a higher prevalence in females than males. Conclusions: Healthcare use disruptions impacted a substantial proportion of residents. Future healthcare planning efforts should consider these data to minimize potential morbidity and mortality from delayed care.

SARS-CoV-2 active infection prevalence and seroprevalence in the adult population of St. Louis County.

BACKGROUND: The true prevalence of COVID-19 is difficult to estimate due to the absence of random population-based testing. To estimate current and past COVID-19 infection prevalence in a large urban area, we conducted a population-based survey in St. Louis County, Missouri. METHODS: The population-based survey of active infection (PCR) and seroprevalence (IgG antibodies) of adults (≥18 years) was conducted through random-digit dialing and targeted sampling of St. Louis County residents with oversampling of Black residents. Infection prevalence of residents was estimated using design-based and raking weighting. RESULTS: Between August 17 and October 24, 2020, 1245 residents completed a survey and underwent PCR testing; 1073 residents completed a survey and underwent PCR and IgG testing or self-reported results. Weighted prevalence estimates of residents with active infection were 1.9% (95% CI, 0.4%-3.3%) and 5.6% were ever infected (95% CI, 3.3%-8.0%). Overall infection hospitalization and fatality ratios were 4.9% and 1.4%, respectively. CONCLUSIONS: Through October 2020, the percentage of residents that had ever been infected was relatively low. A markedly higher percentage of Black and other minorities compared to White residents were infected with COVID-19. The St. Louis region remained highly vulnerable to widespread infection in late 2020.

Factors Associated With Postpartum Diabetes Screening in Women With Gestational Diabetes and Medicaid During Pregnancy.

INTRODUCTION: Women with gestational diabetes are 7 times more likely to develop type 2 diabetes and require lifelong diabetes screening. Loss of health coverage after pregnancy, as occurs in states that did not expand Medicaid, limits access to guideline-driven follow-up care and fosters health inequity. This study aims to understand the factors associated with the receipt of postpartum diabetes screening for women with gestational diabetes in a state without Medicaid expansion. METHODS: Electronic health record and Medicaid claims data were linked to generate a retrospective cohort of 1,078 women with gestational diabetes receiving care in Federally Qualified Health Centers in Missouri from 2010 to 2015. In 2019-2020, data were analyzed to determine the factors associated with the receipt of recommended postpartum diabetes screening (fasting plasma glucose, 2-hour oral glucose tolerance test, or HbA1c in specified timeframes) using a Cox proportional hazards model through 18 months of follow-up. RESULTS: Median age in this predominantly urban population was 28 (IQR=24-33) years. Self-reported racial or ethnic minorities comprised more than half of the population. Only 9.7% of women were screened at 12 weeks, and 20.8% were screened at 18 months. Prenatal certified diabetes education (adjusted hazard ratio=1.74, 95% CI=1.22, 2.49) and access to public transportation (adjusted hazard ratio=1.70, 95% CI=1.13, 2.54) were associated with increased screening in a model adjusted for race/ethnicity, the total number of prenatal visits, the use of diabetes medication during pregnancy, and a pregnancy-specific comorbidity index that incorporated age. CONCLUSIONS: This study underscores the importance of access to public transportation, prenatal diabetes education, and continued healthcare coverage for women on Medicaid to support the receipt of guideline-recommended follow-up care and improve health equity.

Transmission dynamics: Data sharing in the COVID-19 era.

Problem: The current coronavirus disease 2019 (COVID-19) pandemic underscores the need for building and sustaining public health data infrastructure to support a rapid local, regional, national, and international response. Despite a historical context of public health crises, data sharing agreements and transactional standards do not uniformly exist between institutions which hamper a foundational infrastructure to meet data sharing and integration needs for the advancement of public health. Approach: There is a growing need to apply population health knowledge with technological solutions to data transfer, integration, and reasoning, to improve health in a broader learning health system ecosystem. To achieve this, data must be combined from healthcare provider organizations, public health departments, and other settings. Public health entities are in a unique position to consume these data, however, most do not yet have the infrastructure required to integrate data sources and apply computable knowledge to combat this pandemic. Outcomes: Herein, we describe lessons learned and a framework to address these needs, which focus on: (a) identifying and filling technology "gaps"; (b) pursuing collaborative design of data sharing requirements and transmission mechanisms; (c) facilitating cross-domain discussions involving legal and research compliance; and (d) establishing or participating in multi-institutional convening or coordinating activities. Next steps: While by no means a comprehensive evaluation of such issues, we envision that many of our experiences are universal. We hope those elucidated can serve as the catalyst for a robust community-wide dialogue on what steps can and should be taken to ensure that our regional and national health care systems can truly learn, in a rapid manner, so as to respond to this and future emergent public health crises.