Greater Houston Area Research Articles

Abstract TP147: Investigating Potential Racial And Ethnic Biases In Mechanical Thrombectomy Selection For Expanded Indication Populations

Introduction: Endovascular thrombectomy (EVT) performance in clinical practice has grown substantially, including in patient groups previously excluded from clinical trials such as those with advanced age, lower Alberta Stroke Program Early CT Score (ASPECTS) and distal occlusions. However, the access and utilization of EVT in these non-randomized controlled trial (RCT) supported populations across different racial and ethnic groups remains incompletely characterized Methods: Using our prospectively maintained multi-center registry which includes four comprehensive stroke centers around the greater Houston area, we identified patients with large vessel occlusion (LVO) acute ischemic stroke (AIS). Patients were included if LVO was confirmed by non-invasive vascular imaging. The primary outcome was rate of performance of EVT in patients with low ASPECTS (0-5), advanced age (> 80), and distal occlusion (M2 and beyond) by race and was determined by Fisher’s exact test. Results: Among 2,614 patients with LVO AIS, 1,239 (47%) were female, median NIHSS was 13 [interquartile range 5-20], ASPECTS was 9 [7-10]. 28% of the cohort was black, 52% white and 4% Hispanic. The most common occlusion locations were M1 MCA (34%) and M2 MCA (19%). Among the 538 patients aged > 80 years old, 232 (43%) underwent EVT. There were no significant differences in the proportions of patients treated by race (43% white vs 43% black, p=1) . Among 175 patients with ASPECTS 0-5, 59 (34%) underwent EVT. There were no significant differences in the proportions of patients treated by race (44% white vs 35% black, p=0.37). Among 760 patients with occlusion of M2 and beyond, 224 (30%) underwent EVT. There were no significant differences in the proportions of patients treated by race (33% white, 29% black, p=0.28). Conclusion: In this registry from a diverse urban population, we did not identify disparities in EVT performance in patients with non-RCT supported indications by race. Further studies in other clinical settings will be important.

Abstract WP51: Effect Of Automated Large Vessel Occlusion Detection On Endovascular Therapy Treatment Rate: A Multi-Center Cluster Randomized Clinical Trial

Introduction: Automated Large Vessel Occlusion (LVO) detection and software-based care team integration may improve treatment times. Their effect on likelihood to perform Endovascular Thrombectomy (EVT) in LVO Acute Ischemic Stroke (AIS) patients remains undetermined. Methods: We performed a cluster randomized stepped wedge clinical trial across 4 comprehensive stroke centers in the greater Houston area from January 1st 2021 - February 24th 2022. This trial design was chosen due to the impracticality of randomizing at the patient level. An automated LVO detection and workflow manager software (Viz.AI) was implemented at the 4 hospitals in a stepped fashion, with a randomly determined order (Figure 1) . Patients were included if they were diagnosed with LVO AIS based on CT angiogram. Patients who presented during the 2-week transition period at the time of LVO detection software activation were excluded. The primary outcome was proportion of LVO AIS patients treated with EVT adjusted for age, sex and NIHSS and was determined using a mixed-effect logistic regression, with a random effect for cluster (hospital site) and fixed effect for exposure status. Results: Among 834 patients that met inclusion criteria, the median age was 68 [58-79] years, NIHSS 13 [5-20], and 50% were female. Median time from last known well to arrival was 298 [102- 754] minutes. A total of 575 patients were evaluated in the unexposed period and 259 in the exposed. In univariable analysis, there was no significant increase in the proportion of LVO AIS treated with EVT (40.5% vs. 45.6%, unexposed vs. exposed, p=0.17) . In multivariable adjusted mixed-effects model, EVT rates did not change due to software implementation [OR 1.18, p=0.45]. Discussion: In a multi-center cluster randomized trial, implementation of an automated LVO detection software with care team-wide communication did not significantly alter rates of EVT in patients with LVO AIS.

Abstract IA013: Delivering an effective community-driven model to reduce cancer risk at a population level: results from MD Anderson’s Be Well Communities

Abstract Be Well Communities™ is The University of Texas MD Anderson Cancer Center’s place-based strategy for cancer prevention and control, working with communities to promote wellness and reduce modifiable risk factors for cancer. This initiative builds cross-sector partnerships and drives systems change for health by uniting individuals, schools, workplaces, government agencies, health care providers and policymakers to plan and carry out sustainable, community-led solutions that will make positive, long-lasting changes in people’s lives. Be Well Communities is built on 100 years of healthy community initiative best practices, literature, and experience and is aligned with the institution’s strategy and community outreach and engagement efforts. Since 2016, MD Anderson’s Cancer Prevention & Control Platform built a model that creates strong community linkages, advances professional and policy changes, and establishes active health coalitions. Community-driven coalitions ensure that interventions are executed in alignment with the priorities and needs of the community. Key components of effective community-based efforts include creating a shared vision and building trust with the community, creating a diverse network of partners through relationship building and mutual accountability, establishing a governing process with a grassroots component, and leveraging resources, training, and commissioning technical expertise where necessary. Additional components of the model include community assessment, planning, and a multi-year implementation phase – with a vision towards sustainability and evaluation throughout. Foundational to the work is partnership with community-based organizations and clinics who are supported to enhance their capacity to deliver and evaluate evidence-based interventions that are tailored directly to the needs of the community. Together with community partners, this work is positively impacting communities across the Greater Houston Area. More than 50 local, regional and state organizations are actively engaged on Be Well Communities coalitions, guiding the implementation of action plans in partnership with community residents. Since 2017, key milestones include: 7+ million pounds of healthy food distributed 27 sunshades installed at city parks, schools and college campuses 79,000+ students participated in school-based health and physical activity programs 10,000+ college students, staff and faculty have access to tobacco-free education and resources 24 free vaccination clinics hosted 1,900 cancer screenings provided in 12 months Further, for the most mature community in the portfolio, 90% of all interventions were completed or sustained. This collaborative approach, led by the wants and needs of the community, has established an infrastructure that is addressing its short-term goals and promises to improve long-term, cancer-related outcomes in communities. Aligning across sectors with a shared vision, fundamentally changing the way groups work together, is the building block for creating systems change for health. Citation Format: Ruth Rechis. Delivering an effective community-driven model to reduce cancer risk at a population level: results from MD Anderson’s Be Well Communities. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr IA013.

Investigating burn-out contributors and mitigators among intensive care unit nurses during COVID-19: a focus group interview study

ObjectivePast literature establishes high prevalence of burn-out among intensive care unit (ICU) nurses, and the influence of the COVID-19 pandemic in intensifying burn-out. However, the specific pandemic-related contributors and practical...

Fireside Chat on the Asian American, Native Hawaiian, and Pacific Islander Special Edition of the Health Equity Journal Featuring Authors.

Fireside Chat on the Asian American, Native Hawaiian, and Pacific Islander Special Edition of the Health Equity Journal Featuring Authors.

Design for a cluster randomized controlled trial to evaluate the effects of the CATCH Healthy Smiles school-based oral health promotion intervention among elementary school children

BackgroundThe top two oral diseases (tooth decay and gum disease) are preventable, yet dental caries is the most common childhood disease with 68% of children entering kindergarten having tooth decay. CATCH Healthy Smiles is a coordinated school health program to prevent cavities for students in kindergarten, 1st, and 2nd grade, and is based on the framework of Coordinated Approach to Child Health (CATCH), an evidence-based coordinated school health program. CATCH has undergone several cluster-randomized controlled trials (CRCT) demonstrating sustainable long-term effectiveness in incorporating the factors surrounding children, in improving eating and physical activity behaviors, and reductions in obesity prevalence among low-income, ethnically diverse children. The aim of this paper is to describe the design of the CATCH Healthy Smiles CRCT to determine the effectiveness of an oral health school-based behavioral intervention in reducing incidence of dental caries among children. MethodsIn this CRCT, 30 schools serving low-income, ethnically-diverse children in greater Houston area are recruited and randomized into intervention and comparison groups. From which, 1020 kindergarten children (n = 510 children from 15 schools for each group) will be recruited and followed through 2nd grade. The intervention consists of four components (classroom curriculum, toothbrushing routine, family outreach, and schoolwide coordinated activities) will be implemented for three years in the intervention schools, whereas the control schools will be offered free trainings and materials to implement a sun safety curriculum in the meantime. Outcome evaluation will be conducted at four time points throughout the study period, each consists of three components: dental assessment, child anthropometric measures, and parent survey. The dental assessment will use International Caries Detection and Assessment System (ICDAS) to measures the primary outcome of this study: incidence of dental caries in primary teeth as measured at the tooth surface level (dfs). The parent self-report survey measures secondary outcomes of this study, such as oral health related behavioral and psychosocial factors. A modified crude caries increment (mCCI) will be used to calculate the primary outcome of the CATCH Healthy Smiles CRCT, and a two-tailed test of the null hypothesis will be conducted to evaluate the intervention effect, while considering between- and within-cluster variances through computing the weighted-average of the mCCI ratios by cluster. ConclusionIf found to be effective, a platform for scalability, sustainability and dissemination of CATCH already exists, and opens a new line of research in school oral health. Clinical trials identifierAt ClinicalTrials.gov - NCT04632667.

Case growth analysis to inform local response to COVID-19 epidemic in a diverse U.S community

Early detection of new outbreak waves is critical for effective and sustained response to the COVID-19 pandemic. We conducted a growth rate analysis using local community and inpatient records from seven hospital systems to characterize distinct phases in SARS-CoV-2 outbreak waves in the Greater Houston area. We determined the transition times from rapid spread of infection in the community to surge in the number of inpatients in local hospitals. We identified 193,237 residents who tested positive for SARS-CoV-2 via molecular testing from April 8, 2020 to June 30, 2021, and 30,031 residents admitted within local healthcare institutions with a positive SARS-CoV-2 test, including emergency cases. We detected two distinct COVID-19 waves: May 12, 2020–September 6, 2020 and September 27, 2020–May 15, 2021; each encompassed four growth phases: lagging, exponential/rapid growth, deceleration, and stationary/linear. Our findings showed that, during early stages of the pandemic, the surge in the number of daily cases in the community preceded that of inpatients admitted to local hospitals by 12–36 days. Rapid decline in hospitalized cases was an early indicator of transition to deceleration in the community. Our real-time analysis informed local pandemic response in one of the largest U.S. metropolitan areas, providing an operationalized framework to support robust real-world surveillance for outbreak preparedness.

Home-Based Care and Mental Health during a Disaster: A Qualitative Analysis.

Disasters adversely affect individuals' mental health; yet, research is scant on the mental health needs of frontline workers during and immediately after disasters. Our study explored this gap through the perspectives of home-based care providers (HBCP) who provided care during and after Hurricanes Irma and Harvey. In this qualitative study, five in-person focus groups were held between January and November 2019 with 25 HBCP drawn from home health care agencies in southern Florida and the Greater Houston Area. Four themes were identified using an abductive analytic approach: HBCPs' disaster-related mental health needs; HBCP resilience in the context of disaster; psychological tensions associated with simultaneously caring for self, family, and patients; and supporting patients' mental health needs during and after disaster. Our data suggest that HBCP may benefit from formal training and interventions to support their own mental health as well as that of their patients in the context of disasters.

Dietary behaviors and food insecurity among Houston college students during the COVID-19 pandemic

Objective: This study assessed the impact of the COVID-19 pandemic on college students’ nutrition, including dietary behaviors and food security status. Participants: Participants included 140 students between 18 and 25 years of age, who were enrolled in a college or university in the greater Houston area. Methods: Analyses included descriptive statistics, t tests, and ANOVAs to analyze differences in dietary behaviors by demographic variables, and chi-square tests to assess characteristics associated with food security status. Results: The majority of participants reported changing their diets due to the COVID-19 pandemic. There were no significant differences by demographics. However, there were significant differences in food security status by race/ethnicity and social class. Conclusion: This study identified changes and disparities in college students’ dietary behaviors and food security status during the COVID-19 pandemic. Findings help inform future policy, programs, and research to address college students’ nutrition during the ongoing COVID-19 pandemic.

Temporary Firearm Storage and Safe Firearm Storage Counseling at Gun Retailers and Ranges in the Greater Houston Area: A Potential New Partner in Addressing Child and Youth Firearm Injury?

Temporary Firearm Storage and Safe Firearm Storage Counseling at Gun Retailers and Ranges in the Greater Houston Area: A Potential New Partner in Addressing Child and Youth Firearm Injury?

Federally Overlooked Flood Risk Inequities in Houston, Texas: Novel Insights Based on Dasymetric Mapping and State-of-the-Art Flood Modeling

In the United States, the Federal Emergency Management Agency (FEMA) delineates 100-year flood zones to define risks, regulate flood insurance premiums, and inform flood management. Evidence indicates that FEMA flood maps are incomplete, calling much of our current knowledge of U.S. flood hazard inequities into question. We use a state-of-the-art flood hazard model and census tract-level dasymetrically mapped sociodemographic data to examine flood risk inequities in the Greater Houston area, where increasingly frequent and damaging flood events are occurring. We innovate by analyzing federally overlooked 100-year flood risks (100-year flood zones delineated by the flood hazard model that are outside of FEMA 100-year flood zones). Results indicate that nearly 1 million Greater Houston residents live in federally overlooked 100-year flood zones. Black and Asian neighborhoods experience disproportionate risk in federally overlooked pluvial and fluvial flood zones, and Hispanic neighborhoods experience disproportionate risk in all federally overlooked zones (coastal, pluvial, and fluvial). High flood risk and the relative lack of protective resources in federally overlooked 100-year flood zones doubly jeopardizes racial and ethnic minority communities. Our findings and recent flood disasters suggest that future flood impacts in Greater Houston will be catastrophic and unjust unless FEMA revises their risk mapping and management approach to promote long-term public safety and social equity.

Metagenomics Analysis of Viral Families Carried by Aedes Mosquitos in Houston

Mosquitos are known vectors of many serious viral diseases, but little is known about the complete collection of viral strains that they might carry. Historically, we have relied on culturing techniques to study microbial diversity, but genomic analyses have demonstrated that there is much more out there than initially suspected. In this study, we used a metagenomic approach to characterize the viral populations carried by different species of mosquitos found in Houston. Specifically, we sequenced the entire genetic material in pooled mosquito samples, followed by analyses with computational tools to identify each sequence obtained. We collected mosquitos from various locations in Houston and separated them by both species and sex using morphological characteristics and DNA barcoding. Total DNA and RNA were used in order to characterize both DNA and RNA viruses. RNA samples were converted to cDNA to facilitate sequencing and the combined DNA/cDNA libraries were sequenced using 454 technology. We used a modified BLAST workflow developed in‐house to analyze the resulting sequences. Our first analysis involved samples of male and female Aedes aegypti.Our results showed that we are able to detect both DNA and RNA viral sequences in our samples, as well as thousands of unknown or novel sequences. A total of 51 different species of viruses were identified in the female sample, and 40 different species in the male sample. Those of interest include West Nile and Dengue, as well as lesser known viruses, like Nam Dinh. Interestingly, the female sample carried more RNA viruses than the male sample, although further work will reveal if this finding is significant or an experimental artifact. Currently, we are in the process of building libraries from new samples of mosquitos, including other species typically found in our area, such as Culexand Anopheles. We plan on further analyzing the sequence libraries obtained, with particular focus on the unknown sequences, many of which may be viral in origin. These studies will help us better understand the viral collections carried by different mosquitos in the Greater Houston area.

Key determinants of particulate matter 2.5 concentrations in urban environments with scenario analysis

Particulate matter (PM) 2.5 generates a variety of negative effects on health, such as heart and lung disease, asthma, and respiratory symptoms. The pollutants in the atmosphere primarily result from human activities, and, in urban settings, increases in traffic volume and higher building density can elevate the level of PM2.5. Building on previous research, this study primarily focuses on two highly developed urban areas in the Texas Triangle region: Travis County in the Austin Metropolitan Area and Harris County in the Greater Houston Area. It explores different types of urban features, such as urban structures, land use/land cover, traffic volume, and distance from roads, that affect the PM2.5 concentration in urban environments at the local scale. Throughout this study, we use various research methods, including geographically weighted regression, to estimate the PM2.5 concentrations at local scales, 3D city models to derive urban characteristics, and the random forest algorithm to predict the effects of urban features on PM2.5 concentrations. Our findings suggest that developed land use, tall buildings in dense areas, and major traffic networks are the key contributors to PM2.5. However, we also find that tree canopy cover can significantly reduce PM2.5 concentrations.

Unsung Heroes or Exploited Workers? Latino Migrant Day Laborers in Post-Harvey Houston and Critical Environmental Justice

Unsung Heroes or Exploited Workers? Latino Migrant Day Laborers in Post-Harvey Houston and Critical Environmental Justice Daniel Olmos (bio) In August 2017, Hurricane Harvey devastated the Houston metropolitan area and caused approximately $125 billion in property damage, becoming one of the most costly storms in US history. Media outlets and observers attended to the serious socioeconomic plight of homeowners by highlighting the flooding of 150,000 homes and over 60,000 displaced people living in shelters and hotels, as well as featuring the historic role that social media played in connecting first responders to victims when emergency call systems overloaded.1 The storm acutely devastated lowlying areas of Houston, which is home to many disinvested and disadvantaged communities of color—the flooding and the lackluster state response led many to evoke the dramatic scenes of racialized abandonment during Hurricane Katrina on New Orleans in 2005.2 As global warming increasingly intensifies tropical storm systems along coastal regions in the US, climate justice movements insist that the most vulnerable and marginalized communities—also the least responsible for deeply-rooted systemic inequities—are also the most negatively impacted by the effects of global warming.3 While much scholarship has emphasized post-hurricane recovery efforts from the vantage point of Houston residents and businesses, little attention has been paid to the incorporation of Latino migrant day laborers as veritable “second responders” and, even less, as subjects of climate injustice and agents of environmentalism.4 Hurricane Harvey, a Category 4 storm, dumped fifty inches of rainfall and thirty-three trillion gallons of water into major commercial, [End Page 46] industrial, and residential corridors of the Houston region. The spectacles of evacuation and rescue that dominated media representation of the storm during the four-day news cycle obscured the eventual arduous process of recovery, in particular the prevailing mode of disaster recovery based on the exploitation of precarious racialized migrant labor. In the aftermath, unregulated small contractors and individual homeowners recruited mostly Latino day laborers to clear out moldy dry walls, replace rotted flooring, demolish dilapidated structures, and clean hazardous facilities, often with little or sometimes no pay and frequently without proper workplace safety equipment and conditions. “People don’t analyze it. They don’t see the consequences,” Martin Mares, a Mexican immigrant day laborer who has lived in Houston since 1995, noted during the recovery efforts. “They go to work without knowing whether the business will even pay them.”5 The erasure of day labor exploitation was extended by the mass-mediated appeals to resilience and grit in the face of a non-responsive state, namely through hashtag campaigns like #houstonstrong that promoted a neoliberal “rebuild above all else” model of recovery.6 In this context, this essay posits that the devastation wrought on the greater Houston area in the wake of Hurricane Harvey revealed not only the increasing vulnerability of US coastal regions to catastrophic weather patterns as a result of accelerated climate change, but also the socioeconomic relations and structures of racialized exploitation necessary for post-disaster reconstruction. I focus on the role of Latino migrant day laborers in greater Houston’s post-Hurricane Harvey rebuilding efforts and the environmental injustice implications, including the situatedness of day laborers in the face of ecological devastation. In the spirit of what Sarah Wald, David Vazquez, Priscilla Solis Ybarra, and Sarah Jaquette articulate as emerging “Latinx environmentalisms,”7 and drawing on a critical environmental justice framework through a qualitative sociological approach, I examine the conditions under which Latino migrant day laborers experienced racialized, economic, and ecological injustice following Hurricane Harvey, and finally how their subjection and struggle for dignity embodies a critical environmental justice politics in a moment of profound ecological crisis. [End Page 47] From the Anthropocene to Critical Environmental Justice The recruitment and exploitation of Latino day laborers in post-Harvey Houston was structured within the anthropocene era. In 2000, Paul Crutzen and Eugene Strermer introduced the concept of the anthropocene to explain a new stage of geohistorical development characterized by human activity as a “major geological force” and influence on climate patterns.8 While the anthropocene has become a buzzword with many different meanings, the category has fundamentally identified humanity as...

The effect of biologic therapy for immune-mediated inflammatory diseases on clinical outcomes of COVID-19 in the greater Houston area: A retrospective chart review

The effect of biologic therapy for immune-mediated inflammatory diseases on clinical outcomes of COVID-19 in the greater Houston area: A retrospective chart review

Abstract PO-031: Qualitative analysis of focus group data for liver cancer prevention program planning

Abstract Texas currently has the highest reported age-adjusted incidence rate of hepatocellular carcinoma (HCC) in the nation. Minority communities tend to have a higher incidence rate of HCC compared to non-Hispanic Whites. Individuals with a past medical history of fibrosis, cirrhosis, and alcoholic and non-alcoholic fatty liver disease – all of which are potentially preventable – are known to be at greater risk for developing HCC. Early detection of HCC is known to improve survival rates; however, rates of screening for risk factors and timely detection are low. Improved efforts are, therefore, required to educate minority communities on prevention of risk factors that may lead to development of HCC. The HOPE Clinic is a community based 501(c)(3) that aims to provide culturally competent healthcare to all Greater Houston Area. The aim of this analysis is to determine characteristics of an effective and retentive intervention program that would be attractive to and serve the Greater Houston Area using focus group data from HOPE Clinic patient participants. Patients were recruited from the HOPE Clinic to participate in focus groups. A total of five focus group interviews were conducted in English, Vietnamese, and Spanish and translated for analysis to determine patient's knowledge of risk factors of liver cancer, barriers to lifestyle changes, and health management efforts. Focus group data was analyzed using qualitative methods of analysis. Atlas.ti 8 for Windows was used to assign labels (codes) to focus group data, determine frequency of codes, and aid in organization of recurring themes across all interviews. The results of this qualitative analysis found themes of health barriers, motivating factors, willingness to participate in intervention programs, program needs, knowledge of liver health, suggested protective efforts, and past program involvement. Participants often pointed out their awareness of important health behaviors such as nutrition, alcohol consumption, and physical activity while also acknowledging barriers such as time constraints due to overworking, accessibility of physical activity, and culturally specific diets. Fear of illness and aging were prominent motivational factors. Program format should include tailored scheduling with the option of virtual, in person, and asynchronous participation. Content of the program should include objectives such as healthier recipes and food preparation, recipe adaptation, time management skills, and physical activity for beginners. Overall, there was a consensus that interventions should promote positive health behaviors in both younger and older age groups. Citation Format: Jordan Swan. Qualitative analysis of focus group data for liver cancer prevention program planning [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-031.

Health Disparities and Climate Change: The Intersection of Three Disaster Events on Vulnerable Communities in Houston, Texas.

Although evidence suggests that successive climate disasters are on the rise, few studies have documented the disproportionate impacts on communities of color. Through the unique lens of successive disaster events (Hurricane Harvey and Winter Storm Uri) coupled with the COVID-19 pandemic, we assessed disaster exposure in minority communities in Harris County, Texas. A mixed methods approach employing qualitative and quantitative designs was used to examine the relationships between successive disasters (and the role of climate change), population geography, race, and health disparities-related outcomes. This study identified four communities in the greater Houston area with predominantly non-Hispanic African American residents. We used data chronicling the local community and environment to build base maps and conducted spatial analyses using Geographic Information System (GIS) mapping. We complemented these data with focus groups to assess participants’ experiences in disaster planning and recovery, as well as community resilience. Thematic analysis was used to identify key patterns. Across all four communities, we observed significant Hurricane Harvey flooding and significantly greater exposure to 10 of the 11 COVID-19 risk factors examined, compared to the rest of the county. Spatial analyses reveal higher disease burden, greater social vulnerability, and significantly higher community-level risk factors for both pandemics and disaster events in the four communities, compared to all other communities in Harris County. Two themes emerged from thematic data analysis: (1) Prior disaster exposure prepared minority populations in Harris County to better handle subsequent disaster suggesting enhanced disaster resilience, and (2) social connectedness was key to disaster resiliency. Long-standing disparities make people of color at greater risk for social vulnerability. Addressing climate change offers the potential to alleviate these health disparities.

63. PK-RNN-V: A Deep Learning Model for Vancomycin Therapeutic Drug Monitoring using Electronic Health Record Data

BackgroundTherapeutic drug monitoring (TDM) for vancomycin (VAN) with Bayesian models is recommended by national guidelines. However, limited data incorporating the models may hurt the performance. Our aim is to develop a novel deep learning-based pharmacokinetic model for vancomycin (PK-RNN-V) using electronic medical records (EHRs) data to achieve more accurate and personalized predictions for VAN levels.MethodsEHR data were retrospectively retrieved from Memorial Hermann Hospital System, comprising 14 hospitals in the greater Houston area. All patients who received VAN and had any VAN levels were eligible. Patients receiving hemodialysis and extracorporeal membrane oxygenation were excluded. Demographic data, vital signs, diagnostic codes, concomitant medications, VAN administration, and laboratory data were preprocessed as longitudinal data. VAN infusion, VAN level measurement, or each hospital day were the time steps for the models. The dataset was splited 70:15:15 for training, validation, and test sets. Our PK-RNN-V model predicted individual patient volume distribution (v) and VAN elimination (k) at each time step using an irregular timesteps GRU model. To compare, Bayesian models were developed from publicly available models, and tuned to feedback the first VAN level to update the v and k. (VTDM)ResultsA total of 12,258 patients with 195,140 encounters were identified from Aug, 2019 and March, 2020. After exclusion of 6,775 patients, 5,483 patients with 8,689 encounters were included. Table 1 summarized the characteristics of patients included in our study. 55,336 doses of VAN were administered with a median dosage of 1.0 gm. VAN levels were measured 18,588 times at various timings. The median VAN level was 14.7 mcg/mL Table 2 described the performance of our models and VTDM models. Our model exhibited better performance compared to VTDM model (RMSE: 5.64 vs. 6.57, respectively). Figure 1 shows example prediction curves of VAN levels from each model. ConclusionPK-RNN-V model is a novel approach to predict patient PK and VAN levels. Our results revealed promising performance of this model. Our model can take a wide range of real-world patient data into the model. Further studies are warranted for external validations and model optimizations. Disclosures All Authors: No reported disclosures

Building and Advancing Coalition Capacity to Promote Health Equity: Insights from the Health Equity Collective's Approach to Addressing Social Determinants of Health.

This article presents the structure and function of the Health Equity Collective in developing a systemic approach to promoting health equity across the Greater Houston area. Grounded in Kania and Kramer's five phases of collective impact for coalition building, The Collective operationalizes its mission through its backbone team, steering committees, and eight workgroups; each has goals that mutually reinforce and advance its vision. To date, Phase I (generating ideas), Phase II (initiating action), and Phase III (organizing for impact) have been completed. Phases IV (implementation) and Phase V (sustainability) are currently underway.

Implementation of an Evidence-Based Intervention with Safety Net Clinics to Improve Mammography Appointment Adherence Among Underserved Women

The Peace of Mind Program is an evidence-based intervention to improve mammography appointment adherence in underserved women. The aim of this study was to assess effectiveness of the intervention and implementation of the intervention in safety net clinics. The intervention was implemented through a non-randomized stepped wedge cluster hybrid study design with 19 Federally Qualified Health Centers and charity care clinics within the Greater Houston area. A multivariable generalized estimating equation logistic regression was conducted to examine mammography appointment adherence. A survey assessing Consolidated Framework for Implementation Research constructs was also conducted with clinic staff prior to adoption and eight weeks post implementation. One-sided t-tests were conducted to analyze mean score changes between the surveys. A total of 4402 women (baseline period = 2078; intervention period = 2324) were included in the final regression analysis. Women in the intervention period were more likely to attend or reschedule their mammography appointment (OR = 1.30; p < 0.01) than those in the baseline period receiving usual care. Women who completed the intervention were more likely to attend or reschedule their mammography appointment than those who did not complete the intervention (OR = 1.62; p < 0.01). The mammography appointment no-show rates for those in the baseline period, in the intervention period, and who completed the intervention were, respectively, 22%, 19%, and 15%. A total of 15 clinics prior to adoption and eight clinics completed the survey at 8 weeks post implementation A statistically significant mean score decrease was observed in Inner Setting and in two Inner Setting CFIR constructs, Culture–Effort, and Implementation Climate. While the intervention improved mammography appointment adherence, there are opportunities to further integrate Consolidated Framework for Implementation Research constructs. Trial registration: Clinical trials registration number: NCT02296177.