International faculty search

Master of ScienceDepartment of Computing and Information SciencesDaniel A. AndresenThis application enables users to search the database for International Faculty Members who are currently working at the veterinary department. It also helps the users to know more about the faculty members in detail that is about their specialization, area of expertise, their origin, languages they can speak and teaching experience. The main objective of this project is to develop an online application where the faculty members could be searched based on the three major criteria that is department to which the faculty member belong to or based upon the area of expertise of the faculty member or based upon the country. The application is designed in such a way that a combination of this three drop down list would also give us the results if any such kind exists. The major attraction for this application is that the faculty members are plotted on the world map using the Bing API. A red color dot is placed on the countries to which the faculty members belong, and a mouse over on the dot pops up when the mouse pointer is placed on the red colored dot then it would pop up the names of the faculty who hail from that country. These names are in form of hyper links when clicked on them would direct us to the respective faculties profile. This project is implemented using C#.NET on Microsoft Visual Studio 2008 along with the xml parsing techniques and some XML files which stores the profile of the faculty members. My primary focus is to get familiar with .NET framework and to be able to code in C#.NET. Also learn to use MS Access as database for storing and retrieving the data

Patient Polypharmacy use Following a Multi-Disciplinary Dementia Care Program in a Memory Clinic: A Retrospective Cohort Study

Introduction. Dementia increases the risk of polypharmacy. Timely detection and optimal care can optimize the prognosis for patients with dementia, which may in turn reduce polypharmacy. We aimed to compare the change in polypharmacy use among memory clinic patients living with dementia who participate in a dementia care program, vs those who did not. We hypothesized that patients in the dementia care program would reduce their use of polypharmacy compared to those who were not in the program. Methods. We retrospectively analyzed EMR data from a university memory clinic. The final analytic sample consisted of 381 patients: 107 in the program and 274 matched patients not in the program. We used logistic regression of outcomes (five or more concurrent medications) at follow-up, controlled for the same outcome at baseline to assess the change in polypharmacy, and stratified outcomes by prescription and over-the-counter. Results. The two groups did not differ in the use of five or more total and prescription medications at follow-up controlling for the use of 5 or more of the respective medications at baseline and covariates. Being in the program was associated with a threefold lower odds of using 5 or more over-the-counter medications at follow-up (OR=0.30; p<0.001) after controlling for using 5 or more over-the-counter medications at baseline and covariates. Conclusions. Dementia care might reduce polypharmacy of over-the-counter medications, potentially reducing risky medication-medication interactions. More research is needed to infer causality and understand how to reduce prescription medication polypharmacy

Optimizing Retrieval of Biospecimens Using the Curated Cancer Clinical Outcomes Database (C3OD)

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.To fully support their role in translational and personalized medicine, biorepositories and biobanks must continue to advance the annotation of their biospecimens with robust clinical and laboratory data. Translational research and personalized medicine require well-documented and up-to-date information, but the infrastructure used to support biorepositories and biobanks can easily be out of sync with the host institution. To assist researchers and provide them with accurate pathological, epidemiological, and bio-molecular data, the Biospecimen Repository Core Facility (BRCF) at the University of Kansas Medical Center (KUMC) merges data from medical records, the tumor registry, and pathology reports using the Curated Cancer Clinical Outcomes Database (C3OD). In this report, we describe the utilization of C3OD to optimally retrieve and dispense biospecimen samples using these 3 data sources and demonstrate how C3OD greatly increases the efficiency of obtaining biospecimen samples for the researchers.National Cancer Institute (NCI) Cancer Center Support Grant P30 CA168524Biostatistics and Informatics Shared Resource (BISR)Biospecimen Shared Resource (BSR

A Bayesian comparative effectiveness trial in action: developing a platform for multisite study adaptive randomization

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Background In the last few decades, the number of trials using Bayesian methods has grown rapidly. Publications prior to 1990 included only three clinical trials that used Bayesian methods, but that number quickly jumped to 19 in the 1990s and to 99 from 2000 to 2012. While this literature provides many examples of Bayesian Adaptive Designs (BAD), none of the papers that are available walks the reader through the detailed process of conducting a BAD. This paper fills that gap by describing the BAD process used for one comparative effectiveness trial (Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations) that can be generalized for use by others. A BAD was chosen with efficiency in mind. Response-adaptive randomization allows the potential for substantially smaller sample sizes, and can provide faster conclusions about which treatment or treatments are most effective. An Internet-based electronic data capture tool, which features a randomization module, facilitated data capture across study sites and an in-house computation software program was developed to implement the response-adaptive randomization. Results A process for adapting randomization with minimal interruption to study sites was developed. A new randomization table can be generated quickly and can be seamlessly integrated in the data capture tool with minimal interruption to study sites. Conclusion This manuscript is the first to detail the technical process used to evaluate a multisite comparative effectiveness trial using adaptive randomization. An important opportunity for the application of Bayesian trials is in comparative effectiveness trials. The specific case study presented in this paper can be used as a model for conducting future clinical trials using a combination of statistical software and a web-based application. Trial registration ClinicalTrials.gov Identifier: NCT02260388, registered on 6 October 201

Rurality Impacts Mammography Screening Adherence Among Mid-life Women in the Kansas Region

Objective The gold standard for breast cancer screening and prevention is regular mammography; thus, understanding what impacts adherence to this standard is essential in limiting cancer-associated costs. We assessed the impact of various understudied sociodemographic factors of interest on adherence to the receipt of regular mammograms. Methods A total N c = 14,553 mammography-related claims from N w = 6,336 female Kansas aged between 45 and 54 were utilized from insurance claim databases furnished by multiple providers. Adherence to regular mammography was quantified continuously via a compliance ratio, used to capture the number of eligible years in which at least one mammogram was received, as well as categorically. The relationship between race, ethnicity, rurality, insurance (public/private), screening facility type, and distance to nearest screening facility with both continuous and categorically defined compliance were individually assessed via Kruskal–Wallis one-way ANOVAs, chi-squared tests, multiple linear regression models, and multiple logistic regression, as appropriate. Findings from these individual models were used to inform the construction of a basic, multifaceted prediction model. Results Model results demonstrated that all factors race and ethnicity had at least some bearing on compliance with screening guidelines among mid-life female Kansans. The strongest signal was observed in the rurality variable, which demonstrated a significant relationship with compliance regardless of how it was defined. Conclusion Understudied factors that are associated with regular mammography adherence, such as rurality and distance to nearest facility, may serve as important considerations when developing intervention strategies for ensuring that female patients stick to prescribed screening regimens

180 Building an evaluation platform to capture the impact of Frontiers CTSI activities

OBJECTIVES/GOALS: In 2021, Frontiers CTSI revamped its evaluation infrastructure to be comprehensive, efficient, and transparent in demonstrating outputs and outcomes. We sought to build a platform to standardize measures across program areas, integrate continuous improvement processes into operations, and reduce the data entry burden for investigators. METHODS/STUDY POPULATION: To identify useful metrics, we facilitated each Core’s creation of a logic model, in which they identified all planned activities, expected outputs, and anticipated outcomes for the 5-year cycle and beyond. We identified appropriate metrics based on the logic models and aligned metrics across programs against extant administrative data. We then built a data collection and evaluation platform within REDCap to capture user requests, staff completion of requests, and, ultimately, request outcomes. We built a similar system to track events, attendance, and outcomes. Aligning with other hubs, we also transitioned to a membership model. Membership serves as the backbone of the evaluation platform and allows us to tailor communication, capture demographic information, and reduce the data entry burden for members. RESULTS/ANTICIPATED RESULTS: The Frontiers Evaluation Platform consists of 9 redcap projects with distinct functions and uses throughout the Institute. Point-of-service collection forms include the Consultation Request Event Tracking. Annual Forms include a Study Outcome, Impact, and Member Assessment Survey. Set timepoint collections include K & T application, Mock Study Section, and Pilot grant application submission, review, and outcomes. Flight Tracker is used to collect scientific outcomes and integrated with the platform. Using SQL, the membership module has been integrated into all forms to check and collect membership before service access and provide relevant member data to navigators. All relevant data is then synched into a dashboard for program leadership and management to track outputs and outcomes in real-time. DISCUSSION/SIGNIFICANCE: Since the launch of the evaluation platform in Fall 2022, Frontiers has increased its workflow efficiency and streamlined continuous improvement communication. The platform can serve as a template for other hubs to build efficient processes to create comprehensive and transparent evaluation plans

The Effects of COVID-19 Pandemic Policy on Social Needs Across the State of Kansas and Western Missouri: Paired Survey Response Testing

BackgroundStudying patients’ social needs is critical to the understanding of health conditions and disparities, and to inform strategies for improving health outcomes. Studies have shown that people of color, low-income families, and those with lower educational attainment experience greater hardships related to social needs. The COVID-19 pandemic represents an event that severely impacted people’s social needs. This pandemic was declared by the World Health Organization on March 11, 2020, and contributed to food and housing insecurity, while highlighting weaknesses in the health care system surrounding access to care. To combat these issues, legislators implemented unique policies and procedures to help alleviate worsening social needs throughout the pandemic, which had not previously been exerted to this degree. We believe that improvements related to COVID-19 legislature and policy have positively impacted people’s social needs in Kansas and Missouri, United States. In particular, Wyandotte County is of interest as it suffers greatly from issues related to social needs that many of these COVID-19–related policies aimed to improve. ObjectiveThe research objective of this study was to evaluate the change in social needs before and after the COVID-19 pandemic declaration based on responses to a survey from The University of Kansas Health System (TUKHS). We further aimed to compare the social needs of respondents from Wyandotte County from those of respondents in other counties in the Kansas City metropolitan area. MethodsSocial needs survey data from 2016 to 2022 were collected from a 12-question patient-administered survey distributed by TUKHS during a patient visit. This provided a longitudinal data set with 248,582 observations, which was narrowed down into a paired-response data set for 50,441 individuals who had provided at least one response before and after March 11, 2020. These data were then bucketed by county into Cass (Missouri), Clay (Missouri), Jackson (Missouri), Johnson (Kansas), Leavenworth (Kansas), Platte (Missouri), Wyandotte (Kansas), and Other counties, creating groupings with at least 1000 responses in each category. A pre-post composite score was calculated for each individual by adding their coded responses (yes=1, no=0) across the 12 questions. The Stuart-Maxwell marginal homogeneity test was used to compare the pre and post composite scores across all counties. Additionally, McNemar tests were performed to compare responses before and after March 11, 2020, for each of the 12 questions across all counties. Finally, McNemar tests were performed for questions 1, 7, 8, 9, and 10 for each of the bucketed counties. Significance was assessed at P<.05 for all tests. ResultsThe Stuart-Maxwell test for marginal homogeneity was significant (P<.001), indicating that respondents were overall less likely to identify an unmet social need after the COVID-19 pandemic. McNemar tests for individual questions indicated that after the COVID-19 pandemic, respondents across all counties were less likely to identify unmet social needs related to food availability (odds ratio [OR]=0.4073, P<.001), home utilities (OR=0.4538, P<.001), housing (OR=0.7143, P<.001), safety among cohabitants (OR=0.6148, P<.001), safety in their residential location (OR=0.6172, P<.001), child care (OR=0.7410, P<0.01), health care access (OR=0.3895, P<.001), medication adherence (OR=0.5449, P<.001), health care adherence (OR=0.6378, P<.001), and health care literacy (0.8729, P=.02), and were also less likely to request help with these unmet needs (OR=0.7368, P<.001) compared with prepandemic responses. Responses from individual counties were consistent with the overall results for the most part. Notably, no individual county demonstrated a significant reduction in social needs relating to a lack of companionship. ConclusionsPost-COVID-19 responses showed improvement across almost all social needs–related questions, indicating that the federal policy response possibly had a positive impact on social needs across the populations of Kansas and western Missouri. Some counties were impacted more than others and positive outcomes were not limited to urban counties. The availability of resources, safety net services, access to health care, and educational opportunities could play a role in this change. Future research should focus on improving survey response rates from rural counties to increase their sample size, and to evaluate other explanatory variables such as food pantry access, educational status, employment opportunities, and access to community resources. Government policies should be an area of focused research as they may affect the social needs and health of the individuals considered in this analysis

89 Two Newly Developed Frontiers CTSI Applications to Support Recruitment and Trial Management: The Frontiers Trial Finder Mobile App and a Predictive Accrual Web-based App

OBJECTIVES/GOALS: Frontiers CTSI developed applications to ensure its science teams have technological tools to advance their community engagement and trial management. The Trial Finder app is a mobile application that allows users to navigate available trials. The Accrual app will help study teams monitor their recruitment performances in real time. METHODS/STUDY POPULATION: The Data Science team at the University of Kansas Medical Center (KUMC) had previously developed similar applications for The University of Kansas Cancer Center. Both retrieve information from KUMC’s clinical trial management system and ClinicalTrials.gov. This was replicated to include KUMC Pulmonary Critical Care (PCC) and KUMC Neuromuscular (NM) trials. Frontiers CTSI is working with both groups for piloting and feedback. Recruiting and marketing strategies for investigators to add their trials to both apps will be done through existing communication channels and be highlighted on Frontiers trial resource website. Recruiting and marketing strategies of the Frontiers Trial Finder app to the external community will have a focus on, but not limited to, paid social media advertising. RESULTS/ANTICIPATED RESULTS: The Trial Finder app can help providers search for trials their patient may be eligible for during clinic visits and to engage with the community by allowing anyone to download and browse on their Android/iOS device. Built in REDCap forms are used to capture contact information. The Accrual app is a web-based application that helps study teams monitor their recruitment performances in real time and provide an opportunity to adjust strategies. It uses an in-house algorithm to predict if trials will meet timeline goals. This data is conveniently laid out on a single web page so that science teams can overview all their trials’ recruitment performances simultaneously. The next phase of developing these applications is to market their use within Frontiers CTSI and its community catchment area. DISCUSSION/SIGNIFICANCE: Through collaboration, Frontiers CTSI is developing resources to support community engagement and trial management. New innovative applications like these ensure all the main stakeholders involved with clinical trial execution are always engaged and have access to iterative contemporary technologies that support their research

Accrual Prediction Program: A web-based clinical trials tool for monitoring and predicting accrual for early-phase cancer studies

Background: Monitoring subject recruitment is key to the success of a clinical trial. Accordingly, researchers have developed accrual-monitoring tools to support the design and conduct of trials. At an institutional level, delays in identifying studies with high risk of accrual failure can lead to inefficient and costly trials with little chances of meeting study objectives. Comprehensive accrual monitoring is necessary to the success of the research enterprise. Methods: This article describes the design and implementation of the University of Kansas Cancer Center Accrual Prediction Program, a web-based platform was developed to support comprehensive accrual monitoring and prediction for all active clinical trials. The Accrual Prediction Program provides information on accrual, including the predicted completion date, predicted number of accrued subjects during the pre-specified accrual period, and the probability of achieving accrual targets. It relies on a Bayesian accrual prediction model to combine protocol information with real-time trial enrollment data and disseminates results via web application. Results: First released in 2016, the Accrual Prediction Program summarizes enrollment information for active studies categorized by various trial attributes. The web application supports real-time evidence-based decision making for strategic resource allocation and study management of over 120 ongoing clinical trials at the University of Kansas Cancer Center. Conclusion: The Accrual Prediction Program makes accessing comprehensive accrual information manageable at an institutional level. Cancer centers or even entire institutions can reproduce the Accrual Prediction Program to achieve real-time comprehensive monitoring and prediction of subject accrual to aid investigators and administrators in the design, conduct, and management of clinical trials