Community Medicine

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/21651

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    A multi-center retrospective investigation of diagnostic, referral, and early management pathways for pediatric patients with Autism Spectrum Disorder and Developmental Coordination Disorder.
    (2018-03-14) Miller, Haylie; Mauk, Joyce; Bowman, W. Paul; Bailey, Laurie; Hamby, Tyler; Kata, Karolina
    Background: Autism Spectrum Disorder (ASD) and Developmental Coordination Disorder (DCD) can co-occur, but diagnostic procedures vary widely. Some overlap exists in behavioral, motor, and social problems in ASD and DCD, which adds ambiguity to the diagnostic process. Provider- and patient-centered factors contribute to the differences in pathways to care; understanding these factors may lead to more robust guidelines for assessment of patients with suspected ASD, DCD, and ASD+DCD. Objective: Measure prevalence and describe the diagnostic pathway of ASD+DCD at 3 healthcare sites, and describe the diagnostic pathways reported for ASD, DCD, and ASD+DCD. Identify provider- and patient- centered variables related to diagnostic, early management, and referral patterns. Hypothesis: A combination of patient- and provider-centered variables will contribute to differences in diagnostic and management outcomes for patients with ASD, DCD, and ASD+DCD. Methods: This retrospective study evaluated patients diagnosed with ASD, DCD, and ASD+DCD in the Cook Children’s Medical Center (CCMC) network, UNT Health Science Center (UNTHSC), and the Child Study Center (CSC). Charts included patients ages 0-21 years at the time of first entry, with documented diagnosis of ASD, DCD, or ASD+DCD. We collected primary and co-occurring diagnoses, medications, developmental milestones, test scores, social history, time between first concern visit and diagnosis, and services consulted. Results: At CCMC, the number of patients with ASD was 5520, with DCD was 424, and ASD+DCD was 59. At CSC the number of patients with ASD is 1559, with DCD is 46, and ASD+DCD, 232. UNTHSC data collection will take place in March 2018. We used a stratified random sample of 50 subjects from each diagnostic group (ASD, DCD, ASD+DCD) for initial analyses. Analyses are ongoing, and include correlations and analyses of variance to identify relationships and group differences among patient- and provider-centered variables. Conclusion: The number of patients with ASD, DCD, and ASD+DCD served by CCMC and CSC is significantly lower than anticipated given prevalence estimates. ASD+DCD prevalence was higher at CSC than at CCMC. Assessment and diagnostic procedures at CSC are more extensive, and include developmental motor testing. Higher surveillance at this site may explain the higher observed prevalence of ASD+DCD. Further planned analyses will illuminate patient- and provider-centered differences among the 3 groups.
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    Microsimulation to determine likely scope of pharmacogenomic testing in a Diabetic Population
    (2018-03-14) Cross, Deanna; Bowman, Paul; Fulda, Kimberly; Kulkarni, Pruthali
    Purpose: Despite metformin’s standing as the primary treatment drug for Type 2 Diabetes Mellitus, over one-third of patients on metformin monotherapy fail to achieve glycemic control, and 25% have adverse reactions. Furthermore, within 3 years, 21% start on a second drug, usually a sulfonylurea. While combination therapy is effective, 27.8% of those on sulfonylurea therapy present with hypoglycemic episodes, of which 3.6% are severe, resulting in hospitalization and/or death. An individual’s genetic makeup plays a role in their body’s ability to utilize drugs, and can affect their chances of developing potential side effects to pharmacotherapy. Pharmacogenomics utilizes a patient’s genome to establish an appropriate therapy or dosing regimen to ensure that treatments work effectively with minimal side effects. This project aims to determine whether utilizing pharmacogenomic variants to tailor drug regimens in individuals with T2DM would have clinical efficacy. Materials/Methods: We created a model diabetic population using a microsimulation technique based on Tarrant County demographics and allelic variant population frequencies for metformin and sulfonylurea pharmacogenes to determine the frequency of actionable genotypes (variants that play a role in drug pharmacodynamics). Furthermore, we determined whether actionable genotypes varied based on racial/ethnic groups. Results: Between 20 to 60% of the population had 1 or more actionable genotypes for sulfonylurea drugs, depending on race/ethnicity, with Caucasians presenting with 1 or more actionable genotypes approximately 68% of the time. Caucasians also present with actionable genotypes that affect metformin pharmacodynamics 3% of the time, followed by African Americans presenting with actionable genotypes for metformin 2% of the time. Furthermore, almost 50% of the population has 1 or more actionable genotype for either metformin or sulfonylurea pharmacodynamics. Conclusions: Oral hypoglycemic drug therapy efficacy and potential failure may be influenced by the genetic prevalence of allelic polymorphisms, and the degree of influence varies by racial/ethnic group. The data derived from these simulations will be used in an adverse drug reaction model to enable us to determine if pharmacogenomics studies will better allow for the control of HbA1c levels in T2DM, thereby decreasing the incidence of diabetic complications and adverse drug reactions.
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    North Texas Smartphone Contamination Initiative: Proposal to investigate the restroom cellphone use in medical students and healthcare professionals
    (2018-03-14) Reynolds, Conner; Underwood, Jacob; Williams, Trevor; Nikocevic, Eldin; Lindsley, Joshua
    North Texas Cellphone Contamination Initiative: Proposal to investigate the restroom cellphone use in medical students and healthcare professionals Authors: Joshua Lindsley, Jacob Underwood, Trevor Williams, Conner Reynolds, Eldin Nikocevic Situation: Preventable medical errors are the third leading cause of death in the United States annually, accounting for 251,000 lives annually. Healthcare-acquired infections (HAIs) account for nearly 40% of this population, costing the healthcare system $28.4-33.8 billion each year. Background: The rising prevalence of smartphone use has prompted their investigation as potential vectors for infectious transmission in healthcare. Although sophisticated reference applications may be invaluable to healthcare professionals, these smartphones are easily contaminated and rarely disinfected. One potential source for significant smartphone contamination is use in restrooms. Little empirical research investigated this proposition. However, according to several crowd-sourced population surveys, the pervasiveness of restroom smartphone usage ranges from 61-75%. Assessment & Proposed Solution: Given the diverse microbial biogeography found in public restrooms, smartphone usage is an alarming health concern. Through targeted surveillance of medical students and healthcare workers, the proposed study will be the first investigate the linkage between restroom smartphone usage and subsequent contamination. We will also follow previously designed protocols demonstrating that bacteria can be aerosolized and contaminate nearby objects, and apply this principle to mobile phones contamination. The results of this study have potential to impact health policy aimed at reducing the spread of HAIs, significantly improving quality and safety for patients nationwide.
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    Estimated community prevalence of Autism Spectrum Disorder with and without co-occurring Developmental Coordination Disorder significantly exceeds observed prevalence at two Tarrant County sites offering primary and secondary care.
    (2018-03-14) Miller, Haylie; Mauk, Joyce; Bowman, W. Paul; Bailey, Laurie; Hamby, Tyler; Kata, Karolina
    Background: Autism Spectrum Disorder (ASD) can co-occur with Developmental Coordination Disorder (DCD), and ASD+DCD requires integrated care. Cook Children’s Medical Center (CCMC) and the Child Study Center (CSC) are the most comprehensive options for care in Tarrant County, offering integrated developmental pediatrics and secondary ASD services. Lack of integration between primary and secondary services can lead to discontinuity in care or incomplete diagnosis, or prevent families from entering the pathway to ASD-related services altogether. Objective: Determine whether CCMC and CSC serve a patient population proportional to the estimated prevalence of ASD in Tarrant County. If not, it will highlight a need for more primary care sites with integrated autism services. Hypothesis: The number of patients with ASD, DCD, and ASD+DCD served by CCMC and CSC will be significantly lower than estimated prevalence in Tarrant County. Method: This retrospective study evaluated patients who were 0-21 years old at the time of first chart entry, with a diagnosis of ASD, DCD, or ASD+DCD. We compared the observed patient population of ASD, DCD, and ASD+DCD at CCMC and CSC to the expected Tarrant County population. Results: At current prevalence estimates, the expected population of children in Tarrant County with ASD is 8,078, and with DCD is 37,695. At CCMC, the number of patients since 1994 with ASD was 5,520, with DCD was 424, and with ASD+DCD was 59. At CSC, the number of patients since 1994 with ASD was 1,559, with DCD was 46, and with ASD+DCD was 232. The CCMC EMR contained 32 different diagnostic codes for ASD (e.g., Asperger’s Syndrome, active infantile autism, autistic disorder of childhood onset) and 4 codes for DCD (e.g., dyspraxia, developmental coordination disorder). Conclusions: The observed number of patients served was disproportionate to the estimated population. Other public agencies serve a small, non-overlapping population with ASD, unlikely to make up the difference between the estimated and observed population. There is a clear gap in the number of patients with ASD, DCD, and ASD+DCD served at integrated care sites. Many children may be (1) undiagnosed, (2) diagnosed but not seeking care in an integrated care site, or (3) inaccurately diagnosed. Minority groups are at high risk for misdiagnosis; since 41.6% of the Tarrant County population is Black or Hispanic, health disparities may limit their access to of comprehensive evaluation and care.