902 resultados para Medical data


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Objectives. To investigate procedural gender equity by assessing predisposing, enabling and need predictors of gender differences in annual medical expenditures and utilization among hypertensive individuals in the U.S. Also, to estimate and compare lifetime medical expenditures among hypertensive men and women in the U.S. ^ Data source. 2001-2004 the Medical Expenditure Panel Survey (MEPS);1986-2000 National Health Interview Survey (NHIS) and National Health Interview Survey linked to mortality in the National Death Index through 2002 (2002 NHIS-NDI). ^ Study design. We estimated total medical expenditure using four equations regression model, specific medical expenditures using two equations regression model and utilization using negative binomial regression model. Procedural equity was assessed by applying the Aday et al. theoretical framework. Expenditures were estimated in 2004 dollars. We estimated hypertension-attributable medical expenditure and utilization among men and women. ^ To estimate lifetime expenditures from ages 20 to 85+, we estimated medical expenditures with cross-sectional data and survival with prospective data. The four equations regression model were used to estimate average annual medical expenditures defined as sum of inpatient stay, emergency room visits, outpatient visits, office based visits, and prescription drugs expenditures. Life tables were used to estimate the distribution of life time medical expenditures for hypertensive men and women at different age and factors such as disease incidence, medical technology and health care cost were assumed to be fixed. Both total and hypertension attributable expenditures among men and women were estimated. ^ Data collection. We used the 2001-2004 MEPS household component and medical condition files; the NHIS person and condition files from 1986-1996 and 1997-2000 sample adult files were used; and the 1986-2000 NHIS that were linked to mortality in the 2002 NHIS-NDI. ^ Principal findings. Hypertensive men had significantly less utilization for most measures after controlling predisposing, enabling and need factors than hypertensive women. Similarly, hypertensive men had less prescription drug (-9.3%), office based (-7.2%) and total medical (-4.5%) expenditures than hypertensive women. However, men had more hypertension-attributable medical expenditures and utilization than women. ^ Expected total lifetime expenditure for average life table individuals at age 20, was $188,300 for hypertensive men and $254,910 for hypertensive women. But the lifetime expenditure that could be attributed to hypertension was $88,033 for men and $40,960 for women. ^ Conclusion. Hypertensive women had more utilization and expenditure for most measures than hypertensive men, possibly indicating procedural inequity. However, relatively higher hypertension-attributable health care of men shows more utilization of resources to treat hypertension related diseases among men than women. Similar results were reported in lifetime analyses.^ Key words: gender, medical expenditures, utilization, hypertension-attributable, lifetime expenditure ^

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In the United States, “binge” drinking among college students is an emerging public health concern due to the significant physical and psychological effects on young adults. The focus is on identifying interventions that can help decrease high-risk drinking behavior among this group of drinkers. One such intervention is Motivational interviewing (MI), a client-centered therapy that aims at resolving client ambivalence by developing discrepancy and engaging the client in change talk. Of late, there is a growing interest in determining the active ingredients that influence the alliance between the therapist and the client. This study is a secondary analysis of the data obtained from the Southern Methodist Alcohol Research Trial (SMART) project, a dismantling trial of MI and feedback among heavy drinking college students. The present project examines the relationship between therapist and client language in MI sessions on a sample of “binge” drinking college students. Of the 126 SMART tapes, 30 tapes (‘MI with feedback’ group = 15, ‘MI only’ group = 15) were randomly selected for this study. MISC 2.1, a mutually exclusive and exhaustive coding system, was used to code the audio/videotaped MI sessions. Therapist and client language were analyzed for communication characteristics. Overall, therapists adopted a MI consistent style and clients were found to engage in change talk. Counselor acceptance, empathy, spirit, and complex reflections were all significantly related to client change talk (p-values ranged from 0.001 to 0.047). Additionally, therapist ‘advice without permission’ and MI Inconsistent therapist behaviors were strongly correlated with client sustain talk (p-values ranged from 0.006 to 0.048). Simple linear regression models showed a significant correlation between MI consistent (MICO) therapist language (independent variable) and change talk (dependent variable) and MI inconsistent (MIIN) therapist language (independent variable) and sustain talk (dependent variable). The study has several limitations such as small sample size, self-selection bias, poor inter-rater reliability for the global scales and the lack of a temporal measure of therapist and client language. Future studies might consider a larger sample size to obtain more statistical power. In addition the correlation between therapist language, client language and drinking outcome needs to be explored.^

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Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

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Stomach cancer is the fourth most common cancer in the world, and ranked 16th in the US in 2008. The age-adjusted rates among Hispanics were 2.8 times that of non-Hispanic Whites in 1998-2002. In spite of that, previous research has found that Hispanics with non-cardia adenocarcinoma of the stomach have a slightly better survival than non-Hispanic Whites. However, such previous research did not include a comparison with African-Americans, and it was limited to data released for the years 1973-2000 in the nine original Surveillance, Epidemiology, and End Results Cancer Registries. This finding was interpreted as related to the Hispanic Paradox, a phenomenon that refers to the fact that Hispanics in the USA tend to paradoxically have substantially better health than other ethnic groups in spite of what their aggregate socio-economic indicators would predict. We extended such research to the SEER 17 Registry, 1973-2005, with varying years of diagnosis per registry, and compared the survival of non-cardia adenocarcinoma of the stomach according to ethnicity (Hispanics, non-Hispanic Whites and African-Americans), while controlling for age, gender, marital status, stage of disease and treatment using Cox regression survival analysis. We found that Hispanic ethnicity by itself did not confer an advantage on survival from non-cardia adenocarcinoma of the stomach, but that being born abroad was independently associated with the apparent 'Hispanic Paradox' previously reported, and that such advantage was seen among foreign born persons across all race/ethnic groups.^

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This study was a retrospective design and used secondary data from the National Child Abuse and Neglect Data System (NCANDS), provided by the National Data Archive on Child Abuse and Neglect Family Life Development Center administered by Cornell University. The dataset contained information for the year 2005 on children from birth to 18 years of age. Child abuse and neglect for disabled children, was evaluated in-depth in the present study. Descriptive and statistical analysis was performed using the children with and without disabilities. It was found that children with disabilities have a lower rate of substantiation that likely indicates the interference of reporting due to their handicap. The results of this research demonstrate the important need to teach professionals and laypersons alike on how to recognize and substantiate abuse among disabled children.^

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In recent years, disaster preparedness through assessment of medical and special needs persons (MSNP) has taken a center place in public eye in effect of frequent natural disasters such as hurricanes, storm surge or tsunami due to climate change and increased human activity on our planet. Statistical methods complex survey design and analysis have equally gained significance as a consequence. However, there exist many challenges still, to infer such assessments over the target population for policy level advocacy and implementation. ^ Objective. This study discusses the use of some of the statistical methods for disaster preparedness and medical needs assessment to facilitate local and state governments for its policy level decision making and logistic support to avoid any loss of life and property in future calamities. ^ Methods. In order to obtain precise and unbiased estimates for Medical Special Needs Persons (MSNP) and disaster preparedness for evacuation in Rio Grande Valley (RGV) of Texas, a stratified and cluster-randomized multi-stage sampling design was implemented. US School of Public Health, Brownsville surveyed 3088 households in three counties namely Cameron, Hidalgo, and Willacy. Multiple statistical methods were implemented and estimates were obtained taking into count probability of selection and clustering effects. Statistical methods for data analysis discussed were Multivariate Linear Regression (MLR), Survey Linear Regression (Svy-Reg), Generalized Estimation Equation (GEE) and Multilevel Mixed Models (MLM) all with and without sampling weights. ^ Results. Estimated population for RGV was 1,146,796. There were 51.5% female, 90% Hispanic, 73% married, 56% unemployed and 37% with their personal transport. 40% people attained education up to elementary school, another 42% reaching high school and only 18% went to college. Median household income is less than $15,000/year. MSNP estimated to be 44,196 (3.98%) [95% CI: 39,029; 51,123]. All statistical models are in concordance with MSNP estimates ranging from 44,000 to 48,000. MSNP estimates for statistical methods are: MLR (47,707; 95% CI: 42,462; 52,999), MLR with weights (45,882; 95% CI: 39,792; 51,972), Bootstrap Regression (47,730; 95% CI: 41,629; 53,785), GEE (47,649; 95% CI: 41,629; 53,670), GEE with weights (45,076; 95% CI: 39,029; 51,123), Svy-Reg (44,196; 95% CI: 40,004; 48,390) and MLM (46,513; 95% CI: 39,869; 53,157). ^ Conclusion. RGV is a flood zone, most susceptible to hurricanes and other natural disasters. People in the region are mostly Hispanic, under-educated with least income levels in the U.S. In case of any disaster people in large are incapacitated with only 37% have their personal transport to take care of MSNP. Local and state government’s intervention in terms of planning, preparation and support for evacuation is necessary in any such disaster to avoid loss of precious human life. ^ Key words: Complex Surveys, statistical methods, multilevel models, cluster randomized, sampling weights, raking, survey regression, generalized estimation equations (GEE), random effects, Intracluster correlation coefficient (ICC).^

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Objective. To determine the association between nativity status and mammography utilization among women in the U.S. and assess whether demographic variables, socioeconomic factors healthcare access, breast cancer risk factors and acculturation variables were predictors in the relationship between nativity status and mammography in the past two years. ^ Methods. The NHIS collects demographic and health information using face-to-face interviews among a representative sample of the U.S. population and a cancer control module assessing screening behaviors is included every five years. Descriptive statistics were used to report demographic characteristics of women aged 40 and older who have received a mammogram in the last 2 years from 2000 and 2005. We used chi square analyses to determine statistically significant differences by mammography screening for each covariate. Logistic regression was used to determine whether demographic characteristics, socioeconomic characteristics, healthcare access, breast cancer risk factors and acculturation variables among foreign-born Hispanics affected the relationship between nativity status and mammography use in the past 2 years. ^ Results. In 2000, the crude model between nativity and mammography was significant but results were not significant after adjusting for health insurance, access and reported health status. Significant results were also reported for years in U.S. and mammography among foreign-born born women. In 2005, the crude model was also significant but results were not significant after adjusting for demographic factors. Furthermore, there was a significant finding between citizenship and mammography in the past 2 years. ^ Conclusions. Our study contributes to the literature as one of the first national-based studies assessing mammography in the past two years based on nativity status. Based on our findings, health insurance and access to care is an important predictor in mammography utilization among foreign-born women. For those with health care access, physician recommendation should further be assessed to determine whether women are made aware of mammography as a means to detect breast cancer at an early stage and further reduce the risk of mortality from the breast cancer.^

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Introduction. Food frequency questionnaires (FFQ) are used study the association between dietary intake and disease. An instructional video may potentially offer a low cost, practical method of dietary assessment training for participants thereby reducing recall bias in FFQs. There is little evidence in the literature of the effect of using instructional videos on FFQ-based intake. Objective. This analysis compared the reported energy and macronutrient intake of two groups that were randomized either to watch an instructional video before completing an FFQ or to view the same instructional video after completing the same FFQ. Methods. In the parent study, a diverse group of students, faculty and staff from Houston Community College were randomized to two groups, stratified by ethnicity, and completed an FFQ. The "video before" group watched an instructional video about completing the FFQ prior to answering the FFQ. The "video after" group watched the instructional video after completing the FFQ. The two groups were compared on mean daily energy (Kcal/day), fat (g/day), protein (g/day), carbohydrate (g/day) and fiber (g/day) intakes using descriptive statistics and one-way ANOVA. Demographic, height, and weight information was collected. Dietary intakes were adjusted for total energy intake before the comparative analysis. BMI and age were ruled out as potential confounders. Results. There were no significant differences between the two groups in mean daily dietary intakes of energy, total fat, protein, carbohydrates and fiber. However, a pattern of higher energy intake and lower fiber intake was reported in the group that viewed the instructional video before completing the FFQ compared to those who viewed the video after. Discussion. Analysis of the difference between reported intake of energy and macronutrients showed an overall pattern, albeit not statistically significant, of higher intake in the video before versus the video after group. Application of instructional videos for dietary assessment may require further research to address the validity of reported dietary intakes in those who are randomized to watch an instructional video before reporting diet compared to a control groups that does not view a video.^

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The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^

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Background. Nosocomial infections are a source of concern for many hospitals in the United States and worldwide. These infections are associated with increased morbidity, mortality and hospital costs. Nosocomial infections occur in ICUs at a rate which is five times greater than those in general wards. Understanding the reasons for the higher rates can ultimately help reduce these infections. The literature has been weak in documenting a direct relationship between nosocomial infections and non-traditional risk factors, such as unit staffing or patient acuity.^ Objective. To examine the relationship, if any, between nosocomial infections and non-traditional risk factors. The potential non-traditional risk factors we studied were the patient acuity (which comprised of the mortality and illness rating of the patient), patient days for patients hospitalized in the ICU, and the patient to nurse ratio.^ Method. We conducted a secondary data analysis on patients hospitalized in the Medical Intensive Care Unit (MICU) of the Memorial Hermann- Texas Medical Center in Houston during the months of March 2008- May 2009. The average monthly values for the patient acuity (mortality and illness Diagnostic Related Group (DRG) scores), patient days for patients hospitalized in the ICU and average patient to nurse ratio were calculated during this time period. Active surveillance of Bloodstream Infections (BSIs), Urinary Tract Infections (UTIs) and Ventilator Associated Pneumonias (VAPs) was performed by Infection Control practitioners, who visited the MICU and performed a personal infection record for each patient. Spearman's rank correlation was performed to determine the relationship between these nosocomial infections and the non-traditional risk factors.^ Results. We found weak negative correlations between BSIs and two measures (illness and mortality DRG). We also found a weak negative correlation between UTI and unit staffing (patient to nurse ratio). The strongest positive correlation was found between illness DRG and mortality DRG, validating our methodology.^ Conclusion. From this analysis, we were able to infer that non-traditional risk factors do not appear to play a significant role in transmission of infection in the units we evaluated.^

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This retrospective cohort study analyzed data from more than 2200 OSHA-mandated respirator medical evaluations performed between 2004 and 2008, with information initially obtained using an online questionnaire, to determine what factors influence medical clearance and the ability to safely wear respiratory protection in a large petrochemical company.^ The employees were mostly white males with a high school education, ranging in age from 25 to 60 years of age, who had been employed with the company an average of eight years. Their work was typically performed outdoors in a rural or offshore setting. Respirators were typically required for emergency response – escape or rescue only – and/or limited to less than four hours per month.^ Approximately 90% of the population achieved medical clearance by utilizing the online questionnaire. Of the remaining 10%, 66% were cleared after additional "hands-on" medical examination exam; 28% of the individuals' jobs were modified by their supervisor in order to not use a respirator, and 6% of the individuals (n=13) were excluded from wearing a respirator on the basis of the medical examination. The primary causes for exclusion from respirator use were cardiovascular (37.5%) and respiratory (31.3%) issues, followed by psychological (18.8%) and musculoskeletal (12.5%) concerns. Ultimately, over 99% of workers evaluated under this system were found capable of using respiratory protection safely. This questionnaire has proven to be an excellent health screening tool capable of initiating early detection and further investigation of potentially serious medical conditions within a large and diverse population in multiple locations. ^

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The Federal Food and Drug Administration (FDA) and the Centers for Medicare and Medicaid (CMS) play key roles in making Class III, medical devices available to the public, and they are required by law to meet statutory deadlines for applications under review. Historically, both agencies have failed to meet their respective statutory requirements. Since these failures affect patient access and may adversely impact public health, Congress has enacted several “modernization” laws. However, the effectiveness of these modernization laws has not been adequately studied or established for Class III medical devices. ^ The aim of this research study was, therefore, to analyze how these modernization laws may have affected public access to medical devices. Two questions were addressed: (1) How have the FDA modernization laws affected the time to approval for medical device premarket approval applications (PMAs)? (2) How has the CMS modernization law affected the time to approval for national coverage decisions (NCDs)? The data for this research study were collected from publicly available databases for the period January 1, 1995, through December 31, 2008. These dates were selected to ensure that a sufficient period of time was captured to measure pre- and post-modernization effects on time to approval. All records containing original PMAs were obtained from the FDA database, and all records containing NCDs were obtained from the CMS database. Source documents, including FDA premarket approval letters and CMS national coverage decision memoranda, were reviewed to obtain additional data not found in the search results. Analyses were conducted to determine the effects of the pre- and post-modernization laws on time to approval. Secondary analyses of FDA subcategories were conducted to uncover any causal factors that might explain differences in time to approval and to compare with the primary trends. The primary analysis showed that the FDA modernization laws of 1997 and 2002 initially reduced PMA time to approval; after the 2002 modernization law, the time to approval began increasing and continued to increase through December 2008. The non-combined, subcategory approval trends were similar to the primary analysis trends. The combined, subcategory analysis showed no clear trends with the exception of non-implantable devices, for which time to approval trended down after 1997. The CMS modernization law of 2003 reduced NCD time to approval, a trend that continued through December 2008. This study also showed that approximately 86% of PMA devices do not receive NCDs. ^ As a result of this research study, recommendations are offered to help resolve statutory non-compliance and access issues, as follows: (1) Authorities should examine underlying causal factors for the observed trends; (2) Process improvements should be made to better coordinate FDA and CMS activities to include sharing data, reducing duplication, and establishing clear criteria for “safe and effective” and “reasonable and necessary”; (3) A common identifier should be established to allow tracking and trending of applications between FDA and CMS databases; (4) Statutory requirements may need to be revised; and (5) An investigation should be undertaken to determine why NCDs are not issued for the majority of PMAs. Any process improvements should be made without creating additional safety risks and adversely impacting public health. Finally, additional studies are needed to fully characterize and better understand the trends identified in this research study.^

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Accurate ascertainment of risk factors and disease status is vital in public health research for proper classification of research subjects. The two most common ways of obtaining this data is by self-report and review of medical records (MRs). South Texas Women’s Health Project was a case-control study looking at interrelationships between hormones, diet, and body size and breast cancer among Hispanic women 30-79 years of age. History of breast cancer, diabetes mellitus (DM) and use of DM medications was ascertained from a personal interview. At the time of interview, the subject identified her major health care providers and signed the medical records release form, which was sent to the designated providers. The MRs were reviewed to confirm information obtained from the interview.^ Aim of this study was to determine the sensitivity and specificity between MRs and personal interview in diagnosis of breast cancer, DM and DM treatment. We also wanted to assess how successful our low-cost approach was in obtaining pertinent MRs and what factors influenced the quality of MR or interview data. Study sample was 721 women with both self-report and MR data available by June 2007. Overall response rate for MR requests was 74.5%. MRs were 80.9% sensitive and 100% specific in confirming breast cancer status. Prevalence of DM was 22.7% from the interviews and 16% from MRs. MRs did not provide definite information about DM status of 53.6% subjects. Sensitivity and specificity of MRs for DM status was 88.9% and 90.4% respectively. Disagreement on DM status from the two sources was seen in 15.9% subjects. This discordance was more common among older subjects, those who were married and were predominantly Spanish speaking. Income and level of education did not have a statistically significantly association with this disagreement.^ Both self-report and MRs underestimate the prevalence of DM. Relying solely on MRs leads to greater misclassification than relying on self-report data. MRs have good to excellent specificity and thus serve as a good tool to confirm information obtained from self-report. Self-report and MRs should be used in a complementary manner for accurate assessment of DM and breast cancer status.^

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Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

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Introduction. Despite the ban of lead-containing gasoline and paint, childhood lead poisoning remains a public health issue. Furthermore, a Medicaid-eligible child is 8 times more likely to have an elevated blood lead level (EBLL) than a non-Medicaid child, which is the primary reason for the early detection lead screening mandate for ages 12 and 24 months among the Medicaid population. Based on field observations, there was evidence that suggested a screening compliance issue. Objective. The purpose of this study was to analyze blood lead screening compliance in previously lead poisoned Medicaid children and test for an association between timely lead screening and timely childhood immunizations. The mean months between follow-up tests were also examined for a significant difference between the non-compliant and compliant lead screened children. Methods. Access to the surveillance data of all childhood lead poisoned cases in Bexar County was granted by the San Antonio Metropolitan Health District. A database was constructed and analyzed using descriptive statistics, logistic regression methods and non-parametric tests. Lead screening at 12 months of age was analyzed separately from lead screening at 24 months. The small portion of the population who were also related were included in one analysis and removed from a second analysis to check for significance. Gender, ethnicity, age of home, and having a sibling with an EBLL were ruled out as confounders for the association tests but ethnicity and age of home were adjusted in the nonparametric tests. Results. There was a strong significant association between lead screening compliance at 12 months and childhood immunization compliance, with or without including related children (p<0.00). However, there was no significant association between the two variables at the age of 24 months. Furthermore, there was no significant difference between the median of the mean months of follow-up blood tests among the non-compliant and compliant lead screened population for at the 12 month screening group but there was a significant difference at the 24 month screening group (p<0.01). Discussion. Descriptive statistics showed that 61% and 56% of the previously lead poisoned Medicaid population did not receive their 12 and 24 month mandated lead screening on time, respectively. This suggests that their elevated blood lead level may have been diagnosed earlier in their childhood. Furthermore, a child who is compliant with their lead screening at 12 months of age is 2.36 times more likely to also receive their childhood immunizations on time compared to a child who was not compliant with their 12 month screening. Even though there was no statistical significant association found for the 24 month group, the public health significance of a screening compliance issue is no less important. The Texas Medicaid program needs to enforce lead screening compliance because it is evident that there has been no monitoring system in place. Further recommendations include a need for an increased focus on parental education and the importance of taking their children for wellness exams on time.^