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For several decades, social disparities in access to health care remain a major debate in the U.S. health care system. Despite growing attention to health inequalities, different social classes, especially, minority or ethnic groups, and those without health insurance coverage continue to face challenges to health care. To date, due to the complexities of Socioeconomic Status (SES), it is unclear how SES impacts health and income inequality. The purpose of this dissertation was to examine the association of SES and median household income groups with hospitalization outcomes in the United States from 2008 to 2010. To examine the generalizability of this phenomenon, a retrospective study was used to analyze the pattern of care for hospitalized patients between the ages of 18 and 89, using the National Inpatient Sample (NIS) data of the Healthcare Cost and Utilization Project (HCUP). The study sample consisted of 500,000 admission records and stratified and regression analysis were computed to determine the differences by age, sex, race or ethnicity, income, location, diagnoses, procedures, length of stay, payer, and costs affecting each of the defined income categories. Total hospital costs were examined within the categorical income groups by residential zip code and top 10 diagnoses and procedures showed that high medical costs is an issue across SES groups. Descriptive and inferential statistical analyses were performed. Mean, median, standard deviation, and range were used to calculate continuous variables while frequency counts and chi-square tests of association were conducted to evaluate differences in proportion for categorical variables. Linear regression modeling and multivariable modeling techniques were undertaken to test the hypotheses. Measurement and structural models were tested through structural equation modeling statistical techniques using SPSS version 22.0. When compared the SES differences among the four categorical income groups, the results show that people at the lower quintile were more likely to face higher hospitalization due to their income. Each year, many programs are designed to reduce hospital admissions, but regardless of these efforts the rates of hospitalization continue to increase in U.S population. This study recommended scientific approach in understanding of the role SES and income as they impact health disparities, which will potentially help health providers, researchers, policy makers, and public health planners to design individualized and community-wide programs and policies related to income inequality and hospitalization for high risk populations.

Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

▼ A SNOMED CT-encoded problem list is required to satisfy the Certification Criteria for Stage 2 “Meaningful Use”. ICD-10-CM has replaced ICD-9-CM as the reimbursement code set in 2015. Having a cross-map from SNOMED CT to ICD-10-CM would promote the use of SNOMED CT as the primary problem list terminology, while easing the transition to ICD-10-CM. There is no established principle and methodology on systematically and semantically linking SNOMED CT to ICD-10-CM. This research project describes the development of mapping principle, mapping guidelines, mapping tools and mapping methodology for a rule-based crosswalk to support semi-automatic generation of ICD-10-CM codes from SNOMED CT-encoded data. A series of mapping guidelines were developed based on the clinical use case, SNOMED CT modeling convention, and ICD-10-CM classification guidelines. One of the important methodology in developing the map set is using triangulation in generating legacy maps. Using the SNOMED CT to ICD-9-CM map and General Equivalence Mappings sequentially, Indirect Map was generated from SNOMED CT to ICD-10-CM for 96.2% of the SNOMED CT concepts within the scope of the study. Another innovation in this crossmapping research is implementation of a principle to handle age specification. The age rule was one type of rule to handle cases in which one SNOMED CT concept can map to different ICD-10-CM codes depending on the age of the patient. The age rule quality assurance (QA) was a mechanism to capture the age specification that can be easily missed by manual mapping. The results showed that the mapping guidelines ensured the mapping consistency, which potentially would reduce the mapping discrepancy between the two independent parallel mapping efforts. It also made it possible that the map set can be used in a meaningful way when data is exchanged. On this triangulation method in generating legacy map, an Indirect Map generated from SNOMED CT to ICD-10-CM covered a very high percentage of SNOMED CT concepts. Overall, this Indirect Map had a moderate degree of agreement with the Direct SNOMED CT to ICD-10-CM map. However, the indirect synonymy maps have much higher precision and can be used for quality assurance (QA) of the three maps. The age rule QA identified 342 out of 7,277 concepts which potentially required age rules, among these 50.3% turned out to be true positives. Without this QA, a large proportion of age rules in the published Map would have been missed. The outcomes of this research project include a set of mapping principle, mapping guidelines, mapping tools and mapping methodology for a rule-based crosswalk from SNOMED CT to ICD-10-CM. All these could be used as a prototype in other cross standard mappings. For example, in the US, ICD-10-PCS officially replaced ICD-9-CM from October 2015 onwards. A project was formulating earlier this year (2015) for the purpose of creating the map from SNOMED CT procedure to ICD-10-PCS. It is a pleasant finding that tooling, principles and guidelines established in… Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

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The purpose of this study is to determine the hoop stress around dental implant in a circumferential and vertical pattern and to compare stress values to different cantilever length on a cross arch implant supported framework. Material and Methods: A milled cross-arch metal framework supported by 4 implants imbedded in acrylic in addition to one separated implant in the middle. Five T-strain gauge rosette distributed on five dental implants recorded data as they were loaded by 50 and 100 N forces using MTS 810 loading machine. The loading sites were anterior implant, posterior implant, 0.5 Anterior Posterior ,(AP spread) ratio cantilever, 1.0, 1.5 and 2.0 ratio cantilever. Each one of those 7 sites were loaded 10 times for each of the 50 and 100 N generating 360 different reading for each of those groups. Three-way ANOVA was conducted (twice, one for vertical and one for hoop strain) for analysis of strain with factors of: Magnitude of force, extension of cantilever and position of the implants followed by Post hoc Tukey comparison between the groups. Results: The anterior implant is under tension in vertical direction when forces are applied to the cantilever on the contralateral side. The most posterior implant is under less tension in the vertical direction but shows as much strains in the circumferential direction. Post hoc analysis shows cantilever over 1.0 ratio causes same high amount of stress to the system. Conclusion: A ratio up of 0.5 AP spread for the cantilever is statistically acceptable. However, A ratio up to 1.0 AP spread for the cantilever exerts no more tension to the system than the load on the implants.

Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Related Professions.

▼ BACKGROUND: There is a conflict evidence about the association of using ‎bilateral internal mammary ‎artery (BIMA) grafting in diabetics undergoing coronary ‎artery bypass grafting (CABG) ‎surgery and increased risk of contracting surgical site ‎infection. The direct impact of the ‎diabetics glycemic control status and using the ‎optimal grafting method on surgical ‎site infection is still not conclusive in literature. ‎The aim of the study is to evaluate the ‎impact of Bilateral internal mammary artery ‎grafting in diabetic patients, the diagnosis ‎of diabetes mellitus, and its glycemic control ‎status on different kinds of nosocomial ‎infections. The assumption was made that those ‎exposures associated with higher risk of ‎surgical site infection, urinary tract infection, ‎blood stream infection and pneumonia. METHOD: A retrospective cohort is conducted ‎by utilizing Nationwide Inpatient ‎Sample (NIS) data from the Agency of Healthcare ‎Research and Quality (AHRQ). All ‎patients who were admitted to coronary artery ‎bypass grafting (CABG) surgery were ‎retrieved from 2007 to 2012 and grouped based on ‎the exposures of the study. RESULTS: The total sample of the study was 286,487 ‎patients underwent CABG ‎surgery. There were 122,642 (42.81%) patients diagnosed ‎with Diabetes Mellitus, of ‎whom 18,065 (14.73%) had uncontrolled hyperglycemia, ‎‎3,700 (3.01%) received ‎Bilateral (IMA) and 103,577 (84.45%) unilateral or single (IMA) ‎grafting method. The ‎study population was predominantly white (79.78%) and male ‎‎(72.08%) with an average ‎age of 66 (SD ±10.89) old. About 215,740 (75.31%) of ‎patients had developed ‎nosocomial pneumonia, 16,667 (5.82%) urinary tract infections ‎‎(UTIs), 9,442 (3.3%) ‎sepsis or bloodstream infection (BSIs), and 5,302 (1.85%) surgical ‎site infection (SSIs ‎in overall sample population.‎Among diabetic patients, there was no significant difference in comparing ‎BIMA ‎versus SIMA for surgical site infection (SSI) (p-value=0.2491) and blood ‎stream ‎infections (BSI) (p-value=0.6630). The results have also indicated that UTIs ‎‎(4.2% vs. ‎‎5.5%; p-value=0.0005) was significantly lower with BIMA grafting method. ‎However, ‎results did not meet the hypothesis assumption regarding Pneumonias rate ‎‎(76.8% vs. ‎‎70.5%; p-value < 0.0001) and was significantly higher with BIMA compared ‎to SIMA ‎grafting method. Multivariable analysis showed inconsistent result and ‎confirmed that ‎BIMA grafting predicts higher odd of BSI by 44.6% in diabetic, ‎compared to SIMA ‎grafting (OR: 1.446; 95% CI: 1.22-1.71; p<.0001). ‎The cross unadjusted baseline results for all nosocomial infections ‎were ‎significantly lower in diabetic patients compared to non-diabetic; Except for UTI ‎was ‎significantly higher by the presence of diabetes in BIMA grafting population ‎‎(n=10,223) ‎‎(4.2% vs. 3.39%; p-value= 0.0393). Multivariable analysis has confirmed ‎that Diabetes ‎Miletus increase the risk of UTI by 21.7% in BIMA population (OR: ‎‎1.217; 95% CI: 1.21-‎‎1.22; p<.0001). ‎The bivariate analysis results indicated… Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

▼ BACKGROUND: Autologous bone marrow concentrate (BMAC) plus amniotic tissue products contain concentrated growth factors, CD34+ stem cells, and mesenchymal stem cells (MSCs) which yield angiogenic, trophic, and anti-inflammatory effects on tissues and may be useful in the regeneration of connective tissue. AIM: The author presents a study of 21 patients (20 ACL reconstruction, 1 ultrasound-guided injection) who received bio-enhanced STEMNEXA (BMAC plus amniotic AlphaGEMS) in conjunction with traditional treatment. METHOD: Patient data on ACL reconstruction and AT tendonitis were collected from Riordan-McKenna Institute. Post-treatment MRI images and impressions were obtained from Dr. Paul Marsh (Monticello Diagnostic Imaging). Non-surgical method (AT BMAC injection at the clinic) - In an office setting, bone marrow was aspirated from the metaphyseal area of the medial tibia and concentrated with a closed system. The resulting BMAC was injected intralesionally into the affected tendinotic mid-substance area under ultrasound guidance. Surgical method (ACL reconstruction) – In an operation room setting, bone marrow was aspirated from the iliac crest and was then placed in the Magellan centrifuge to spin down the cells to help harvest the stem cell and plasma platelet rich areas of the blood. The resulting BMAC was then injected at the time of surgery into the base of the graft to aid in healing. Searches via PubMed and Google Scholar were performed to identify both scientific investigations and review articles to ensure inclusion of pertinent data. RESULTS: The study included a sample size of 20 ACL reconstruction surgical patients between the ages of 19-57. Post-surgery MRI results with Relative Strength Intensity (RSI) measurements of ACL reconstruction graft treated with BMAC were compared against RSI of intact PCL. Between 16 and 24 weeks, the researcher noticed not only a decrease in the RSI, but also a level of saturation (plateau) indicating incorporation of the graft. The RSI for ACL and PCL closely converged between 16 and 24 weeks, clearly indicating homogeneity between the healing ACL graft and intact PCL. Research Question (RQ1): Is there a relationship between the use of biologics and decreased time to recovery/healing of injured connective tissue as compared to traditional treatment methods? Research Question (RQ2): Is there a relationship between the use of biologics and increased homogeneity of injured connective tissue as compared to traditional treatment methods? In the present study, recovery time decreased for patients who were treated with biologics (p <.05). The resulting RSI was compatible with the RSI of the uninjured, intact tendon/ligament (p<.05), thereby proving that homogeneity increased with the use of biologics. No correlation was observed between independent factors such as age and gender vs recovery time (p=1). CONCLUSION: Use of biologics (BMAC) in both the injection for AT tendinopathy and surgical ACL graft reconstruction has shown to decrease time to… Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

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This research investigates type 2 diabet type 2 diabeteses (T2D) and its risk factors, analyzes its prevalence and progression and identifies which risk factors affect different regions of Saudi Arabia by utilizing the 2013 Saudi Health Interview Survey. Our findings showed a high prevalence of T2D in Saudi Arabia (11.5%), with the highest in Hail and Aseer at 16.9% and 15.3%, respectively. On the other hand, Eastern had the lowest at 7.9%. Overall, we found that age and BMI were the most effective predictors. Age was the most effective, impacting all thirteen regions. The group aged 65 years and older had the highest risk; the 45- to 64-year-old age group, however, had the highest number of diagnoses. Al-Madinah had the highest prevalence of T2D in this age group at 56.9%. The 15- to 44-year-old group had the highest risk in Aseer at 4.8%. In Northern Borders, the odds ratio was the highest for the 65 plus age group, at 59.15. BMI was an effective predictor of T2D in nine regions. In Eastern, the odds ratio for the obese group was 4.3 compared to people of normal weight. In Al-Jouf, obese women had the highest percentage of T2D at 44.44% of cases. Work status was an important risk factor in Tabuk, Eastern, Al-Jouf, and Aseer. The retired group had the highest prevalence in these regions, except for Aseer where the employed group had the highest risk; retired people in Aseer are still involved in farm work, which may contribute to fewer T2D cases. Smoking status was an effective predictor in Hail, Al-Qassim, Riyadh, and Makkah. Ex-smokers had the highest incidence of T2D. Marital status was an effective predictor for Hail, Al-Qassim, and Riyadh. The divorced group had the highest prevalence of T2D. Education was an effective predictor for Riyadh and Aseer; the illiterate group had the highest risk. Diet was a good predictor only in Aseer. Shisha and hookah use were effective predictors in Riyadh. Understanding this data can help lower the prevalence of diabetes, provide better diabetes care, and lower healthcare costs for the Ministry of Health.

Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

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The projection of the U.S. national healthcare expenditure in year 2019 is $4.7 trillion. Medical errors are part of this increasing healthcare costs because they cause tens of thousands of deaths in the U.S. hospitals each year, more than major diseases such as AIDS, breast cancer combined to highway accidents (Chiang S. Jao, Daniel B. Hirer) [10]. Based on a research published in the British Medical Journal (BMJ) in 2016 and conducted by (Michael Daniel & Martin A Makary) [98], Medical error is ranked the third cause of death in the US. With the advancement in technology, we have seen during the last years, important improvements in the design as well as the use of electronic health records (EHRs), Computerized Physician Order Entry (CPOE), and Clinical Decision-Support Systems (CDSS), and Diagnosis Decision-Support Systems (DDSS) to improve the quality of health care delivery; progress have been made but challenges remain. Medication errors can be: •Wrong drug, •Wrong dose, •Wrong route, •Wrong patient, •Bad combination, •Bad reaction to list a few, and are found at every stage from prescription and administration of drugs to monitoring. They hurt about 1.5 million people, and cost billions of dollars each year according to the Institute of Medicine of the National Academies. Medication errors can happen anywhere, from Doctors offices to hospitals, and pharmacies and your home. Sound-Alike / Look-Alike also known as drug name errors, are the most common causes of medication errors, they originate from poor communication between health care providers, poor communication between patients and their providers. To reduce the likelihood of ham related to medications and Adverse Drug Events (ADEs), many interventions have been attempted including notably: The US Food and Drug Administration (FDA), government legislation, policy makers, drug utilization reviews, health professionals, and patients education, all of this with limited success. The aim of this dissertation is to evaluate medication errors related to Sound-Alike drug names, and to propose a new approach of preventing them by "Embedding the Novel Decision Algorithm" coupled with "Confused Drug Names, Generic and Brand drug names" and "Doses" within a computerized provider order entry (CPOE) during the drug prescribing process.

Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

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Background: Ontologies characterize complex and detailed information and are extensively used in healthcare research. Medical information (textbooks, expert opinions, clinical evidence) has information on conditions and its corresponding procedures (treatments), but this information is not captured or structured in any ontology. The objective of the research is to create a condition-procedure ontology from real world data to be utilized in observational research or electronic health record (EHR) system. Methods: Predictive models are developed to learn from five datasets (administrative claims, hospital charge data) to generate two algorithms (diagnostic and therapeutic) to predict condition-procedure relationships in the SNOMED-CT vocabulary. A reference set with 100 positive pairs per algorithm, and 32,132 negative pairs were developed. Predictive models were constructed by designing 51 possible covariates that describe condition-procedure pairs from Optum© De-Identified Clinformatics® Data Mart Database – Socio-Economic Status (Optum) dataset and determining which covariates discriminated between the positive and negative controls, as measured by Area Under Receiver Operator Characteristic Curve (AUC). External validation of the final algorithms was performed on 4 other databases. The final algorithms were applied across the universe of condition and procedure pairs in all five databases to construct the full condition-procedure ontology, and the ontology was evaluated for validity and coverage of condition and procedure concepts from the set of identified condition-procedure pairs. An additional analysis was trained to classify diagnostic vs. therapeutic intervention based on the overlap of pairs within the two algorithms. Results: Algorithms include the following covariates: condition-procedure occurring together, relative risk, support and sensitivity. Both algorithms had AUCs greater than .90, and external validation also showed similar results. In Optum, 98% of conditions and 63% of procedure codes had at least one relationship identified in the ontology. The intervention type analysis resulted in an AUC of 0.79. Conclusions: Real-world data can be utilized to construct a medical ontology of condition-procedure relationships with strong performance and good coverage. These results can be utilized to fuel research efforts in healthcare such as cohort generation and computer provider order entry systems by understanding conditions and procedures and their application to diagnose or treat a patient.

Advisors/Committee Members: Srinivasan, Shankar (chair), School of Health Professions.

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BACKGROUND: “Asthma is a chronic inflammatory disorder of the airways....In susceptible individuals; this inflammation causes recurrent episodes of wheezing, breathlessness, chest tightness, and coughing, particularly at night or in the early morning. These episodes are usually associated with widespread but variable airflow obstruction that is often reversible either spontaneously or with treatment. The inflammation also causes an associated increase in the existing bronchial hyper responsiveness to a variety of stimuli” PURPOSE OF THE STUDY: This study will evaluate the impact of demographic and clinical predictors on the prevalence of childhood asthma among minority children aged 0-17 in United States. METHODS: For this research, data from the 2011-2012 survey will be employed to conduct the required statistical tests using SAS SOFTWARE to answer the addressed research questions. A total of 95,677 NSCH interviews were completed nationally by parents/caregivers of children and youth approximately 1,876 in each state and the District of Columbia, ranging from 1,811 in South Dakota to 2,200 in Texas. The Statistical analysis will begin with an estimation of the national prevalence of asthma among children aged 0-17 years and living in the United States. Characteristics of the sample population will then be compared with the general population to assess if there are differences or validate how the sample population represents the general population. The characteristics in Table 41 will show how levels asthma and severe asthma are distributed among children by their age, gender, race/ethnicity, SES, clinical predictors and insurance status. RESULTS: Results have shown that being from low SES and minority race/ethnicity group (Hispanic, Non-Hispanic Black, and multi R racial/other Non-Hispanic) will increase the asthma and severe asthma rates among children living in the US. DISCUSSION: Conducting a new study on a national scale to display the differences in childhood asthma prevalence among minority population living in United States is valuable for measuring the prevalence of this chronic disease and the discrepancy burden among US children; and for developing intervention programs for minority population living in US. This study will also find what is still confounding and unknown about childhood asthma and recommend areas for further research.

Advisors/Committee Members: Srinivasan, Shankar (chair), Haque, Syed (internal member), Coffman, Frederick (internal member), School of Health Related Professions.

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Quality improvement in healthcare has been one of the key challenges in the United States for decades now. To overcome those challenge, healthcare organizations have employed many of the common Quality Improvement Methodologies (QIMs). Those methodologies and others have been some of the most effective tools for quality improvement in many other industries, including manufacturing and supply chain. However, it is unclear as to how QIMs are utilized in healthcare settings and if the QIM implementations can benefit from the commonly implemented Health Information Technologies (HITs). This study evaluates the hypothesis of whether or not QIMs are implemented using HIT systems in hospitals and practices in the United States. This involves evaluating the types of implemented QIMs as well as investigating the outcomes of the employed methodologies in terms of efficiency, throughput and financial impact. Moreover, the study forms an understanding on how the different HITs that exist in many healthcare settings are used as part of QIMs. The study also assesses the obstacles that prevent hospitals and practices from utilizing HITs in QIMs. To conduct the study, two datasets have been obtained, which are the Dorenfest Institute dataset and the Healthcare Information and Management Systems Society (HIMSS) Analytics data source. In addition, a survey has been conducted to collect data about how healthcare settings in the United States have been utilizing QIMs in the last ten years. Finally, the allocated and collected data have been analyzed and the results have been presented and discussed.

Advisors/Committee Members: Haque, Syed S (chair), Srinivasan, Shankar (internal member), Coffman, Frederick (internal member), School of Health Professions.

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This study developed a modified technology acceptance model (TAM) based of the actual adoption of the privacy of health information that suggested that external factors of culture and awareness of health information privacy predicted internal factors of privacy, including confidentiality, accountability, and regulations and policies. The study was concerned with the effects of culture and the nature of privacy, as well as the ways in which people’s sensitive information is accessed and maintained by healthcare facilities. The study provided detail regarding the need for improved information privacy in the Saudi healthcare setting. A survey instrument was designed and used to assess the knowledge of the privacy of health information among Saudi professionals in the fields of IT, medicine, and law. The data were analyzed to determine whether or not there was any connection between participants’ characteristics, especially from a religious culture perspective, and their attitudes about the privacy of health information. One-way ANOVAs were conducted to assess differences across professions for each of the outcome and predictor variables. No significant differences were found for accountability, or regulations and policies. Significant differences among professions were found for confidentiality, awareness, and culture. Post hoc analyses indicated that medical professionals reported significantly greater adherence to confidentiality than did law professionals, but they demonstrated significantly lower awareness and culture. Law professionals were also significantly higher in culture than were information technology professionals.

Advisors/Committee Members: Haque, Syed (chair), Srinivasan, Shankar (internal member), Coffman, Frederick (internal member), School of Health Related Professions.

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Over the past decade, clinical documentation improvement (CDI) programs have undergone quite an evolution and continue to evolve even today, particularly as the implementation of the new International Classification of Diseases, version 10 (ICD-10) system draws near. Before the Prospective Payment System (PPS) was established, Physicians focused on taking care of their patients without concerning themselves about quality or detailed documentation. They were reimbursed by Insurance companies without in-depth enquiries about services provided. With the introduction of the PPS, quality of patient care, length of stay during admission, severity of illness, and risk of mortality, became important benchmarks. CDI software models became more and more necessary as more hospitals adopted CDI programs to assist in improving Physician documentation in the patient’s medical record. This study first describes the need for a comprehensive electronic CDI model. Secondly, descriptive statistics will be used to determine the relevance of the different metrics collected as data in the new CDI model. Then, analysis of the collected data will be performed using the MS-DRG severity level and APR-DRG severity level to show the effects and contributions of a functional CDI program in relation to a hospital’s reported and coded statistics. Consequently, results of descriptive statistics show that between 19 to 32.5 percent of queries were generated monthly as a result of inadequate documentation by Physicians in patients’ medical records in relation to the total number of records reviewed and entered in the CDI software by the CDI Specialists. Other results of analyses show that a good CDI program significantly and positively impacts on different hospital metrics like the accuracy of coded data, case mix index (CMI), length of stay (LOS), severity of illness (SOI), risk of mortality (ROM), and reimbursement. In conclusion, the results of this study reveal that a significant positive ripple effect is achieved when an efficient CDI program is implemented, and this notion should serve as a basis to obtain a comprehensive CDI model where data collection can be better utilized to positively impact patient outcomes.

Advisors/Committee Members: Srinivasan, Shankar (chair), Coffman, Frederick (internal member), Kirk, Kathleen (internal member), School of Health Related Professions.

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A largely aging population, increase in chronic diseases, and rising costs are leading to the requirement for worldwide healthcare reform (Wilson, Whitaker, & Whitford, 2012). Wilson, Whitaker, and Whitford (2012) resolved, "To meet these needs, nurses are being encouraged to practice to the full extent of their skills and take significant leadership roles in health policy, planning, and provisions" (Wilson et al., 2012). "Nurses are frequently restricted in their scope of practice even as they comprise the largest group of health professionals" (Wilson et al., 2012). Wilson et al. asserted, "Nurses can help improve health services in a cost effective way, but to do so, they must be seen as equal partners in health service provision" (2012). The purpose of this study is to examine if there is a correlation between the level of computer skills among nurses working in a hospital setting and the patient safety culture of the hospital in order to promote successful electronic medical record in the nursing practice. The methodology for this study is a questionnaire design that will be used to survey hospital patient safety culture and nurses’ views using computer self-efficacy systems in a hospital setting. This data collection and the presentation of the necessary findings and results will provide key insights for the evaluation of this research management. All statistical analyses will be performed using SPSS for Windows (IBM SPSS 19.0, SPSS Inc., Chicago, IL). All of the analyses will be two-sided with a 5% alpha level. Demographic characteristics of the study sample will be described using the mean, standard deviation, and range for continuous scaled variables, and frequency and percent for categorical scaled variables. Cronbach’s alpha will be used to measure the internal consistency reliability of the computer self-efficacy, teamwork within hospital units aspect of patient safety culture, hospital management support for patient safety aspect of patient safety culture, communication openness aspect of patient safety culture, and feedback and communication about errors aspects of the patient safety culture scale scores.

Advisors/Committee Members: Srinivasan, Shankar (chair), Coffman, Frederick (co-chair), Kirk, Kathleen (co-chair), School of Health Related Professions.

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Background: Pancreatic cancer is very aggressive with few symptoms before the cancer can diagnosed and usually the cancer is advanced when it was found. It is the most deadly type of cancer, and it is listed as the fourth leading cause of cancer-related death with a poor prognosis because of the late finding of the disease. To patients, the pancreatic cancer diagnosis is a life-changing disaster; however, to maximally extend the pancreatic cancer patients’ life is most important task after diagnosis. In this research study, we found certain statistical significant relationships between the death of pancreatic cancer patients and the comorbidities & demographics. Furthermore, patients with some comorbidities or demographics can make their life longer or shorter. Objectives: To develop a mathematic model to predict the death of pancreatic cancer patients using certain patients’ comorbidities and demographics. Also, pancreatic cancer patients with certain comorbidities or demographics can predict their rest of life will be longer or shorter. Methods: The study uses HCUP NIS year 2005-2009 data files as research source database. With retrieving pancreatic cancer patient from NIS data files, the database used in this study includes pancreatic cancer patients’ information with their comorbidities and some demographics. The algorithm used in this research study in 1) Logistic regression ROC curve calculation 2) Logistic regression Odds Ratio calculation. Results: 1) In output ROC curve, the area under the ROC curve (AUC) is 0.725 which is >0.5. It means when randomly pick one patient from the disease group (diagnosed as pancreatic cancer) and one from the no-disease group (not diagnosed as pancreatic cancer) and do the test on both. The patient with the more abnormal test result (Died) should be the one from the disease group (diagnosed as pancreatic cancer). 2) 11 comorbidities can significantly influence on life of pancreatic cancer patients, both LCL and UCL of odds ratio are either <1 or >1 in all 11 comorbidities, which means if patients were diagnosed as one of 11 comorbidities, they might either live longer or live shorter. Conclusions: The study results were cross verified by 3 types of cancer patients, which is pancreatic cancer, breast cancer and stomach cancer. Those 11 comorbidities have the same statistical significance effect on influencing patients’ life. So far no literatures can be found on such kind of study, this study can be considered as a new research field in the future.

Advisors/Committee Members: MITAL, DINESH P (chair), Srinivasan, Shankar (internal member), Coffman, Frederick (internal member), School of Health Professions.

▼ Background In today’s complex and high risk healthcare environment the race to implement health information technology (health IT) in the care delivery system is becoming more prevalent in United States hospitals but the science to support its safe and effective use is contradictory at best. Since the 1999 Institute of Medicine Report, To Err is Human, Building a Safer Health System; there has been an increasingly intensive focus on the prevention of medical errors and the improvement of hospital safety and quality. In more recent years information technology has been identified as having the potential to reduce and prevent a wide range of issues, including medical errors, thus increasing patient safety, improving the quality of care, and reducing costs. Many hospitals and provides have integrated health IT into the patient care process, usually in the form of decision support systems, electronic health records, provider order entry systems, and the like. However, not all providers, clinicians, and researchers are in agreement on the impact these computerized systems have on safety, quality, and patient outcomes. With contradicting results in the literature and gaps in the evidence of the safe and effective use of health IT there is much to be learned in this area. This research project aims to quantify the impact of health IT on hospitals in the United States by investigating inpatient medical claims data, specifically medical errors and mortality rates and how they are impacted by health IT implementation data. The stage of health IT implementation from year to year will be evaluated for its impact on the number of medical errors and mortality rates. Methods To address the study objectives data from two datasets, the HIMSS Analytics datasets, provided by the Healthcare Information Management and Systems Society (HIMSS) and the Healthcare Cost and Utilization Project’s (HCUP) National Inpatient Sample (NIS) datasets provided by the Agency for Healthcare Research and Quality (AHRQ), were aggregated to form the analysis dataset. To accurately match the hospitals in each dataset the hospital’s Medicare ID code was used. Once the datasets were matched, the study outcomes, number of medical errors and mortality rates, were drawn from the HCUP data and the health IT stages was derived from the HIMSS data. The International Classification of Disease version 9 (ICD-9) codes were used to identify medical errors from the HCUP data. To address the primary and secondary objectives, both SAS and SPSS were utilized for data manipulation, data cleaning, and analysis. As part of the analysis descriptive statistics on hospital characteristics were assessed to determine the characteristics of hospitals at different stages of health IT implementation. Additionally, analysis of variance (ANOVA) was performed to determine the effects of health IT on medical errors and mortality rates. Finally multiple regression analysis was performed to determine if health IT stage is a predictor of medical errors and mortality rates. Results… Advisors/Committee Members: Haque, Syed (chair), Srinivasan, Shankar (internal member), Coffman, Frederick (internal member), School of Health Professions.

▼ Obesity has reached near epidemic proportions in the United States. Rising obesity and its associated comorbidities result in deleterious effects on health status[4-6] and a significant increase in health burdens [7, 8]. Excess cost attributable to overweight and obesity was reported to be approximately $92.6 billion dollars, comprising between 6 – 10% of the total health care expenditure of the US [9, 10]. Obese individuals had 36% higher annual health care costs than non-obese individuals [11]. Type 2 Diabetes (T2DM) has the common characteristic of obesity or being overweight. In addition, the researchers found that while two out of every 1,000 normal weight people had been diagnosed with diabetes, some 18 out of 1,000 obese people had the disease and there was a 41% increase in the incidence of diagnosed diabetes during that time. Researchers confirmed that the more fat tissue a person has the less sensitive that person becomes to insulin. Therefore a greater amount of insulin is required to maintain the body's regulation of blood glucose levels. Fat cells release a protein that leads to the development of T2DM [17]. Obesity prevalence of the pre-diabetic and diabetic conditions is more common in certain subgroups of the population. For African Americans, the prevalence of obesity is high, particularly African American women. The risks of morbidity and mortality associated with diabetes poses serious problems African American women as they affected by obesity related comorbidities disproportionately [14]. Although prevalence rates of obesity and diabetes have reached epidemic proportions in the African American population, the relationship between obesity and hospital health care use, cost and length of stay has received limited attention and failed to provide consistent results. Even though obesity is one of the biggest drivers of preventable chronic diseases and healthcare cost in the United States, obesity rates continue to grow. Taking account of culture and social economic factors, this study serves as a model for future studies on hospital length of stay and health care cost in high risk populations of primary diseases with comorbidities. The study provides a baseline for obese African American women with T2DM. The study design is a retrospective, correlation, quantitative analysis on lengths of hospital stay and cost among adult African American women categorized according to their weight status with T2DM. This study will be driven by the following four research questions and associated statistical hypotheses: Research Question 1 (RQ1). Is there a relationship between individual health factors of interest (obesity and diabetes) and hospital length of stay (LOS) among African American females? Research Question 2 (RQ2). Is there a relationship between individual health factors of interest (obesity and diabetes) and hospital costs among African American females? Research Question 3 (RQ3). How co-morbidities and life factors are related to individual health factors of interest (obesity and diabetes)… Advisors/Committee Members: Haque, Syed (chair), Srinivasan, Shankar (co-chair), Shabata, Masayuki (internal member), School of Health Professions.

▼ The overall goal of the project was to identify the factors and costs associated with Colon Cancer patients in terms of mortality, length of stay and costs in different types of clinical settings across the United States. Accordingly this research study utitlized the datasets for 2008 to 2010 available from the Nationwide Inpatient Sample (NIS) database with hospitalization characteristics of patients admitted with Colon Cancer as the principal diagnosis. Some of the important results found in this study were: Between 2008 and 2010 the age and population adjusted incidences and the hospital discharges both decreased significantly which is a promising trend speaking well of the state of health care in the United States as also possibly due to the effectiveness of nutritional counseling, patient education, screening for men aged 50 and above. It was found that while the total number of colon cancer patient discharges decreased significantly between 2008 to 2010, the Total Charges however significantly risen up between 2008 and 2010. The mean charges increased by nearly 8 %. The number of discharges across the various hospital types and their locations across the United States as shown above revealed that those large hospitals in metropolitan regions and those that are private not-for-profit have more discharges compared to the other types. Patients who are uninsured and those on Medicaid (low income) are more in number over the years 2008 to 2010 as compared to those on Medicare and Private Insurance which have decreasing trends. It was found that the mean and median length of stay of colon cancer patient discharges remained more or less the same between 2008 and 2010. It was found that the number of in-hospital mortality or deaths significantly reduced between 2008 and 2010. Alongside Home Health Care increased while discharges to another hospital also decreased (with a smaller decrease in discharge to another institution such as rehab facility and nursing home). The number of in-hospital deaths has a decreasing trend in the number of deaths over the years 2008 to 2010. Southern United States has more (nearly 2 times) in-hospital deaths compared to the other regions in all the 3 years. This study seems to indicate that mortality is positively correlated with the total costs and this may be due to a significant admission source is from emergency department. The in-hospital mortality prediction model above revealed significant risk for patients with hypertension (nearly 100%) and with obesity (62 % more) Patients with white ethnicity have lower risk of dying in the hospital compared to the other ethnicities which all have similar odds ratio intervals. This research study was limited to the datasets available from the Nationwide Inpatient Sample (NIS) database with hospitalization characteristics of patients admitted with Colon Cancer as the principal diagnosis. A similar large scale dataset based future study is indeed warranted to analyze demographic and hospital based outcomes… Advisors/Committee Members: Haque, Syed (chair), Srinivasan, Shankar (internal member), Mital, Dinesh (internal member), School of Health Related Professions.

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Among different types of cancers which occur in men, prostate cancer is the most commonly occurring one. However, prostate cancer epidemiology is not completely identified. Neither the causation nor pathogenesis of prostate cancer can be totally understood by today’s information. As a result, prostate cancer screening tests cannot always detect the disease. Prostate-specific antigen (PSA) blood test is the most widely used test to screen men for prostate cancer. However, PSA blood test adversaries accuse this test as rendering misguided results that lead to over-diagnosis and overtreatment. According to The National Cancer Institute, men who go through a prostate biopsy procedure because of an elevated PSA test result, only about 25 percent of them actually have prostate cancer. The other 75% of men might face the side effects of prostate biopsy which includes serious infections, pain, and bleeding. This study utilized the Nationwide Inpatient Sample (NIS), and the Surveillance, Epidemiology, and End Results (SEER) Program data to identify some key risk factors for those patients who are more likely to be diagnosed with prostate cancer. In addition, an Artificial Neural Network has been implemented a long with the most used classification methods that include Logistic Regression, k-Nearest Neighbors, Naïve Bayes classifier, Decision Tree classifier, and Support Vector Machine, in order to recognize prostate cancer in an early stage. All these classification methods’ results were analyzed using confusion matrix and Receiver Operating Characteristic (ROC) analyses. This study found that age, ethnicity, family history of cancer, fat intake, vitamin D deficiency, inflammation of prostate, vasectomy, and hypertension are positively associated with prostate cancer. Although, obesity, alcohol abuse, and smoking were significantly associated with the prostate cancer, this association found to be negative. The result of classification methods’ tests showed that the Artificial Neural Network had success rates of 87.53% on NIS data and 99.31% on SEER data compared to Logistic Regression (81.71%, 84.95%), k-Nearest Neighbors (73.46%, 91.62%), Naïve Bayes classifier (70.86%, 86.56%), Decision Tree classifier (78.02%, 90.34%), and Support Vector Machine (72.33%, 88.52%). In conclusion, this study tried to minimize the PSA false result by identifying more key risk factors and providing a prediction tool based on Artificial Neural Network to predict and to support the clinical decision in prostate cancer screening.

Advisors/Committee Members: Srinivasan, Shankar (chair), Haque, Syed (internal member), Mital, Dinesh (internal member), School of Health Related Professions.

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Disorders of Temporomandibular Joint (including capsulitis of TMJ, degenerative arthritis, internal derangement, dislocation, myofacial pain, ankyloses, headache, sleep disorders, trigeminal neuralgia, Cranio-maxillofacial trauma, and other related TMJ diseases) are some of the leading causes of chronic pain. The serious personal consequences of severe, constant facial, head and neck pain from these disorders make these problems a major social issue. One of the greatest challenges facing health care systems internationally is meeting the health needs of their populations with the available resources especially for In-patient. This study explored the association of temporomandibular joint complexity with socio-demographic variables, multidisciplinary management of the TMD during patient hospitalization and selected co-morbidities characteristics based on the 2003 to 2010 nationwide inpatient sample (NIS) of the health care cost and utilization project (HCUP) provided by the agency for health care research and quality (AHRQ) data for TMD In-patients between 2 and 97 years old. There is a strong positive correlation between temporomandibular disorders and hypertension and a weaker but nonetheless positive correlation between temporomandibular disorders and diabetes, temporomandibular disorders and depression, and temporomandibular disorders and weight. The finding of this study support the hypotheses that Socio-demographic factors (age, race, disposition of patient, primary expected payer, patient location, gender, source, length of stay, and median income) affect incidence of TMD and hospital stays, Comorbidities exist that are significantly related to TMD incidence and hospitalization costs. Results of eight years nationwide epidemiological estimates of hospitalizations attributed to temporomandibular joint disorders in the United States demonstrate changes in socio-demonstrate and hospital related factors. Also eight-year trend analysis of hospitalizations for temporomandibular disorders showed that mean length of stay between (3.06 - 3.25) while per year charge increased.

Advisors/Committee Members: Syed, Haque (chair), Srinivasan, Shankar (internal member), Mittal, Dinesh (internal member), School of Health Professions.

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Endodontically treated teeth are often structurally compromised and require proper prosthodontic restoration following endodontic therapy to ensure long-term success. As a result and as the number of endodontic procedures in contemporary dentistry have steadily increased in the past decade, tooth restoration is becoming an integral part of restorative practice in everyday dentistry. Although the subject has been widely researched and published in dental literature, the topic of best way to restore root canal treated teeth still remains an area prone to high error rates in decision-making. Complexity of the domain is largely due to multi-factorial considerations and need for evaluation of a wide range of restorative techniques of varying intricacies. Determining the best restorative treatment plan following endodontic therapy requires sound knowledge of principles that span across multiple dental disciplines of endodontics, orthodontics, periodontics, and prosthodontics. Memorization of a large and ever-increasing number of decision rules to be meaningfully used at the point-of-care can be arduous, especially for dental students and less experienced clinicians. Clinical experts with their knowledge and years of experience treating patients can help in the process, but may not always be around to provide assistance. Misdiagnosis and mistreatment of such teeth can lead to adverse clinical consequences and significant inconvenience to the patient as well as financial implications both for the patient and provider. To address this problem, we have developed a clinical decision support and training system based on expert knowledge and evidence-based guidelines. Using Corvid expert system development framework and careful consideration of factors necessary for success of clinical decision support systems, we have developed a working prototype of a web-based, interactive system that can be launched at the operatory and can be easily integrated into providers’ workflow. One of the important goals of the system is to train users to think holistically like an expert while problem-solving and planning restorative treatment. Based on information entered by the user, system comes up with recommendations, alerts and treatment prognosis. Treatment options provided with justifying explanations can help clinicians provide decision-making rationale to the patients, better inform and educate them, and thus better manage their expectations and ensure their satisfaction and compliance. Since the knowledge base of our system is developed using expert guidelines that are known to be effective, we expect to see improved restorative treatment outcomes for endodontically treated teeth.

Advisors/Committee Members: Mital, Dinesh (chair), DiPede, Louis (internal member), Srinivasan, Shankar (internal member), School of Health Professions.

▼ Background: Simulation plays a fundamental role in the provision of healthcare education. It endows the trainees with a safe environment where they can develop, improve and sharpen their medical skills through continual and purposeful self-practice as well as constructive feedback. This study delves into the fundamental role simulators have with regard to educational theory and promotion of effective learning and to examine the effectiveness of a Ultrasound Interactive Console Simulator (USICS) relative to a Ultrasound Scanning Machine and to validate the functionality of the USICS. Method: This study’s core objective was to establish whether it is possible to implement an effective web-based distance education system that will facilitate users become fully acquainted with the elements and uses of an actual ultrasound instrument. Ultrasound Interactive Console Simulator (USICS) is an online application that was developed to enhance the learning effectiveness, which utilizes the qualities and supplies of the World Wide Web to build a significant learning atmosphere where learning is adopted and maintained. The participants were registered to enable them to use the system. During registration, the participants were given directions about the ultrasound simulation system’s basic functions and keys. There are two different methods in this study; one is a questionnaire that consist of eighteen multiple choices questions was used in the data collection of this study to investigate the similarity, the content effectiveness, construct validity, and easiness of usage. A Likert scale (1 - 5) was used to get the assessment from sonographer experts over the use of the USICS. After that we apply Cronbach's alpha test to test the face, content, construct validity. The other method is pretest and posttest experiments to examine that the USICS is a comparative effectiveness for learning factor. Paired T-Test was applied on this experiment. Results: Some of the important results found in this study were: • The results of operations performed by the USICS are similar to the other ultrasound machines such as the Philips Clear Vue machine. • There are no variations in the content effectiveness and construct validity between the simulator system (USICS) and the Philips Clear Vue machine. • The USICS is a useful and effective supplement to conduct training on a real-life Ultrasound Scanner. Conclusion: To facilitate the acquisition of technical skills as would be obtained from a generic Ultrasound scanning machine a simplistic perspective frames simulation was employed to endow the students with a safe and comprehensive alternative to conducting clinical procedures. It is firmly believed that the Ultrasound Interactive Console Simulator (USICS) aims to satisfy the growing demand for effective tools for online healthcare education and specifically in the area of Ultrasound scanning training. In a bid to strike the right balance in the simulation of an ideal clinical scenario it is imperative to align the simulator in a way that… Advisors/Committee Members: Srinivasan, Shankar (chair), Haque, Syed (internal member), Coffman, Frederick (internal member), School of Health Related Professions.

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The increase in the prevalence of obesity in a growing number of populations worldwide presents a rising health threat in this millennium. Overall, about 13% of the world adult population (11% of men and 15% of women) fell into the obese category in 2014. Management of overweight and obesity used to be through non-surgical methods including diet, exercise, medication, and changing life styles. However, commitment to all these methods is very hard. Hence, surgical intervention has been used on a wide scale. Many types of bariatric surgical procedures were applied, mostly restrictive types such as Laparoscopic Sleeve Gastrectomy, Laparoscopic Adjustable Gastric Banding, or Roux-en-Y Gastric Bypass. The overall goal of this research is to identify the factors and costs associated with patients undergoing different types of gastrectomy, in terms of length of stay in the hospital and the operations’ costs in different types of clinical settings across the United States. Accordingly in the second phase of the project, a prospective study was conducted to evaluate some variables in the LSG candidates, such as hemoglobin level, vitamin levels (B12 and D), and thyroid hormone levels before and after the operation. Moreover, similar study and data sources were made use of from King Khalid University Hospital, Riyadh, Kingdom of Saudi Arabia. Most patients who underwent the LSG had different kinds of comorbidity, for example; among 2012 candidates in the US, there were 34.22% who had hypertension, complicated or uncomplicated; 15.26% had uncomplicated diabetes; and 12.35% complained of depression. According to this study’s results, a statistically significant association was found between length of stay in the hospitals, and consequently the total cost, and the following comorbidities: obesity (b=1.119, p<0.001), hypertension (b=0.076, p=0.022), and deficiency anemia (b=0.506, p<0.001). No statistically significant evidence of association between length of stay or total cost and hypothyroidism (p=0.12) or uncomplicated diabetes (p=0.385) was found. Regarding Saudi patients who received LSG between 2014 and 2015, no statistically significant difference between level of Hb or Vitamin B12 was found in patients before and after the LSG, while there was a statistically significant difference in the level of vitamin D before and after the operations. Although Sleeve Gastrectomy is popular currently as a solution for obesity, research into the procedure’s long-term effects is scarce. More research is required to improve outcomes and to maximize the benefits of those procedures.

Advisors/Committee Members: Srinivasan, Shankar (chair), Haque, Syed (internal member), Coffman, Frederick (internal member), School of Health Related Professions.

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The aim of this study is to examine the prevalence and usage of Open Source Software (OSS), and it is adoption by healthcare providers in the United States, along with the factors influencing or inhibiting this adoption process. Moreover, exploring characteristics of healthcare provider systems that associated with the adoption of HIT, with a focus on open source EHR. The study research questions includes: • What types of OSS products that healthcare providers use? • What is the extent of OSS adoption in healthcare providers? • What factors promoting or inhibiting the adoption of OSS products in healthcare providers? • What is the adoption trend of OSS in the past years? • Do OSS applications benefit from the government incentives programs such as Meaningful Use Incentives? • How are the prevalence and the adoption rate of OSS applications compared to proprietary systems in the available datasets? A secondary data analyzes were used to investigate these issues, also to examine and characterize the types of OSS products adopted by healthcare providers.

Advisors/Committee Members: Srinivasan, Shankar (chair), Haque, Syed (internal member), Coffman, Frederick (internal member), School of Health Professions.

▼ The purpose of the study was to explore the relationship between acculturation status and diabetes prevalence in U.S. Hispanics. Thus, the study goal was to determine if acculturation status predicts diabetes prevalence in Hispanics in the U.S. The main hypothesis for this study is: Acculturation status significantly predicts diabetes prevalence in Hispanic adults. This main hypothesis is based on the main research question: How does acculturation status relate to diabetes prevalence in adult Hispanics in the U.S.? In addition, the study included an investigation into covariates that might influence the relationship between acculturation status and diabetes prevalence. Thus, the relationships between age, gender, occupation, income, health insurance, physical activity and fitness, alcohol use, smoking and tobacco use, weight history, anyone on a special diet, types of food available at home, and types of food prepared-eaten and diabetes prevalence were explored. This study was therefore driven by the following research questions and associated statistical hypotheses: Research Question1: How does acculturation status relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #2: How does age relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #3: How does gender relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #4: How does occupation relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #5: How does income relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #6: How does health insurance relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #7: How does physical activity and fitness relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #8: How does alcohol use relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #9: How does smoking and tobacco use relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #10: How does weight history relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #11: How do acculturation status, age, gender, occupation, income, health insurance, physical activity and fitness, alcohol use, smoking and tobacco use, and weight history relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #11b: How do acculturation status, age, gender, occupation, income, health insurance, physical activity and fitness, alcohol use, smoking and tobacco use, weight history, anyone on a special diet, types of food available at home, and types of food prepared-eaten relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #12: How does anyone on a special diet (any family member) relate to diabetes prevalence in adult Hispanics in the U.S.? Research Question #13: How does types of food available at home relate to diabetes prevalence in adult Hispanics in the U.S.? Research… Advisors/Committee Members: Srinivasan, Shankar (chair), Coffman, Frederick (internal member), Kottiech, Samer (outside member), School of Health Professions.

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As the United States healthcare system transitions to a pay for performance model in response to increasing costs and utilization, assessing quality of care has come to the forefront. Venous thromboembolisms (VTE), which include deep vein thrombosis (DVT) and pulmonary embolism (PE), is a key measure of quality of hospital care and are associated with increased morbidity, mortality and cost in hospitalized patients. Traditional ways of measuring quality and identifying adverse events such as VTE using administrative data are convenient but lack accuracy. Manual review of clinical records is widely considered the gold standard but resource intensive. Consequently, this study sought to determine the accuracy of Natural Language Processing (NLP) and machine learning classifiers in identifying VTE from free text data. This study used radiology reports performed within 30 days of surgery for hospital patients sampled from 2011 through 2014 as part of the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP). Though records for this sample were previously reviewed and VTE cases identified, a total of 909 ultrasound reports and 1,837 computed tomography (CT) angiogram reports were again manually reviewed to identify DVT/PE within each report and served as the gold standard. The Naïve Bayes, k-Nearest Neighbors (kNN), C4.5 decision tree, and support vector machine (SVM) classifiers were trained on 70% of the total preprocessed reports and performance was assessed on the remaining 30%. DVTs were identified in 16.8% of all ultrasound reports and PEs were identified in 5.0% of all CT angiogram reports. SVM yielded the best results in classifying both DVT and PE, with precision of 91.3%, recall of 95.5% and F-measure of 93.3% for DVT classification and precision of 93.1%, recall of 87.1% and F-measure of 90.0% for PE classification. In conclusion, NLP along with statistical machine learning classifiers can accurately identify VTE from narrative radiology reports.

Advisors/Committee Members: Srinivasan, Shankar (chair), Coffman, Frederick (internal member), Stetson, Pete (outside member), School of Health Professions.

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Research shows that high sodium consumption is positively correlated with hypertension. However, little is known about variations on the impact of high sodium consumption on hypertension among a variety of adult American subpopulations. This study investigated the impact of sodium on hypertension in a variety of adult America subpopulations by conducting an analysis of Centers for Disease Control's (CDC) National Health and Nutrition Examination Survey (NHANES) 24-hour dietary recall data from 2005-2014. Participants ages 20 years and above were used in the study. Analysis of the data included applying weighted factors to the selected sample to account for sampling bias and allow for accurate comparisons between samples and population estimates. Data analysis was done using SAS version 9.4 Software Package. There was a decrease in the two year period 2007-2008 of sodium consumption and a increase in hypertension rate. There was no significant change in sodium consumption from 2005-2014. Fifty four percent of the people consumed more than the daily recommended sodium intake by the American dietary guidelines. Results showed that African Americans consumed more sodium than any other race in America. Also, African Americans have the highest hypertensive rate in the study. Highly educated individuals consume more than the recommended amount of sodium (2300mg) compared to those with less than high school education. On the contrary, the results further shows that less educated participants had higher blood pressure than the more educated individuals. It was found that, low income earners consumed more sodium but middle income earners had highest hypertension. Male consume more sodium than their females counter parts and has higher hypertension than females. The results shows that 98% of the participants had isolated systolic hypertension and as people age, their blood pressure becomes higher. The results further shows participants with higher BMI consume more sodium and had higher blood pressure. Also, the more you age the higher your blood pressure. The study highlighted areas that can be targeted for designing health intervention programs that will be targeted to specific subgroups of the American population.

Advisors/Committee Members: Coffman, Fredrick D (chair), Srinivasan, Shankar (internal member), Haque, Syed (internal member), School of Health Professions.

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Idiopathic pulmonary fibrosis (IPF) is a rapidly progressive immune mediated lung disorder that leads to death in the majority of patients, regardless of treatment, within 3-5 years of diagnosis. 1-3 Pulmonary fibrosis is often the final common pathway of many known causes of interstitial lung disease, such as sarcoidosis, silicosis, drug reactions, infections and collagen vascular diseases. The overall goal of the project is to identify the factors and costs associated with IPF patients in terms of mortality, length of stay and costs in different types of clinical settings across the United States. We used data rom the Nationwide Inpatient Sample (NIS) for calendar years 2007-2012 to perform a series of analyses to identify any factors and costs associated with IPF patients, particularly those pertaining to mortality, length of stay (LOS), and costs across the various clinical settings in the US. A series of parametric and non-parametric methods were used. Parametric methods included linear regression models, correlation analysis using Pearson correlation coefficients, paired and unpaired t-tests, and one-way ANOVA. A series of non-parametric methods were also used including: Wilcoxon rank sum tests, Mann-Whitney tests, Spearman correlations, and Kruskal-Wallis tests. Descriptive analyses were employed to compute sample mean, median, standard deviation, and interquartile ranges for study variables. Finally, binary outcomes and categorical variables were examined using the following: logistic regression models, chi-square tests, contingency coefficients, and McNemar’s test. We found a mean expenditure per IPF patient of 68,925 (standard deviation = 16,4049), with a median of 28,257. We found the distribution of total charges to be significantly different from the normal distribution (p<0.001). Further investigation revealed a maximum charge of 4,162,849, which is approximately six times as high as the 99th percentile total charge of and 147 times as high as the median. These results indicate that the distribution of total costs are skewed heavily by a relative few patients with extremely high bills. LOS also varied wildly with the mean stay being 7.84 days with a standard deviation of 13.60 days. LOS ranged from zero days to 1158 days, which corroborates our conclusion about the distribution of total costs. The patient who stayed 1158 days was hospitalized for 858 days more than any other patient. The next highest LOS values were 300 days, 250 days, 196 days, and 160 days, which further plays to our notion of the extremely expensive few. LOS varied in a statistically significant way between white and black patients (p<0.05). Only 11.2% of all patients in the data set died during the study period (11.2% of whites, 9.5% of blacks, 11.2% Hispanics, 12.2% of Asian/Pacific Islander, 13.0% of Native Americans). Finally, only 12% of all IPF patients passed away, while slightly more (13.8%) of all IIP patients died during the study period.

Advisors/Committee Members: Srinivasan, Shankar (chair), Coffman, Frederick (internal member), Haddad, Richard (outside member), School of Health Professions.

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Background: Asthma is one of the most common chronic diseases that affect the airways in the lungs causing inflammation due to reacting to any infection or trigger that stimulate the asthma attack. Such a disease might be able to affect the health-related quality of life (HRQoL) including: activity limitations, physical health, and mental health of these adult patients in certain ways. Objectives: Since there is no clear research or study that gave an integrated comprehensive view of the impact of asthma along with different associated factors including: behavioral factors (smoking, frequency of smoking and quitting, exercise, health-routine checkup, and alcohol use), clinical factors (obesity, depressive disorder, diabetes, influenza and pneumonia vaccines), and socioeconomic factors (stress, healthcare coverage, income and education level) on HRQoL in adult patients in the United States, the overall goal of this research is designed to investigate this impact. Methodology: Data of this research is obtained from Behavioral Risk Factor Surveillance System (BRFSS) 2014. Different statistical procedures and methods including: extracting data, descriptive analysis, inferential analysis, and predictive analysis would be preformed by using Statistical Analysis System Software (SAS) 9.4. Results: adult patients of asthma have activity limitations by 64.90%, physical health problems by 163.40%, and mental health problems by 163.53% more than adult healthy people. Smoking limits activity by 116.18% as well as increases physical and mental health problems by 19.12% and 40.41%. Also, other behavioral factors play great roles in HRQoL in adult patients of asthma. Obesity limits activity by 73.57% as well as increases physical and mental health problems by 41.50% and 17.20%. Also, other clinical factors play great roles in HRQoL in adult patients of asthma. Stress limits activity by 188.52% as well as increases physical and mental health problems by 90.17% and 157.20%. Also, other clinical factors play great roles in HRQoL in adult patients of asthma. Conclusion: Even if there are few associated factors that improve HRQoL in adult patients of asthma, the majority of these factors worsen HRQoL. Finally, it can be confirmed that these associated factors along with asthma can lead to poorer HRQoL in adult patients of asthma in the United States.

Advisors/Committee Members: Coffman, Frederick (chair), Haque, Syed (internal member), Srinivasan, Shankar (internal member), School of Health Professions.

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Background: Complete denture is considered one of the most challenging treatment modalities in dentistry. Any error occurs during any step of the complete denture fabrication can result in patient’s complaint. Troubleshooting complete denture complaints is very challenging for several reasons. First, all the teeth are connected into one denture base that is supported by a movable resilient mucosa make it difficult to isolate the errors. Second, one patient’s complaint could be due to several causes and at the same time one cause can lead to many patient’s complaints. Third, the diagnosis of each patient’s complaint must be approached systematically because adjusting the denture in a wrong spot may add another problem. Most of the complete denture treatment is provided by general dentists and depend only on their undergraduate training and clinical experience. There is a concern about the competency and level of skills of the undergraduate students in mastering the complete denture skills due to limited exposure to enough cases. The purpose of this research is to develop a new clinical decision support and training system to aid the general dentists and undergraduate students in diagnosis and management of complete denture complaints. Method: The new clinical decision support and training system was developed using Exsys Corvid Core software. The knowledge base of the system for the complete denture complaints, the complaints causes and the management protocol for each complaint were retrieved from the literature. The software was successfully loaded with 123 rules representing 48 patients’ complaints along with its detailed diagnostic methods and management protocol. After system development, the system was validated by ten expert prosthodontists using a survey questionnaire. The questionnaire results were statistically evaluated using Cronbach’s Alpha test. Results: The Cronbach’s Alpha reliability coefficient was 0.847, which represent a good internal consistency. The validation questionnaire results showed that all ten prosthodontists agreed on the need of such system and its user friendliness. Also, all prosthodontists agreed that the system is a good tool to assist the general dentists and undergraduate students in diagnosis and management of complete denture complaints. 90% of the prosthodontist agreed with the knowledge base of the system for the complete denture complaints, the causes of each complaints and the management protocol for each complaint. Conclusion: The clinical decision support and training system to aid the general dentists and undergraduate students in diagnosis and management of complete denture complaints was developed. The overall agreement of the ten evaluating prosthodontists with the system indicates that the system was successfully developed.

Advisors/Committee Members: Srinivasan, Shankar (chair), Coffman, Frederick (internal member), Kamel, Mohamed (outside member), School of Health Professions.

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Although the advancement of surgical techniques and immunosuppressive therapy has significantly improved the outcomes of kidney transplantation in patients with end stage renal disease (ESRD), post-transplantation outcomes remain a big challenge. Accordingly, the goal of this dissertation was to determine which variables might have the most critical impact on the graft and patient survival time. One such variable which seemed significant but not well studied was the Blood Urea Nitrogen (BUN) level of the donor. Therefore, using the United Network for Organ Sharing (UNOS) registry database (October 1987 to March 2016), a retrospective (longitudinal) cohort study was setup to examine the relationship between the BUN level of the deceased donor and the survival of the graft and the patient while controlling for certain other variables. The final sample consisted of 168,081 patients in the United States. Multivariate cox regression analysis revealed that high log BUN level of deceased donor remained an independent predictor of graft loss (hazard ratio [HR], 1.080; 95% hazard ratio confidence limits [CI], 1.032 - 1.131; P = 0.0009) and patient death (hazard ratio [HR], 1.063; 95% hazard ratio confidence limits [CI], 1.007 - 1.121; P = 0.0262) compared to low log BUN level of deceased donor. Significant findings from this study indicate that high log BUN level (> 2.79 mg/dl) of deceased donor is independently associated with decreased graft and patient survival time compared to low log BUN level of deceased donor. It is to be noted that White, Black and Hispanic donors races have significant differences at 5 year graft and patient survival time while donors of other races (Asian, American Indian/Alaska native, Native Hawaiian/other Pacific Islander, and multiracial) did not show a statistically significant influence on graft and patient survival due to genetic influences. These results can potentially contribute to a more efficient allocation of resources to donor sources with better outcome prospect.

Advisors/Committee Members: Coffman, Frederick (chair), Srinivasan, Shankar (co-chair), Gohel, Suril (co-chair), School of Health Professions.