When face-to-face physical medical exams are not possible, virtual physical exams, in the form of a pictorial medical exam/history, can be substituted, and telemedicine can be the means to deliver these virtual exams. The goal of this work was to determine if presence in the form of a visual and/or pictorial medical history can be of benefit to clinicians in the diagnosis of medical conditions of individuals with developmental disabilities (DDs) and/or intellectual disabilities (IDs), in particular those who cannot, because of their cognitive and/or physical disabilities, verbally relate their illness to a clinician. Virtual exams can also be useful in cases where clinicians may need additional advice from fellow experts, especially if those experts are not physically present. A web-based telemedicine application used for treating persons with DD/IDs was developed. This application includes a visual medical history component incorporated into an electronic medical records application. The purpose is to allow the clinician to use an environment that integrates a written and visual representation of a patient’s medical history and physical findings to aid the clinician in determining a medical diagnosis. Twenty-two clinicians and five direct service aids of a New York State Developmental Disabilities Services Office facility, who deliver healthcare to DD/ID patients on a daily basis, accessed the telemedicine application instead of their traditional hardcopy/paper medical history when examining patients. A comprehensive survey was distributed to the clinicians to determine the effectiveness of the application as well as help answer the primary questions proposed by this research. The results of this study showed that presence in the form of a video medical history is preferred by clinicians rather than having just a written medical history of the patient. Clinicians felt the visual medical history component of the telemedicine application was useful and informative for delivering healthcare to individuals with DD/ID and enabled them in diagnosing a patient as well as lessened the need to transfer patients to the emergency room, resulting in a significant cost savings.

Diabetes is the seventh leading cause of death in the United States. With the population rapidly aging, it is expected that 1 out of 3 Americans will have diabetes by 2050. Mobile devices and mobile applications have the potential to contribute to diabetes self-care by allowing users to manage their diabetes by keeping track of their blood glucose levels. Usability is important for systems that help people self-manage conditions such as diabetes. Age and diabetes-related cognitive decline might intensify the impact of usability issues for the users who need these mobile applications the most. As highlighted by usability researchers, the context of use (i.e. environment, user, task, and technology) has a significant impact on usability. The environment (lighting, temperature, audio and visual distractions, etc.) is of special interest to the mobile usability arena since in the case of mobile devices, is always changing. This dissertation aims to support the claim that context and more specifically environmental distraction such as semantic auditory distractions impact the usability of mobile applications. In doing so, it attempts to answer the following research questions: 1) Does semantic auditory distractions reduce the effectiveness of a blood glucose tracking mobile application? 2) Does semantic auditory distractions reduce the efficiency of a blood glucose tracking mobile application? 3) Does semantic auditory distractions reduce the user satisfaction of a blood glucose tracking mobile application? To answer the study research questions, a true experimental design was performed involving 30 adults with type 2 diabetes. Participants were paired based on their age and experience with smartphones and randomly assigned to the control (no semantic auditory distractions) or experimental (semantic auditory distractions) group. Research questions were tested using the general linear model. The results of this study confirmed that semantic auditory distractions have a significant effect on efficiency and effectiveness, and hence they need to be taken into account when evaluating mobile usability. This study also showed that semantic auditory distractions have no significant effect on user satisfaction. This dissertation enhances the current knowledge about the impact of semantic auditory distractions on the usability of mobile applications within the diabetic senior population.

A new hospital in United Arab Emirates (UAE) plans to adopt health information technology (HIT) and become fully digitalized once operational. The hospital has identified a need to assess basic computer literacy of new employees prior to offering them training on various HIT applications. Lack of research in identifying an accurate assessment method for basic computer literacy among health care professionals led to this explanatory correlational research study, which compared self-assessment scores and a simulated actual computer skills test to find an appropriate tool for assessing computer literacy. The theoretical framework of the study was based on constructivist learning theory and self-efficacy theory. Two sets of data from 182 hospital employees were collected and analyzed. A t test revealed that scores of self-assessment were significantly higher than they were on the actual test, which indicated that hospital employees tend to score higher on self-assessment when compared to actual skills test. A Pearson product moment correlation revealed a statistically weak correlation between the scores, which implied that self-assessment scores were not a reliable indicator of how an individual would perform on the actual test. An actual skill test was found to be the more reliable tool to assess basic computer skills when compared to self-assessment test. The findings of the study also identified areas where employees at the local hospital lacked basic computer skills, which led to the development of the project to fill these gaps by providing training on basic computer skills prior to them getting trained on various HIT applications. The findings of the study will be useful for hospitals in UAE who are in the process of adopting HIT and for health information educators to design appropriate training curricula based on assessment of basic computer literacy.

BACKGROUND: Several studies have demonstrated the association between the time to hypertension event and multiple baseline measurements for adults, yet other survival cardiovascular disease (CVD) outcomes such as high cholesterol and heart attack have been somewhat less considered. The Fels Longitudinal Study (FLS) provides us an opportunity to connect adult blood pressure (BP) at certain ages to the time to first CVD outcomes. The availability of long-term serial BP measurements from FLS also potentially allows us to evaluate if the trend of the measured BP biomarkers over time predicts survival outcomes in adulthood through statistical modeling. METHODS: When the reference standard is right-censored time-to-event (survival) outcome, the C index or concordance C, is commonly used as a summary measure of discrimination between a survival outcome that is possibly right censored and a predictive-score variable, say, a measured biomarker or a composite-score output from a statistical model that combines multiple biomarkers. When we have subjects longitudinally followed up, it is of primary interest to assess if some baseline measurements predict the time-to-event outcome. Specifically, in this study, systolic blood pressure, diastolic blood pressure, as well as their variation over time, are considered predictive biomarkers, and we assess their predictive ability for certain time-to-event outcomes in terms of the C index. RESULTS: There are a few summary C index differences that are statistically significant in predicting and discriminating certain CVD metric at certain age stage, though some of these differences are altered in the presence of medicine treatment and lifestyle characteristics. The variation of systolic BP measures over time has a significantly different predicting ability comparing with systolic BP measures at certain given time point, for predicting certain survival outcome such as high cholesterol level. CONCLUSIONS: Adult systolic and diastolic BP measurements may have significantly different ability in predicting time to first CVD events. The fluctuation of BP measurements over time may have better association than BP measurement at a single baseline time point, with the time to first CVD events.

Thesis advisor: John J. Michalczyk / The internet is changing health care right under out very noses. In doing so, it may have great impact on the physician-patient relationship. This relationship exists along a continuum, with paternalism at one end and total patient autonomy at the other. Various aspects of web-based health care (eHealth) are pushing the equilibrium one way or the other. Aspects of eHealth considered include: general health information websites, internet pharmacies, health communication infrastructures (as in physician-patient email and electronic medical records), and finally web-brokered organ transplantation. While there is obviously much to be aware of in terms of quality on the internet, it is concluded that an integration of eHealth into traditional medicine (thus creating cybermedicine) may not only help to mitigate the managed care crisis, but may also change the physician-patient relationship—hopefully for the better. / Thesis (BS) — Boston College, 2005. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: College Honors Program.

Primary care physicians (PCPPs) have been slow to implement electronic health records (EHRs), even though there is a U.S. federal requirement to implement EHRs. The purpose of this phenomenological study was to determine why PCPPs have been slow to adopt electronic health record (EHR) systems despite the potential to increase efficiency and quality of health care. The complex adaptive systems theory (CAS) served as the conceptual framework for this study. Twenty-six PCPPs were interviewed from primary care practices (PCPs) based in southwestern Ohio. The data were collected through a semistructured interview format and analyzed using a modified van Kaam method. Several themes emerged as barriers to EHR implementation, including staff training on the new EHR system, the decrease in productivity experienced by primary care practice (PCP) staff adapting to the new EHR system, and system usability and technical support after adoption. The findings may contribute to the body of knowledge regarding EHR system implementation and assist healthcare providers who are slow to adopt EHRs. Additionally, findings could contribute to social change by reducing healthcare costs, increasing patient access to care, and improving the efficacy of patient diagnosis and treatment.

During the selection and retention process in a medical record technology program, it is advantageous to identify those students who will fulfill the program's course requirements, as well as subsequently pass the accreditation examination. Graduates of such a program at Wbstern Kentucky University were studied to identify these demoaraphic and academic indicators. Using a stepwise multiple regression analysis, the variables of high school grade point average (GPA), college GPA, and composite ACT score were found to be significantly related to medical record GPA. Using the maximum Rsquare improvement technique, the variables of high school GPA, college GPA, age entering the program, English ACT score and number of credits at graduation were found to be significantly related to overall college GPA at graduation. Multiple regression analysis indicated that high school GPA and composite ACT score were found to be the best predictors of overall performance on the accreditation exam, though the relationship was not significant. Using the discriminant analysis technique, several variables were found to be significant in determining which students will pass the exam and which students will fail. Based on information age when entering the program, and number of medical record core courses repeated contributed significantly to the model. The model was applied to the actual data with a pass/fail accuracy rate of 82% for all students and a rate of 84% for those students passing the exam. Based on additional information after graduation, the variables of medical record GPA, composite ACT score, age when entering the program, and number of credits received at graduation contributed significantly to the model. The model was applied to the actual data with a pass:fail accuracy rate of 78% for all students and a rate of 89% for those students failing the exam.

With exponential growth on a daily basis, there is potentially valuable information hidden in complex electronic medical records (EMR) systems. In this thesis, several efficient data mining algorithms were explored to discover hidden knowledge in insurance claims data. The first aim was to cluster three levels of information overload(IO) groups among chronic rheumatic disease (CRD) patient groups based on their clinical events extracted from insurance claims data. The second aim was to discover hidden patterns using three renowned pattern mining algorithms: Apriori, frequent pattern growth(FP-Growth), and sequential pattern discovery using equivalence classes(SPADE). The SPADE algorithm was found to be the most efficient method for the dataset used. Finally, a prototype system named myDietPHIL was developed to manage clinical events for CRD patients’ and visualize the relationships of frequent clinical events. The system has been tested and visualization of relationships could facilitate patient education.

Hydropathic molecular modeling is a computer-aided molecular design technique for obtaining, representing, and understanding the properties and interactions of biomacromolecular complexes in the biological environment. Hydropathic INTeraction (HINT) is a novel empirical force field to calculate the free energy of intermolecular interaction based on experimentally determined partition coefficients (log Po/w). It includes all the expected interactions between molecules such as hydrogen bonding, hydrophobic, electrostatic, acid-base, and Coulombic interactions, entropy, solvation and others. HINT tools were used to determine, evaluate, and analyze protein-ligand interactions in different research projects: 1) We used these tools to discover small molecule inhibitors of PsaA, a potential target for Streptococcus pneumoniae. We screened and scored potential molecules to obtain hits. After the growth conditions for both the wild type and PsaA mutant of S. pneumoniae were optimized, we then tested our hits. A few compounds passed through the three-stage assay protocol and confirmed the inhibition of PsaA with MICs between 125-250 μM. 2) The SAR of C-3 and C-5 pyrrole-based antitubulin agents at the colchicine-binding site with explicitly solvated models was performed. After docking with GOLD at the colchicine site, post-docking scoring and evaluation were performed with HINT. The total HINT score correlates with binding and activity; similarly, the significance of individual functional groups, protein residues and interactions amongst a collection of compounds can be quantitated. The possibility of water-mediated interactions in a way solvent accessible part of the pocket was considered by subjecting molecular models to MD simulations. Several water molecules were identified to be contributing to the binding and were confirmed by HINT scoring. Finally, using hydropathic molecular modeling tools helped us to understand, evaluate, analyze, and improve protein-ligand interactions in different biological systems.

The aim of this study is to examine the impact of a cloud-based CDS alerting system for SIRS, a precursor to sepsis, and sepsis itself, on adult patient and process outcomes at VCU Health System. The two main hypotheses are: 1) the implementation of cloud-based SIRS and sepsis alerts will lead to lower sepsis-related mortality and lower average length of stay, and 2) the implementation of cloud-based SIRS and sepsis alerts will lead to more frequent ordering of the Sepsis PowerPlan and more recording of sepsis diagnoses. To measure these outcomes, a pre-post study was conducted. A pre-implementation group diagnosed with sepsis within the year leading up to the alert intervention consisted of 1,551 unique inpatient visits, and the three-year post-implementation sample size was 9,711 visits, for a total cohort of 11,262 visits. Logistic regression and multiple linear regression were used to test the hypotheses. Study results showed that sepsis-related mortality was slightly higher after the implementation of SIRS alerts, but the presence of sepsis alerts did not have a significant relationship to mortality. The average length of stay and the total number of recorded sepsis diagnoses were higher after the implementation of both SIRS and sepsis alerts, while ordering of the Sepsis Initial Resuscitation PowerPlan was lower. There is preliminary evidence from this study that more sepsis diagnoses are made as a result of alert adoption, suggesting that clinicians can consider the implementation of these alerts in order to capture a higher number of sepsis diagnoses.