Hospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts. In this study, we will be proposing a framework on how the readmission analysis and other healthcare models could be deployed in real world and a Machine learning based solution which uses patients discharge summaries as a dataset to train and test the machine learning model created. Current systems does not take into consideration one of the very important aspect of solving readmission problem by taking Big data into consideration. This study also takes into consideration Big data aspect of solutions which can be deployed in the field for real world use. We have used HPCC compute platform which provides distributed parallel programming platform to create, run and manage applications which involves large amount of data. We have also proposed some feature engineering and data balancing techniques which have shown to greatly enhance the machine learning model performance. This was achieved by reducing the dimensionality in the data and fixing the imbalance in the dataset. The system presented in this study provides a real world machine learning based predictive modeling for reducing readmissions which could be templatized for other diseases. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

Magister Legum - LLM / A person should at all times try to avoid the blemish of a previous conviction and a criminal record entered against his name. A criminal record entered against his name could have detrimental consequences for an individual. An accused is usually aware of this if he is involved in a trial and is thereafter convicted and sentenced. However, the same result could occur where a person paid an admission of guilt fine. Such a person could be aware that he has attained a record, but it could also be that a payee1 of a fine is very unaware that he has attained a criminal record that is entered against his name. This study focusses on the legal consequences of the payment of such an admission of guilt fine and will endeavour to investigate the remedies available to an uninformed payee of such fines.

ABSTRACT Predicting On-the-Job Teacher Success Based on a Group Assessment Procedure Used for Admission to Teacher Education by LaVaun Gene Faulk, Doctor of Education Utah State University, 2008 Major Professor: Deborah Byrnes, Ph.D. Department: Elementary Education Students who have graduated in Elementary Education at Utah State University, since 1997 when the group assessment interview procedure was adopted, and have been employed as teachers for at least two years were contacted. Students were located with the help of the Utah State Office of Education (USOE) and the Office of Teacher Education, Graduation, and Educator Licensing at USU. Permission to interview each teacher’s supervisor was obtained from each study participant. Principals were contacted and interview dates set. A self-anchoring interview was conducted to provide quantitative data on the success of each teacher. This new data was then used to compare each participant’s success as seen by supervisors to existing data already on record at USU. Specifically, principal interview data were compared to the participant’s student teaching scores, prior academic achievement data (grade point average and American College Test scores), and ratings the teacher received on the group assessment interviews when applying to the elementary education teacher training program at USU. (107 pages)

Factors in the Admissions Process Influencing Persistence in a Master’s of Science Program in Marine Science. Melissa L. Dore, 2017: Applied Dissertation, Nova Southeastern University, Abraham S. Fischler College of Education. Keywords: academic persistence, admission counseling, graduate students, marine science education, examinations This applied dissertation was conducted to provide the graduate program in marine sciences a valid predictor for success in the admissions scoring systems that include the general Graduate Record Exam. The dependent variable was persistence: successfully graduating from the marine sciences master’s programs. This dissertation evaluated other values including the applicant’s age, gender, undergraduate GPA, letters of recommendation, and acceptance level (Accepted with Academic Requirement (probation) or Full Acceptance). The writer statistically showed that two values proved most significant in defining a student’s persistence: undergraduate major GPA and age when entering the program. An analysis of the data allowed the marine science master’s programs to develop an index to assist students to succeed in the program as well as reduce the time to completion.

A comparison of the voluntary and involuntary patients at Dammasch State Hospital, Wilsonville, Oregon. A representative sample of cases over time, were chosen for the year 1976, 72 voluntary and 72 involuntary patients. One-hundred and twelve variables were coded onto sheets for each patient. The variables concerned marital status, job history, history of violent acts, present living situations and relationships, as well as drug history and diagnosis and treatment in the hospital. The data were coded onto cards and a computer analysis was done using Factor and Discriminant Function Analysis. It was hypothesized the populations of persons voluntarily admitted and involuntarily committed would be different in several ways. (A) The population of involuntarily committed persons would have more anti-social aggression in their histories. This hypothesis was partially supported by the data. The involuntarily committed had a significantly higher incidence of being under a current legal charge at the time of commitment. There was no significant difference between the two populations in the number of previous incarcerations or on 'violence committed within the family'. (B) Persons involuntarily committed would have significantly fewer relationships with persons in the community and fewer ties to persons they support financially or emotionally or that support them emotionally or financially. This hypothesis was partly supported by the data. The two populations were approximately equal on all the variables of relationship and living conditions except 'lives with mate'; for this variable the voluntary patients had a higher score. (C) Involuntarily committed persons would have less successful job histories. None of the items of the job history were significantly different in the two populations. (D) The involuntary population was more likely to have alcoholism as a secondary diagnosis. The voluntary population was more likely to have alcoholism as a primary diagnosis. This hypothesis was not clearly supported by the data. It was found that the voluntary population was more likely to abuse alcohol and the involuntary population was more likely to use alcohol. (E) The involuntary population was more likely to have experienced violence in their homes, while children. There were insufficient data in the hospital records concerning childhood to test this hypothesis. In the factor which contained the variable 'commitment' there were no elements of a history of dangerousness. The only significant correlation with commitment was 'prescription of phenothiazines in the hospital'; this result may point to the use of drugs as 'chemical restraints'. No other variable which indicated relationships, job history, social status, or dangerousness correlated significantly with commitment. These were the most important findings in the study.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第20623号 / 社医博第81号 / 社新制||医||9(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 木原 正博, 教授 中川 一路, 教授 平家 俊男 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

The purpose of this study was to determine factors that impact the final grades of full admission and developmental students who were enrolled in selected 22 undergraduate business courses during the fall 2015 and spring 2016 semesters. Also, this study examined the interaction of students’ ethnicity, gender, age, and classification on their final course grades in selected business courses at a rural public HBCU. The research design for this study was casual-comparative research. A 2X2 and a 2X4 factorial ANOVA was used to determine whether there was a main effect on students’ final grades considering each independent variable. Out of a population of 393 students enrolled, 320 students participated in this study. After the data were collected and analyzed, the researcher determined that there was a statistically significant relationship between student’s final grade and course delivery, ethnicity, and classification. There was no statistically significant interaction on student’s final grades between course delivery and student admission status, gender, age, ethnicity, and classification. Conclusion and recommendations based on the findings in this study indicated that students attending the rural public HBCU and enrolled in business courses that offered the same courses in both face-toace and online formats performed better in face-toace courses than in the online courses.

Hospitals around the country are struggling to provide timely access to inpatient beds. We use discrete event simulation to study the inpatient admission and discharge processes in US hospitals. Demand for inpatient beds comes from two sources: the Emergency Department (ED) and elective surgeries (NonED). Bed request and discharge rates vary from hour to hour; furthermore, weekday demand is different from weekend demand. We use empirically collected data from national and local (Massachusetts) sources on different-sized community and referral hospitals, demand rates for ED and NonED patients, patient length of stay (LOS), and bed turnover times to calibrate our discrete event simulation model. In our computational experiments, we find that expanding hours of discharge, increasing the number of days elective patients are admitted in a week, and decreasing length of stay all showed statistically significant results in decreasing the average waiting time for patients. We discuss the implications of these results in practice, and list the key limitations of the model.

Indiana University-Purdue University Indianapolis (IUPUI) / Postdischarge follow-up appointments are widely thought to improve the safety of transition for patients moving from the hospital to home. They provide an opportunity for outpatient primary care providers to detect problems or failures of postdischarge care. Readmissions can be used to reflect the quality of postdischarge or transitional care. This study evaluated whether patients with an outpatient follow-up appointment scheduled with their primary care provider within five calendar days of discharge had fewer 30-day readmissions than those patients who had appointments scheduled six days or longer from discharge. No difference in readmission rate was detected between the two groups.

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