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Introduction

Hospital readmission rates have become a critical metric in healthcare as they are indicators of the quality of care provided to patients. High rates of readmission not only indicate poor patient outcomes but also pose significant financial burdens on healthcare systems. Predicting hospital readmission rates has therefore become a crucial area of research, with the potential to improve patient outcomes and reduce healthcare costs.

This thesis aims to explore the various factors that contribute to hospital readmissions and develop predictive models to identify patients at high risk of readmission. By understanding the underlying causes of readmissions and implementing effective prediction models, healthcare providers can intervene early and provide targeted interventions to prevent costly readmissions.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Overview of hospital readmission rates
2.2 Factors contributing to hospital readmissions
2.3 Existing predictive models for readmission rates
2.4 Importance of early intervention in reducing readmissions
2.5 Impact of readmissions on healthcare costs
2.6 Patient characteristics associated with high readmission rates
2.7 Role of healthcare providers in reducing readmission rates
2.8 Technology and data analytics in predicting readmission rates
2.9 Strategies for reducing readmission rates
2.10 Gaps in current research on predicting hospital readmission rates

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Data analysis techniques
3.4 Selection of variables for predictive modeling
3.5 Model validation strategies
3.6 Ethical considerations
3.7 Pilot testing
3.8 Sample size determination

Chapter 4: Discussion of Findings
4.1 Descriptive analysis of study population
4.2 Factors influencing hospital readmission rates
4.3 Development of predictive models
4.4 Model performance evaluation
4.5 Comparison with existing models
4.6 Implications for healthcare providers
4.7 Recommendations for future research
4.8 Challenges and limitations of the study

Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Implications for healthcare practice
5.3 Limitations of the study
5.4 Future research directions
5.5 Conclusion

Thesis Overview

Hospital readmission rates have emerged as a critical issue in healthcare, with implications for both patient outcomes and healthcare costs. This thesis aims to explore the factors contributing to hospital readmissions and develop predictive models to identify patients at high risk of readmission. By understanding the underlying causes of readmissions and implementing effective prediction models, healthcare providers can intervene early and provide targeted interventions to prevent costly readmissions.

The literature review in Chapter 2 provides an overview of hospital readmission rates, factors contributing to readmissions, existing predictive models, and strategies for reducing readmission rates. Chapter 3 outlines the research methodology, including research design, data collection methods, data analysis techniques, and model validation strategies. Chapter 4 discusses the findings of the study, including the development of predictive models, model performance evaluation, and implications for healthcare providers. Finally, Chapter 5 presents the conclusion and summary of the project, highlighting key findings, implications for practice, limitations of the study, and recommendations for future research.

Overall, this thesis aims to contribute to the growing body of research on predicting hospital readmission rates and provide valuable insights for healthcare providers seeking to improve patient outcomes and reduce healthcare costs.

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