1.0 INTRODUCTION:
This chapter gives an overview on the aims, objectives, background of the study and operation environment of the system.
1.1 BACKGROUND OF THE STUDY
Appointment scheduling systems are used by primary and specialty care clinics to manage access to service providers, as well as by hospitals to schedule elective surgeries. Many factors affect the performance of appointment systems including arrival and service time variability, patient and provider preferences, available information technology and the experience level of the scheduling staff. In addition, a critical bottleneck lays in the application of Industrial Engineering and Operations Research (IE/OR) techniques. The most common types of health care delivery systems are described in this article with particular attention on the factors that make appointment scheduling challenging. For each environment relevant decisions ranging from a set of rules that guide schedulers to real-time responses to deviations from plans are described. A road map of the state of the art in the design of appointment management systems is provided and future opportunities for novel applications of IE/OR models are identified.
Appointment Management system is a desktop application that is designed to help fix schedule and appointment from the management of organization and the customers, send messages to customers either by phone or email. With this computerized system there will be no loss of record or member record which generally happens when a non – computerized system is used. It is designed in Visual Studio and the database used is Microsoft SQL Server 2005.
1.2 STATEMENT OF THE PROBLEMS
There are problems found in appointment which include:
1.3 OBJECTIVE OF THE STUDY
The project aims and objectives that will be achieved after completion of this project are discussed in this subchapter. The aims and objectives are as follows:
SCREEN SHOTS OF THE APPLICATION
1.4 SIGNIFICANCE OF THE STUDY
The significance of this study is to help and give benefits to students, staff and school management of knowing what appointment system is all about and the problems found in appointment.
1.5 LIMITATION OF THE STUDY
1.6 SCOPE OF THE STUDY
This research work will concentrate on creating new appointment, and other details will be viewed for entry by the student as the case may be, with a case study of UNITECH HOSPITAL.
1.7 ASSUMPTION OF THE STUDY
During the process of data collection, information relating to Appointment Management System was obtained from the Internet (www.wikipedia.com/appointment). The information was collected during the course of my industrial attachment. Hence, it is assumed that all the data collected are correct and contains no false information.
1.8 DEFINITION OF TERMS
📚 Over 50,000 Project Materials
📱 100% Offline: No internet needed
📝 Over 98 Departments
🔍 Software coding and Machine construction
🎓 Postgraduate/Undergraduate Research works
📥 Instant Whatsapp/Email Delivery
The project topic, "Predicting Disease Outbreaks Using Machine Learning and Data Analysis," focuses on utilizing advanced computational techniques to ...
The project on "Implementation of a Real-Time Facial Recognition System using Deep Learning Techniques" aims to develop a sophisticated system that ca...
The project topic "Applying Machine Learning for Network Intrusion Detection" focuses on utilizing machine learning algorithms to enhance the detectio...
The project topic "Analyzing and Improving Machine Learning Model Performance Using Explainable AI Techniques" focuses on enhancing the effectiveness ...
The project topic "Applying Machine Learning Algorithms for Predicting Stock Market Trends" revolves around the application of cutting-edge machine le...
The project topic, "Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems," focuses on the integration of machine learn...
Anomaly detection in Internet of Things (IoT) networks using machine learning algorithms is a critical research area that aims to enhance the security and effic...
Anomaly detection in network traffic using machine learning algorithms is a crucial aspect of cybersecurity that aims to identify unusual patterns or behaviors ...
Predictive maintenance is a proactive maintenance strategy that aims to predict equipment failures before they occur, thereby reducing downtime and maintenance ...