Home / Mathematics / TIME SERIES ANALYSIS OF PATIENT ATTENDANCE, UNIUYO TEACHING HOSPITAL

TIME SERIES ANALYSIS OF PATIENT ATTENDANCE, UNIUYO TEACHING HOSPITAL

 

Table Of Contents


<p> </p><p><br>Title page &nbsp; — &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – i &nbsp; &nbsp; </p><p>Declaration — &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; -ii</p><p>Approval page — &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; -iii</p><p>Dedication — &nbsp; &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; -iv</p><p>Acknowledgement — &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; -v &nbsp; &nbsp; </p><p>Table of content &nbsp; — &nbsp; &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; -vi &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Abstract — &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; – &nbsp; &nbsp; &nbsp; -vii</p> <br><p></p>

Project Abstract

ABSTRACT Time series analysis is a powerful statistical method used to understand and predict patterns in data that change over time. In the healthcare sector, analyzing patient attendance data can provide valuable insights for resource allocation, appointment scheduling, and overall hospital management. This study focuses on applying time series analysis techniques to patient attendance data from the University of Uyo Teaching Hospital (UUTH) in Nigeria. The objectives of this research are to analyze historical patient attendance data at UUTH, identify any existing patterns or trends, and develop a forecasting model to predict future patient attendance. The study utilizes a dataset containing daily patient attendance records over a period of several years, capturing information such as the number of patients seen each day, types of medical services provided, and seasonal variations in attendance. The initial step involves exploratory data analysis to understand the distribution of patient attendance over time and detect any anomalies or missing values. Descriptive statistics and data visualization techniques are used to identify patterns such as daily, weekly, and seasonal fluctuations in patient visits. The analysis also includes identifying any outliers or unusual spikes in attendance that may require further investigation. Next, time series modeling techniques such as ARIMA (AutoRegressive Integrated Moving Average) are applied to the patient attendance data to develop a forecasting model. ARIMA models are particularly well-suited for capturing trends, seasonality, and irregular patterns in time series data. By fitting the model to historical data, the study aims to generate accurate predictions of future patient attendance at UUTH. The research also explores the impact of external factors such as public holidays, disease outbreaks, or other events that may influence patient attendance patterns. By incorporating these variables into the forecasting model, the study seeks to improve the accuracy of predictions and provide hospital administrators with valuable insights for capacity planning and resource management. Ultimately, the findings of this study aim to enhance the efficiency and effectiveness of patient care delivery at UUTH by leveraging time series analysis to optimize hospital operations. By understanding and predicting patient attendance patterns, healthcare providers can improve appointment scheduling, allocate resources more effectively, and ensure high-quality care for patients in need.

Project Overview


1.1 INTRODUCTION

University of Uyo Teaching Hospital since its inception in 1994 has received considerable amount of people, for treatment medical advice, family planning and a host of other reason. Different categories of people have patronized the hospital for its efficiency.

It is therefore in the best interest of the researcher to use his or her knowledge of statistic application is the attendance of ill health (patients) attending the hospital. It does not and here the research as will look forward to classifying, arranging and recording the monthly, quarterly, annual, bi-annual attendance of patients in the hospital.

In an attempt to introduce efficient methods and routine towards comparing the total attendance of, in and out patient this in general comprises of male, female and children patient attending the hospital.

To crown it all, it shall be in form of data (secondary, primary data) depending on the set of people wishing to use it and purpose or criterion behind using the research, the data collected will be analysis organized, summarized and compiled. Since hospital patronage is consistent and continuous process, it will be an efficient data collection, centres and will promote statistical application and voluminous data i.e. moving average and time series analysis.

1.2 AIMS OF OBJECTIVE

  1. To determine whether there is an increase or decrease in patients’ attendance.
  2. To forecast the patient attendance by using linear trend method
  3. To forecast for patient attendance using the fitted trend equation from 2008 to 2012

1.3 SCOPE AND LIMITATION

This research will limit it analysis on the comparison of the attendance of patient. (IN and OUT) based on secondary data collected from the hospital University of Uyo Teaching Hospital from (1994 to 2007).

VARIOUS DEPARTMENT OF THE HOSPITAL

The hospital consists of nine (9) departments. The various departments include:

Medical Department: The Medical Director is the overall boss of the hospital. He is only answerable to the AkwaIbom State Commissioner of Health. He is in charge of all medical cases.

Administration Department: Hospital secretary is the head of this department. He heads all the administrative staff of various departments of the hospital and all heads of department are under him and answerable them, as every head administered on his behalf.

Nursing Service Department: The nursing service department is in charge with central of nurses, their posting, their duty roster, their shifting training to other post basic courses.

Medical Record Department: This department deals with keeping record and collection of data.

Laboratory: Technologist works in the laboratory and for the operation of laboratories equipment.

Pharmacy Department:The pharmaceutical department is in charge with the supply of drugs, drugs custody, drug protection and storage etc.

Radiology Department: The radiology is in charge with x-ray e.g. chinstraps etc.

Ophthalmology Department:Ophthalmology department is in charge with all cases of eye, its treatment etc.

E.N.T Department: This department is in charge with all cases of ear


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