Project Description
Healthcare is a critical sector that directly affects individuals' quality of life. In this project, we will evaluate hospital performance, treatment costs, patient satisfaction and overall quality of healthcare by analyzing various healthcare data. Our goal is to increase the efficiency of healthcare, increase patient satisfaction and improve the performance of healthcare providers. This analysis will assist healthcare managers and policy makers in improving service quality and optimizing healthcare systems.
Project Usage Areas
This project has several uses for healthcare administrators, hospital administrators and healthcare policy makers:
Evaluation of Hospital Performance: Evaluating the performance of hospitals in terms of capacity utilization, treatment costs and patient satisfaction.
Analysis of Treatment Costs: Identifying ways to increase cost effectiveness by analyzing the costs of different types of treatment.
Examining Patient Satisfaction: Identifying ways to increase patient satisfaction by analyzing patient feedback.
Improving the Quality of Healthcare: Improving the overall quality of healthcare services by analyzing efficiency and quality indicators.
Policy and Strategy Development: Developing effective health policies and strategies using health services data.
Dataset Description
The data set to be used in this project includes health services data. The dataset consists of four main files in total:
patients
PatientID: Patient ID
PatientName: Patient name
BirthDate: Date of birth
Gender: Gender
Country: Country
Hospital Information (hospitals)
HospitalID: Hospital ID
HospitalName: Hospital name
Location: Location (City, Suburban, Rural)
Capacity: Capacity (number of beds)
Rating: Evaluation (between 1-5)
Treatment Records (treatments)
TreatmentID: Treatment ID
PatientID: Patient ID
HospitalID: Hospital ID
TreatmentDate: Treatment date
TreatmentType: Treatment type (Surgical, Medication, Therapy, Control)
Cost: Cost
Patient Feedback (patient_feedback)
FeedbackID: Feedback ID
PatientID: Patient ID
HospitalID: Hospital ID
FeedbackDate: Feedback date
Rating: Evaluation (between 1-5)
Comments: Comments
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate healthcare performance and make strategic decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
If you want to lay the foundations of Python and gain competence in data analysis and science, you can immediately register for a 1-month intensive Python camp. Take a look now at the interactive and practice-oriented training program developed in Helsinki, inspired by Finnish education models, consisting of ~40 hours of live lessons, ~50 comprehensive projects, ~15 quizzes and countless coding exercises!