Health Care Analytics With Microsoft Excel

Introduction

In this project, I carried out data analysis on this healthcare dataset of a hospital using Microsoft Excel, the aim of this exploratory data analysis was to gain insights into the most relevant factors that affect patient care.
This report provides a comprehensive analysis of the patient dataset, focusing on the following key variables: Gender, Medical Condition, Insurance Provider, Billing Amount, and Medication.
The objective of this analysis is to uncover trends and insights that can inform healthcare management decisions, improve patient care, and optimize billing processes.
Data cleaning, analysis, exploration and visualization was done using just Microsoft Excel.

Data Structure And Preparation

The dataset for this project was gotten from kaggle.com
The dataset contains Fourteen columns and over Ten thousand and one rows. Records in the dataset include; Gender, Medical Condition, Insurance Provider, Billing Amount, Medication, Admission type, Test results and so many more.
Here is what the dataset looks like:

Data Cleaning And Preparation

The dataset had no outliers, errors, duplicates, missing rows and columns, so the data cleaning process was smoothly done

Analysis And Insights:

An overview of the dashboard shows the most important metrics captured and analysed from the dataset, which include; Count of Patients By Gender, Number of patients per medical condition and the Total billing amount by insurance provider.

1)Count of patients By Gender:

Male Patients: The analysis shows that there are 4,925 male patients, accounting for 49% of the total patient population.

Female Patients: There are 5,075 female patients, representing 51% of the total patient population.
•The patient population is relatively evenly split, with a slight majority of female patients.
•The difference in percentage between male and female patients is just
2%.

2)Number of Patients per Medical Condition

Asthma: The analysis indicates that asthma is the most prevalent condition, with the highest number of patients diagnosed. This suggests a significant public health concern, requiring focused medical attention, patient education, and resource allocation. High asthma prevalence could be linked to environmental factors, genetic predisposition, or other socio-economic conditions.

Diabetes: On the other end of the spectrum, diabetes has the lowest patient count. While it is less prevalent compared to asthma, diabetes remains a critical condition requiring continuous management and monitoring. The lower count may be attributed to effective preventive measures, early detection, and management strategies, or possibly underreporting.

3) Total Billing Amount by Insurance Provider

Cigna: The analysis indicates that Cigna accounts for the highest total billing amount among the insurance providers. This implies that a significant portion of the healthcare provider’s revenue comes from patients insured by Cigna, the high billing amount could be due to the volume of services provided or the higher reimbursement rates negotiated with Cigna.

Medicare: On the other hand, Medicare has the lowest total billing amount. This could be attributed to lower reimbursement rates, fewer Medicare-covered patients, or a combination of both. Understanding this disparity is crucial for financial planning and resource allocation.

Overview of the Dashboard: