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https://github.com/ninadpatil09/hospital_emergency_room_analysis

This comprehensive analysis delves into the performance and characteristics of the hospital's emergency room over the past year. By scrutinizing key metrics and patient demographics, this study aims to provide valuable insights for optimizing patient care, resource allocation, and overall operational efficiency.
https://github.com/ninadpatil09/hospital_emergency_room_analysis

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This comprehensive analysis delves into the performance and characteristics of the hospital's emergency room over the past year. By scrutinizing key metrics and patient demographics, this study aims to provide valuable insights for optimizing patient care, resource allocation, and overall operational efficiency.

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# Hospital_Emergency_Room_Analysis



# Overview

This comprehensive analysis delves into the performance and characteristics of the hospital's emergency room over the past year. By scrutinizing key metrics and patient demographics, this study aims to provide valuable insights for optimizing patient care, resource allocation, and overall operational efficiency.



Tableau Public Dashboard Link - https://public.tableau.com/app/profile/ninad.patil/viz/Tableau-EmergencyRoomDashboard/Dashboard1



![Dashboard 1 (2)](https://github.com/NiNja-09/Hospital_Emergency_Room_Analysis/assets/60342946/d0879642-20d1-49c8-ae6e-5678eed60c8a)



# Insights

1. Average Waiting Time and Patient Satisfaction:



The average waiting time of 35.26 minutes indicates the time patients spend waiting before receiving medical attention in the emergency room.

Despite the relatively short wait time, the average patient satisfaction score of 4.99 out of 10 suggests that patients are generally dissatisfied with the waiting experience.



2. Patient Demographics:



Over the past year, a total of 9,216 patients visited the emergency room.

The gender distribution shows a near-equal split, with females comprising 48.69%, males 51.05%, and a small portion not confirmed (0.26%).

The major patient age group is between 19 and 65 years, indicating that the working-age population is more likely to require emergency medical care.



3.Department and Specialty Distribution:



The General Practice Department has the highest patient intake, with a focus on orthopedics and physiotherapy.

The distribution of patients across different departments suggests a higher demand for orthopedics and physiotherapy services.

Gastroenterology and renal departments have recorded fewer patients compared to other departments, indicating potential areas for improvement in attracting patients or managing referrals.



4. Patient Race and Ethnicity:



White and African American patients are the most common racial/ethnic groups in the patient population.

The hospital serves a diverse patient population, which may require culturally sensitive care.



5.Variability in Wait Times:



The analysis reveals variations in average wait times throughout the day.

On some occasions, patients experience relatively shorter wait times of 3 to 4 hours, indicating efficient handling during those periods.

However, there are instances of higher average wait times, particularly during a single hour or for 3 hours during certain times of the day.

Identifying the reasons behind these fluctuations could lead to better resource allocation and improved patient experience.



6. Age Distribution:



Patients in the age groups of 0-18 and 66+ are roughly equal in number, suggesting a relatively consistent need for emergency care across different age brackets.



# Conclusion

In conclusion, the analysis of the hospital emergency room data provides insights into various aspects of patient demographics, departmental preferences, waiting times, and patient satisfaction. These insights could be used to optimize resource allocation, improve patient experience, and tailor medical services to better meet the needs of the diverse patient population. Additionally, addressing the low patient satisfaction score and understanding the reasons behind the variability in wait times are critical areas for improvement.