Hospital-Wait-Time-Analysis

Hospital Wait Time Analysis – Data-Driven Solutions for Better Patient Experience

Problem Statement:

A clinic has been receiving numerous complaints about long wait times from patients. Addressing this is critical to improving patient satisfaction, operational efficiency, and overall healthcare delivery.

Analysis Overview:

After conducting a thorough analysis of hospital data, the following key insights and recommendations emerged:

Key Findings:

1. Overall Wait Time Analysis: The average wait time (38.91) is significant (benchmark in US 30 minutes, p-value: 0.001), highlighting a systemic issue that requires immediate attention. High variability in wait times during peak periods indicates potential bottlenecks in patient flow.

2. Time-Based Patterns: Certain days of the week consistently experience longer wait times. Peak hours during the day lead to substantial increases in wait times. 🔹 Recommendations: Adjust staffing levels for high-volume days. Improve appointment scheduling to manage peak hours effectively. Allocate additional resources during busy periods.

3. Doctor Type Impact: Wait times differ notably across various doctor types and specialties. 🔹 Recommendations: Address potential understaffing in specific specialties. Develop and implement optimized scheduling algorithms. Redistribute patient loads more evenly among available doctors.

4. Financial Class Analysis: Patients from different financial classes experience varying wait times. 🔹 Recommendations: Address inefficiencies in handling certain insurance types. Streamline documentation and check-in processes. Standardize procedures across all financial classes to ensure equity.

Actionable Recommendations:

1. Staffing Optimization: Increase staffing during peak hours and high-demand days.
2. Process Improvements: Streamline check-in and patient registration for faster processing.
3. Patient Flow Management: Introduce a real-time queue management system.
4. Monitoring & Continuous Improvement: Establish real-time wait time monitoring with alert systems.

How to run the code:

1. Prerequisites:

• Install the required libraries: pip install pandas plotly dash

2. Run the code:

• Place the dataset (hospital_data_sampleee.xlsx) in the same directory as the code.
• Run the script: python hospital_dashboard.py
• Open the dashboard in your browser at http://127.0.0.1:8050.