Introduction

Hospital readmissions remain one of the most pressing challenges in healthcare systems. They not only affect patient outcomes but also place additional strain on hospital resources. As part of a recent project, I analyzed hospice patient records to uncover patterns in admissions, discharges, and readmissions. The goal was to provide actionable insights for government funding justification and quality of care improvement.

🏥 Project Overview

Total patients served: 2,404

Total discharged: 1,592 (≈66% discharge rate)

Total readmissions: 2,250 (≈94% readmission rate — very high)

Average length of stay: 86 days

Top diagnoses: Dementia, Digestive organ diseases, Respiratory diseases

This analysis was done using Power BI dashboards, which helped visualize patient journeys and highlight operational bottlenecks.

🔍 Key Problems Identified

1. High Readmission Rate

94% of patients were readmitted, suggesting serious gaps in follow-up care and chronic disease management.

Older patients (75+ years) were the most vulnerable, with conditions such as dementia, heart disease, and urinary tract infections dominating readmissions.

2. Capacity & Service Strain

With an average length of stay of 86 days, staff, bed space, and equipment were under immense pressure.

Seasonal spikes in admissions (Feb–Apr) further highlighted resource gaps.

3. Chronic Disease Burden

Admissions were dominated by long-term illnesses such as dementia and digestive system diseases, requiring continuous and specialized care.

4. Data Quality Issues

Wrongly entered admission, discharge, and readmission dates affected the accuracy of the analysis.

Lack of a unified system to track patients across multiple visits.

💡 Insights

The facility is managing complex, chronic conditions with limited resources.

High readmission rates reflect both patient medical needs and gaps in continuity of care.

Data quality issues underscore the importance of adopting digital health solutions like Electronic Medical Records (EMR).

✅ Recommendations

1. Readmission Reduction Strategies

Post-Discharge Programs: Follow-up calls, home visits, and medication adherence monitoring.

High-Risk Clinics: Specialized outpatient clinics for chronic diseases (e.g., dementia, heart failure).

Community Care: Partnerships with local health workers for elderly patient support.

Predictive Monitoring: Use Power BI dashboards to develop readmission risk scores.

2. Funding Advocacy

Present government agencies with case-mix severity evidence to justify funding for staff, infrastructure, and specialized equipment.

Highlight average length of stay (86 days) and chronic disease admissions to support the case for continuous funding.

3. Data Quality & EMR Implementation

Deploy an Electronic Medical Records (EMR) system to ensure accurate and consistent data capture.

Key EMR features should include:

Patient Unique ID for tracking across multiple admissions.

Structured fields for admission/discharge dates.

Integration with reporting tools for real-time dashboards.

Benefits include stronger funding justification, improved care continuity, and reliable analytics for decision-making.

👥 My Role in the Project

I worked as the Data Analyst, responsible for:

Cleaning and preparing raw patient data.

Building Power BI dashboards to visualize admissions, discharges, and readmissions.

Conducting the statistical analysis and translating findings into actionable insights.

Collaborating with healthcare administrators, clinical staff, IT/data teams, and management to interpret results and design solutions.

🎯 Outcome

Produced interactive dashboards that revealed critical patient care and resource gaps.

Highlighted the need for targeted post-discharge programs to reduce readmissions.

Demonstrated the importance of accurate data collection and made the case for adopting an EMR system.

Equipped management with evidence-based insights to strengthen government funding requests.

📌 Conclusion

This project showed how data-driven healthcare management can uncover hidden challenges, guide funding decisions, and directly improve patient outcomes. By adopting EMRs and targeted care strategies, hospitals can both reduce readmissions and provide stronger evidence for government and donor support.

Author: Chinenye Joy Asogwa