Delayed Transfers of Care

Introduction

This project visualizes NHS Delayed Transfers of Care (DTOC) data through an interactive Power BI dashboard. It focuses on understanding delay patterns across local authorities and responsible organizations, helping improve patient discharge processes and hospital efficiency.

Problem Statement

Delayed Transfers of Care often result in resource strain, extended hospital stays, and reduced service capacity. Without clear analytics, identifying where and why these delays occur can be challenging. This project transforms raw NHS DTOC data into actionable insights for better operational planning and performance evaluation.

Key Objectives

  • Build a Power BI dashboard analyzing delay patterns by authority and organization.
  • Identify key reasons behind delayed discharges.
  • Improve data visibility for healthcare performance management.
  • Support evidence-based decisions to optimize patient flow.

Data Sources

  • Removed null and duplicate records.
  • Standardized column headers and data types.

Data Cleaning

  • Removed null and duplicate records.
  • Standardized column headers and data types.
  • Created calculated columns for delay reasons and total delayed days.

Data Modeling

  • Established relationships between local authority, responsible organization, and delay categories.
  • Created DAX measures for Total Delayed Days, NHS Delays, Social Care Delays, and Joint Delays.
  • Implemented filters for Year, Month, and Responsible Organization.

Dashboard Design

  • Clean and minimal layout for easy navigation.
  • KPI cards summarizing Total, NHS, Social Care, and Joint Delays.
  • Donut charts for Delay Reasons and Responsible Organizations.
  • Bar charts comparing performance across local authorities.

Data Modeling

  • NHS accounted for the highest proportion of delayed days.
  • Certain local authorities showed recurring delay trends due to social care coordination.
  • Joint delays were minimal but highlighted gaps in inter-agency communication.
  • Visualizing trends over time revealed seasonal spikes requiring targeted action.

Summary

The dashboard successfully highlights patterns in NHS delayed transfers, offering transparency and accountability across organizations. It converts complex datasets into accessible insights, enabling strategic improvement in patient flow management.

Learnings

  • Data modeling consistency is crucial for accurate KPI calculations.
  • Visualization clarity directly impacts decision-making confidence.
  • Stakeholder-focused dashboards improve communication between NHS and social care teams.
Link to the Project See Report here