Engineering Showcase: Transforming Surgical Data Management for Enhanced Patient Care

Introduction: Comprehensive data collection of surgical data

A healthcare organisation has been undertaking a widespread data collection initiative, gathering information on surgery activities in numerous hospitals. This data is collected routinely, analysed, and benchmarked against various indicators to facilitate improvements in surgical care and efficiency in healthcare facilities.

Facing the challenge of increasing data volume and the complexity of analyses, the organisation identified the need to upgrade their data management infrastructure. They sought Edge Health‘s expertise to transition to a modern cloud-based solution that would accommodate large-scale data collection and analysis while ensuring security and accessibility.

Methodology: Engagement, modern tools, light touch process

We worked closely with the client’s team to co-develop a robust data pipeline and a versatile metric engine capable of dynamically constructing metrics, such as utilisation rates, based on all collected data, updated bi-weekly. These metrics were then securely made accessible to authorised users across the organisation.

The data pipeline was built using Azure and Databricks, leveraging a unified data access layer to ensure seamless integration and efficient data management.

The data management workflow begins with healthcare providers submitting anonymised data to a centralised system. This data undergoes rigorous quality checks in managed databases. Our custom-built pipelines then restructure and segment the data, streamlining the analysis process. A specially designed metric engine calculates various performance indicators, which are then visualised on dashboards for a wide user base.

The result: A modern infrastructure that is continuously operating to provide insight

The new infrastructure now continuously processes theatre data from operations across all submitting organisations and displays it back to enable benchmarking and improvement on the ground. The transition to this new infrastructure was smooth, with significant improvements in processing power, robustness, and automated data handling.

The updated system has markedly increased processing speed and improved data access. It supports a larger number of concurrent users and offers quicker response times for data queries. These advancements have greatly enhanced the ability of analysts to access and utilise information, leading to better-informed strategies for healthcare improvement.

Automation of data operations has further optimised the system’s efficiency. Routine updates and tasks are now managed automatically, minimising errors and saving valuable time.