*Purpose: The future of medicine will be enabled by big data. With the promise of data-driven knowledge and decision-making, innovative big-data projects are ongoing in every area of medicine. Data driven decisions are well balanced and more insightful. We have integrated Business Intelligence(BI) software solution based on our centre’s Electronic Health Record (EHR) and ancillary clinical databases. This has enabled deeper insight with unprecedented speed into our clinical work and outcome.

*Methods: All software used are as follows, Microsoft (MS) SQL Management Studio 17, MS Power BI Desktop and R 3.5 with the Integrated Development Environment (IDE), our EHR transplant database. Connection to various data sources is direct and real time. The data is first extracted, combined and then transformed in data warehouse. Different data models are created which are easily shared for reports. Visually Rich interactive and responsive dashboards are then configured to display data in different visualisations(fig1)

*Results: We’ve been using the above methods since the start of 2018. The results are quick and accurate. It has identified past performance patterns and provided future performance projection data. We have improved management of transplant wait list as it provided instant update and cross validation on the patient’s status. We’ve combined surgical complication and medical data models to gain greater insight in order to identify and improve risk factors. It has provided greater insight into our transplant results and complications. It has streamlined data recall process which is performed in an instant using natural language query. Such exercise would be slow moving and burdensome otherwise, thereby improving productivity. By highlighting data errors e.g. missing and duplicate entries, it has provided a feedback loop for data cleansing and completion leading to improvement in patient follow up and outcomes.

*Conclusions: BI has become essential tool in many industries. For health industry it offers real time data-based insight which can serve to track and improve quality of care. Future use of BI could include machine learning as an aid to decision making in complex clinical scenarios.

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