Identifying cost savings and efficiencies from patient records and administration systems
Healthcare providers are under continuous pressure to deliver world-class services for patients both in terms of the medical procedures as well as the overall experience of the treatment process, within tight financial controls. Hospital administrators are faced with the daily task of balancing the needs of patients with the complexities of managing thousands of doctors, nurses and ancillary staff as well as the facilities and technical resources it takes to maintain an efficient, modern-day health service.
In order to ensure that these twin objectives are met within the constraints of a restricted budget administrators need to regularly review accepted processes and procedures and identify the changes that could deliver efficiency improvements and potential cost savings. A difficult thing to do in a busy and complex, working hospital environment without the ability to take a step back and look at every aspect of every patient interaction from an objective viewpoint. A mammoth task involving detailed analysis of thousands, if not millions of data points that would need months of work to complete.
Xanadata’s big-data analytics platform incorporates the latest parallel processing power and machine learning algorithms needed to extract actionable intelligence from terabytes of unstructured data in hours rather than the days, weeks or months normally required. With a range of reporting options available, including a unique 3D augmented intelligence visualisation of the scanned data, hospital administrators are provided with a detailed analysis based on quantifiable evidence of where a particular process could be improved for both the benefit of the patients and the front-line staff.
Using its advanced AI and machine learning algorithms Xanadata provides granular analysis of the massive data-sets and identifies patterns and behaviours from an array of sources that would otherwise be difficult, if not impossible, to spot using traditional methodologies and limited human processing power. By significantly speeding up the data scanning element of the analytics project, healthcare providers can rapidly reap the benefits of deploying the resultant cost and proficiency improvement changes without the extensive delays associated with typical operational review timescales.
• Patient treatment records
• Ward Management
• Patient treatment-path analysis – Admission to Discharge
• Cost and Efficiency Savings
• Solution Brief
• Case Study