Integrated care is one of healthcare’s cornerstone strategies, and is key to reducing the inefficiencies present in traditional health systems. However, it necessitates a fundamental shift to value-based healthcare – a data-driven approach which derives insights from the analysis of complex datasets. And while value-based healthcare delivery is widely acknowledged to deliver better outcomes for patients, translate scientific discoveries into patient benefit, and help restructure care delivery, its implementation continue to present both opportunities and challenges.
“The benefits that accrue from the system that Aridhia is developing are enormous… I think that the system will be foolproof.” Mr John Hines, Pathway Director, London Cancer
AnalytiXagility maximises the potential of healthcare’s existing data by establishing a secure data lake, driven by datasets, ontologies and information governance, to enable the rapid acceleration of local analytic capability and support the move towards value-based healthcare delivery.
Combining collaborative agile data linkage and advanced analytical tools and models to answer population and disease focused questions, AnalytiXagility can be used to enhance service delivery, stratify patient risk and improve clinical outcomes, all while adhering to strict information governance requirements.
AnalytiXagility directly supports the NHS National Information Board’s framework for utilising data and technology to transform outcomes for patients and citizens, while offering a significant reduction in costs compared to traditional approach to data management.
AnalytiXagility Project Edition is available on a subscription basis via the UK Government’s G-Cloud Digital Marketplace, delivering a physical connection to the NHS N3 private network, and permitting end user connectivity from NHS trust sites.
AnalytiXagility services are currently being deployed to analyse and visualise data across an integrated care pathway for renal cancer for London Cancer – a partnership of NHS, academic, charity and cancer specialists. Combining data from several source systems, the 62 day journey from referral to treatment will be visualised, enabling referring and renal specialists to analyse the pathway across organisations and patients. Download the full London Cancer case study.
In Scotland, at NHS Tayside and NHS Fife, an AnalytiXagility patient and cancer tracking solution integrates a variety of data sources for use by administrative staff. This solution replaces manual analysis, delivering an improved reporting mechanism which frees up staff to focus on other core tasks, and makes it easier and more cost-effective for the boards to produce reliable and accurate reporting. The service includes tracking for NHS Scotland’s 18-week referral-to-treatment guarantee, stage of treatment waiting-times guarantee and radiology diagnostic monthly monitoring information report, as well as 31-week and 62-week cancer-tracking guarantees, and a prospective patient tracking application, as an aid to service improvement.
Risk stratification is a core analysis capability at the heart of any integrated care programme. AnalytiXagility underpins the free-to-use, Nuffield Trust developed PARR-30 model, which Aridhia has developed into a risk of readmission within 30 days predictive service. Available to all clinical teams as a web app that works across all tablet and desktop computers, the AnalytiXagility PARR-30 Community Edition focuses on improving service delivery and patient outcomes for chronic disease management. The service is currently is being used by a Response and Rehabilitation team as part of an integrated health and social care service for adults and primarily older people within its triage process.
AnalytiXagility services also underpin a risk stratification application currently in use in general practice in NHS Tayside and NHS Grampian. This application – utilising the PEONY II model – provides a portfolio of risk scores for chronic disease in the over 40s, predicting the risk of admission to secondary care within 12 months. The scores generated are based on aggregated primary and secondary care chronic disease patient data at a patient, practice and population level.
Aridhia’s data challenge events take the idea of data hackathons and applies them to real healthcare data. Challenge days enable healthcare providers to invite multidisciplinary teams from across an integrated care programme to explore, learn and derive insights from data collected across their primary, secondary and social care systems, whilst adhering to the strictest information governance.
“This is the first time where we’ve been able to address joined up datasets… we’re now able to ask questions of connected datasets and it’s giving us some fantastic insights. We needed reassurance that our datasets were secure, one of the things that we were convinced about is that the Aridhia platform is physically secure and that no patients’ data could be identified.” Kambiz Boomla, GP Tower Hamlets & QMU GP’s clinical effectiveness group
At the WELC data challenge day, three years of healthcare data from across three London Boroughs, 200 NHS organisations, primary, secondary and social care, amounting to 180m rows of data, was loaded into the AnalytiXagility platform. Five multidisciplinary teams including clinicians, CSU analysts, data scientists and NHS managers ‘competed’ to see who could gain the most pertinent insights from this unique dataset – something that had never been done before.
Aridhia has supported major diabetes programmes in Kuwait, which has one of the highest prevalence rates in the world. The Dasman Diabetes Institute’s Kuwait Health Network platform combined data from four primary health centres, lab services and secondary care to deliver patient profiles, a disease registry and analytical services from an extensible diabetes dataset.
In the UK, an Academic Health Science Centre (AHSC) is deploying AnalytiXagility’s services to provide an information portal for people with diabetes, drawing data from primary care trusts and local GP practices. The dataset will link information across NHS organisations, creating a powerful, securely held resource, which can be used to build a picture of the local diabetic population. Aridhia’s data science team will interrogate the data, helping to understand the local population, its health and services, creating tailored reports of local needs, performing sophisticated analysis and answering complex questions.