As the NHS continues to evolve, we are collaborating with partners across healthcare to create innovative solutions that solve some of the NHS’ most pressing challenges.
Our priority with all of our partnerships remains our NHS customers, and together, we ensure that you get the most value for your patients and populations.
We have joined forces with data automation experts, InSource, to deliver a comprehensive programme that gives command-level control of, and powerful insight into, accurate trust-wide or system-wide data for targeted elective care recovery.
Learn moreWe use the latest methodologies in advanced analytics and data science to identify clinical variation, health access and inequalities, efficiency savings, predict patient risk and improve patient outcomes.
Provides NHS organisations with bespoke healthcare analytics, with a dedicated lead analyst acting as the key point of contact, delivering continuity of expertise tailored to evolving customer needs.
Our data experts are able to assist you in organising and integrating health and care data from across the health and care system, together with important wider determinants of health. Our data scientists mine the data to find anomalies, patterns and correlations to predict outcomes.
Developing innovative visualisations and analysis that enable organisations to gain a better understanding of their data. We utilise tools such Tableau and Power BI to provide bespoke analysis which makes it easier to identify trends, patterns, and outliers within large data sets.
Predictive modelling uses statistical techniques and supervised machine learning algorithms to predict future adverse outcomes. Predictions are made at patient-level to predict the risk of an adverse outcome and can further be aggregated into risk groups at provider or system-level where appropriate. Alternatively, forecasting techniques predict the future at an aggregate level, taking into account historical trends and seasonality.
AI is the capability of a machine or system to imitate intelligent human behaviour. Machine Learning is a subset of AI that includes statistical techniques to enable systems to learn and improve at tasks with experience. At Dr Foster, we are using techniques like supervised machine learning to predict the risk of an emergency admission, or to predict the risk of falls, as well as unsupervised machine learning to support current rules-based patient segmentation analysis.
The visual language in InFocus is consistent, ensuring that once users know how to interpret one indicator, they know how to interpret all of them. Simple colour coding based on recognized statistical processes in conjunction with immediate access to the patient data that the indicators are reporting on, means the user can both see where issues are and pull the records to look in more detail.
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