The National Association of Primary Care defines a three-step approach to population health management.
Whether you are in primary care, an acute trust, commissioner, or an Integrated Care System, we can support healthcare systems and their constituents on the journey towards population health management. We have created an end-to-end population health management solution suite to provide you with the technology, services and experts you need to maintain, improve and proactively manage your population’s health and wellbeing.
Risk stratification will help you identify and target appropriate proactive interventions and enable systems to gain a detailed picture of the future risk profile of its population. Using the latest machine learning techniques, we will help you predict and proactively manage your population’s care needs.
Learn morePopulation segmentation analysis will help you identify the patients who are the highest-cost users across care settings. It will provide you with a greater understanding of the patient characteristics as well as needs for specific segments, including wider determinants of health.
Our outcomes dashboards give you the ability to track the performance of interventions for particular patient segments. Population based interventions help achieve improved patient outcomes, better patient experience and a reduction in system-wide healthcare cost.
Learn moreThe health economics domain requires specialist expertise and knowledge of health economic and actuarial methods, which can be developed internally or via partnerships with other organisations. Our experts are able to calculate the system-wide cost and provide financial forecasting support.
Learn moreOur dedicated experts can provide the support and expertise required to maximise the returns from your business intelligence tools, as well as provide additional support for your informatics teams. Areas of expertise include clinical analytics, population health, predictive analytics and health economics.
Learn moreOur Command Centres will help Integrated Care Systems improve outcomes and tackle inequalities, enhance productivity, and make best use of resources and to strengthen local communities and manage their populations’ health and wellbeing.
Learn moreInFocus+ is the advanced functionality package of our InFocus dashboards, able to take in different types of data, and making it easier and quicker to identify and predict areas of variance and opportunities for improvement, both for your own organisation, as well as for your system.
Learn moreOur Big Data Platform manages your data, making it available for analysis and research. At the heart, a Unified Data Layer provides scalability for managing and consuming data, surrounded by an Insight Layer where raw data becomes actionable insight.
We 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.
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.
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.
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.
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.
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