Population Health Segmentation & Risk Stratification

Graphnet is uniquely positioned to support organisations to undertake patient segmentation and risk stratification. Our population health solutions bring a substantial amount of information into a centralised location to enable effective and automatic modelling.

Access to a rich pool of data and population health analytics tools means segmentation can be performed based on characteristics such as age, gender, and specific diseases but also on morbidity and healthcare utilisation patterns. Individuals can then be stratified within a specific subpopulation according to the risk of experiencing an adverse event, such as defined undesirable health outcomes or the extent of their healthcare utlisation.

From risk stratification to prevention: Our end-to-end solution enables the identification, classification and prevention of care deficits. Risk stratification engines can be integrated to enable the early detection of patients at risk or those who have negative health trajectories. Automated ‘what-if’ models can give clinicians lists of preventive and reactive models driven by data and evidence.

Cohort mapping engine build localised registries: The cohort mapping engine delivers standardised diseases and wellness registries. The engine also gives users the ability to include their own mappings which enables localisation.

Frailty: The electronic frailty index (eFI) delivers the ability to stratify the entire elderly population. Frailty deficits are calculated and a full history for each patient can be analysed.

Data and model APIs: Our APIs allow the integration of our business intelligence and data science packages with third party tools, and vice versa. Following the REST API structure means that our APIs enable easy to use industry standard integration with third party applications.

Graphnet also works closely with Johns Hopkins HealthCare Solutions. The Johns Hopkins ACG System, a risk stratification model designed by Johns Hopkins University, can be integrated into Graphnet’s population health platform. It supports the work of clinical teams through the accurate identification of the right people for the right care management intervention. It assists ICSs in their strategic planning through a more granular understanding of how risk and disease prevalence is distributed within their populations and to support a more sophisticated approach to allocating resources to reflect need and reduce inequity.