Our health and the challenges facing the health system have transitioned from single diseases that threaten longevity to an accumulation of chronic conditions such as diabetes and obesity. These conditions bring illness as well as leading to several other conditions themselves.
Illness has traditionally been seen as a cost, however maintaining the health of populations can deliver prosperity for individuals, employers and healthcare services.
Analysis in this field has traditionally been backward-looking and taken a ‘one-size-fits-all’ approach. Health systems remain organised around, and incentivised, for single diseases and illness.
Our health analytics approach leverages the increasing availability of data and our cutting-edge modelling approaches to put timely actionable data in the hands of key stakeholders. The health needs of individuals and populations vary greatly; we provide bespoke analysis to shift populations from illness to health.
How we can help
We bring clarity to decision makers across healthcare and life sciences who face increasingly complex health demands from ageing populations with increasing multimorbidity.
Through combining actuarial, statistical and machine learning approaches, our data-driven approach brings to light the health needs of populations and a more comprehensive approach to capturing health impacts and costs of chronic diseases and their related conditions. We support the transition to provide optimum services today – care pathways, preventive approaches or therapeutics – for a healthier tomorrow.
Our technology specialists develop interactive and dynamic dashboards within the organisation to provide ongoing decision support to clients.
For healthcare providers and insurers
- We integrate healthcare demand patterns over time, by patient, condition(s) and staff-type into a dynamic, interactive dashboard, and help healthcare organisations deliver more sustainable operations alongside improving patient outcomes.
- Managing chronic diseases well vastly reduces the risk of illness, hospitalisation and/or death to patients and reduces costs for providers. Doing this requires careful management of a host of clinical and lifestyle risk factors. We identify individuals with specific chronic conditions, co-morbidities, their physiological and lifestyle risk factors and integrate this data into an interactive platform to monitor and improve care pathways. Our detailed approach helps implement personalised care pathways that optimise testing, treatment and specialist referrals to keep patients healthier longer.
- Individuals living with just one chronic disease is becoming the exception rather than the norm. We map out clusters of chronic diseases in specific populations, patient groups and individuals. This allows care pathways to coalesce around the real health and prevention needs of patients enabling more joined-up care, and fewer clinic visits.
Disease patterns and risk stratification
- Ageing and multimorbidity means that population health (and illness) profiles vary more than ever. We use our cutting-edge modelling approaches to estimate health needs and disease patterns in more granular detail reflecting that health is personal to each of us.
- This allows healthcare providers to develop and better match services needed by their populations today and in the future, improving health outcomes more sustainably.
- We can generate more accurate and personalised health and risk projections to allow dynamic pricing according to traditional measures such as mortality risk, as well as morbidity and healthcare usage.
- With finite resources, decision makers want to invest in services and interventions with the biggest return on health. Our intervention modelling brings the choices and trade-offs to light. We estimate the health, economic and equity effects of a range of interventions, from drugs to public health measures, for individuals or whole populations, to allow comparisons in an interactive dashboard to inform decision makers.
Within life sciences
- Clustering of conditions in multimorbidity
- We identify the common clusters of co-morbidities for a given index condition and how these patterns vary by age, sex and over time. By integrating this into an interactive dashboard it brings clarity to patterns of the true-health needs of patients to enable a more comprehensive approach to chronic disease care.
Mapping and forecasting the burden of disease
- Knowing the size and composition of a disease burden today and in the future is crucial. We forecast disease and health patterns in populations and patient groups for specific conditions and related co-morbidities in more detail and bring to life through interactive and dynamic visualisations rather than traditional approaches. This helps map out what trends mean for healthcare utilisation and costs with increasing granularity for a range of stakeholders.
Health economic and outcomes research
- Estimating the cost-effectiveness of interventions (drugs or programmes) has been a bed-rock of evidence informed decision making for years. In the era of multimorbidity, doing this on a disease by disease basis is often mismatched to the population's health needs, and impacts. We estimate the health, economic and healthcare usage effects of given interventions on the index condition and its related multimorbidity in order to capture the wider perspective of health impacts across the health economy.
Our latest thinking
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