What is health risk assessment?

Using data about a patient to predict how severe an illness is likely to be, and how likely they are to develop one. Its value is in timing: a risk identified before the condition progresses is something a clinician can act on, and the same information afterwards is a record of what happened.

Why focus on chronic disease?

Because of where the money and the harm concentrate. Five chronic conditions — cancer, cardiovascular disease, diabetes, obesity and kidney disorder — account for more than 72% of healthcare expenditure. Identifying high-risk patients and risk factors is what allows preventive procedures to be recommended at all.

What does a clinician do with a risk score?

Guide preventative care, ideally controlling disease progression before it starts. The score is an input to that conversation, not a verdict — which is why it has to arrive with the factors behind it rather than as a number on its own.

Is this only a clinical capability?

No. The same predictive work is applied to the revenue cycle, automating time-consuming and repetitive tasks there. Prediction is a general capability; the clinical application is the one with the largest consequence.

What data does it need?

Enough history to establish what normal looks like for a comparable population, which is why models trained at scale outperform ones trained on a single site. A model built from one hospital data can only recognise that hospital patterns.

Predictive Analytics & Risk Assessment

Ai-powered Predictive Analytics and Risk Assessment Solution in Healthcare

Nano Health promotes preventative care and disease management, reduce health disparities, and enhance health outcomes.

Chronic Disease Prevention

Health risk assessment can be employed to predict the severity of an illness, and it can be extended for chronic disease prevention by recognizing early warning symptoms. Before the condition grows, the patient's clinician can guide preventative care, ideally controlling disease progression.

A small number of chronic conditions account for a disproportionate share of healthcare spending: cancer, cardiovascular disease, diabetes, obesity and kidney disease.

By recognizing high-risk patients and risk factors, medical experts can recommend preventive care procedures to reduce the probability of chronic disease development.

Accelerating Revenue Cycle

Automating time-consuming and repetitive processes, such as accounts payable, Nano Health automation solutions enhance billing efficiency, reduce costs, and improve the healthcare providers' financial performance.

Patient Healthcare Plan Management

Nano Health automation solutions enhance patient care coordination, and case administration and boost better remote monitoring of patients within the healthcare system. Health care providers can gain visibility into the information that matters, such as patients shifting from their healthcare programs, helping them to assure better quality of care.

Efficient Workforce Utilization

Nano Health intelligent automation solutions support replacing repetitive, highly labour-intensive tasks with software bots to improve process efficiency and reduce labour costs. These solutions help refocus employees to better value-added positions to leverage their healthcare and clinical expertise for better patient care.

To learn how Nano Health offers patient-centered health risk assessments.

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How this works with the rest of the suite

NANO BRAIN
Prediction needs a model trained on what has already happened at scale, which is what BRAIN supplies.
NANO DDI
Risk scores are only useful inside an analytical layer that can act on them across a population.
NANO CPW
A predicted risk has to lead somewhere — the pathway is the agreed intervention it triggers.
NANO RCM
The same predictive work accelerates the revenue cycle by automating repetitive tasks in it.

Frequently asked questions

What is health risk assessment?: Using data about a patient to predict how severe an illness is likely to be, and how likely they are to develop one. Its value is in timing: a risk identified before the condition progresses is something a clinician can act on, and the same information afterwards is a record of what happened.
Why focus on chronic disease?: Because of where the money and the harm concentrate. Five chronic conditions — cancer, cardiovascular disease, diabetes, obesity and kidney disorder — account for more than 72% of healthcare expenditure. Identifying high-risk patients and risk factors is what allows preventive procedures to be recommended at all.
What does a clinician do with a risk score?: Guide preventative care, ideally controlling disease progression before it starts. The score is an input to that conversation, not a verdict — which is why it has to arrive with the factors behind it rather than as a number on its own.
Is this only a clinical capability?: No. The same predictive work is applied to the revenue cycle, automating time-consuming and repetitive tasks there. Prediction is a general capability; the clinical application is the one with the largest consequence.
What data does it need?: Enough history to establish what normal looks like for a comparable population, which is why models trained at scale outperform ones trained on a single site. A model built from one hospital data can only recognise that hospital patterns.