Population health management has been talked about in NHS primary care for years. The NHS Neighbourhood Health Framework, published on 17 March 2026, turns that talk into a formal requirement. ICBs are expected to incentivise proactive population health management through risk stratification, and practices are expected to demonstrate that they know their population, who is at highest risk, and what they are doing about it.
The challenge for most practices is not the intention. It is the data. You cannot manage population health without knowing what your population is presenting with, which patients are contacting you repeatedly, where demand is concentrated, and which patients in your high-risk cohort have not contacted you at all.
That data is already being generated if your practice operates structured total triage. The question is whether you are using it.
What Population Health Management Actually Requires
The framework is specific about what population health management looks like at practice and neighbourhood level.
Risk stratification of your registered population using validated tools to identify patients in priority cohorts. The four national cohorts are: people over 75 with moderate to severe frailty, care home residents, housebound patients and those approaching end of life, and people with multiple long-term conditions. ICBs may add locally determined groups.
Care planning for complex patients. The framework targets 95% of people with complex needs having an agreed, documented care plan by 2027. Those plans must be shared across the Integrated Neighbourhood Team and accessible to professionals from other organisations working with your patients.
Proactive outreach rather than reactive response. The framework’s logic is that the highest-risk patients should not be the ones contacting you in crisis. They should be identified, stratified, and actively managed before they escalate.
Data sharing with the INT. Population health management at neighbourhood level requires that the community nurses, social care workers, mental health practitioners, and allied health professionals in your INT have access to the same patient data your practice holds, within information governance requirements.
All of this depends on one thing: a clear, accurate, current picture of your population. And for most practices, that picture is most readily built from their front door data.
The Triage Data You Are Already Generating
Every time a patient contacts your practice, they are telling you something about your population’s health needs. The problem is that in practices without structured triage, that information is captured as a phone call note, a receptionist’s memory, or a free-text field that no one systematically analyses.
Structured total triage changes this. When every contact, whether submitted online or captured from a phone call by staff, goes through a consistent triage process with coded presenting problems and urgency levels, the data that comes out the other side is genuinely useful for population health planning.
Consider what you can see after three months of structured triage data:
Demand patterns. Which days and times generate the most contacts? From which patient groups? Are Monday mornings consistently generating twice the acute demand of Wednesday afternoons? That information allows you to staff proactively rather than reactively.
Presenting problem distribution. What are your patients actually contacting you about? If 20% of contacts are administrative queries that require no clinical input, that is a process improvement opportunity. If musculoskeletal problems make up a consistent slice of contacts but patients are predominantly being routed to GPs rather than physiotherapists, that is an ARRS utilisation problem.
Repeat attenders. Which patients are contacting the practice repeatedly with the same presenting problem? High-frequency contacts often signal unmanaged long-term conditions or unmet social needs. They are also often patients who should be on a proactive care plan, not bouncing through reactive triage every three weeks.
Silent high-risk patients. This is the hardest group to identify without data. Risk stratification can tell you who should be contacting your practice based on their clinical profile. Comparing that list to your actual contact data tells you who is not contacting you, who is likely deteriorating unseen, and who needs an outreach call rather than waiting for the next crisis.
At Priory Medical Group in York, implementing structured triage via Klinik gave the network, for the first time, data on the true demand they faced and the tools to share that workload across the team. Clinical Directors described having visibility of demand patterns that allowed them to plan resources better across the day and the week. That is population health insight, produced as a byproduct of front door triage.
From Reactive to Proactive: The Data Journey
The framework’s expectation is that practices move from a reactive model, responding to whoever contacts them, to a proactive one, identifying and managing risk before it escalates. Making that shift requires a different relationship with data.
Stage 1: Know what is coming in. Structured triage data tells you what your population is presenting with, in real time. This is the baseline. Without it, you are guessing at demand.
Stage 2: Know who is not coming in. Risk stratification of your registered population, cross-referenced against your triage contact data, identifies high-risk patients who are not presenting. These are the patients most at risk of a crisis. They are also the patients the framework’s priority cohort focus is designed to address.
Stage 3: Match resource to demand. Once you know what is coming in and who is not, you can start aligning your MDT capacity to actual need. This is where triage routing data and ARRS utilisation data connect. If your pharmacists are running at 70% utilisation while GPs are managing a queue of medication queries, your routing is not matching resource to demand.
Stage 4: Demonstrate outcomes. The framework’s commissioning model rewards neighbourhood providers who can evidence demand reduction, proactive management of priority cohorts, and appropriate MDT utilisation. This requires longitudinal data. Practices that started capturing structured triage data in 2024 or 2025 have a two-year evidence base. Practices starting now are building from a lower base.
What Your ICB Will Be Looking For
From 2026/27, ICBs are setting neighbourhood health plans and beginning to track progress against the framework’s five national goals. The data they will use is a combination of what their clinical systems and reporting infrastructure captures and what neighbourhood providers submit or demonstrate.
For practices, this creates a clear set of questions to prepare for:
- Can you show your ICB your risk stratification data for the four priority cohorts?
- Can you show what proportion of contacts from high-risk patients were actioned within 24 hours?
- Can you demonstrate the distribution of demand across your MDT, and how ARRS roles are being utilised?
- Can you show trends in repeat attenders, and evidence of any outreach or proactive care interventions for high-frequency contacts?
- Can you show your data on same-day access compliance, broken down by urgency code?
If the answer to most of these is that you would need to pull the data together manually from multiple sources, your data infrastructure is not aligned with what commissioning will require. If the answer is that these are standard outputs from your triage system, you are ready for the conversation.
Analytics as a PCN Leadership Tool
For PCN Clinical Directors, there is a leadership dimension to this that goes beyond compliance. The practices in your PCN will have different demand profiles, different patient populations, and different pressure points. You cannot manage resource allocation across a network of 5 to 10 practices without data on what each one is facing.
Structured triage data, aggregated across a PCN, gives Clinical Directors something genuinely useful: a real-time view of where demand is concentrated, which practices are under pressure, and whether the workload distribution across the network is equitable. A practice seeing consistently higher acute demand relative to its list size may need additional support or resource. A practice with consistently low pharmacist utilisation may need routing review.
This is the kind of insight that makes PCN leadership operational rather than administrative. It is also the kind of insight that positions a PCN as a credible SNP candidate, an organisation that manages its population with evidence rather than instinct.
Making the Most of the Data You Are Already Generating
If your practice is already using a structured triage platform, the first step is to look at what data it is producing and how it is being used.
Common gaps in practices that have structured triage but are not fully using the data:
The data exists but is not reviewed regularly. Triage analytics are checked occasionally rather than forming part of weekly clinical and operational planning. Setting a standing agenda item for triage data review in your MDT meeting changes this.
Urgency coding is not being verified. The triage system assigns urgency levels, but no one is regularly checking whether those levels are being recorded correctly in the clinical system and whether the clinical system data matches what the triage system shows.
Demand data is not informing staffing. Patterns showing peak demand on certain days or at certain times are visible but not acted on. Adjusting rota patterns based on demand data is a straightforward operational improvement that structured triage makes possible.
Population health insight is not being shared with the INT. The risk stratification data generated by combining triage contacts with clinical system data on priority cohorts is highly relevant for INT working. If it is sitting inside the practice but not reaching community nurses, pharmacists, and social care colleagues, the INT cannot use it.
Frequently Asked Questions
What is population health management in primary care?
Population health management is the practice of using data about your registered population to anticipate health needs, identify risk, and manage care proactively rather than reactively. In primary care, this involves risk stratification of your patient list, proactive care planning for high-risk patients, and using demand data to align resource to need.
What data does the NHS Neighbourhood Health Framework require practices to produce?
The framework sets expectations around risk stratification of priority cohorts, agreed care plans for 95% of patients with complex needs by 2027, shared care records accessible to INT members, and data sharing to support patient identification and monitoring. The specific reporting requirements will be set by ICBs in neighbourhood health plans.
What are the four national priority cohorts under the framework?
People over 75 with moderate to severe frailty, care home residents, housebound patients and those approaching end of life, and people with multiple long-term conditions. These cohorts represent roughly 3 to 5% of most practice populations but account for a disproportionate share of unplanned activity and acute demand.
How does triage data support risk stratification?
Triage data shows which patients are contacting your practice, how often, with what presenting problems, and what urgency level was assigned. Cross-referencing this with your clinical system data on patient risk factors identifies both high-frequency attenders who may need proactive management and high-risk patients who are not contacting you, a group often at risk of undetected deterioration.
What is a care plan and who should have one?
A care plan is a documented, agreed summary of a patient’s health needs, the care they are receiving, who is responsible for each element, and what the goals are. The framework sets a target of 95% of patients with complex needs having an agreed care plan by 2027. Care plans must be accessible to all INT members working with the patient.
How does Klinik generate population health insight?
Klinik captures every contact in structured form, codes urgency and presenting problem, and generates analytics on demand patterns, routing outcomes, and repeat attenders. This data can be reviewed in real time, shared across the PCN, and used to inform INT working, staffing decisions, and proactive outreach for high-risk patients. Practices using Klinik describe having, for the first time, data on the true demand they face and the tools to share the workload across the team.
Does the framework require practices to use specific analytics tools?
No. The framework sets outcome expectations, not tool mandates. But practices that cannot produce the data to demonstrate those outcomes will struggle in the commissioning environment the framework creates. Having a triage system that generates structured, coded demand data is the most direct way to build the evidence base the framework requires.