MOD011086 Population Healthcare and Health Improvement Assignment Sample 2026 | ARU

Improving Population Health Outcomes by Assessing Community Health Needs:  A Critical Systems Perspective in Northamptonshire Integrated Care System

Abstract

Community Health Needs Assessments, CHNAs, are central to the statutory duty of Integrated Care Systems, ICSs, to reduce health inequalities in England. This critical essay evaluates the CHNA process in Northamptonshire ICS, where a 4.2-year male life expectancy gap exists between Corby and South Northamptonshire. Drawing on systems theory, equity theory, and implementation science, it argues that current CHNA practice is limited by reliance on incomplete data, tokenistic participation, weak links to commissioning, and failure to integrate environmental determinants. The analysis integrates core frameworks including Dahlgren and Whitehead, the Social Ecological Model, and the Behaviour Change Wheel, alongside the Health and Care Act 2022, NHS Population Health Management, and NHS Net Zero. Three recommendations are proposed to shift CHNA from annual description to continuous, participative, and accountable system change.

Introduction: Chna As A Mechanism For Equity In Northamptonshire

Health inequalities in England are geographically patterned and politically produced. In 2026, a man born in Corby, Northamptonshire, can expect to live 4.2 years less than a man born 20 miles away in South Northamptonshire [NHS Northamptonshire, 2025]. This gap persists despite universal NHS coverage and the legal duty on Integrated Care Systems to reduce inequalities introduced by the Health and Care Act 2022 [Department of Health and Social Care, 2022].

A Community Health Needs Assessment, CHNA, is the systematic process of identifying health needs, disparities, assets and gaps in services within a defined population to inform resource allocation [Ravaghi et al., 2023]. In England the statutory equivalent is the Joint Strategic Needs Assessment, JSNA. The rationale for CHNA extends beyond clinical care. As Whitehead argues, health inequities are “unnecessary, avoidable and unfair”, and Braveman et al. contend that achieving equity requires explicit attention to structural disadvantage faced by marginalised groups [Whitehead, 1992; Braveman et al., 2011]. Thus CHNA should reallocate resources from treatment to prevention and action on wider determinants.

However, the potential of CHNA is undermined when it becomes a technocratic, annual reporting exercise. Ravaghi et al.’s scoping review found a lack of longitudinal evidence that CHNAs produce sustained health improvements, suggesting a fundamental disconnect between assessment and action [Ravaghi et al., 2023]. Using Northamptonshire ICS, population 761,000 across two unitary authorities, as a case study, this essay critically evaluates the CHNA cycle. It draws on systems theory [Carey and Crammond, 2015], the Dahlgren and Whitehead Rainbow Model [Dahlgren and Whitehead, 1991], the Social Ecological Model [McLeroy et al., 1988], and the Behaviour Change Wheel [Michie, Atkins and West, 2014] to argue that CHNA will only improve population health if it is reconceptualised as continuous, participative, and integrated with environmental policy [NHS England, 2025b].

Conceptual And Theoretical Limitations Of Current Chna Practice

The first limitation of CHNA is conceptual confusion between healthcare need and health need. Healthcare need relates to access to services. Health need refers to broader conditions that produce avoidable illness. If CHNA is limited to hospital activity and waiting lists it will reflect service pressure, not its causes. Whitehead’s definition of equity demands we ask not “which services are most used?” but “which groups face preventable disadvantage, and why?”. Braveman et al. extend this by framing equity as justice, requiring intervention on systemic disadvantage [Braveman et al., 2011].

Three frameworks expose why a clinical focus is inadequate for Northamptonshire. The Dahlgren and Whitehead Rainbow Model *(Appendix 1)* situates individual lifestyle within layers of community, living and working conditions, and socio-economic policy [Dahlgren and Whitehead, 1991]. It explains why Corby’s higher rates of COPD, diabetes and obesity reflect poverty, housing quality and food insecurity, not just individual behaviour. The Social Ecological Model *(Appendix 2)* further shows influence across individual, interpersonal, organisational, community and policy levels [McLeroy et al., 1988]. The Behaviour Change Wheel operationalises this by arguing effective intervention must target capability, opportunity and motivation [Michie, Atkins and West, 2014]. Without this, digital-first pathways risk blaming individuals for “non-compliance” while ignoring the 8% digital exclusion in Corby.

A second limitation is the failure to address power and systems. Carey and Crammond argue that reducing inequalities requires “systems change” that challenges budget silos and existing power structures, not just new programmes [Carey and Crammond, 2015]. Carey and Friel similarly highlight that public administration capacity is often the key constraint in implementing action on social determinants [Carey and Friel, 2015]. An assets-based approach [Birgel et al., 2023] is necessary to avoid deficit narratives, but must not devolve state responsibility to under-resourced communities. The evidence supports this tension: systematic reviews show interventions on wider determinants can reduce inequalities, but effects are context-sensitive and inconsistent [Bambra et al., 2010]. Therefore a robust CHNA must combine epidemiology with analysis of institutional power and community capacity.

Critical Appraisal Of The Chna Process And Healthcare-Public Health

Collaboration In Northamptonshire Ics

Applying the CDC 5-stage model to Northamptonshire [Centres for Disease Control and Prevention, 2013] reveals methodological competence but governance failure.

In terms of governance and data, CHNA is delivered via JSNA and the Health and Wellbeing Strategy [Great Britain, 2012; Great Britain, 2022]. Northamptonshire’s profile uses HES, ONS and IMD 2019 data, showing 4 LSOAs in Corby in the most deprived 10% and a clear social gradient in life expectancy *(Appendix 3)* [Public Health England, 2019]. However two problems emerge. First, administrative data creates “data injustice” by excluding homeless people and migrants. Second, there is a “data-to-action” gap. The existence of a Population Health Management dashboard [NHS England, 2023] does not guarantee resources are reallocated to Corby. NHS England now mandates quarterly review of quantitative and qualitative evidence, yet practice remains annual [NHS England, 2025a].

Priority setting is inherently political. While criteria of burden, inequity and cost-effectiveness [Drummond et al., 2023] suggest CVD, mental health and digital exclusion should be prioritised, decision-making in Northamptonshire sits with the ICB Board. Nava et al. found that in collaborative CHNAs, organisational priorities often override evidence [Nava et al., 2023]. Furthermore, application of Wilson and Jungner screening principles [Wilson and Jungner, 1968] can privilege conditions with measurable tests over complex harms like food insecurity. An equity lens may therefore require investing in less “efficient” interventions for smaller, disadvantaged groups [Braveman et al., 2011].

Implementation is the greatest weakness. The Topol Review calls for a digitally capable workforce, yet delivery is blocked by workforce burnout and poor IT interoperability. The Behaviour Change Wheel provides a design tool, but can be misused to individualise structural problems. Advising physical activity is ineffective without safe green space and transport. Carey and Crammond are correct that leverage points lie in commissioning and regulation [Carey and Crammond, 2015]. Evaluation is similarly weak. It focuses on process not outcomes, and there is a critical lack of longitudinal evidence linking CHNA to health improvement [Ravaghi et al., 2023]. PHM offers potential for real-time monitoring [Watson et al., 2023], but models trained on historical utilisation reproduce bias.

Collaboration is essential because no single organisation controls the determinants of health. Public health provides epidemiology, the NHS provides clinical data, local government controls housing and planning, and the VCSE provides trust [Carey and Friel, 2015]. The Health and Care Act 2022 and 2026 Neighbourhood Health Framework provide the structure [Department of Health and Social Care and NHS England, 2026]. However, structure is not culture. The NHS is judged on waiting times while councils are judged on budgets, creating misaligned incentives. Genuine collaboration requires pooled budgets and shared accountability.

Two policy areas must now be integrated. First, digital transformation raises AI ethics concerns around transparency and exclusion [Tandem Health, n.d.]. Second, environmental sustainability. The NHS is responsible for 4% of UK emissions. Romanello et al. show climate impacts fall disproportionately on deprived groups, while Tennison et al. demonstrate the carbon footprint of care itself [Romanello et al., 2024; Tennison et al., 2021]. The NHS Net Zero strategy [NHS England,

2025b] therefore requires CHNAs to include air quality, fuel poverty and green space. In Northamptonshire this means mapping health need along transport corridors.

Recommendations And Conclusion

To move from description to impact, three recommendations are proposed for Northamptonshire ICS.

First, establish a Community Health Equity Partnership Board within 3 months, co-chaired by the Director of Public Health and a paid community representative. Its mandate is a single PHM dashboard reporting quarterly on clinical outcomes, inequality gaps, and carbon metrics *(Appendix 3)*. This operationalises data justice and aligns with NHS Net Zero [NHS England, 2025b]. Economic rationale is clear as prevention is cost-saving [Drummond et al., 2023].

Second, commission targeted digital inclusion and CVD prevention in Corby using the Behaviour Change Wheel [Michie, Atkins and West, 2014]. Provide devices and navigation support to 2,000 high-risk patients in the most deprived areas alongside workforce training per the Topol Review. Justification: remote monitoring reduces CVD admissions by 15% [NICE], but only if digital exclusion is addressed first.

Third, embed environmental and surveillance indicators in annual CHNA. From 2026, every assessment must report air quality, heat risk and green space alongside disease prevalence. Hold quarterly public forums and publish reasons for discontinued actions. This ensures CHNA functions as surveillance and aligns health with environmental policy. A pilot budget of £120,000 is proposed.

In conclusion, the strength of CHNA lies in its potential to connect evidence to collective action. Its weakness lies in the space between identifying need and making accountable resource decisions. The Northamptonshire case demonstrates that methodological rigor alone is insufficient. Four factors drive failure: reliance on incomplete service data, tokenistic community involvement, weak links between recommendations and budgets, and uncritical adoption of national policy.

CHNA must be reconceptualised. It must be continuous, not annual. Participative, not consultative.

Evaluative, not descriptive. And integrated, linking health data with environmental and economic data. Legislation provides the mandate [Great Britain, 2022], but leadership must provide the will to publish budgets, admit data gaps, and transfer power. Only then can Northamptonshire ICS move beyond measuring the 4.2-year gap, and begin to close it.