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Population Health Management?


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Thursday, 26 August 2021

Population Health Management?

One of the frequently heard phrases of the moment is population health management – but what is it and does it work. The blog is from a longer article by Monica Duncan exploring the topic.

One of the frequently heard phrases of the moment is population health management – but what is it and does it work. The blog is from a longer article by Monica Duncan exploring the topic.

What is Population Health Management?
Population health management (PHM) is a is a way to improve the current and future health and well-being of people within and across a defined local, regional and national population while reducing health inequalities. It includes action:

  • To reduce the occurrence of ill health
  • To deliver appropriate health and care services
  • On the wider determinants of health.

Population health management is one of many tools using data to guide the planning and delivery of care to achieve maximum impact on population health. It often includes segmentation and stratification techniques to identify people at risk of ill health and to focus on interventions that can prevent that ill health or equip them to manage it. The Social Care Institute for Excellence (SCIE 2018) describes PHM as a methodology to put together a comprehensive understanding of population health needs by joining up data about:

  • Health behaviours and status
  • Clinical care access
  • Use and quality of available services
  • Social determinants of health.

These four areas combine to provide comprehensive baseline information about the locality in terms of health and other challenges faced by residents. This is then analysed to gain further understanding about the levels of current and future need by segmenting the data broadly along the following lines:

  • Those who are generally well and who will benefit from health interventions to maintain their general good health – for example screening programmes for hypertension;
  • Those who are currently well but have been identified as being at risk of developing long term conditions – for example people who may have mobility problems;
  • People with long term conditions who will benefit from early interventions and secondary prevention services to stop or delay progression – for example people with diabetes or cardiac problems;
  • People with complex needs or frailty who need individualised co-ordinated care with a high level of continuity.

Factors associated with success are high quality local data and effective information management systems. The statistical analysis used to model future projections must be robust and supported by credible algorithms which incorporate tacit knowledge from service users and professional staff involved in care delivery. When modelling future demand, allowance must be made for levels of uncertainty and scenario plans should model the possible interactions of various parameters with audit trails of assumptions made. PHM, if used correctly, is an important enabler to improve care outcomes for the local population. The quality of the information produced is only as good as the quality of the data used, the way in which it is used and the extent to which information produced is regarded as credible and useful by both service users and front-line staff.

Why is it population health management important?
PHM is important because it informs how we design and implement integrated care systems. It is fundamental to how health care will be delivered in community settings and enable primary care networks (PCNs) to deliver care as close to home as possible. PHM provides support for local teams to understand and look for the best way to meet the medical, social and wellbeing care needs of both individuals and communities within a defined population. It also provides a strong link to public health data to predict the likelihood of patterns of disease occurring.

How does population health management work?
Data is the fundamental building block of PHM. Data is used to model current states of health care in given locations and, often by using modelling techniques, predict future demands and likely impacts of interventions (for example screening) or unexpected events (such as COVID-19) on given populations. This modelling helps to identify local or national ‘at risk’ cohorts. The potential impact of interventions can be tested against the models to assess the likelihood of proposed interventions improving health outcomes of people already affected or preventing illness from occurring. Further details of how PHM can support healthcare can be found at the PHM Academy at www.england.nhs.uk/integratedcare/phm/ (NHS England 2021).

In an integrated care system, NHS organisations, in partnership with local councils and others, take collective responsibility for managing resources, delivering NHS standards, and improving the health of the population they serve. PHM is a fundamental building block for integrated care systems because it provides the baseline information of local needs by joining up data about social determinants of health, health behaviours and status, access to services and ways in which existing services are used. This baseline information can then be used to model predictions about how current services can be better aligned and resourced to meet the needs of current and future service users.

Local services can provide better and more joined-up care for patients when different organisations work collaboratively in an integrated system. Improved collaboration can help to make it easier for staff to work with colleagues from other organisations to meet the needs of the people they are trying to help. PHM provides the shared data about local people’s current and future health and wellbeing needs. Joint care-planning and support addresses both the psychological and physical needs of an individual recognising the huge overlap between mental and physical wellbeing. Joint posts and joint organisational development are likely to become more commonplace and community nurses will have a vital contribution to planning and delivery of integrated care to improve health and care outcomes for their local populations.

Monica Duncan is a health economist with a clinical (nursing) background, a degree in neurosciences, an MBA and an MSc in Health Economics and Policy. She also has extensive experience and training in change management, service evaluation, cost effectiveness analysis, population health and redesigning services. Contact if you would like more information on the support Monica can provide.

Mubarak says:
Aug 27, 2021 04:58 AM

Monica Duncan has really deep knowledge about PHM.

Mubarak says:
Aug 27, 2021 05:02 AM

I really appreciate, PHM literacy is very important for proper health services.