Latest from PPP, News, Thought leadership May 18, 2023

Population health in business: Enabling public-private collaboration through data

By Mary Brown and Eliot Gillings -

PPP’s Population Health in Business series the examines the impact of public-private collaboration on data and how to maximise the benefits of health-relevant data held by businesses.

Key insights:

While the term ‘health data’ only refers to data that provides information about specific health metrics, ‘health-relevant data’ has a much broader definition.
Health-relevant data may only tangentially pertain to the health of an individual or population but is nonetheless a key consideration in the development of effective population health strategies.
Health-relevant data may be collected by a variety of different bodies. Ensuring this data is interoperable and can be combined will be key to improving the quality of insight.
Quantitative data may enable decision makers to assess a population at a high level, but these datasets must be balanced with qualitative data to respond to inequalities within a region.
Effective collection and sharing of data will require strong public trust, and collaboration between businesses and local leaders.
Strategies for population health should be outcome-oriented, and approaches to data collection, sharing and use should reflect the goals of a local area.
Stronger population health datasets can enable greater levels of ESHG (Environmental, Social, Health and Governance) investment.

Introduction

As identified in the previous two insight summaries, businesses can contribute to the integrated care agenda of their area by bettering the health of their employees, and of the community they are situated in. Data collected and held by businesses measure the effectiveness of their health strategies, as well as contribute to NHS data and help to inform population health management strategies in the area.

Population Health Management (PHM) is a data-driven approach to the provision of health and social care that aims to holistically assess, and respond to, the needs of a population. Rather than drawing conclusions exclusively from pools of health data that may be narrow and uninclusive, the overseers of PHM strategies are empowered to also utilise health-relevant data and qualitative information to gain greater insight into a population’s needs.

The strength of a PHM strategy is contingent on the quality and the diversity of the data it uses. Incomplete data sets limit the ability of those overseeing PHM strategy, to assess population need and develop locally responsive plans that target health inequalities within their region.

Effective population health is a core aspiration of integrated care and ICSs must harness all local assets at their disposal to enable effective PHM strategy. One such asset is private business, which possesses vast quantities of data that could be used to improve the quality of PHM insights. Businesses themselves can also benefit from increased data sharing in a health context, as PHM insights can be used to improve understanding of workforce wellbeing and help develop community engagement strategies. The way in which public and private organisations collaborate to improve data quality, and availability, should therefore be viewed as a key component of a strong PHM approach – and parties who possess data relevant to PHM should work together to share this information in a mutually beneficial manner.

“Accessing health-relevant data will demand that businesses optimise their approaches to data collection and form partnerships with the custodians of health data and health-relevant data.”

This insight summary outlines the key thoughts and recommendations put forward by contributors to the third roundtable of the Population Health and Business series, Enabling public-private collaboration through data. Contributors to the roundtable were asked to consider the role of data in PHM approaches within the private sector – and how these approaches could foster greater synergy between public and private sector approaches.

Contributors outlined that, in order to enable effective action on employee and community health and wellbeing, private businesses must seek to utilise PHM insights. To ensure these insights draw from sufficiently diverse and detailed data, however, businesses must utilise both health data and health-relevant data in their PHM approaches. The strongest and most consistent source of health-relevant data held by private businesses are Occupational Health (OH) records, and as such this insight summary gives special attention to the accessibility of OH data.

Accessing health-relevant data will demand that businesses optimise their approaches to data collection and form partnerships with the custodians of health data and health-relevant data. However, the formation of these partnerships should not be viewed as exclusively benefitting businesses – as the health-relevant data collected by businesses can also be a valuable tool to the PHM strategies of other private bodies and the public sector.

There is a tremendous opportunity for mutually beneficial data exchange that could significantly improve the PHM approaches of the private and public sectors alike. Ensuring the realisation of this opportunity, however, will require parties to have greater clarity on both how and why they could share and utilise data from various sources. This will require the Department for Work and Pensions (DWP) and the Department for Health and Social Care (DHSC) (in partnership with ICS leaders) to provide updated guidance for the collection and sharing of data from PHM approaches – and to develop incentives to drive this behaviour among businesses.

Health and health-relevant data

The use of health data offers benefits for the public and private sectors, as well as the public at large. By understanding patient histories in greater depth, and combining this information to gain a detailed insight into a population’s unique needs, organisations can act more effectively to reduce health inequalities – which, in turn, benefits the public.

Better use of health data can:

Promote a better understanding of disease risks and causes.
Support better diagnosis and care.
Support service improvement and planning.
Support research and innovation in the NHS.
Improve patient safety.
Allow evaluation of government and NHS policy.

As an institution, the NHS is well placed to utilise data-driven insights to inform its work. Due to the single-payer nature of the NHS, and the allocation of NHS numbers as a unique patient identifier, the NHS has access to rich longitudinal data for its patients.

However, the data currently collected and held by the NHS gives only a partial picture of population health. This is because routine data does not represent those who do not access NHS services; it lacks information about a patient’s health between interactions with health services; data quality can be low dependent on choices made by clinicians and clinical coders; and the grounds upon which the data is collected often shapes what gets recorded. Furthermore, the clinical data collected by NHS services do not tend to take into account the social determinants of an individual’s health, which is the biggest indicator of healthy life expectancy and the factor which has the most impact on health inequalities.

“Health-relevant data describes all data which may indicate something about a person’s health, including the social determinants of health, which are a significant indicator of healthy life expectancy and health inequalities.”

Datasets that better represent local populations can be synthesised, but this is an imperfect science. In order to create a synthetic dataset, a machine learning (ML) model must be trained on the original set before either generating new data, or pulling data from other sources. This means that an ML model must be developed with a clear understanding of where the gaps are within a dataset, and what the value of that data is.

PHM approaches, however, are not necessarily intended to be teleological in this manner. While data scientists may, in some instances, have a clear view that a dataset fails to represent a certain segment of the population, there may be other instances when datasets are used to conduct latent class analyses to identify new underserved groups. As such, while synthesis can (and should) be used in the appropriate conditions, there is a need to continually revise and develop collection approaches and broaden the scope of data used.

Data that can be used to enrich an individual’s personal health records, and to inform population health understanding and strategy, can be derived from multiple sources. Health-relevant data describes all data which may indicate something about a person’s health, including the social determinants of health (SDOH), which are a significant indicator of healthy life expectancy and health inequalities. Health-relevant data should be connected to clinical data and included in medical records. This will help create a more comprehensive picture of an individual’s health, making it easier to identify those most at risk of poor ill health – this will in turn inform medical care, advice and lead to more effective public health interventions.

Sourcing health-relevant data can, however, present the following challenges:

Security: The sharing of health data is closely regulated, however the sharing of health-relevant data is not. While this ostensibly means that sharing health-relevant data should be easier, a lack of regulation may exacerbate security concerns among the public.
Specificity: Health-relevant data is a nebulous concept and encompasses a broad range of information that can be collected and held by various custodians. In order for health-relevant data to be collected and shared at scale, greater specificity on what constitutes health-relevant data will be required.
Partnerships: While few partnerships exist to facilitate the exchange of health data, even fewer exist for the exchange of health-relevant data. This, in turn, means that enabling better PHM will require a significant effort to create collaboration between organisations that may be presently unaware of one another.

Accessing health-relevant data

While the custodians of health data are typically public health bodies, the custodians of health-relevant data may be private businesses. Moreover, while guidance for data sharing between public bodies may be inconsistent, there is comparatively little guidance available for private businesses on how to share health-relevant data with one another, or with the public sector – complicating the development of the diverse and robust datasets needed to inform effective PHMs.

The Open Life Data Framework, launched by the APPG for Longevity in November 2022, provides an example of what public-private sector data sharing can look like for the purpose of longer healthy life expectancy and the reduction of health inequalities. In the Open Life Data Framework, health-relevant data includes:

Healthcare system-generated data.
Consumer health and wellness industry-generated data.
Digital exhaust is generated as a by-product of consumers’ daily online activities.
Non-health demographic, social and health data.

In the Framework, occupational health (OH) data is not explicitly mentioned. However, businesses’ OH records can often contain valuable sources of health-relevant data, with the potential to greatly enrich health data at the local level. Businesses may hold data on employee sick leave, household status, indications of deprivation, mental health, educational attainment, or lifestyle information, alongside other metrics that they may choose to measure.

“To ensure that businesses are able to share data easily and regularly, it will be imperative to streamline processes and to ensure that labelling and categorisation conforms to an agreed standard.”

OH data could be used in tandem with clinical data held by the NHS to provide a detailed view of a patient’s needs and a population’s unique characteristics. PHM insights generated by public bodies could then be shared back as anonymised data that could be compared with in-house insights to provide a stronger and better contextualised view of workforce and community need.

However, to ensure that businesses are able to share data easily and regularly, it will be imperative to streamline processes and to ensure that labelling and categorisation conforms to an agreed standard. While data integration tools can make the pooling of heterogenous data easier, the more closely aligned sets are with regard to formatting and structure, the easier they can be integrated, making analysis less time consuming and more accurate.

This insight summary concurs with The Hewitt Review’s recommendation that NHS England, in collaboration with DHSC and local government (including through the Department for Levelling Up, Housing and Communities (DLUHC), the Local Government Association (LGA) and other local government representative bodies or stakeholders) should define “standards on data taxonomy and interoperability and coordinating data requests to the system” to facilitate better ICS performance.

However, as private businesses possess large amounts of data that could be utilised to improve PHM approaches, this recommendation should be expanded to include business groups. Consultation with business groups should occur at the regional level, through whatever body assumes the role presently filled by local enterprise partnerships (LEPs).

LEPs (of which there are currently 38) serve as a conduit for local businesses (including SMEs) to partner with one another and local authorities. These partnerships are able to assess local economic opportunity and set the foundations for collaborative action that drives economic growth and job creation, improves infrastructure and raises workforce skills. Moreover, some of these partnerships are already involved in the sharing of data sharing between private businesses and local authorities.

In the March 2023 Budget, it was announced that LEPs would stop receiving central government support as of April 2024, and their functions would be taken on by local government. The DLUHC and the Department for Business and Trade (DBT) are presently consulting on next steps for LEPs and intend to publish an updated policy paper by the summer of 2023 on this topic. These consultations should include discussion of the role of ICPs as forums for local NHS leaders to connect with non-health organisations relevant to the aims of the ICS. Health and Wellbeing Boards (HWBs) should also be party to consultation, to ensure that new taxonomy standards remain consistent with the language used in Joint Strategic Needs Assessments (JSNAs).

Linking datasets for better public health interventions

Although there is a wealth of health data describing patient health presently held by the NHS, health services are less able to benefit from such data when datasets are not linked. Linking datasets is essential for improved care: at the personal care level it allows health professionals to access all relevant information about each patient, and at the public health level, it leads to a better understanding of disease patterns and health conditions (as witnessed during the Covid-19 pandemic) and has the potential to enable better population health management and the reduction of health inequalities.

Roundtable participants were quick to note that the public often assumes health data is routinely linked, and, as one participant noted “most people are quite shocked when they find that is not necessarily the case.” Despite efforts being made to link patient data into a single shared care record (ShCR) across different ICSs, patient data is not always linked. While each ICS has some form of a shared care record, the progress of these care records is inconsistent.

“The LCR CDC works with the public sector, private businesses and academic organisations to create an environment where data can be securely accessed, linked and analysed to the benefit of the community’s health.”

Moreover, while large amounts of primary care data (GP data) are captured in electronic health records (EHRs), these are often connected at a local level but not across the NHS. Secondary and tertiary (specialist) care data (including A&E, Outpatient and Inpatient data) also tend to be collected in different service areas, and often through differing EHR systems (some of which have yet to be fully digitised). Community services data (including health visiting, midwifery care and district nursing) is sometimes collected by NHS digital through the Community Services Data Set, but not always – and though NHS data is broadly able to be linked, this data tends to sit in silos meaning it is often not fully linked.

However, while data linkage in the NHS is not yet uniform, there have been a number of strong efforts to link data at the population level, both locally and nationally. The Liverpool City Region Civic Data Cooperative (LCR CDC) is an example of how data collection and linkage at the local level can improve healthcare delivery. A data governance project in the Liverpool city region, the LCR CDC works with the public sector, private businesses and academic organisations to create an environment where data can be securely accessed, linked and analysed to the benefit of the community’s health. It connects civic organisations, industry experts and community organisations to mobilise health and health-relevant data, while also advocating for better use, and engaging communities on the logistics and benefits of data sharing. It also drives research by using data to create positive change, demonstrating to organisations how they can make the best use of data to generate insights which benefit them and can be fed back into the system.

Presently, the LCR CDC functions as a mediator, connecting stakeholders with one another. Often, this involves connecting businesses with platforms such as Combined Intelligence for Population Health Action (CIPHA) or programmes such as System P – both of which are led by local authorities, the NHS and the University of Liverpool. While CIPHA serves as a tool to observe and analyse PHM data at scale and operates a trusted research environment (TRE) for researchers, System P is a programme aimed at leveraging PHM data to identify groups who may interact with public services differently (and supporting them to interact with them more effectively).

In the context of the LCR CDC, which is the first programme of its kind in the UK, the creation of a TRE makes sense. In the long-term, however, ICS leaders should seek to share TREs. This is because simpler and broader TREs are likely to enable faster and better information exchange as outlined in The Goldacre Review, which notes that the fewer TREs there are, the more opportunities researchers will have to cross-pollinate with one another. Consultation regarding the future of LEPs should, therefore, also address the need to reduce the number of possible destinations for data to maximise accessibility for businesses and local authorities alike.

Supporting business to enable better PHM

Businesses should be supported by and collaborate with their local ICS to actively collect data from their employees about physical and mental health alongside information pertaining to overall wellbeing and lifestyle. Surveys can be an effective way to collect information from employees, as well as extracting data from existing HR systems which may include detailed information regarding sick leave, employee usage and attendance of benefit offerings, and health information already on record.

Businesses are, however, diverse in structure, culture, size and organisation. As such, available information and budgets vary. This makes collecting data in standardised and useable formats somewhat difficult. Roundtable participants noted that “currently, it is easier to work with large organisations who have functional HR departments and find it easier to submit and analyse their data. The big gap is [that] the organisations which make up the majority of the private sector workforce do not have that data, and do not understand the value of the data or its importance to health”.

“Once public-private partnerships are established, an ICS can begin to deliver public health interventions within workplaces.”

To enrich NHS records with OH data, all businesses within an ICS should be offered support from the ICP to collect and share their health-relevant data. This support should include robust guidance on data taxonomy. Guidance should also address how data collection and sharing may be altered within an ICS to improve said insights, and recommendations on how businesses could respond to assessed needs within the local population.

Roundtable participants also noted that partnerships with businesses could be a valuable tool for the ICS, for service delivery as well as for data collection. Once public-private partnerships are established, an ICS can begin to deliver public health interventions within workplaces. Undertaking these interventions within settings where a large portion of the population works will help them to reach a broader portion of the community – and ICSs can benefit from the familiarity, proximity and trust that employees tend to have with their employers. In this way, as one roundtable participant noted, “occupational health can begin to be seen as a sort of applied form of public health.” Closer relationships between businesses and the ICS can only lend further credibility to this framing.

It should also be noted that there is a significant gap between the OH capabilities of large firms and those of smaller firms – and that this gap could, potentially, create stark inequalities both within and between ICSs, depending on the makeup of local enterprises. While the promise of £1 million of additional funding from DHSC and DWP for innovation in OH for SMEs should help to reduce this gap, this commitment must be supported by further efforts to empower ICS leaders to respond to the unique challenges faced by SMEs in their area.

The tide is moving in this direction. The Chancellor, Rt Hon Jeremy Hunt MP, emphasised in the Spring 2023 budget the importance of improved OH services and pledged to support businesses to provide OH services and expand SME subsidy schemes. These promises were accompanied by plans to implement regulations requiring employers to provide OH services, as well as tax incentives and a long-term workforce plan. Such commitments are promising, but it will be crucial that these efforts include ICSs to ensure that support is maximally responsive to the unique needs of SMEs – and that the expansion of OH services does not impact the shareability of OH data.

Public concern around public-private health data sharing

Public concern around data sharing and privacy forms a major barrier to the formation of private-public data partnerships, as many individuals harbour concerns over personal medical data getting into the wrong hands. These fears, unfortunately, are not invalid. In 2013, NHS England began the care.data programme, which aimed to bring together health and social care data from across the NHS for improved patient care. However, the programme failed to earn the trust of the public and of many medical professionals – in part because the purpose of the scheme was poorly explained and, in part, because the scheme’s data security was frequently breached.

“Ben Goldacre himself, author of The Goldacre Review, opted out of sharing his NHS data via the scheme, due to concerns around risks of deanonymisation. Both the NHS and the private sector must learn from previous mistakes.”

As a result, more than 1 million people chose to opt out of the programme – and care.data faced severe criticism for sharing sensitive medical information with commercial organisations. More recently, the General Practice Data for Planning and Research scheme (which planned to make GP data available for researchers and companies) was abandoned in 2021 after more than a million people opted out of the scheme. Ben Goldacre himself, author of The Goldacre Review, opted out of sharing his NHS data via the scheme, due to concerns around risks of deanonymisation. Both the NHS and the private sector must learn from previous mistakes. This means that time must be taken to appropriately engage the public on data preserving techniques and the technologies used to reduce the risk of data mismanagement and breaches.

One of the key promises of the Government’s Data Saves Lives strategy is the creation of Secure Data Environments (SDEs), a type of TRE which is to become the default for NHS and social care organisations to provide access to de-identified data for research purposes. This means that personal data linked to an individual will never leave a secure server and will only ever be used for agreed upon research purposes. In spite of this level of security, the public should nonetheless be well informed of how SDEs will operate, how they will benefit, and be encouraged to not opt out of the scheme.

“ICS leaders ‘must demonstrably show both employers and patients where data has been used to make a difference and improve lives to increase enthusiasm and engagement.'”

However, distrust of the sharing of health data goes beyond a general unease over private companies having access to medical information held by the public sector. A Report by Deloitte published in 2022 reported that 46 per cent of employees do not think their organisation should be able to monitor their health data, even if it enabled them to offer wellbeing support, and only 21 per cent believed their personal health data would be used responsibly by employers.

To address these concerns, roundtable attendees noted that central government and ICS leaders “must demonstrably show both employers and patients where data has been used to make a difference and improve lives to increase enthusiasm and engagement.” The public should understand the purpose and value of their personal data contributions to both health systems and employers, and should see a clear benefit to participation.

Roundtable participants pointed out that “most people are very happy to share their data if there is a point to it, and a clearly explained benefit for the wider population.” As such, for data collection programmes to be successful, “a sort of social contract between the ICS, businesses and citizens should be formed” in which data sharing is well understood as a key tool for improving the health of an area, and something for which there is a shared responsibility. Data governance should be clear and uncontroversial.

The Open Life Data Framework advocates that a Trust Framework for private sector-derived health data which should be created, and that it should be governed by clear rules pertaining to the following:

Data rights (e.g. GDPR)
Legal frameworks (e.g. links to data processing agreements
Scope and assignation of liability
Mechanisms for redress
Consent and consent management
User experience guidelines

This insight summary concurs with the Open Life Data Framework’s suggestions for the governance of data but adds that the public must also be engaged regularly to judge their perceptions and their experiences – as these are the metrics by which PHM strategies will be evaluated in the real world. The Liverpool City Council Civic Data Cooperative, for instance, has been able to successfully engage citizens in their data collection initiatives by holding “discussion events, public consultation groups and community-led review boards.”

It may also be fruitful to consider whether the public should be involved in the setting of priorities for data collection, or even the setting of ICS objectives more broadly. Within clinical research, for instance, the use of patient-reported outcome measures (PROMS) has been shown to increase patient trust and improve the quality of insight generated by studies. Though there are extant issues with the validation of PROMs within clinical settings, ensuring these provide accurate and valuable information in the context of a PHM strategy should be possible provided ICS leaders develop sufficiently robust methodologies.

For increased trust and understanding, roundtable participants also suggested the use of Plain Language Summaries (PLSs) should be explored. PLSs are often used to inform non-specialist audiences in a clinical trial process about the process, risks and benefits of participation. PLSs that clearly explain the importance of health and health-relevant data to participants would likely be a helpful tool for engaging the public with the process, purpose and data privacy mechanisms of the trial. The understanding facilitated by the PLS could also engender a sense of mutual trust and improve data collection, enabling employers to develop and synthesise more comprehensive datasets.

On that matter, it should also be acknowledged by all stakeholders that there is a relationship between the manner in which data is collected, and public trust. Where the purpose of data collection is unclear and fails to demonstrate a clear benefit to an individual, it is likely to erode trust. As such, DHSC and DWP should cooperate to develop a set of guidelines for safe and transparent data collection to be utilised by businesses and local authorities. This guidance for data collection should not seek to be proscriptive, as the variance between workforces and regions necessitates that system leaders adapt to their surroundings. Instead, guidance should identify potential problem areas, and guide the thinking of systems leaders in a manner akin to the HRA’s PPI guidance.

ESHG investment and innovation

The integration of OH data, and other health-relevant data, into PHM frameworks may also be a means to integrate health into environment, social and corporate governance (ESG) agendas – enabling private sector organisations engaged with PHM to better access the growing pool of ESG-focused investment.

By 2026, ESG-focused institutional investment is expected to grow 84 per cent globally, but already the demand for ESG investment products is beginning to outstrip supply. The primary reason for supply failing to keep pace with demand is that ESG investments are difficult to validate, because ESG regulation is complex and inconsistent, and because the data needed to assert a product’s ESG credentials is not always readily available.

“Each element of ESG has a measurable impact on people’s health. Accordingly, health and health-relevant data could be used to measure the ESG credentials of a product or service.”

Many asset managers have suggested that the conversion of products, from non-ESG to ESG, will be their focus as they seek to satisfy demand from investors. Converting products in this manner, however, will require either the lowering of the threshold for ESG designation, or the use of new data sources to show the ESG credentials of the products in question.

Each element of ESG has a measurable impact on people’s health. Accordingly, health and health-relevant data could be used to measure the ESG credentials of a product or service. This would not only enable asset managers and investors to more easily identify ESG products or services, it would also enable companies (and local authorities) to assess and respond to their impact on health outcomes with greater clarity.

Such data collection will also build up the evidence base for businesses to allocate resources to health improvement. Research from consultancy firm Carnall Farrar, commissioned by the NHS Confederation, demonstrates that investment in health generates major growth for businesses, finding that every £1 spent on health in the NHS generates £4 of economic growth by increasing workforce numbers.

The adoption of ESHG frameworks, however, poses the following challenges:

Clarity: ESG frameworks are already complex and can often be difficult to use. In order to meaningfully incorporate health information into ESG frameworks without deterring users, the accessibility of relevant data must also be carefully considered.
Interoperability: ESG frameworks are also inconsistent, and their methodologies can vary greatly. The inclusion of health information may yield different result depending on the calculator – reducing the value of ESHG frameworks.
Consistency: The value of ESHG frameworks will be greatly diminished unless their insights correspond to the ambitions and actions of local authorities. While many councils and ICSs have published ESG strategies, these approaches would need to be updated should businesses adopt an ESHG approach.
Returns: The upshot for a business of investing in workforce and community health can be significant, but not in the short-term. Improvements in health outcomes and associated business benefits may emerge years, if not decades, after interventions are implemented. This is particularly true for interventions targeting increased healthy life expectancy which impact the onset of longer-term health conditions. As such, the evidence for encouraging business investment into health may not be fully available for years to come.

The challenges to adopting an ESHG approach, however, are not unique to the concept of ESHG. Any framework that enables organisations to map out and respond to their non-financial impacts will necessarily be complex and far from perfect (at least early on). As such, organisations seeking to develop robust ESHG frameworks should not be deterred in their pursuit – rather they should collaborate as closely as possible to minimise the impact of the aforementioned challenges.

This collaboration is already occurring through initiatives such as Business for Health, who have already begun the process of bringing together a range of voices to discuss and advocate for ESHG as a concept. These initiatives should initially be focused on the development of data platforms that can enable organisations to easily assess, respond to and show their impacts. Such tools, even though they are likely to be imperfect initially, may support other businesses to visualise their own ESHG profile with greater clarity and consistency – thereby building further momentum for ESHG as an approach to business.

Conclusion

Even before the Covid-19 pandemic, health inequality in the UK was getting worse. In the ten-years between the publication of Sir Michael Marmot’s Fair Society and Build Back Fairer the life expectancy of the UK’s poorest people has declined, and the rate of child poverty has risen (to the point where more than one out of every five children are living in poverty). This is an unsustainable and unacceptable trend – and one that all businesses and organisations should be seeking to reverse.

Of the six areas identified by Marmot as “essential to meeting the health inequality and life expectancy challenge head on” three are directly impacted by the conditions of one’s employment (employment and working conditions, ensuring that everyone has at least the minimum income necessary for a healthy life, and healthy and sustainable places in which to live and work). More broadly, however, businesses also play a significant role in determining the health of the communities they serve through their business practices and their impact on metrics such as gross value added (GVA).

“ICSs should begin their search for high-quality data with the businesses on their doorstep.”

Better use of health and health-relevant data can enable businesses and local authorities to become more aware of (and accountable for) their impacts, and can enable closer public-private collaboration. However, enabling the effective use of health and health-relevant data will require ICSs and businesses to find answers to questions relating to accessibility, methodology, security and incentive.

This insight summary, which outlines the key contributions and recommendations that emerged from the third and final session of the Population Health in Business series, discusses the importance of health-relevant data, and how businesses and ICSs can effectively partner to share this data. This report also discusses the benefit of enhanced health-relevant data sharing, for both ICSs and private businesses, and how relevant parties may overcome barriers to collaboration – which has also been addressed within The Hewitt Review.

However, while Hewitt found that “that timely, relevant, high-quality and transparent data is essential for integration, improvement, innovation and accountability,” the review is relatively mute on the matter of where that data should come from. Despite recognising that “data collection should increasingly include outcomes rather than mainly focusing on inputs and processes,” and suggesting that there is a need to move beyond “cumbersome paper-based data collection,” The Hewitt Review makes little comment on where ICSs should be looking to in the search for accurate and well-rounded data. This insight summary suggests that ICSs should begin their search for high-quality data with the businesses on their doorstep – and should view their interfacing with local businesses as an opportunity to get everyone working together to reduce health inequalities.

Recommendations

1. NHS health records should be enriched with health-relevant data. Data collected by businesses should contribute to records. This will help to complete patient records and inform more effective and comprehensive population health management strategies.

2. The Department for Levelling Up, Housing and Communities (DLUHC) and the Department for Business and Trade (DBT) should include ICS leaders in their consultations regarding the future of local enterprise partnerships (LEPs). The LEP serves as a valuable forum for businesses in an area to set joint priorities and interface with local authorities – making them a valuable institution for the facilitation of rapid and effective data sharing.

3. NHSE, DHSC, DLUHC, and the LGA should develop taxonomy and interoperability standards for health and health-relevant data – for both health and non-health organisations. ICSs should be consulted in the setting of these standards, as should LEPs.

4. The creation of civic data cooperatives should be a priority nationwide, as other ICS leaders and local authorities should seek to replicate the success of the Liverpool Region Civic Data Cooperative. These partnerships should strive to be as simple as possible, using a minimal number of TREs to encourage easy data sharing and cross-pollination between researchers.

5. ICSs should seek to collaborate with businesses to deliver public health services – such as hosting a pop-up diagnostic centre within a place of business. In these instances, health systems can benefit from the familiarity, proximity and trust that employers may have with their employees.

6. NHSE must go further to repair the reputation of public-private data sharing. The benefits of participation in health data collection schemes should respond to the priorities of populations and should be made clear via the use of plain language summaries.

7. DHSC and DWP should develop guidance for data collection that can be used by both local authorities and private businesses. This guidance should steer the thinking of systems leaders but should not be proscriptive as data collection approaches must remain adaptable.

8. ICSs and businesses alike should view the development and implementation of data platforms as a health equity priority. This is because platforms that enable organisations to assess, respond to and show their impacts will be crucial to evaluating the success of PHM approaches and growing support for ESHG frameworks.

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