As the NHS strives towards its goal of achieving net-zero carbon emissions by 2045, it faces several challenges in leveraging their data to its full advantage. Effective data management and analysis are crucial in all aspects of NHS operations; for you cannot manage what you don’t measure and tracking progress towards sustainability targets is no exception.
In contributing to the climate change effort, the NHS are creating a healthier living environment that will have a positive impact on population health and ultimately reduce the strain on the public health system. It’s been projected that if the UK were to achieve net zero by 2040 significant health benefits would be realised including saving 5,770 lives per year through the reduction of air pollution.
Using the right data in the right way to reduce their carbon footprint will literally save lives.
The biggest stumbling block in healthcare data management is the complexity and sheer size of the health data landscape. This is difficult to navigate given healthcare provision by its very nature is a complex undertaking and a complexity that won’t go away. There is also a level of unpredictability as the system is forced to adapt as the environment around it changes. With the existence of numerous interdependencies, governing bodies and diverse population health requirements compounded by many external factors shaping health outcomes the healthcare industry is seeking to make, successfully managing the data landscape is no mean feat.
The United Nations shared a blueprint for peace and prosperity through 17 Sustainable Development Goals with the intent a better way of living can only be achieved through a global partnership. This notion of partnership and knowledge sharing is something the NHS are struggling to effectively implement and thus causing problems in how they effectively manage data.
An implication of having 200 + trusts who act largely independently is that data exists in siloes and thus there is an inability to compare data sets like for like. As a result, there are scalability issues so any success with sustainability initiatives in one trust or hospital is rarely replicated in another and remains a case of isolated progress. For example, the SHINE (Sustainable Healthcare in Newcastle) rewards programme at Newcastle Hospitals NHS Foundation Trust. Shine is a staff benefits program which rewards staff for saving energy, reducing waste, travelling sustainably, and taking part in other sustainable actions. The programme is aimed at motivating staff to make behavioural changes to help the trust reach net zero through the accumulation of points and rewards.
Although this is a great initiative, it is not a replacement for having the right green infrastructure across all NHS estates in terms of consistent approaches to staff engagement, knowledge, and technological capabilities. As with most cases with data work across the NHS, there is no formal forum to share this. The lack of dedicated space to share best practices means other staff can’t learn from the work or replicate it nor can anybody reuse their own local data. With a system frequently deprived of a common of knowledge it creates difficulty in training new staff or developing the existing workforce with green data skills.
It’s understandable these compatibility issues would crop up, with different factions and trusts monitoring and measuring their data in their own way. Typically, this data is managed on different systems that cannot be cross-referenced. In terms of the sustainability programme, different trusts use different metrics to measure the improvements they’ve made in environmental areas as highlighted in their individual Green Plans. For example, University Hospitals Bristol and Weston NHS Foundation Trust measure their success with a ‘Sustainable Development Assessment Tool’ whilst University Hospitals Plymouth measure their progress with the Model Health System Sustainability Metrics. While each trust has it own unique needs, without a standardised way of measuring improvements in key categories like waste management and energy efficiency it creates difficulty in scoping national trends.
Figure 4: University Hospitals Bristol and Weston NHS Foundation Trust measuring their sustainable development with the SDAT in the Annual Sustainability Report 2020/2021
Figure 5: University Hospitals Plymouth measuring their sustainable development in the Annual Report 2022/2023.
For instance, these tables are taken from Bristol’s Annual Sustainability Report 2021/2022 and University Hospitals Plymouth Annual Report 2022/2023. It’s interesting to see how differently they’ve measured their ‘environmental year’ and the difficulties that crop up in comparing them like for like.
This compatibility issue has been emphasised further under the new care structure of Integrated Care Systems (ICS) replacing Clinical Commissioning Groups (CCGS). The coming together of multiple systems and methods of data management has proved challenging. Andrew Whittingham, the Associate Director of Finance at NHS Cheshire CCG stated, “one of the main issues we’ve found is having data that is comparable or being coded and processed in the same way”. Thus creating ‘information jams’ in generating reliable national trend predictions and solutions as very little data can be linked with detailed clinical information outside the original trust or body it was collected in.
But the shift to ICS also creates an opportunity to improve data quality as it demands a unified data-driven approach in managing processes to drive quality, safety and efficiency. With a greater pool of data from paired CCGs if they all eventually coded in the same way, it could help predict trends with greater accuracy and future spikes in activity. To benefit from data sets like these, strides need to be taken in making interoperability the default.
The issue of siloed work and lack of training becomes more glaring when its brought to clinicians and commissioners’ doors who don’t have the skills or given the necessary support to ask good questions of the data presented to them. As a result, the current use of data analysis to support decision-making in the NHS is variable and often poor.
The data quality across the NHS is also problematic as competency frameworks and enforced data standards are largely absent. The quality of the data varies from trust to trust and even more granularly on a hospital-to-hospital, department-to-department basis. Consequently, without detailed official guidance, it has led to long and drawn-out decision-making processes that hamper positive change being made for people and the planet.
Furthermore, the data science skills of the analytic workforce means are not being used effectively. The poor data analytics can also be partly attributed to the ‘coalface analytics’ historically being neglected in favour of aetiological research. The 10,000 strong ‘data analyst’ workforce is underutilised within the NHS as they sit in largely in junior, administrative roles focused primarily on data gathering and entry and don’t have the essential data science skills to spot patterns in inefficient services, the opportunities to improve the quality of care offered and identifying key insights. This has created uncertainty in deciphering the right data to start with and purging obsolete information. There is no point in collecting data if you can’t evaluate whether the new interventions that were implemented achieved their logistic objectives.
Once in these roles, analysts are given little to no guidance on the skills they need to build upon to progress and develop. Ben Goldacre remarks upon how current NHS job descriptions require them to become generalist managers to rise in seniority so there is no incentive to specialise in data analyst skills as this will not help them when looking to be promoted.
Given data analytics teams largely work in isolation, without any external knowledge sharing or collaboration from other analytics teams operating from different trusts/boards, innovative ways of working are stunted, and excellent examples of data analytics can’t be capitalised on. To relieve the system from a swell of impractical data work national standards are needed to reduce data silos. This will stop staff outside the direct analytic team from being blocked from critically reviewing the methods to spot errors and fix them as well as spot opportunities for reuse.
The NHS have also demonstrated using acquainted methods of data collection can lead to problems. In September 2020, during COVID, 15,841 coronavirus cases were lost due to poor software choices. Public Health England were using an old file format of Excel, it could only handle about 65,0000 rows of data as opposed to the 1 million plus Excel is typically capable of managing.
The United Nations asserted “data is the lifeblood of decision-making and the raw material for accountability”. This holds true for all organisations, yet the NHS rely upon a lower quality of data than they are capable of producing due to an underutilised analytic workforce that lacks clear career trajectories, good analytic work being produced in siloes, lack of regulated standards, using antiquated technologies to process their data and a historic failure to harness existing best practice into a common of knowledge. To ensure a more agile, efficient, and evidence-based decision-making to guarantee the NHS can consistently align with the UNSDG, improvements to data management and analysis are essential.
The nature of this work is essential to ensure data is utilised to deliver improvements in patient care, earlier identification of problems and efficiency gains within key sustainability issues. There is a need to centralise and take a holistic approach to data by integrating nationally driven as well as locally led plans to improve the environment and population health. This will provide opportunities to spot where costs and carbon are being lost unintentionally and ensure a sustainable culture is embedded, with good data at the forefront of all decisions.
Read the next blog in the series on how the NHS should tackle their data management and analysis…
[1] NHS England (2022) Delivering a ‘Net Zero’ National Health Service. Available at: https://www.england.nhs.uk/greenernhs/wp-content/uploads/sites/51/2022/07/B1728-delivering-a-net-zero-nhs-july-2022.pdf.
[1] Shah, A. (2019) ‘Using data for improvement’, BMJ: British Medical Journal, 364. Available at: https://www.jstor.org/stable/26958046?seq=1 (Accessed: 31 July 2023).
[1] Shah, A. (2019) ‘Using data for improvement’, BMJ: British Medical Journal, 364. Available at: https://www.jstor.org/stable/26958046?seq=1 (Accessed: 31 July 2023).
[1] United Nations (2015) The 17 sustainable development goals, United Nations. United Nations. Available at: https://sdgs.un.org/goals.
[1] Health Foundation (2021) How better use of data can help address key challenges facing the NHS. Available at: https://www.health.org.uk/publications/long-reads/how-better-use-of-data-can-help-address-key-challenges-facing-the-nhs (Accessed: 23 May 2023)
[1] Sustainable Healthcare in Newcastle (SHINE) Report 2019-2020 (2020) Newcastle Hospitals NHS Foundation Trust. Available at: https://www.newcastle-hospitals.nhs.uk/resources/sustainable-healthcare-in-newcastle-shine-report-2019-2020/ (Accessed: 31 July 2023).
[1] Shine Sustainable Healthcare (no date) Flourish at Newcastle Hospitals. Available at: https://www.flourishatnewcastlehospitals.co.uk/flourish-key-themes/sustainable-healthcare/ (Accessed: 31 July 2023).
[1] Goldacre, B., Bardsley, M., Benson, T. et al. (2020) Bringing NHS data analysis into the 21st century. Journal of the Royal Society of Medicine. 113(10), pp. 383–388. https://doi.org/10.1177/0141076820930666
[1] U.H.P.N. Trust (no date) Sustainability, University Hospitals Plymouth NHS Trust. Available at: https://www.plymouthhospitals.nhs.uk/sustainability (Accessed: 31 July 2023).
[1] Sustainable development (no date) www.uhbristol.nhs.uk. Available at: https://www.uhbristol.nhs.uk/about-us/sustainable-development
[1] University Hospital Bristol and Weston NHS Foundation Trust, Annual Sustainability Report 2020-21. Available at https://www.uhbw.nhs.uk/assets/1/annual_sustainability_report_uhbw_2020-21.pdf.
[1] University Hospital Plymouth NHS Trust, Annual Report 2022-2023, Available at download.cfm (plymouthhospitals.nhs.uk).
[1] CHS Healthcare (2020) Driving quality, safety and efficiency with data in Continuing Healthcare. Available at: https://www.chshealthcare.co.uk/driving-quality-safety-and-efficiency-with-data-in-continuing-healthcare/ (Accessed: 23 June 2023)
[1] Health Foundation (2021) How better use of data can help address key challenges facing the NHS. Available at: https://www.health.org.uk/publications/long-reads/how-better-use-of-data-can-help-address-key-challenges-facing-the-nhs (Accessed: 23 June 2023)
[1] Health Foundation (2021) How better use of data can help address key challenges facing the NHS. Available at: https://www.health.org.uk/publications/long-reads/how-better-use-of-data-can-help-address-key-challenges-facing-the-nhs (Accessed: 23 June 2023)
[1] Goldacre, B., Bardsley, M., Benson, T. et al. (2020) Bringing NHS data analysis into the 21st century. Journal of the Royal Society of Medicine. 113(10), pp. 383–388. https://doi.org/10.1177/0141076820930666
[1] Goldacre, B., Bardsley, M., Benson, T. et al. (2020) Bringing NHS data analysis into the 21st century. Journal of the Royal Society of Medicine. 113(10), pp. 383–388. https://doi.org/10.1177/0141076820930666
[1] Goldacre, B., Bardsley, M., Benson, T. et al. (2020) Bringing NHS data analysis into the 21st century. Journal of the Royal Society of Medicine. 113(10), pp. 383–388. https://doi.org/10.1177/0141076820930666
[1] Health Foundation (2021) How better use of data can help address key challenges facing the NHS. Available at: https://www.health.org.uk/publications/long-reads/how-better-use-of-data-can-help-address-key-challenges-facing-the-nhs (Accessed: 23 June 2023)
[1] Mahase, E. (2020) ‘Covid-19: Only half of 16 000 patients missed from England’s official figures have been contacted’, BMJ, p. m3891. Available at: https://doi.org/10.1136/bmj.m3891.
[1] United Nations (2015) The 17 sustainable development goals, United Nations. United Nations. Available at: https://sdgs.un.org/goals.
Written By Charlie Dawson