NHS0031

Written evidence submitted by Becton Dickinson UK Ltd

Summary of our position
The COVID-19 pandemic had had a significant impact on the delivery of NHS elective care and has resulted in increased waiting times and a backlog of cases. In February 2022 NHS England published the ‘Delivery plan for tackling the COVID-19 backlog of elective care’ which outlined its ambitions to address the backlog. The target of reducing the number of patients with a two-year wait was largely achieved by the target date of July 2022 and the focus is now on reducing the number of patients with a waiting time of one and a half years or more.

Becton Dickinson (BD) believes the focus on 78-week waiters is the correct strategy to improve patient’s experience of the NHS and we believe this can be achieved through increased automation and digitisation of NHS services, particularly within medication management and pathology services. BD is ready and willing to engage with Government ministers and Department of Health and Social Care officials on these matters to provide insight and expertise.

Conclusion
BD believes that the best way to impact NHS backlogs and waiting times is by increasing the speed of digitisation and automation of services to increase treatment capacity and free up staff time to perform other duties linked to reducing backlogs. Two areas that BD believes will have an immediate impact are the automation of medication management services to offer a closed medication management (CMM) system and by increasing the digitisation of pathology services.

Recommendation
BD recommends that the NHS expedites the speed of digitisation and automation of services to increase capacity and contribute towards the reduction in NHS backlogs. The increased automation of medication management services and the digitisation of pathology services are two areas that will have a demonstrable impact on the reduction of waiting times and the NHS backlog.

Background information

The design of national recovery plans
BD believes that when medication management relies on manual processes, lacks inventory control and involves redundant documentation procedures, it can be time-consuming, inefficient and error-prone1. The automation of medication management services will reduce medication errors and thus improve patient safety, optimise the pharmacy inventory and save on drug costs. Furthermore , widespread implementation of CMM would be beneficial to nurse productivity and increase time to improve patient care and address NHS backlogs and waiting times. The published evidence suggests positive impacts of automated dispensing systems and should encourage hospitals to invest in automation2.

Digital pathology has the potential to improve the way in which pathology services are delivered and provide improvements in the quality and speed of cancer diagnostics, as well as reducing the work pressure on an understaffed pathology service. Data from the Royal College of Pathologists, collected in 2016, stated that 32% of cellular pathologists were over the age of 55 and expected to retire in the next five years3. In digital pathology services slides can be scanned at a high resolution using a microscope lens and the digital slide can then be streamed to a pathologist using specialist software enabling a diagnosis to be made on a computer screen. This process increases the flexibility of delivering pathology services as well as speeding up the process and improving capacity.

With many clinical decisions being based on laboratory data, errors at any stage of the laboratory workflow can have a major impact on diagnostic and treatment pathways4.  Standardisation and improvements in laboratory technologies play a key role in increasing laboratory accuracy, reducing mistakes and increasing the quality of laboratory data5. Automation affords for laboratory scaling capacity, helping to ensure surges in patient specimen volumes do not impact quality and turn-around-time (TAT)6 and subsequently, the ability for clinicians to manage patient care effectively and safely7,8. Through automation, processes are also standardised, driving quality and consistency, and ultimately, will help to improve clinical decisions and patient outcome4.

Implementation of the recovery plans
NHS Trusts that have already implemented automated medication management services and digital pathology services are benefitting in terms of time saved and improvements in patient safety. Avoidable adverse drug events are estimated to cost the NHS £98,462,582 per year, consuming 181,626 bed days and causing or contributing to 1708 deaths9.

Early progress made in recovery services
BD believes that increasing automation within pathology labs will increase laboratory efficiency and productivity and remove human error. Standardisation of processes will give more reproducible, consistent results as well as improving lab and staff safety by reducing the risk of repetitive strain injuries.  Standardisation will reduce the number of false positive and false negative results which will improve patient care by increasing the likelihood of providing a correct diagnosis first time as well as reducing the costs associated with the need to re-test.

BD also believes that an increased focus on safety will improve efficiency, since avoidable harm to patients or healthcare workers will impact patient throughput and help address NHS backlogs and waiting times.

BD has a focus on sustainability and has made commitments in five areas where we see the most opportunity to create meaningful change over the next decade: climate change, product impact, a responsible supply chain, a healthy workforce/community and transparency10.

NHS Trusts are moving towards increased levels of digital health care provision post-pandemic resulting in improved patient experience through shorter waiting times and reduced time spent in hospital. Accelerating the move towards digital healthcare will improve patient outcomes and cut down NHS backlogs by relieving the workloads of NHS clinicians.

About our organisation
BD is a global medical technology company that is advancing the world of health by improving medical discovery, diagnostics and the delivery of care. BD leads in patient and health care worker safety and the technologies that enable medical research and clinical laboratories. The company provides innovative solutions that help advance medical research and genomics, enhance the diagnosis of infectious disease and cancer, improve medication management, promote infection prevention, equip surgical and interventional procedures and support the management of diabetes. 

The company partners with organisations around the world to address some of the most challenging global health issues. BD has more than 65,000 associates across 50 countries who work in close collaboration with customers and partners to help enhance outcomes, lower health care delivery costs, increase efficiencies, improve health care safety and expand access to health.

References
1. Ebel T, George K, Larsen E, Neal E, Shah K, Shi D. Strength in unity: The promise of global standards in healthcare. New York City, NY, United States: McKinsey & Company; 2013

2. Batson S et al. Automation of in-hospital pharmacy dispensing: a systematic review. Eur J Hosp Pharm. 2021 Mar, 28(2): 58-64. Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907692/ (Accessed 9th November 2022)

3. Cancer Research UK. Testing times to come? An evaluation of pathology capacity across the UK 2016.  https://www.cancerresearchuk.org/sites/default/files/testing_times_to_come_nov_16_cruk.pdf (accessed 9th November 2022)

4. WHO. Laboratory Quality Management System Handbook. 2011

5. J.J.M. van Dongen, L. Lhermitte, S. Böttcher, et al on behalf of the EuroFlow Consortium (EU-FP6, LSHB-CT-2006-018708). EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia. 2012, 26 (9): 1908-75.

6. Angeletti S, De Cesaris M, Hart JG, et al. Laboratory Automation and Intra-Laboratory Turnaround Time: Experience at the University Hospital Campus Bio-Medico of Rome. J Lab Autom. 2015;20(6):652-658.

7. Howanitz J.H. and Howanitz P.J. Laboratory results. Timeliness as a quality attribute and strategy. Am J Clin Pathol. 2001;116(3):311-5

8. Carraro P. and Plebani M. Errors in a Stat Laboratory: Types and Frequencies 10 Years Later. Clinical Chemistry 2007;53: 1338-1342

9. Elliott RA, Camacho E, Jankovic D, et al. Economic analysis of the prevalence and clinical and economic burden of medication error in England. BMJ Quality & Safety. 2020;30:96-105

10. BD. Environmental Social and Governance Report 2021. Available at https://investors.bd.com/static-files/3cd64f37-762a-4aa7-bd81-9b9030172dee (Accessed 9th November 2022)

November 2022