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A recent paper (from clinicians and Human Factors specialists at the Royal Surrey NHS Foundation Trust) jointly supported by Elsevier and BJA Education clarifies what Human Factors (HF) is by highlighting and redressing key myths.  The learning objectives from the paper are as follows: Identify common myths around HF Describe what HF is Discuss the importance of HF specialists in healthcare Distinguish the importance of a systems-based approach and user-centred design for HF practice.  It explains that HF is a scientific discipline in its own right, a complex adaptive system very much like healthcare. Its principle have been used within healthcare for decades but often in an informal way.  A link to the summary of the article on Science Direct and further links to purchase the paper can be found here: https://www.sciencedirect.com/science/article/abs/pii/S2058534923000963?dgcid=author 

Carl Heneghan discusses the role of modelling in the Covid-19 pandemic.

This Rapid Evidence Scan from Moore et al. examined the effectiveness of virtual hospital models of care. While no reviews evaluated a complete model, tele-healthcare only and tele-healthcare with remote telemonitoring interventions demonstrated similar or significantly better clinical or health system outcomes including reduced hospitalisations, readmissions, emergency department visits and length of stay, compared to usual care, including those delivered without home visits or face-to-face care. The use of the Internet showed mixed but promising results. The strongest evidence was for cardiac failure, coronary heart disease, diabetes and stroke rehabilitation. Nurses played a central role in home visiting, providing telephone support and education. However, the studies were heterogenous and the results should be interpreted with caution.

Although most current medication error prevention systems are rule-based, these systems may result in alert fatigue because of poor accuracy. Previously, we had developed a machine learning (ML) model based on Taiwan’s local databases (TLD) to address this issue. However, the international transferability of this model is unclear. This study examines the international transferability of a machine learning model for detecting medication errors and whether the federated learning approach could further improve the accuracy of the model. It found that the ML model has good international transferability among US hospital data. Using the federated learning approach with local hospital data could further improve the accuracy of the model.

The biopsychosocial model is both a philosophy of clinical care and a practical clinical guide. Borrell-Carrió et al. discuss the principles behind the biopsychosocial model and its application.

This research, published by PLoS ONE, highlights how community-based antenatal care, with a focus on continuity of carer reduced health inequalities and improved maternal and neonatal clinical outcomes for women with social risk factors. The findings support the current policy drive to increase continuity of midwife-led care, whilst adding that community-based care may further improve outcomes for women at increased risk of health inequalities. 

This paper from Samson et al. discusses the properties of complex systems and a systems approach to incident investigation, describes the differences between reactive and proactive safety approaches and describes some of the system-focused models applied to patient safety incident investigations.

Plan Do Study Act (PDSA) cycles are an ideal quality improvement tool that can be used to test an idea by temporarily trialling a change and assessing its impact. PDSA is a very structured four-step cycle which requires effort and discipline. It incorporates careful and detailed consideration of the following: Plan: A plan of what is to be tested including questions to be answered, predictions and answers to the questions and a plan for collection of data to answer the questions. Do: Carry out the test of change according to the plan, recording observations including unexpected outcomes/observations. Study: A comparison of the data against the predictions made in the plan and study the results. Act: Make a decision about the next course of action. Whilst the PDSA cycle originates from industry, it has been incorporated into the Model for Improvement It can be used to test ideas in the real or simulated context.

‘Systems thinking’ is often recommended in healthcare to support quality and safety activities but a shared understanding of this concept and purposeful guidance on its application are limited. Healthcare systems have been described as complex where human adaptation to localised circumstances is often necessary to achieve success. Principles for managing and improving system safety developed by the European Organisation for the Safety of Air Navigation (EUROCONTROL; a European intergovernmental air navigation organisation) incorporate a ‘Safety-II systems approach’ to promote understanding of how safety may be achieved in complex work systems. Authors of this paper, published by BMJ Open Quality, aimed to adapt and contextualise the core principles of this systems approach and demonstrate the application in a healthcare setting.

Complex systems consist of many dynamic interactions between people, tasks, technology, environments (physical and social), organisational structures and arrangement and external factors, such as the influence of national policy or regulation. The nature of these interactions often results in unpredictable changes in system conditions (such as patient demand, staff capacity, available resources and organisational constraints) and goal conflicts (such as the frequent pressure to be efficient and thorough). To achieve success, people frequently adapt to these system conditions and goal conflicts. But rather than being planned in advance, these adaptations are often approximate responses to the situations faced at the time.  Therefore, to understand patient safety or staff wellbeing (and other emergent outcomes) we need to look beyond the individual components of care systems to consider how outcomes (wanted and unwanted) emerge from interactions in, and adaptations to, everyday working conditions. Follow the link below to the NHS Education Scotland (NES) website to find out more about systems thinking and access systems approach resources.

System thinking encourages the consideration of the interacting forces contributing to problems to enable the design and implementation of strategies to address the underlying conditions that perpetuate those problems. This article from Bradley et al. in eClinical Medicine provides an illustration of the various forces to be resolved to effectively respond to COVID-19. Bradley DT, Mansouri MA, Kee F, Garcia LMT. A systems approach to preventing and responding to COVID-19. 

Simon Whitely in this video responds to some of the comments received on his last video, where he talk about a high-level HCS Model of the Healthcare System and how interactions with the general public are key for patient safety. He also talks about the challenges between managing safety and the potential impacts upon the overall economy.

Safety-I is defined as the freedom from unacceptable harm. The purpose of traditional safety management is therefore to find ways to ensure this ‘freedom’. But as socio-technical systems steadily have become larger and less tractable, this has become harder to do. Resilience engineering pointed out from the very beginning that resilient performance – an organisation’s ability to function as required under expected and unexpected conditions alike – required more than the prevention of incidents and accidents. This developed into a new interpretation of safety (Safety-II) and consequently a new form of safety management. Safety-II changes safety management from protective safety and a focus on how things can go wrong, to productive safety and a focus on how things can and do go well. For Safety-II, the aim is not just the elimination of hazards and the prevention of failures and malfunctions but also how best to develop an organisation’s potentials for resilient performance – the way it responds, monitors, learns, and anticipates. That requires models and methods that go beyond the Safety-I toolbox. This book introduces a comprehensive approach for the management of Safety-II, called the Resilience Assessment Grid (RAG). It explains the principles of the RAG and how it can be used to develop the resilience potentials. The RAG provides four sets of diagnostic and formative questions that can be tailored to any organisation. The questions are based on the principles of resilience engineering and backed by practical experience from several domains. Safety-II in Practice is for both the safety professional and academic reader. For the professional, it presents a workable method (RAG) for the management of Safety-II, with a proven track record. For academic and student readers, the book is a concise and practical presentation of resilience engineering.

Mindful organising is a key integrating concept in resolving the organisational accident. Mindful organising is both the unique source of critical information about the normal operation, as well as the key recipient of intelligence about the operation, ensuring that operational actions are always informed by the most current, relevant information about potential risks no matter how remote. Highlights of the paper: Principles of mindful organising are operationalised in a Mindful Governance model. The model is grounded in two cases studies in contrasting aviation organisations. The case studies led to the development of three prototype web applications.

Health and social care faces a conflict between safe and appropriate staffing and the (government) directive to be cost efficient. In a time of clinical and support staff shortages, increasing demand for services and financial austerity, there is a need for a consistent approach to workforce analysis, benchmarking and planning across the health and social care to enable informed decision-making across finance, HR and nursing management to put the patient and their safety at the centre of all we do. 'Establishment Genie' is an online workforce planning, safe staffing and benchmarking tool. It has been co-developed and tested with more than 300 teams across acute, community, residential care, hospice and independent providers of care. This has been supported by input from NHSE, NHS Professionals, The Florence Nightingale Foundation, Safe Staffing Alliance, Royal College of Nursing, Health Education England, Queen’s Nursing Institute and academic nurse staffing experts. Case study examples The following case studies show how trusts have been using the tool. Roles and responsibilities of staff have been reviewed and new workforce plans have been co-designed with staff at the frontline to deliver new ways of working that put the patient at the centre of care – whatever the setting. The Hillingdon Hospitals - Safety Supervision and Savings.pdfThe Hillingdon Hospitals - Ward Reconfiguration for Safety.pdf GIG Cymru NHS Wales - Residential Nursing homes Case Study.pdfChelsea and Westminister Hospital Case Study - Empowering Staff.pdf GIG Cymru NHS Wales - District Nursing Principles Case Study (1).pdfBerkshire Health Community Nursing Case Study.pdf Organisational benefits Integrated care levels, costs and common language enables clinical and corporate leads to collaborate and meet the requirements of a next-generation health and social care workforce: Precise staffing profiles and options appraisal support CIP development and budgeting. Gap analysis compared to budget and standards for exact hours and WTE requirement for each band. Uplift for leave is specific to each role and expected joiners, avoiding blanket uplifts that may not fit the needs of the unit. Governance and control underpinned by agreed, costed roster templates, with ready reckoners to keep within range. Improved recruitment and retention with evidence of staffing levels and support. Outcomes track quality, with benchmarking to assure. Clinical benefits Professional judgement in workforce planning is supported by this NICE-endorsed tool: Planning care levels and WTE for expansion, efficiency, reconfiguration and new service models. Evaluating alternative shift models to reorganise, invest or save. Modelling skill-mix and impact of new roles. Understanding and validating variation. Challenging peaks and troughs in cover to improve safety, release capacity and release cost savings. Benchmarking and triangulation of patient care levels, with outcomes for correlation. Mapping other staff group input across each setting. Background on 'Establishment Genie' Creative Lighthouse was founded in response to frustration at the focus on financially led decisions in health and social care management that did not consider the safety and care of patients or staff. We set out to build a platform that would allow all management groups in the healthcare sector to collaborate on safe staffing and financial governance. Creative Lighthouse self-funded the development of a unique workforce-planning tool under the brand name ’Establishment Genie’, endorsed by the National Institute of Health and Care Excellence (NICE) in 2017. In April 2017, the Creative Lighthouse team were awarded a grant from Innovate UK to continue to develop the tool to include all settings of care in the knowledge that patient safety and workforce planning is not only the responsibility of acute services, but of all providers and commissioners of care. This is a critical aspect of enabling the improvement of quality and patient outcomes in a cost effective way, whilst providing data driven analytics to support professional judgment. About the author I am a healthcare professional with over 15 years’ experience working in and consulting to public and private health and social care organisations. I have worked with a variety of health and care sector clients in the delivery of complex change, from transformational change and organisational design process to programme leadership and execution. I am passionate about the safe staffing agenda, recognising that in order for any organisation to ensure appropriate care and evidence for professional judgement, there must be consistency in approach and a way of linking staffing levels to quality outcomes that can then be benchmarked within and across organisations. This passion resulted in the birth of ‘Establishment Genie’.

In this article, Human Factors Consultant, Jayne Higgs, talks about systems thinking. She highlights the different components that contribute to systems thinking (including human factors) and argues that this approach can aid a move away from a narrow-perspective blame culture.

The Patient Experience Journal (PXJ) is a peer-reviewed, open-access journal published in association with The Beryl Institute. PXJ is committed to disseminating rigorous knowledge and expanding the global conversation on evidence and innovation on patient experience. Grounded in their core principles, PXJ engages all perspectives, with a strong commitment to patients included.

This article in the Washington Post simply describes COVID-19, how it spreads and how extensive social distancing helps.

Suzette Woodward has been studying safety since the 1990s. In her commentary published in the Journal of Patient Safety and Risk Management, she describes three concepts: complex adaptive systems, three models of safety, and safety I and safety II. This paper explores work from: Plsek and Greenhalgh Charles Vincent and Rene Amalberti Erik Hollnagel

Larouzee and Le Coze describe the development of the “Swiss cheese model” and the main criticisms of this model and the motivation for these criticisms.  The article concludes that the Swiss cheese model remains a relevant model because of its systemic foundations and its sustained use in high-risk industries and encourages safety science researchers and practitioners to continue imagining alternatives combining empirical, practical and graphical approaches.

Healthcare practitioners, patient safety leaders, educators and researchers increasingly recognise the value of human factors/ergonomics and make use of the discipline's person-centred models of sociotechnical systems. This paper from Holden et al. first reviews one of the most widely used healthcare human factors systems models, the Systems Engineering Initiative for Patient Safety (SEIPS) model, and then introduces an extended model, ‘SEIPS 2.0’. SEIPS 2.0 incorporates three novel concepts into the original model: configuration, engagement and adaptation. The concept of configuration highlights the dynamic, hierarchical and interactive properties of sociotechnical systems, making it possible to depict how health-related performance is shaped at ‘a moment in time’.  Engagement conveys that various individuals and teams can perform health-related activities separately and collaboratively. Engaged individuals often include patients, family caregivers and other non-professionals. Adaptation is introduced as a feedback mechanism that explains how dynamic systems evolve in planned and unplanned ways. Key implications and future directions for human factors research in healthcare are discussed.

This article in the Journal of Patient Safety argues that embedding patient safety initiatives is not just about establishing linear protocols, but changing the habits of complex organisations, beginning at the level of the clinical team. They highlight that Safety II is drawing attention to the complexity in healthcare systems and outline the use of Cultural-Historical Activity Theory (CHAT) as a way to align learning theory and complexity theory as a framework for patient safety initiatives.

In 2017, a change (serendipity) in the philosophy of occurrence investigations took place at NS (Dutch Railways). It seems the investigations conducted and published before and after 2017 are different, both in the way the investigations are executed and in their effects on the organisation. This research has been carried out to find out if, in what way, and to what degree the two specific types of investigations are different with a special interest in the effects of the investigations on the organisation. This research, published by Lund Universities Libraries, comprises two parts. In part 1 a comparative analysis is conducted on investigation reports — scrutinising five reports pre-2017 and four reports post-2017. The analytical framework is derived from Hollnagel's categorisation regarding incident investigation models, which delineates three models: sequential, epidemiological, and systemic. The findings show that there are distinctions in both the nature and effects of the investigation reports. Investigations conducted pre-2017 exhibit characteristics of the sequential model due to a focus on what went wrong, (broken) components and measures that mostly aim at the sharp end operator (train drivers, conductors, train dispatcher) such as training and discussing specific findings of the investigations with those involved only.

Robert Barker, author of the book, 'The Time Based Organisation: Recreating and Transforming Existing Organisations', highlights how time-based analysis can be used in the NHS to transform the patient journey. Huge amounts of untapped potential and waste exist in the NHS, yet all the equipment, assets and infrastructure are already in place. Overall patient journey throughput times are currently too long, but the combined strengths of time-based analysis, which looks at value adding processes through the lens of time and NHS staff who know these processes better than anyone else, can transform the NHS patient journey. In the example below, you will see large amounts of non-value adding time (wait and queue). The value adding time here is around 8%. The NHS patient journey typically reflects the management structure where specialists control the treatment islands of efficiency but nobody is responsible for the non-value adding time gaps. Hence long waits and queue times. Tracking a patient journey using the lens of time identifies a lot of non-value adding time and additional costs that impact both the patient’s health and costs. Analysing the flow of patients is undertaken by value adding staff, your best consultants. Transformation of the treatment process journey is needed now more than ever, since it will include “What stops staff doing the best days work they can”. Note – Time-based transformation is driven by value adding employees not management consultants, but it requires support from NHS leaders.