Design as a quality improvement strategy: The case for design expertise.

Bad design in safety-critical environments like healthcare can lead to users being frustrated, excluded or injured. In contrast, good design can make it easier to use a service correctly, with impacts on both the safety and efficiency of healthcare delivery, as well as the experience of patients and staff. The participative dimension of design as an improvement strategy has recently gained traction in the healthcare quality improvement literature. However, the role of design expertise and professional design has been much less explored. Good design does not happen by accident: it takes expertise and the specific reasoning that expert designers develop through practical experience and training. Here, we define design, show why poor design can be disastrous and illustrate the benefits of good design. We argue for the recognition of distinctive design expertise and describe some of its characteristics. Finally, we discuss how design could be better promoted in healthcare improvement.

A systems approach to developing user requirements for increased pulmonary rehabilitation uptake by COPD patients.

Chronic Obstructive Pulmonary Disease is a progressive lung disease associated with anxiety, depression, and reduced health-related quality of life. Pulmonary rehabilitation (PR) is a cost-effective and transformative treatment, but 31% of referred patients do not take up their PR appointment. The study aimed to develop user requirements for an intervention to increase PR uptake. A systems approach, the Engineering Better Care framework, was used to develop a system map of the PR pathway, translate evidence-based user needs into user requirements, and validate the user requirements in a stakeholder workshop. Eight user requirements addressed patient and health care practitioner needs to understand what PR entails, understand the benefits of PR and have positive conversations about PR to address patient concerns. The solution-independent user requirements can be applied to the development of any intervention sharing similar goals. The study demonstrates potential in taking a systems approach to more challenges within respiratory medicine.

Towards a better understanding of mental health care delivery systems: From stories to system components.

The growing demand for better quality of care, together with an increasing awareness of limited resources, is bringing attention to the need for design in healthcare. In mental health, considered the largest single cause of disability in the UK, the need is great. Existing services often fail to meet current levels of demand and do not consistently deliver good quality care for all service users. The design of better delivery systems has the potential to improve service user experience and care outcomes. This paper reports how through the interactive and participatory method of storytelling, the key components of a mental health delivery system were identified. We explain each of the ten components and discuss their implications for system understanding and service design. A model of a mental health delivery system has also been proposed.

Codesigning a systemic discharge intervention for inpatient mental health settings (MINDS): a protocol for integrating realist evaluation and an engineering-based systems approach.

INTRODUCTION: Transition following discharge from mental health hospital is high risk in terms of relapse, readmission and suicide. Discharge planning supports transition and reduces risk. It is a complex activity involving interacting systemic elements. The codesigning a systemic discharge intervention for inpatient mental health settings (MINDS) study aims to improve the process for people being discharged, their carers/supporters and staff who work in mental health services, by understanding, co-designing and evaluating implementation of a systemic approach to discharge planning. METHODS AND ANALYSIS: The MINDS study integrates realist research and an engineering-informed systems approach across three stages. Stage 1 applies realist review and evaluation using a systems approach to develop programme theories of discharge planning. Stage 2 uses an Engineering Better Care framework to codesign a novel systemic discharge intervention, which will be subjected to process and economic evaluation in stage 3. The programme theories and resulting care planning approach will be refined throughout the study ready for a future clinical trial. MINDS is co-led by an expert by experience, with researchers with lived experience co-leading each stage. ETHICS AND DISSEMINATION: MINDS stage 1 has received ethical approval from Yorkshire & The Humber-Bradford Leeds (Research Ethics Committee (22/YH/0122). Findings from MINDS will be disseminated via high-impact journal publications and conference presentations, including those with service user and mental health professional audiences. We will establish routes to engage with public and service user communities and National Health Service professionals including blogs, podcasts and short videos. TRIAL REGISTRATION NUMBER: MINDS is funded by the National Institute of Health Research (NIHR 133013) https://fundingawards.nihr.ac.uk/award/NIHR133013. The realist review protocol is registered on PROSPERO. PROSPERO REGISTRATION NUMBER: CRD42021293255.

Systems approach to improving traumatic brain injury care in Myanmar: a mixed-methods study from lived experience to discrete event simulation.

OBJECTIVES: Traumatic brain injury (TBI) is a global health problem, whose management in low-resource settings is hampered by fragile health systems and lack of access to specialist services. Improvement is complex, given the interaction of multiple people, processes and institutions. We aimed to develop a mixed-method approach to understand the TBI pathway based on the lived experience of local people, supported by quantitative methodologies and to determine potential improvement targets. DESIGN: We describe a systems approach based on narrative exploration, participatory diagramming, data collection and discrete event simulation (DES), conducted by an international research collaborative. SETTING: The study is set in the tertiary neurotrauma centre in Yangon General Hospital, Myanmar, in 2019-2020 (prior to the SARS-CoV2 pandemic). PARTICIPANTS: The qualitative work involved 40 workshop participants and 64 interviewees to explore the views of a wide range of stakeholders including staff, patients and relatives. The 1-month retrospective admission snapshot covered 85 surgical neurotrauma admissions. RESULTS: The TBI pathway was outlined, with system boundaries defined around the management of TBI once admitted to the neurosurgical unit. Retrospective data showed 18% mortality, 71% discharge to home and an 11% referral rate. DES was used to investigate the system, showing its vulnerability to small surges in patient numbers, with critical points being CT scanning and observation ward beds. This explorative model indicated that a modest expansion of observation ward beds to 30 would remove the flow-limitations and indicated possible consequences of changes. CONCLUSIONS: A systems approach to improving TBI care in resource-poor settings may be supported by simulation and informed by qualitative work to ground it in the direct experience of those involved. Narrative interviews, participatory diagramming and DES represent one possible suite of methods deliverable within an international partnership. Findings can support targeted improvement investments despite coexisting resource limitations while indicating concomitant risks.

Can compliment and complaint data inform the care of individuals with chronic subdural haematoma (cSDH)?

OBJECTIVES: To explore the frequency and nature of complaints and compliments reported to Patient Advice and Liaison (PALS) in individuals undergoing surgery for a chronic subdural haematoma (cSDH). DESIGN: A retrospective study of PALS user interactions. SUBJECTS: Individuals undergoing treatment for cSDH between 2014 and 2019. METHODS: PALS referrals from patients with cSDH between 2014 and 2019 were identified. Case records were reviewed and data on the frequency, nature and factors leading up to the complaint were extracted and coded according to Healthcare Complaints Analysis Tool (HCAT). RESULTS: Out of 531 patients identified, 25 (5%) had a PALS interaction, of which 15 (3%) were complaints and 10 (2%) were compliments. HCAT coding showed 8/15 (53%) of complaints were relationship problems, 6/15 (33%) a management problem and 1/15 (7%) other. Of the relationship problems, 6 (75%) were classed as problems with communication and 2 (25%) as a problem with listening. Of the compliments, 9/10 (90%) related to good clinical quality and 1/10 (10%) to staff-patient relationship. Patients were more likely to register a compliment than family members, who in turn were more likely to register a complaint (p<0.005). Complaints coded as a relationship problem had 2/8 (25%) submitted by a patient and 6/8 (75%) submitted by a relative. CONCLUSIONS: Using the HCAT, routinely collected PALS data can easily be coded to quantify and provide unique perspective on tertiary care, such as communication. It is readily suited to quality improvement and audit initiatives.

Systems approach to health service design, delivery and improvement: a systematic review and meta-analysis.

OBJECTIVES: To systematically review the evidence base for a systems approach to healthcare design, delivery or improvement. DESIGN: Systematic review with meta-analyses. METHODS: Included were studies in any patients, in any healthcare setting where a systems approach was compared with usual care which reported quantitative results for any outcomes for both groups. We searched Medline, Embase, HMIC, Health Business Elite, Web of Science, Scopus, PsycINFO and CINAHL from inception to 28 May 2019 for relevant studies. These were screened, and data extracted independently and in duplicate. Study outcomes were stratified by study design and whether they reported patient and/or service outcomes. Meta-analysis was conducted with Revman software V.5.3 using ORs-heterogeneity was assessed using I2 statistics. RESULTS: Of 11 405 records 35 studies were included, of which 28 (80%) were before-and-after design only, five were both before-and-after and concurrent design, and two were randomised controlled trials (RCTs). There was heterogeneity of interventions and wide variation in reported outcome types. Almost all results showed health improvement where systems approaches were used. Study quality varied widely. Exploratory meta-analysis of these suggested favourable effects on both patient outcomes (n=14, OR=0.52 (95% CI 0.38 to 0.71) I2=91%), and service outcomes (n=18, OR=0.40 (95% CI 0.31 to 0.52) I2=97%). CONCLUSIONS: This study suggests that a systems approaches to healthcare design and delivery results in a statistically significant improvement to both patient and service outcomes. However, better quality studies, particularly RCTs are needed.PROSPERO registration numberCRD42017065920.

A systems approach to healthcare: from thinking to -practice.

Medicine is increasingly complex, involving a highly connected system of people, resources, processes, and institutions. Attempts to improve care involve disruptions to this system, with the potential for wide-ranging consequences, both positive and negative. Despite this, many improvement methodologies are poorly equipped to manage either complexity or risk - instead focusing on discrete interventions whose effects are narrowly monitored. Engineers have long understood that complex problems require a systems view, and that attempts to make things better can themselves introduce new risk into a system. Given this, an engineering systems approach may be of significant value to those trying to improve healthcare. Two fundamental questions emerge from such an approach: what can we do better, and what could possibly go wrong? This paper describes the evolution of a systems approach to healthcare, and explores a recently co-developed framework outlining a systems approach based upon a synergy between healthcare and engineering.

An Integrated Model of Patient and Staff Satisfaction Using Queuing Theory.

This paper investigates the connection between patient satisfaction, waiting time, staff satisfaction, and service time. It uses a variety of models to enable improvement against experiential and operational health service goals. Patient satisfaction levels are estimated using a model based on waiting (waiting times). Staff satisfaction levels are estimated using a model based on the time spent with patients (service time). An integrated model of patient and staff satisfaction, the effective satisfaction level model, is then proposed (using queuing theory). This links patient satisfaction, waiting time, staff satisfaction, and service time, connecting two important concepts, namely, experience and efficiency in care delivery and leading to a more holistic approach in designing and managing health services. The proposed model will enable healthcare systems analysts to objectively and directly relate elements of service quality to capacity planning. Moreover, as an instrument used jointly by healthcare commissioners and providers, it affords the prospect of better resource allocation.