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Significant racial and socioeconomic disparities in care quality and patient safety persist across and within countries. Recent evidence continues to show that a significant cause for the persistence of health disparities is grounded in systemic racism,1 that is, the way that the ideology of inferiority is embedded in health infrastructures, laws, policies and societal practices to perpetuate widespread unfair treatment of people of colour.2
These conditions undermine care quality and patient safety through the ways they are embedded in existing quality and safety infrastructure and their effects on patients and families. Compared with white patients, the electronic health records of black patients have 2.5 times the odds of having negative descriptors and stigmatising language (eg, ‘aggressive’) in their history and physical notes, which elicited less attention to patient concerns (eg, pain) and correspondingly less aggressive treatment.3 Voluntary safety reporting tends to understate the number and range of safety events experienced by black patients relative to automated systems (eg, the global trigger tool).4 Moreover, a recent report from the Urban Institute in the USA found that black patients had higher rates of adverse patient safety events on 6 of 11 measures and higher failure to rescue rates.5 The underlying conditions related to racism and structural inequities also impose a ‘cognitive tax’ on patients and families that has been shown to increase cognitive errors that impair ability to share symptoms and treatment adherence in ways that negatively affect care quality.6 To the extent these have received attention, it has been via specific quality improvement (QI) projects explicitly focused on inequities with specific (chronic) conditions such as diabetes.7 However, in only focusing on equity during specific ‘equity’ QI projects, QI teams miss opportunities to address how disparities and inequities embed in everyday care in ways that inhibit quality and safety. We therefore argue for infusing attention to disparities and equity into the building blocks of all QI work.
QI projects seek to systematically explore and reveal underlying causes of gaps in quality and safety and make changes to everyday practice to address them. As such, the legitimacy and familiarity of QI and its associated tools to improve care provide a vehicle for sustained attention to equity enhancement across organisational activities and not just specific projects to enhance equity. We argue that QI research and practice can be a powerful tool for equity enhancement. More specifically, we illustrate three ways in which all QI projects can broaden their consideration of the influences on quality and safety outcomes to include attention to disparities and equity. In other words, QI can be a tool for improving quality and safety equitably even when the project itself is not an ‘equity project’. Specifically, organisations can create the conditions for equity by (1) improving the data infrastructure for QI, (2) modifying the composition of QI project teams, and (3) taking actions that make simultaneous equity enhancement and QI more likely via the sustained use of multiple QI cycles in their everyday work. QI project teams can ensure these three activities reflect attention to structural inequities as we detail below. Structural inequities describe how clinically defined issues, for example, symptoms, attitudes or diseases, represent the downstream implications of a number of upstream decisions related to differences in food delivery systems, zoning laws, urban and rural infrastructures, medicalisation, or even the very definitions of illness and health across patient populations.8 We argue this expanded attention is most impactful when it is infused into the data infrastructure, team composition and sustained actions of QI teams.
We start by detailing what we mean by structural inequities and how QI teams and their members can address both structural and outcome inequities (eg, safety and quality) in their everyday work. We then elaborate on the data infrastructure, team composition, and actions that make simultaneous equity enhancement and QI more likely and sustainable. For each, we illustrate how attention to structural inequities reshapes how a QI team enacts the plan–do–study–act (PDSA) cycle. We use PDSA as a representative and widely adopted tool of QI to provide a window into how QI teams can embed greater structural imagination and closer attention to structural inequities to (a) increase health equity by reducing existing quality and safety disparities in care and (b) ensure that quality and safety enhancing interventions (eg, ‘teach-back’ at discharge to reduce readmissions9) are also equitable. In doing so, we also detail how a focus on structural inequity that cascades through data, team composition and actions by QI teams ensures that PDSA cycles are truly iterative by broadening the measures considered, voices involved and interventions implemented.10
Sensitising QI teams to structural inequities
As systems thinking revolutionised safety research and practice by shifting thinking away from individual human errors at the sharp end, closer attention to structural factors and inequities holds similar promise for improving quality and safety more equitably. Although early efforts to increase understanding of structural factors have focused on medical education,8 we illustrate how everyday shifts in attention and language provide a foundation for greater equity. More specifically, paying greater attention to both the social conditions and practical logistics that shape patients’ lives and impede access and adherence11 can help overcome simple explanations of ‘non-compliance’ and stigmatising (eg, ‘aggressive, combative, hysterical’) and dismissive (eg, ‘frequent fliers’) language that marginalises specific patients or groups of patients.12
We argue that recognising the inequitable distribution of access to high-quality safe care necessitates QI teams to expand the set of factors they interrogate. Broadly, this entails recognising the structures that shape clinical interactions, considering the possibility of structural interventions and collaboration with other stakeholder groups with deeper expertise.8 As an example of considering structural factors and a structurally targeted intervention, one QI team examined patient geographical location through zip code mapping or geocoding, which led to identifying and implementing a new diabetes management programme (telephonic intervention) that targeted high diabetes prevalence zones. Subsequently, black patients in these high diabetes zones increased their HbA1c testing by 15%.7
For QI teams attending to structural inequities, they must consider structural conditions that give rise to quality and safety disparities and also question whether interventions and new practices they propose may fail to reduce or even exacerbate disparities. For instance, QI teams could consider how issues related to power differences between patients and providers,11 medicalisation of society,8 technology access (eg, internet for telemedicine), transportation, food and housing (eg, rental issues), work (eg, labour and immigration concerns) or care-related resources (eg, protective equipment) affect improvement initiatives. A key objective for QI teams then becomes examining quality and safety issues not only in terms of any disparities that exist within the QI area in question (eg, pregnancy-related mortality rates), but also the proposed solutions. That means exploring structural inequities facing the focal patient population and aiming for interventions that account for the true diversity of patient circumstances and work to minimise burden on patients (eg, through flexible scheduling, open access, extended hours that minimise the work/care trade-off).6 For the following considerations regarding data, teams and actions, we focus on structural inequities as they relate to race and ethnicity to provide consistent, focused examples that are applicable in many countries.13 We also note that our proposed approach would similarly apply to other differences related to experiencing inequitable care that may even be more salient in specific countries, for example, differences in language, geography or disability.
Rethinking QI data
For QI teams to effectively examine disparities in quality and safety issues and devise inclusive, equity-enhancing solutions, they need a data infrastructure that supports these efforts. The data that enable QI teams to do their work with attention to structural inequity need to make clear any disparities that exist by providing disaggregated data by, for example, race and ethnicity on quality and patient safety incidents. This differs from attempts to ‘correct’ for race in clinical algorithms or guidelines that can exacerbate racial disparities.14 Instead, we focus on these data as a means of pointing to and addressing the underlying social conditions that create inequities.14 15 Examining existing measures of quality (eg, Consumer Assessment of Healthcare Providers and Systems) and safety (eg, voluntary reports or trigger tools), for example, by ethnicity, race and socioeconomic status can reveal disparities in the experience of care quality and patient safety.5 Measures reported in these ways can also help track the extent to which improvement efforts actually enhance equity for a given improvement target. These efforts need to go beyond assessing disparities in quality and safety by, for example, ethnicity, race or socioeconomic status, but should also include data that enable QI teams to regularly interrogate their assumptions regarding the patients receiving proposed improvements, and more specifically whether they may have the resources required to benefit. That is, does the intervention require some financial security, specific food access, social networks (ie, helpful vs disruptive friends and family), legal status, residence and physical safety, and functional health literacy11 for it to be effective? In other words, the data collected should provide a fuller, more nuanced depiction of the lived experience of the patients affected.16 A process for refreshing the data infrastructure for a given improvement target that considers structural inequities informs how QI teams plan (ie, prepare for change), do (ie, select measures) and act (eg, identifying facilitators and broadening communication), and enables QI projects of all types to become equity enhancing.
Constructing QI teams to enhance equity
QI teams are better positioned to enhance equity while addressing quality and safety issues when they engage with the affected patients, families and communities in ways that deepen empathy, trust and understanding. This is more likely when QI teams are intentionally constructed to give voice to experiences of marginalisation that are consequential for quality and safety processes, by having care providers who are members of marginalised communities and/or broadening the roles (eg, social workers), perspectives and voices (eg, patients, families, community leaders) included in QI teams. For example, having social workers on QI teams means the social forces shaping patients’ lives that may affect the viability of a particular intervention will receive greater attention. Social workers can also bring greater connection and outreach to partner (community and social service) organisations and communities such that there is greater voice, representation and engagement with, for example, communities of colour. Bringing broader engagement and communication with populations that are disproportionately affected by poor quality and safety outcomes helps ensure that their interests and experiences shape QI projects undertaken, how they are carried out and the interventions developed.16 In other words, ensuring QI efforts are broadly equity enhancing means that such concerns inform how QI teams are created during the plan stage and how diverse voices centred and engaged to interventions become well tailored and spread through the act stage. This approach to building QI teams informs how QI leads plan and also how the team acts, allowing them to spread their innovations through a broader set of communication channels and social interactions given a more diverse team.
Actions to sustain QI outcomes and efforts
QI teams can take actions to make QI more likely and sustainable via connecting providers and caregivers to their purpose (eg, a prosocial motivation to serve the underserved17), broadening their perspective, and, in turn, inducing experimentation. These activities not only sustain commitment to enhancing equity, but also sustain commitment to QI. QI efforts become self-limiting when they ignore the emotional experience of the individuals undertaking these efforts or when they do not attend to the human and organisational dynamics that preclude sustainability.18 We argue that incorporating structural inequities into QI projects can redress the exhaustion and loss of meaning that often undermines improvement efforts by reinfusing meaning, integrative thinking and experimentation into QI work. Healthcare practitioners may be more likely to adapt and engage in change to make a widespread, positive impact on health, especially for the most vulnerable and marginalised (ie, a strong other-orientation19). Other-orientation combined with attention to structural inequities induces greater perspective taking and integrative thinking to devise more ambitious and holistic solutions to problems.19 In part, this occurs through outreach and building deeper relationships with patients and community partners (eg, food, housing), and even incorporating patients as co-producers of QI work. Other-orientation may also increase as QI teams understand how their work relates to the work of adjacent departments and organisations, thus increasing the overall quality of care.20 The motivation, engagement and cognitive flexibility elicited through these actions help ensure that each stage of a PDSA cycle is truly iterative and changes are regularly refined as new data emerge.10
QI holds the possibility of being a tool for enhancing equity across all initiatives. Doing so requires an attentional shift to include rigorous examination of structural inequities and their influence on quality and safety issues and devising solutions. It also requires rethinking the data infrastructure and team composition to better equip all QI teams with the necessary capabilities to notice, consider and address these structural factors. Rethinking QI work in this way holds the potential to motivate QI teams and sustain their work and improvement.
Patient consent for publication
Contributors Both authors were involved in planning, writing and modifying the viewpoint.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Commissioned; internally peer reviewed.