• Six Sigma
• Lean management
• Healthcare quality improvement

Lean Six Sigma (LSS) is a quality improvement (QI) methodology that has gained popularity in recent decades in health care management as a means to reduce waste and unwarranted variability.1 A combination of Lean Management System and Six Sigma, the principles and tools of LSS have been adapted from the manufacturing sector to the more service-oriented healthcare settings.2 3 At the same time, diversity, equality and inclusion (DEI) are increasingly acknowledged as core tenets of high-quality healthcare delivery and that concerted institutional changes are necessary to support DEI efforts.2 3

For the most part, the increased emphasis of DEI has been running parallel to LSS and QI. Indeed, the philosophies, principles and tools are largely separate, with DEI often described as a ‘lens’ through which to focus efforts towards an aspirational target and LSS as a method for QI.4 5 DEI explicitly recognises the heterogeneity of a population and the need to design systems that may offer differential service to achieve equity. LSS strives to achieve consistency in both process and outcome. While many observers have noted opportunities for synergy,6 an existential tension between LSS and DEI remains: how do we reduce unnecessary variation in health outcomes while tailoring care to patient’s individual circumstances?

In this viewpoint, we discuss six practical suggestions to QI specialists to harmonise LSS methods with DEI principles from conception to dissemination (table 1). Because LSS significantly overlaps with other QI methods, tools and principles, many suggestions may apply globally within other paradigms.

1. Promote inclusivity among QI teams.

Central to DEI is meaningful representation of vulnerable populations within teams that contribute to their care.7 QI emphasises the importance of using voice of the customer and stakeholder analysis in designing change efforts to best achieve results, minimise unintended consequences and build ‘buy-in’. Seeking to increase representation to support DEI aims is a natural extension of these principles.

However, inclusion for the sole sake of inclusion risks becoming mere tokenism, which is entirely insufficient in the promotion of institutional change. Worse, tasking professionals who are under-represented with solving equity issues that are not of their own making may place an undue burden, termed the ‘minority tax’.8–10 Deep and meaningful interactions with DEI content experts may help mitigate these risks. Additionally, clear delineation of decision-making authority, tasks and expectations may also be beneficial in creating team cultures that prioritise DEI. Indeed, LSS practitioners should reinforce that all team members should be expected to consider DEI aims as integral to their work and part of their responsibilities. Where a team or team member lacks the expertise to address a specific DEI question, the onus is on that team or individual to seek advice, similar to additional fact finding around informatics or economic concerns, for example.

Another method of promoting inclusivity is to include patients as members of the QI team. Depending on the size, scope, methods and aims of a study, it may be feasible to have patients advise and consult specialists in QI. Patient and family advisory boards may be one resource for seeking patient input. At the same time, QI teams should be alert to the potential disparities that these boards may reinforce.11

2. Incorporate measurements that reflect diversity within populations.

QI relies heavily on measures, especially the validity, accuracy and reliability: this is an area of intersection between DEI and LSS because judicious selection of measures may help prioritise DEI efforts. Thus, interactions with relevant DEI content experts may prospectively inform the tools and measures used in QI initiatives.

LSS practitioners can synergise these concerns in many ways. First, the selection of measures should adequately reflect diversity with respect to human physiology and dimensions of diversity such as language and culture. Even previously validated measures are increasingly recognised as incorporating long-standing biases.12 Second, operational definitions should also be articulated during the earliest stages of project planning in order to determine if they intentionally or unintentionally exacerbate inequalities. For example, in the USA, race has been used as a factor in calculating the glomerular filtration rate (GFR), a measure of kidney function, based on historical beliefs about physiological differences among African Americans and non-African Americans.13 This has led to underdiagnosis of chronic kidney disease by nearly half among black adults.14 LSS practitioners can promote DEI simply by using more recent race-neutral, non-race-adjusted calculations for estimated GFR.

Third, LSS practitioners should consider environmental, genetic, cultural and other differences that drive variability in populations and consider stratification of measures. The advent of precision medicine provides enormous opportunities for QI specialists for practical implementation to benefit diverse populations. Teams can seek more nuanced or modified metrics to be better applicable for diverse populations.

3. Identify stakeholders that share socioeconomic or demographic affinities.

Considering diversity may result in more complex numerical distribution of data. Indeed, assumptions that simplify calculations may unknowingly contribute to greater or reinforced disparity, particularly those from vulnerable or marginalised communities. To counter this tendency, QI teams should engage with DEI content experts and recognise stakeholder groups through LSS tools such as scatter plots and rational subgrouping. Additionally, these tools may help LSS practitioners to gain greater insight into drivers of inequitable baseline performance, complexity of unwarranted variability, strategies to promote better performance among stakeholder groups and optimal allocation of scarce resources towards QI.

Multidimensional measures or composites may be more useful than conventional statistics such as simple means and medians. The greater availability of advanced software that can process big data makes this more practical than it would have been even a decade ago. A move towards incorporating multivariate control charts (where multiple measures of performance reflect diversity, such as Hotelling’s T² chart) may be more appropriate than conventional control charts alone. Alternatively, other statistics like cumulative sum (CUSUM) and estimated weighted moving average may be more sensitive for detecting changes in smaller subpopulations.15 While the context, setting and scope will help determine the specific variables and select which multivariate chart is most appropriate, we can envision control charts that holistically combine means for different aspects of inclusivity (access to care, healthcare outcomes, patient satisfaction, etc).

4. Adopt a holistic view of socioeconomic determinants of health as inputs of unwarranted variation.

While LSS is an improvement methodology, DEI is a set of foundational concepts. Therefore, they cannot be compared directly to one another. Yet there are many opportunities for mutually beneficial interactions. DEI tends to have a broadness of scope and examines diversity from multifaceted angles. Practitioners of LSS may benefit from interactions with DEI concept experts in expanding their scope and examining assumptions that underpin variability and bias, including socioeconomic determinants of health. Root cause analysis may be a useful LSS tool to explore these.

One important factor to consider in human factors is implicit bias, specifically how implicit bias may drive poorer outcomes. By definition, implicit biases are difficult to measure, but labelling implicit bias as a human factor contributing to disparities and unwarranted variability enables greater definition and articulation of inputs.16 A practical manner to incorporate this within an LSS tool is within the Ishikawa (root cause analysis) diagram.17 Although the structure of Ishikawa diagrams varies, most include some form of ‘human’ input as a ‘rib’ (manpower/people/skill, etc). Inclusion of implicit bias within this rib would be a meaningful step to reconcile the aims of DEI with the procedures of LSS.

LSS experts should also recognise the larger societal trends that may not be the foci of QI projects. Recognition of these larger trends helps establish the context of the LSS project in several ways. First, it may help to better calibrate expectations and aims. By recognising the downstream effects of the project on people beyond the intended audience, team members can advance the significance of the project to entire communities and societies, depending on the scale. Second, it may help to better understand stakeholders involved in the QI process who would otherwise be marginalised since they may not be directly involved with the project. Third, it may help shape sustainability plans once QI projects end. Two tools may be particularly useful in categorising and analysing socioeconomic factors that may be impacting the execution of projects: Strength, Weakness, Opportunities, Threats analysis and Political, Economic, Sociological, Technological, Legal and Environmental analysis.18

5. Maintain equity among vulnerable stakeholders on project completion.

The majority of effort in LSS is promotion of systems-based change. A less discussed but equally important aim of LSS is to maintain the level of change. Because many sources of inequity stem from the inequitable decay of processes that preferentially disadvantage vulnerable populations, maintenance of improvement efforts should be a high priority.

LSS emphasises that sustainability plans have to be drafted early, even prior to the implementation itself. Because of this, it may be worthwhile to pilot interventions or obtain preliminary data in vulnerable populations first. In vulnerable populations, uptake of the intervention should be particularly monitored since it may provide indications of what may happen once the project is completed. Because groups representing vulnerable populations are, by definition, smaller, more sensitive statistics like CUSUM that allow for monitoring of smaller magnitude of changes may be necessary.19 If dealing with rarer events in smaller populations, a t-chart or g-chart may be more appropriate.

Once completed, sustainability and control plans need to specifically mention how these changes will be sustained and maintained in vulnerable populations and other stakeholder groups. This means continuing measurements, as noted above, and drafting more comprehensive control plans that address specific populations. As part of this process, it also means engaging in larger dialogues within vulnerable populations to understand how processes can be sustained and grown as new situations arise.

6. Create a culture of DEI within the larger QI community.

A culture that champions diversity, equity and inclusion throughout the larger QI community can be built in part through publications and presentations. The Standards for Quality Improvement Reporting Excellence 2.0 guidelines have been used to guide the drafting of manuscripts and assess the quality of published work.20 However, it currently does not address DEI. Perhaps including a criterion in the future specifically for DEI may be a way to promote a culture of DEI.

It may also be necessary to map the landscape of DEI within QI. Systematic reviews, scoping reviews and other critical evaluations of published literature can serve as important vehicles to popularise DEI concepts within the community. Similarly, these publications can identify knowledge gaps to facilitate the spread of ideas and generate a robust research agenda that encourages DEI within LSS.

Just as important is generating new knowledge through original research that scrutinises the validity of QI approaches to improve DEI. Because much of LSS is an adaptation from the manufacturing industries, many of the rigorous tests for validity have not yet been applied for LSS tools. The addition of DEI to LSS provides opportunities to test how modifications of existing tools can help achieve their intended ends.

Incorporating DEI in QI culture also requires a greater interface with experts from the DEI sphere. Since DEI experts tend to base their worldviews on sociological and anthropological groundwork while LSS is an adaptation from industry, it may be difficult to interface these concepts. Greater coordination with experts in DEI and investment into junior investigators in QI, particularly LSS, may be a path forward.

Diversity, equity and inclusion are enduring and essential values in healthcare. Incorporating these values is essential if LSS methodologies are to remain relevant. Fortunately, many of these modifications can be readily incorporated and can improve the quality of projects that use LSS. Others will require greater effort and questioning some basic assumptions regarding the aims of QI. Regardless, the incorporation of diversity, equity and inclusion as core concepts within LSS will strengthen the community and its role in healthcare as a whole.