Aiming beyond equality to reach equity: the promise and challenge of quality improvement

Abstract

Quality improvement must move beyond only measuring average quality and change and focus on equity to support achieving the quality needed for effective universal health coverage, argue Lisa Hirschhorn and colleagues

Close to 20 years after the seminal Institute of Medicine report Crossing the Quality Chasm, the Lancet Global Health Commission on High Quality Health Systems found that poor quality care accounts for more deaths than lack of access to care. The most disadvantaged populations have the worst outcomes, reflecting how much work is needed.¹ We use the Institute of Medicine definition of quality, which emphasises equity as one of the six dimensions of quality,² to call for the quality improvement (QI) community to include equity more effectively as we work to ensure the quality needed to achieve the promise of universal health coverage. We believe that QI can be a powerful tool to achieving equitable high quality healthcare, but better methods and focus are needed.

The World Health Organization defines equity as “the absence of avoidable, unfair, or remediable differences among groups of people, whether those groups are defined socially, economically, demographically or geographically or by other means of stratification.”³ But equity is often forgotten or not explicitly measured and targeted in interventions for health system improvement. Experience shows that traditional QI methods can maintain or worsen health inequities across subpopulations. These failings are exposed by the current covid-19 pandemic, where, unsurprisingly, inequities intrinsic in health systems and society are magnified for the most disadvantaged populations.⁴

There can be three possible outcomes of QI on equity: improvement for all but maintenance of the equity gap (equality in improvement); improvement more in the disadvantaged population (decreasing the gap); or improvement more in the advantaged population (widening the gap).⁵ QI initiatives must prioritise equity in how they design and measure change among disadvantaged subpopulations and strengthen the evaluation needed to know which of these three outcomes they have achieved. For example, the US based Diabetes QI Collaborative improved care for white but not Latino patients, worsening inequity and widening the gap. Analysis found flaws in the programme design contributing to this outcome, such as English-only communication, absence of interventions to deal with barriers specific to the Latino population, and no disaggregation of data to detect changes by ethnic subgroup.⁶ Similarly, pay-for-performance initiatives, which have gained popularity with global funders, can also result in worsening equity. For example, Medicare’s Hospital Readmissions Reduction Program was associated with higher rates of readmission among black people for conditions not targeted by the financial scheme in safety net hospitals but not in more resourced hospitals.⁷

How can we do better?

These examples underscore the importance of proactive identification of drivers of inequities, and QI designed with clear equity related aims. This intentional integration into QI aims, intervention design, and programme evaluation is required to reduce inequities as quality is improved. This work will require expanding interventions to include the underlying political, social, and structural causes of health inequities.^{5 8 9 10}

National health systems, payers such as insurance and donors, and QI implementers must also expand their scope to identify and tackle these factors outside the individual provider or facility, such as social determinants of health, governance, and health system design, which can happen only by engaging communities more deeply in identifying solutions.^{1 10} Work is also needed to tackle the intrinsic and extrinsic biases within the health system and in the community, which can underlie ineffective QI design and implementation. Increasing the involvement of patients and community members in QI design, raising their expectations of health system performance, and prioritising measurement of patient reported outcomes and experiences are also improvement strategies needed to achieve equity.¹

We also recommend that designers incorporate planned data disaggregation upfront to look at changes among commonly disadvantaged subgroups such as wealth, race, and location. Measurement should include implementation outcomes such as acceptability and adoption and data elements needed to understand the underlying factors associated with success or failure in reducing inequity as quality improves. Disciplines such as implementation sciences and disparities research offer tools and frameworks that can accelerate this work.^{11 12}

While this broader approach to QI may seem daunting, we describe an initiative led by two of the authors (HM and AK) in Ethiopia and lessons learnt to inform how we can improve the way we design, implement, and define success of QI.

Equity focused QI: the Ethiopia healthcare quality initiative

The Ethiopia healthcare quality initiative began with the Institute for Healthcare Improvement supporting development by the Ethiopia Ministry of Health of a national healthcare quality strategy in 2015, setting the vision and leadership for a high quality equitable health system and the high priority interventions and policies needed to translate the strategy into action. This was supported by the building of QI competency at all levels of the health system to create local champions, who served as Ministry of Health employed QI experts, to sustain capability building in the country.

These steps were important in facilitating the co-design and testing with the Ministry of Health of a district-wide approach to managing and improving quality explicitly to support populations with the worst maternal and newborn health system experience and outcomes and show the impact of QI on maternal and newborn health. The Institute for Healthcare Improvement worked with the Ministry of Health to include equity in site selection, which led to inclusion of pastoralist communities, given their worse maternal and newborn health outcomes. This intentional inclusion of some of the hardest to reach and underserved ethnic groups deepened understanding of diverse population needs, preferences, and health system challenges and their impact on quality.

The initiative also prioritised broad stakeholder engagement, leveraging QI expertise and leadership within the federal and regional governments in the country. These strategies resulted in a cadre of embedded improvement leaders trained to prioritise equity who will continue the work beyond partner engagement. Federal and regional leaders supported district level leadership to build a culture of learning through improvement collaboratives and identify local contextual factors that needed to be tackled. Key stakeholders across the health system, including patients, community health workers, clinical providers, and data managers, convened in learning sessions to empower frontline providers with QI methods and to use their own data to identify problems in inequity of quality and access, create and test solutions, and spread positive change quickly.

Measurement and feedback were designed to increase the input of patients and communities as core to increasing equity by ensuring that they informed problem prioritisation and solutions. Patient experience was put at the centre of the improvement process through community engagement in the collaboratives and inclusion as a performance measure. In addition, government quality unit leaders trained providers to use data to advocate effectively for solutions identified through this engagement but beyond their immediate resources, further increasing the involvement of patients and communities.

The Ethiopian healthcare quality initiative resulted in improved quality overall, with two thirds (67%) of facility QI teams reporting over 90% adherence to all labour and delivery bundles and almost 75% of these teams reporting improvement in at least one outcome of maternal and neonatal service coverage.¹³ Importantly, inequity of quality was reduced for indicators such as antenatal care (equity gap reduced from 15 to 8 percentage points) and similar improvement was seen for new measures across regions, with some of the largest improvements found in the traditionally disadvantaged pastoralist areas.

How can the QI community increase equity of QI focus and outcomes?

We make the following recommendations, including which data we use and how we use them and how QI is designed, implemented, and monitored, to help accelerate the work to improve inequities through QI.^{5 9} The appendix on bmj.com gives further details on how these recommendations were applied in the Ethiopia healthcare quality initiative.

Engage better

Ensure that you have identified your key stakeholders in and beyond the QI team to understand the root causes from perspectives within and external to the health system. This should include people representing the lived experience of inequities in quality and policy makers able to facilitate the system changes needed. Keeping these individuals as active participants as you design, test, and refine the QI will increase your understanding and more effectively tackle quality and inequity. This strategy was important in Ethiopia and has been seen in other improvement work. For example, participatory women’s groups—used to identify and convene women often from marginalised subgroups—support their prioritisation, and problem solving at the household level has been effective in reducing neonatal mortality and reducing inequities.¹⁴ While this approach may not be traditionally categorised as QI, the purposeful engagement of these women to join in a structured process of problem identification and resolution is an area where QI can increase impact on inequity.

Measure and use data better

Design and use your data to identify inequities from the start. In many contexts, the lack of relevant data may be part of the problem of continued neglect, implicit bias, and structural inequities. Programme designers may need to look beyond traditional health metrics, including qualitative measures to iteratively identify disparities and underlying causes, to inform the work to improve quality and close the equity gaps. Planning for disaggregation from the start, similar to that planned in the work in Ethiopia, is also critical. For example, the English NHS has included health equity indicators to identify disadvantaged neighbourhoods and impact of expanding primary care in equity of access.¹⁵ Through disaggregation, covid-19 research has rapidly identified disparities in outcomes and identified the need to design QI to tackle underlying determinants as well as quality of care received.¹²

Design better

Prioritise tackling barriers identified through your stakeholders of groups least served by the health system. Reaching the most disadvantaged will take innovations in strategies and learning from other groups already showing progress in these areas. For example, the role of patient navigators to improve uptake of cancer screening among African American women has now been expanded to increase access and uptake in settings across Africa, Asia, and Europe for other conditions.^{16 17} The use of community health workers to improve access and uptake of interventions to reduce child mortality among those in more remote areas is another example of equity focused interventions.¹⁸

Improve better

Move beyond conventional ways for improvement to include areas outside the scope of traditional QI and take a “whole quality management” approach. The work requires quality planning and leadership that intentionally prioritises equity; tackling gaps in the health system structure such as human resources, systems, health financing, and governance associated with disparities^{1 19}; and moving beyond the health system to include social determinants of disease and factors such as female empowerment and education associated with better access and survival.^{20 21} The work will require new partnerships and interdisciplinary approaches to deal with the often vast quality gaps and where root causes also go beyond the health sector.²²

Learn better

A robust internal learning system is required to monitor QI implementation to iteratively adjust to ensure equity while increasing impact. Lessons from disciplines such as implementation science, disparities research, realist evaluation, and patient centred outcomes research to better understand contextual factors will need to be applied during QI, and those that will influence implementation strategies will also strengthen equity targeted QI. For example, in Bangladesh, recognition that strategies that improved access to family planning were ineffective owing to systems and culture barriers informed adaptation to strategies and improved uptake.²³ More effective dissemination of results of equity focused QI is also needed to move the focus beyond the already broad literature describing existing disparities. This approach will also help the QI community understand and learn how and why QI did or did not improve quality and if disparities were reduced or eliminated.^{24 25}

Conclusion

QI impact is challenged by approaches that can ignore or even worsen inequities. As illustrated by the Ethiopia initiative, a participatory strategy to improve the design and implementation of solutions needs to go beyond the traditional clinical and individual focus and QI methods to include the broader systems, governance, and intersectoral responses needed to tackle underlying social determinants of access and health and structural inequity. Intentional stakeholder engagement from leadership through to frontline providers and, critically, the patient and community is needed to inform the design, ensuring the QI tackles root causes within and beyond the health system and support work throughout its implementation. Investment in measurements to monitor equity and increase patient involvement through experiential quality and patient reported outcomes is also needed. Changing what and how we measure will need commitment from funders, insurers, multilateral and bilateral institutions, policy makers, and other leaders who define metrics for accountability and payment, and will need to increase community engagement in this process. A multidisciplinary approach including implementation science, patient centred outcomes, and research can offer additional tools to QI to better understand context, strengthen stakeholder engagement, and create more generalisable knowledge to accelerate scale and adapt quickly to meet the needs of the most disadvantaged. While goals of scale and equity often conflict, health system leadership must act to transform this dynamic and achieve high quality care for all.

Key messages.

• Poor quality care accounts for more deaths globally than lack of access to care

• Work to achieve universal health coverage therefore needs to consider effectiveness and equity

• Without prioritisation of equity, population level improvements in healthcare may mask those left behind because of economics, gender, ethnicity, or location

• We suggest five key areas where strategies for quality improvement need to tackle inequity: stakeholder engagement, measurement, design, improvement work, and learning

Web extra.

Extra material supplied by authors

Appendix: Ethiopian Healthcare Quality Initiative’s implementation of five strategies to improve quality with equity