Shifting gears: Creating equity informed leaders for effective learning health systems.

Leadership is vital to a well-functioning and effective health system. This importance was underscored during the COVID-19 pandemic. As disparities in infection and mortality rates became pronounced, greater calls for equity-informed healthcare emerged. These calls led some leaders to use the Learning Health System (LHS) approach to quickly transform research into healthcare practice to mitigate inequities causing these rates. The LHS is a relatively new framework informed by many within and outside health systems, supported by decision-makers and financial arrangements and encouraged by a culture that fosters quick learning and improvements. Although studies indicate the LHS can enhance patients' health outcomes, scarce literature exists on health leaders' use and incorporation of equity into the LHS. This article begins addressing this gap by examining how equity can be incorporated into LHS activities and discussing ways leaders can ensure equity is considered and achieved in rapid learning cycles.

Fairness for Whom? Learning Health Systems' Approach to Equity in Healthcare.

Many healthcare systems use "equity" as a catch-all term to underscore their commitment to delivering care matching users' needs. Despite its ubiquity, it is often haphazardly used and applied to care and improvement efforts. As the learning health systems (LHSs) approach gains prominence, LHS researchers have sought to embed equity into their work while navigating systems with differing views of equity. We examine several components of equity, its definitions within LHSs and knowledge from LHSs' equity approach that could be implemented across systems. We conclude by suggesting various ways in which readers can embed equity into their respective LHSs.

Everybody's talking about equity, but is anyone really listening?: The case for better data-driven learning in health systems.

Data collection, analysis, and data driven action cycles have been viewed as vital components of healthcare for decades. Throughout the COVID-19 pandemic, case incidence and mortality data have consistently been used by various levels of governments and health institutions to inform pandemic strategies and service distribution. However, these responses are often inequitable, underscoring pre-existing healthcare disparities faced by marginalized populations. This has prompted governments to finally face these disparities and find ways to quickly deliver more equitable pandemic support. These rapid data informed supports proved that learning health systems (LHS) could be quickly mobilized and effectively used to develop healthcare actions that delivered healthcare interventions that matched diverse populations' needs in equitable and affordable ways. Within LHS, data are viewed as a starting point researchers can use to inform practice and subsequent research. Despite this innovative approach, the quality and depth of data collection and robust analyses varies throughout healthcare, with data lacking across the quadruple aims. Often, large data gaps pertaining to community socio-demographics, patient perceptions of healthcare quality and the social determinants of health exist. This prevents a robust understanding of the healthcare landscape, leaving marginalized populations uncounted and at the sidelines of improvement efforts. These gaps are often viewed by researchers as indication that more data is needed rather than an opportunity to critically analyze and iteratively learn from multiple sources of pre-existing data. This continued cycle of data collection and analysis leaves one to wonder if healthcare has a data problem or a learning problem. In this commentary, we discuss ways healthcare data are often used and how LHS disrupts this cycle, turning data into learning opportunities that inform healthcare practice and future research in real time. We conclude by proposing several ways to make learning from data just as important as the data itself.

Saying and doing are different things: a scoping review on how health equity is conceptualized when considering healthcare system performance.

INTRODUCTION: Ensuring healthcare systems provide equitable, high quality care is critical to their users' overall health and wellbeing. Typically, systems use various performance frameworks and related indicators to monitor and improve healthcare. Although these frameworks usually include equity, the extent that equity is reflected in these measurements remains unclear. In order to create a system that meets patients' needs, addressing this uncertainty is important. This paper presents findings from a scoping review that sought to answer the question 'How is equity conceptualized in healthcare systems when assessing healthcare system performance?'. METHODS: Levac's scoping review approach was used to locate relevant articles and create a protocol. Included, peer-reviewed articles were published between 2015 to 2020, written in English and did not discuss oral health and clinician training. These healthcare areas were excluded as they represent large, specialized bodies of literature beyond the scope of this review. Online databases (e.g., MEDLINE, CINAHL Plus) were used to locate articles. RESULTS: Eight thousand six hundred fifty-five potentially relevant articles were identified. Fifty-four were selected for full review. The review yielded 16 relevant articles. Six articles emanated from North America, six from Europe and one each from Africa, Australia, China and India respectively. Most articles used quantitative methods and examined various aspects of healthcare. Studies centered on: indicators; equity policies; evaluating the equitability of healthcare systems; creating and/or testing equity tools; and using patients' sociodemographic characteristics to examine healthcare system performance. CONCLUSION: Although equity is framed as an important component of most healthcare systems' performance frameworks, the scarcity of relevant articles indicate otherwise. This scarcity may point to challenges systems face when moving from conceptualizing to measuring equity. Additionally, it may indicate the limited attention systems place on effectively incorporating equity into performance frameworks. The disjointed and varied approaches to conceptualizing equity noted in relevant articles make it difficult to conduct comparative analyses of these frameworks. Further, these frameworks' strong focus on users' social determinants of health does not offer a robust view of performance. More work is needed to shift these narrow views of equity towards frameworks that analyze healthcare systems and not their users.