The three numbers you need to know about healthcare: the 60-30-10 Challenge

Abstract

Background: Healthcare represents a paradox. While change is everywhere, performance has flatlined: 60% of care on average is in line with evidence-or consensus-based guidelines, 30% is some form of waste or of low value, and 10% is harm. The 60-30-10 Challenge has persisted for three decades. Main body: Current top-down or chain-logic strategies to address this problem, based essentially on linear models of change and relying on policies, hierarchies, and standardisation, have proven insufficient. Instead, we need to marry ideas drawn from complexity science and continuous improvement with proposals for creating a deep learning health system. This dynamic learning model has the potential to assemble relevant information including patients' histories, and clinical, patient, laboratory, and cost data for improved decision-making in real time, or close to real time. If we get it right, the learning health system will contribute to care being more evidence-based and less wasteful and harmful. It will need a purpose-designed digital backbone and infrastructure, apply artificial intelligence to support diagnosis and treatment options, harness genomic and other new data types, and create informed discussions of options between patients, families, and clinicians. While there will be many variants of the model, learning health systems will need to spread, and be encouraged to do so, principally through diffusion of innovation models and local adaptations. Conclusion: Deep learning systems can enable us to better exploit expanding health datasets including traditional and newer forms of big and smaller-scale data, e.g. genomics and cost information, and incorporate patient preferences into decision-making. As we envisage it, a deep learning system will support healthcare's desire to continually improve, and make gains on the 60-30-10 dimensions. All modern health systems are awash with data, but it is only recently that we have been able to bring this together, operationalised, and turned into useful information by which to make more intelligent, timely decisions than in the past.

Trauma and Violence Informed Care Through Decolonising Interagency Partnerships: A Complexity Case Study of Waminda’s Model of Systemic Decolonisation

“…In this model ( Figure 2 ), “interactions” include networks, cliques, hierarchies and heterarchies [ 24 ] while “ideas” encompass beliefs, conceptual understandings, thoughts and plans. Viewed through the lens of complexity, the present results elucidate how ideas that are held and shared by the workforce are critical in generating local rules, processes and collective behaviours resulting in positive or negative outcomes and unintended consequences [ 23 ]. However, the workforce is highly diverse in terms of knowledge, motivations, history and lived experience of individuals, and as such ideas and interactions within organisations and beyond are highly variable.…”

“…Our approach to this case study is informed by complexity theory, which depicts health services as functioning within an interconnected ecological system that cannot be considered separately from its environment [ 20 , 21 ]. In health systems research, complexity theory depicts the interdependencies and interactions between system elements (e.g., individuals, collectives or processes) and the processes of “self-organisation” into a dynamic integrated system [ 22 , 23 , 24 , 25 ]. This approach has recently been used in the context of primary health care responses to violence against women in New Zealand [ 25 ] and in primary health settings in Canada that are trauma and violence informed [ 26 ].…”

Nobody ever questions—Polypharmacy in care homes: A mixed methods evaluation of a multidisciplinary medicines optimisation initiative

“…Some 10% of healthcare is harmful, and 30% is wasted: identifying the 10% requires change [ 66 ], but change is more difficult where information is complex [ 49 ]. ADRs and prescribing cascades are hard to detect [ 47 ], and medical science remains unapplied [ 67 ].…”

Leaders' Perspectives on Learning Health Systems: a qualitative study

“…Waiting times for some elective procedures in public hospitals are considered too long, with up to 15% of patients waiting over twelve months in 2015-16 [28,30]. Ine ciency, waste and provision of low value care are recognised in the Australian health system, and are estimated to account for 30-40% of national health costs, through ineffective health interventions, administrative ine ciencies and ine cient pricing [31,32]. Quality and safety considerations are also recognised with up to 17% of total hospital activity and expenditure related to adverse events; and one in ten patients will experience some form of harm while in the health system (such as infections, medication complications, delirium and cardiac complications) estimated to cost 9% of total hospital expenditure [32][33][34].…”