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Journal of Evaluation in Clinical Practice ISSN 1365-2753
The Affordable Care Act: a case study for understanding and applying complexity concepts to health care reform D. Justin Larkin BS BA,1 R. Chad Swanson DO MPH,2,3 Spencer Fuller BA4 and Denis A. Cortese MD5,6 1
MD Candidate, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Affiliate Faculty, Department of Health Sciences, Brigham Young University, Provo, UT, USA 3 Physician, Department of Emergency Medicine, Intermountain Healthcare, Provo, UT, USA 4 MD Candidate, School of Medicine, University of California, San Diego, La Jolla, CA, USA 5 Foundation Professor and Director, Healthcare Delivery and Policy Program, Arizona State University, Tempe, AZ, USA 6 Emeritus President and CEO, Mayo Clinic, Rochester, MN, USA 2
Keywords complexity science, health care policy, health care reform Correspondence Mr D. Justin Larkin Perelman School of Medicine University of Pennsylvania Suite 100 Stemmler Hall Philadelphia, PA 19104-6056 USA E-mail: [email protected] Accepted for publication: 5 September 2014 doi:10.1111/jep.12271
Abstract Rationale, aims and objectives The current health system in the United States is the result of a history of patchwork policy decisions and cultural assumptions that have led to persistent contradictions in practice, gaps in coverage, unsustainable costs, and inconsistent outcomes. In working toward a more efficient health system, understanding and applying complexity science concepts will allow for policy that better promotes desired outcomes and minimizes the effects of unintended consequences. Methods This paper will consider three applied complexity science concepts in the context of the Patient Protection and Affordable Care Act (PPACA): developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels. Results and conclusions Transforming the US health system, or any other health system, will be neither easy nor quick. Applying complexity concepts to health reform efforts, however, will facilitate long-term change in all levels, leading to health systems that are more effective, efficient, and equitable.
Introduction The current health system in the United States is the result of a history of patchwork policy decisions and cultural assumptions that have led to persistent contradictions in practice, gaps in coverage, unsustainable costs, and inconsistent outcomes. The recent debate over health care reform has brought the fragmented, inefficient and inequitable nature of that system into the glare of media attention and under public scrutiny. Discussions, dominated by special interest groups, have typically omitted ‘complexity science’ approaches: those that consider the inherently complex nature of the system as a whole and the interrelations of its subsystems [1]. The process leading the US Congress to pass the Patient Protection and Affordable Care Act [2] (PPACA, see Table 1) illustrated the heart of the problem: legislators substituted polarizing rhetoric in place of serious public dialogue about a shared vision of an ideal US health system. Even the US Supreme Court’s narrow decision in June 2012 to uphold the individual mandate and Medicaid expansion provisions of the PPACA by a vote of 5 to 4 highlights the divided nature of the country.
With that Supreme Court decision on the two controversial issues, there seemed to be a growing consensus that the core provisions of the PPACA would remain intact. In fact, and more recently, the problems with the federal exchange rollout and other delays have generated much scrutiny from opponents of the PPACA, but have done little to slow the momentum of the implementation of the legislation. While the PPACA will likely improve equity through increased insurance coverage [3], there is still a need to address components and processes within the still inefficient health system that make it a large financial burden on US citizens without resulting in the desired population and individual health outcomes. The reductionist and linear views of the biomedical paradigm that drive current policy and reform are insufficient to understand the dynamic and complex interactions of the various actors and stakeholders involved in the health system and to offer solutions that promote lasting change. Complexity approaches offer a different set of solutions [4] that account for the non-linear, complex and multidimensional processes [5] that characterize health systems. In working towards a more efficient health system, understanding and applying complexity science concepts will
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Table 1 Summary of various key provisions included in the Patient Protection and Affordable Care Act Provisions to improve coverage • Require US citizens and legal residents to have health insurance, the so-called ‘individual mandate’. • Create state-level insurance exchanges so that individuals and businesses can purchase insurance. • Require employers to offer coverage. • Expand Medicaid (the government-run health insurance programme for the poor) to 133% of the federal poverty level. • Improve coverage of patients’ pre-existing conditions, and expand dependent coverage. Provisions intended to control health care costs • Minimize administrative costs by standardizing health insurance operating rules and other procedures. • Restructure Medicare payments to discourage fee-for-service payments. • Establish a body of professionals – an Independent Payment Advisory Board – that will submit legislative proposals to control costs. • Create an ‘Innovation Center’ within the Centers for Medicare and Medicaid Services to encourage and test innovative payment structures. • Incentivize the formation of ‘accountable care organizations’, wherein providers share in cost savings if they meet criteria such as: coordinate comprehensive care, improve quality and promote evidence-based medicine. Provisions intended to improve the health care delivery system • Establish an institute to support comparative effectiveness research. • Award grants that propose medical malpractice tort reform. • Establish Medicare and Medicaid pilot programmes based on ‘bundled payments’; payments for episodes of care lasting 30 days for a given condition. • Increase payments to primary care providers. • Establish the National Prevention, Health Promotion and Public Health Council to coordinate federal prevention, wellness and public health activities and make funds available for research around those areas. • Improve payment for preventative measures, and provide grants for wellness programmes. Adapted from Summary of New Health Reform Law [45].
allow for policy that better promotes desired outcomes and minimizes the effects of unintended consequences [6]. Others have utilized concepts of complexity science as a framework for more effective health care reform [7,8] and as a lens to understand the US health care reform in particular [6,9]. We hope to continue that discussion by applying a complexity science lens to various provisions of the PPACA. This is a timely consideration, as many of the most impactful provisions of the bill have gone into effect in 2014 and many more will take effect in the coming years, thus setting the course for the US health care system for the near and distant future. A comprehensive analysis of the legislation in the PPACA is beyond the scope of this paper, as is a detailed overview of complexity. Rather, this paper will provide a brief introduction to complexity concepts and approaches, and consider three applied complexity science concepts in the context of the PPACA: developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels.
Complexity and health: a brief introduction Practices and policies in the US health care system over the past 100 years have largely been based on mechanistic assumptions rooted in scientific reductionism [10]. The randomized, controlled trial – considered by many the ‘gold standard’ in medical research – highlights this dominating perspective: all confounding variables are controlled so that we consider one intervention isolated from all other factors. Our reductionist mindset is not limited to medical research or interventions. For example, we too often work in silos, reimburse for one service and educate and train for a specific 134
patient encounter. Linear causality dominates this perspective; we assume that a particular action will result in a corresponding result. We might suppose that paying providers for their services will result in optimal outcomes, or that prescribing a medication for an illness to treat the underlying pathophysiology of the disease. While this reductionist approach to medicine has resulted in successes in managing certain diseases, ranging from the development of vaccines and antibiotics to the improvement of the art and science of surgical techniques, it is inadequate to address the challenges of our current complex health care system [4]. The health care system has been described as a complex, adaptive system because it has five key characteristics: diverse agents that learn, non-linear interdependencies, emergence, co-evolution, and self-organization [11]. Health care providers, patients, policy makers, citizens and many others are the agents that make up the health care system. All of these individuals have unique perspectives, assumptions, relationships, personality characteristics, experiences and goals that influence the way that they act in the system. They learn from experience in the system to optimize their position locally. A doctor prescribes unnecessary antibiotics to appease her patient [12]. An insurance company limits the drugs on its formulary to prevent the prescription of more expensive drugs [13]. The effects of their actions often have unpredictable outcomes [6,13,14]. A small act can have large effects, such as a rumor resulting in the firing of an administrator. Conversely, a large act, such as requiring blood cultures for pneumonia patients can have relatively small effects; the intervention might not result in improved outcomes [15]. When agents self-organize into structures, those phenomena are described as emergent. The systemic effects of emergence are unpredictable and are decided by how agents adapt in response to the new structures. This principle is illustrated by the increase in
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nosocomial infection rates due to the emergence of resistant bacteria secondary to widespread antibiotic usage [16]. As an example on the health system level, conferences have emerged that train doctors how to document their clinical encounters to maximize their billing under the current fee-for-service (FFS) structure. These, too, are examples of co-evolution: when a complex system changes, its environment changes as well [17]. Reductionist approaches to health often result in significant unintended consequences because of the unpredictable nature of the system [6,14]. No one individual is in charge of the entire system, and no one person or organization can predict how others are going to react because diverse agents self-organize to optimize locally. Indeed, ‘the essence of complexity science is in the study of patterns and relationships, rather than objects and substance’ ([17], emphasis added). By focusing attention on these patterns and relationships, complexity science helps stakeholders to anticipate self-organization and unintended consequences, and in turn to create policy that allows for quick response to changes in the system. We turn our attention to three applied complexity science concepts in the context of the PPACA: developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels.
A shared vision around reimbursement for value A shared vision unites people behind an idea that transcends their different backgrounds and experiences by providing a common motivator for transforming behaviour. It can also be viewed as an ‘attractor’, or a force that naturally influences all aspects of a system [18,19]. A vision owned by all stakeholders is a powerful force for the long-lasting change needed in the US health system as it encourages the self-organizing power of the complex system to work in favour of, rather than against, policy initiatives [20]. Currently, the shared vision in the United States is weak. Patients are motivated to reduce the negative effects of disease; providers to offer as many services as can be justified for their patients; governments to reduce costs and prevalence of specific diseases; and insurance companies to have the highest bottom line. Furthermore, pharmaceutical and biotechnology companies are incentivized to drive up utilization of their products, resist price controls, and protect their patent rights; legislators to use health care as a means to gain the votes necessary for election; lawyers to earn financial gain on mistakes by health care professionals without helping the system learn from those mistakes; and employers to take advantage of the tax free nature of providing insurance benefits (instead of offering higher salaries) and to help their employees be present and productive at work. In short, these attractors are each optimized to financially profit the respective stakeholder – an outcome the US health system achieves quite successfully. The fragmented and divergent nature of these attractors results in a US health system that seems to be working against itself as much as it works together; this limits dynamic adaptation and prevents the health system from effectively reaching its most important goal – producing individual and population health equitably and efficiently.
© 2014 John Wiley & Sons, Ltd.
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Ultimately, performance and accountability in the US health system will only improve once a shared vision unites the interests and activities of all shareholders [21]. One rallying point that has the potential to unite the many stakeholders in the health system is value. Value is simply defined as the outcomes achieved per dollar spent to achieve those outcomes over time [22]. Because higher spending is not currently correlated with improved outcomes [23], there is much room for improving the value of the US health care system. Oftentimes, outcomes and costs are narrowly viewed as specific, final clinical outcomes or the money spent on an individual service rendered to a patient, respectively. Consistent with the reductionist paradigm, these metrics are often poor, overly simplified surrogates that do not accurately reflect system success or failure. For value to act as a unifying attractor, it must encompass a system-wide understanding of outcomes and costs (see Fig. 1). For example, our view of outcomes must include what we as a society value most: population health, the patient’s experience of health, care coordination, patient safety and clinical care [18,24]. At the same time, cost measurement must incorporate the total costs of the full cycle of care for the patient’s medical condition, not the individual services, while also considering the spending over time for a particular condition, population or payer [21,22]. Until the system becomes centred on value, it will constantly adapt and realign itself around other core drivers like disease management or cost containment without adequate consideration of the effects of unintended consequences [18]. An important measure of the PPACA, then, is if it moves us towards unity around payment for value. The polarized passing of the legislation, the tight Supreme Court decision to uphold it and the ensuing political gridlock regarding amendment of its provisions [25] has created a strong division among policymakers and citizens, which inhibits the open, public discourse that catalyses the development of a shared vision [26]. Even though the current political landscape is far from united under a shared vision, the PPACA does include many provisions that focus on improved outcomes and lower costs. One example that just completed its first round of evaluation with mixed results is the pilot-testing programme for Accountable Care Organizations, as reported in the Wall Street Journal [27]. Other examples of provisions in the PPACA that may lead to high-value health care
Figure 1 Definition of value as it applies to health care with examples of patient outcomes and components of total cost. Value can serve as a rallying point for developing a shared vision. Adapted from A Roadmap to High-Value Healthcare Delivery [22].
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include contracting directly with provider groups through riskbased payment; allowing states to test and fully integrate care for Medicare and Medicaid patients (including oversight of all funds); establishing a high-value care collaborative to implement, document and disseminate proven care methods; and rewarding hospitals that provide high-value care [22]. While the PPACA has the potential to nudge the US health system towards more equitable, affordable and high-quality health care, it falls short of uniting diverse stakeholders behind a shared vision of value. One of the greatest impediments to a shared vision around value is the current FFS reimbursement mechanism. The FFS model fragments the health system because it sets each actor in financial conflict with the others. This reimbursement scheme contributes to increasing costs, Medicare and Medicaid fraud, a lack of inter-doctor collaboration, system-wide inefficiency and poor health outcomes [28,29]. Although the PPACA largely maintains the current reimbursement structure, it does provide some development programmes and other incentives to test the pay-forperformance (PFP) model ([2], Sections 3001 and 10326), representing a step in the transition from FFS to one that is more accountable for patient and community outcomes [24]. For example, the PPACA includes three value-based purchasing or PFP, programmes designed to incentivize improved outcomes. One specific programme, hospital value-based purchasing, bases up to 2% of payment on achievement of quality performance standards and patient satisfaction while also rewarding achievement and improvement ([2], Section 10327). Previous literature has shown, however, that PFP, as it is currently being implemented, does not consistently result in higher quality care and better clinical outcomes and can even result in unintended consequences [30–32]. Instead of promoting value, PFP merely incentivizes compliance to certain processes [22]. Because value depends on outcomes, not processes [21], current PFP payment structures may continue to come up short of the goal of high-value health care. Before these programmes can truly incentivize valuedriven health care, stakeholders must increasingly unite behind a shared understanding of value, and outcomes and costs must be measured according to that understanding.
Creating an environment for emergence through simple rules The health system in the United States is characterized by the complex, adaptive interactions of many agents and processes. Such interactions are best directed by simple rules: aims, limits and incentives [6,9]. To make progress towards desired outcomes, simple rules must be based upon the desired common attractor, or shared vision [7]. When simple rules are implemented, which are focused on the common attractor, new system roles and processes emerge, which work towards the established shared vision. In other words, the system has the ability to adapt to new, unforeseen circumstances on its own without being forced or coerced. Instead of attempting to control a complex system through reductionist strategies, stakeholders should unite behind a ‘good enough vision’ and create an environment where an efficient system can self-organize and emerge based on local context and needs [9,33]. The natural tendency within health care reform, however, is to utilize top-down, master plans. Complex systems like health, however, cannot be governed by master plans [34] 136
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because local actors without a shared vision work to ‘game’ the system. When simple rules are replaced with command-andcontrol policies, these top-down reform attempts stifle the innovation, emergence and adaptation found in healthy complex systems that can naturally and efficiently direct the system towards the shared vision [35]. In accordance with this prevailing tendency, the PPACA employs reductionist and command-and-control practices by implementing provisions that attempt to optimize subsystems instead of the system as a whole (see Table 2 for examples from the PPACA). Such reform initiatives too often focus on linear processes – individual components, budgetary concerns or disease-specific initiatives [7] – while not considering the outcomes that these changes will have as the respective subsystems interact, create feedback loops and adapt. Without a shared vision and with aims, incentives and limits that only focus on value within a given subsystem, the PPACA may fall short of creating an environment where high-value system behaviour can emerge. For example, the quality-focused incentives and limits included in the PPACA for providers treating and receiving reimbursement for Medicare patients ([2], Sections 3001–3008) have the potential to improve outcomes and reduce cost for these specific Medicare patients and the Medicare subsystem. However, the PPACA fails to incentivize these same outcomes for all patients and does not consider how this may affect the treatment offered to other patients that the doctor cares for outside of the Medicare system, for good or for bad. Value is surely a focus for many of the aims, limits and incentives in the legislation, but because the various stakeholders and subsystems still have their own fragmented goals and objectives, value may take on a different meaning for each. Aside from lacking a shared understanding of value, the provisions and ‘rules’ in the PPACA are often too prescriptive to enable the complexity of the health system to naturally and efficiently adapt and emerge. Even though the PPACA does offer some room for adaptation and emergence through flexibility given to the states to tailor the provisions to their specific circumstances, like providing grant funds for them to allocate to groups that improve health care quality ([2], Section 4202 and 5303), simple rules are intended to guide the dynamic processes of the system, not to serve as ways to force compliance. Without a shared vision and simple rules as guiding forces for emergence of effective and innovative system components, the PPACA may have limited impact and will likely result in significant unintended consequences [6]. An insightful illustration of this principle is the provision of the PPACA that expands Medicaid to cover approximately 11 million people up to 138% of the Federal Poverty Level [35]. Coupled to the expansion was a limit set on states that did not comply – the loss of federal Medicaid funding. While expanded coverage is an admirable aim, the prescriptive nature of the provision did not allow for local adaptation or innovation. The result was a massive backlash from dissenting states and ultimately in the Supreme Court trial that upheld the expansion, but deemed the limits imposed by this provision to be coercive and provided the states with the option to either to opt-in or opt-out of the expansion. Consequently, nearly half the states have declined to participate, largely as a result of the programme being too expensive to implement [35], thus leaving millions of people in those states without coverage and the system with a huge burden to bear [36].
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Table 2 Examples of ‘simple’ rules (aims, limits and incentives) of the Patient Protection and Affordable Care Act. If simple rules are based on a unified shared vision, they will guide self-adaptation and the emergence of innovative and efficient system components that can help achieve desired system outcomes Aims to [3] 1. Achieve near-universal coverage through shared responsibility among government, individuals and employers. 2. Improve the fairness, quality and affordability of health insurance coverage. 3. Improve health care value, quality and efficiency while reducing wasteful spending and making the health care system more accountable to a diverse patient population. 4. Strengthen primary health care access and preventive health care. 5. Make strategic investments in the public’s health, through both an expansion of clinical preventive care and community investments. Limits on [2] 1. Medicare reimbursement for medical services based on quality standards (Section 3001). 2. Amount and uses of federal funding for demonstration (pilot) projects (Section 2707, 6301). 3. Employers who do not offer employer-sponsored health care coverage (Section 9001). 4. Sharing and use of data (Section 4302). 5. For states that do not comply with Medicaid expansion (Section 2001).* Incentives for [2] 1. Prevention of chronic diseases (Section 4108). 2. Rewarding insurance plan and treatment quality through market-based incentives (Section 1311). 3. Improving health outcomes through: quality reporting, effective case management, care coordination and medication and care compliance initiatives (Section 1311). 4. Implementation of activities to prevent hospital readmission such as education and counseling, planning and reinforcement (Section 1311). 5. Programmes to improve patient safety, reduce medical errors and reduce health and health care disparities (Section 1311). 6. Meeting performance and savings guidelines (ACOs) (Section 2706). *The Supreme Court decision in 2012 revoked the right of HHS to withhold anything but expansion funds to states who did not comply with the expansion, thus reducing the limiting effect of this simple rule [35].
Herein lies the importance for first developing a shared vision, as the combination of a lack of shared vision and a suppression of emergence can lead to a system that is not optimally reaching its potential. Once a shared vision is established on value, and simple rules focused on this shared vision are established, the environment necessary to deliver the desired outcomes through local emergence and innovation without having to ‘force’or ‘control’the system will be in place [7] (see Table 3 for a comparison of the current shared vision and simple rules with those of a future, ideal health system).
Embracing transformational leadership at all levels Since health depends on factors outside of the control of government such as individual behaviour, it is beyond the scope of health reform legislation to create a shared vision or to completely create the environment for emergence [9]. This is up to individuals – leaders – who enact transformational change at all levels. Successful reform of the US health system (or any other health system) along complexity science lines will require change in cultural assumptions about health. This will require that more health professionals become ‘system stewards’ [37], or that they see themselves as responsible for the current status of the health system they are a part of and realize that they have the power to do something about it. These stewards, influential individuals at all levels and even unlikely change agents [26], need to increase their social engagement with and political advocacy for systems level health issues. System stewards from clinical medicine, health education, public health practice, nursing, health policy, community engagement and other disciplines will need to create and disseminate a shared vision around value [38] and establish an environment for efficient system structures to emerge.
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This will not be a discrete process, but rather one that is continuous and iterative. It will require challenging prevailing mental models (see Table 4), considering how their disciplines affect the entire system, communicating and collaborating with colleagues from other disciplines more frequently, planning strategically for opportunities to make lasting structural changes in our health system, and embracing efficient and innovative (though often unanticipated) structures and processes [39]. In other words, systems stewards should adjust perceptions through continuous, interdisciplinary dialogue as they make sense of and adaptively learn from system intricacies and dynamics. Sensemaking, the process of constructing actionable interpretations from many sources of system data [40], can be facilitated by exploratory models and frameworks [41]. By engaging with each other in sensemaking, stewards will be better equipped to react productively and efficiently to system changes [42], attributes that are imperative for an intervention’s success [40]. Indeed, even seemingly small systems-oriented discussions and actions can have larger, unanticipated positive effects [43]. A key to recognizing and challenging prevailing mental models may be found in educating the rising crop of professionals in complexity and systems science principles. In a 2009 report [29], the Medicare Payment Advisory Commission (an independent congressional agency) emphasized that the Medicare programme is the single largest supporter of graduate medical education and strongly encouraged steps towards longterm system changes. This report discusses the importance of reforming medical education even before discussing innovations like the implementation of ACOs and bundled payments, as well as the need for more system-focused courses and programmes throughout a health professional’s education. It advises ‘Reforming medical education will be a key component to transforming 137
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Current system
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Ideal future system (based on the ‘Triple Aim’ [46])
Shared vision
Maximize profits and other outcomes within siloed professions: • Individualism • Doctor autonomy • Emergency and intensive care • Intolerance for misses • Professional tribalism
Maximize the value of the overall system: • The patient at the centre of health care, not other stakeholders • Optimum population health • Effectiveness • Efficiency • Safety and patient satisfaction • Lower per capita cost of health care
Simple rules
• Reimburse on fee-for-service basis (confounded by price controls and a Relative Value System) • Do as many tests and procedures as needed regardless of cost • Provide more specialty care • Allow doctors, hospitals, insurance and pharmaceutical companies to operate independently
• Reimburse for keeping people healthy (pay for value) • Promote health by focusing on prevention and wellness • Educate and train in interdisciplinary teams • Measure patient outcomes and satisfaction through comprehensive, system-wide metrics • Create learning organizations that drive innovation
Table 3 Comparison of the current shared vision and simple rules with those of a future, ideal health system
Table 4 Some mental models and component beliefs that will need to be challenged for successful health reform • • • • • • • • • •
Health is (is not) a human right. Clinical outcomes should (should not) determine health care delivery practices. Provider payments should (should not) be based on delivery of value. Health care is (is not) best managed by fostering competition. Health is (is not) best improved by trying to prevent diseases and injuries before they happen. End of life care and decisions are (are not) best managed in a facility setting. Clinical medicine and population health approaches should (should not) continue to function relatively independently. All health expertise and responsibility is (is not) vested in professionals with formal training and credentials. Patients and their families can (cannot) take significant responsibilities for their own health. Health providers should (should not) be involved in social mobilization and political advocacy.
the nation’s healthcare delivery system from one that historically has focused on care for acute illness to one that values patientcentered care, quality improvement, and resource conservation. Our medical schools and residency training programs need to emphasize a set of skills and knowledge that will equip students and residents to practice and lead under reformed payment incentives.’ Yet, the PPACA contains little that addresses current professional education curricula and the need for a focus on increasing value in the health system. Limited consideration of education reform makes it more difficult to develop a shared vision and create an environment for emergence as doctors, hospital administrators, public health professionals, insurance providers, nurses, policy makers and lawyers are trained in outdated and inefficient delivery practices. As system stewards embrace complexity science principles and challenge mental models, they begin to see that their everyday actions matter. They begin to see that their actions can result in incremental changes that may eventually lead to ‘tipping points’ and, ultimately, the fundamental change that the US health system needs [44]. 138
Conclusion To reform a complex and self-organizing system such as health requires much more than legislative action. Systems reform will require systems stewards who advance a shared vision around value and create an environment for emergence of efficient system structures within their respective spheres of influence through continuous dialogue, sensemaking and learning. Ultimately, this may lead to a paradigm shift among all stakeholders. The complexity concepts that we apply to the US health care system above can and should be applied by health reformers at all health systems levels – from clinics to communities to nations – around the world to improve efficiency and equity. Systems concepts applied to health reform will foster direct links to policy making, result in better ownership, and enhance and build national capacity in solving health system problems [37]. Transforming the US health system, or any other health system, will be neither easy nor quick. Applying complexity concepts to health reform efforts, however, will facilitate long-term change in all levels, leading to health systems that are more effective, efficient and equitable.
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Acknowledgements We thank Bill Rouse, Stan Finklestein, Joel Moses, Larry Green, Scott Cooper, Patrick Kamba and several anonymous reviewers for contributions to earlier drafts of this document.
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19. Stacey, R. (1995) The science of complexity: an alternative perspective for strategic change processes. Strategic Management Journal, 16 (6), 477–495. 20. Dooley, K. (1997) A complex adaptive systems model of organization change. Nonlinear Dynamics, Psychology, and Life Sciences, 1 (1), 69–97. 21. Porter, M. E. (2010) What is value in health care? New England Journal of Medicine, 363 (26), 2477–2481. 22. Cortese, D. & Smoldt, R. (2012) A Roadmap to High-Value Healthcare Delivery. Phoenix, AZ: Healthcare Transformation Institute. 23. Fisher, E., Goodman, D., Skinner, J. & Bronner, K. (2009) Health Care Spending, Quality, and Outcomes, p. 6. Lebanon, NH: The Dartmouth Institute for Health Policy and Clinical Practice. 24. VanLare, J. & Conway, P. (2012) Value-based purchasing – national programs to move from volume to value. New England Journal of Medicine, 367 (4), 292–295. 25. Weisman, J. (2013) Partisan gridlock thwarts effort to alter health law. The New York Times, May 26. 26. Sturmberg, J. P., Martin, C. M. & Moes, M. M. (2010) Health at the center of health systems reform: how philosophy can inform policy. Perspectives in Biology and Medicine, 53 (3), 341– 356. 27. Beck, M. (2013) Mixed results in health pilot plan. The Wall Street Journal, Jul 16. 28. Fisher, E. S., McClellan, M. B., Bertko, J., Lieberman, S. M., Lee, J. J., Lewis, J. L. & Skinner, J. S. (2009) Fostering accountable health care: moving forward in Medicare. Health Affairs, 28 (2), w219–w231. 29. Medicare Payment Advisory Commission (2009) Report to the Congress: improving incentives in the Medicare program. Washington (DC): US House of Representatives, p. 262. 30. De Bruin, S., Baan, C. & Struijs, J. (2011) Pay-for-performance in disease management: a systematic review of the literature. BMC Health Services Research, 11 (1), 272. 31. Serumaga, B., Ross-Degnan, D., Avery, A. J., Elliott, R. A., Majumdar, S. R., Zhang, F. & Soumerai, S. B. (2011) Effect of pay for performance on the management and outcomes of hypertension in the United Kingdom: interrupted time series study. British Medical Journal, 342, d108. 32. Petersen, L. & Woodard, L. (2006) Does pay-for-performance improve the quality of health care? Annals of Internal Medicine, 145 (4), 265–272. 33. Prigogine, I. (1976) Order through Fluctuation: Self-Organization and Social System. Evolution and Consciousness: Human Systems in Transition, pp. 93–126. Boston, MA: Addison-Wesley Publishing. 34. Gawande, A. (2009) Testing, testing: the health-care bill has no master plan for curbing costs. Is that a bad thing? The New Yorker, Dec 14. 35. Kaiser Family Foundation (2012) A guide to the Supreme Court’s decision on the ACA’s Medicaid expansion. Menlo Park (CA): Kaiser Family Foundation. 36. Pear, R. (2013) States’ policies on health care exclude some of the poorest. The New York Times, May 24. 37. De Savigny, D. & Adam, T. (eds) (2009) Systems Thinking for Health Systems Strengthening. Geneva: World Health Organization. 38. Fisher, E. S., Berwick, D. M. & Davis, K. (2009) Achieving health care reform – how physicians can help. New England Journal of Medicine, 360 (24), 2495–2497. 39. Brook, R. H. (2010) Medical leadership in an increasingly complex world. Journal of the American Medical Association, 304 (4), 465– 466. 40. McDaniel, R. R. (2007) Management strategies for complex adaptive systems: sensemaking, learning, and improvisation. Performance Improvement Quarterly, 20 (2), 21–41.
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41. Kurtz, C. F. & Snowden, D. J. (2003) The new dynamics of strategy: sense-making in a complex and complicated world. IBM Systems Journal, 42 (3), 462–483. 42. Jordan, M. E., Lanham, H. J., Crabtree, B. F., Nutting, P. A., Miller, W. L., Stange, K. C. & McDaniel, R. R. (2009) The role of conversation in health care interventions: enabling sensemaking and learning. Implementation Science, 4, 15–28. 43. Green, L. W. & Kreuter, M. W. (2010) Evidence hierarchies versus synergistic interventions. American Journal of Public Health, 100 (10), 1824–1825.
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44. Gladwell, M. (2000) The Tipping Point: How Little Things Can Make a Big Difference. Boston, MA: Little, Brown and Company. 45. Kaiser Family Foundation (2010) Summary of new health reform law. Menlo Park (CA): Kaiser Family Foundation. 46. Berwick, D. M., Nolan, T. W. & Whittington, J. (2008) The triple aim: care, health, and cost. Health Affairs, 27 (3), 759–769.
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Journal of Evaluation in Clinical Practice ISSN 1365-2753
The Affordable Care Act: a case study for understanding and applying complexity concepts to health care reform D. Justin Larkin BS BA,1 R. Chad Swanson DO MPH,2,3 Spencer Fuller BA4 and Denis A. Cortese MD5,6 1
MD Candidate, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Affiliate Faculty, Department of Health Sciences, Brigham Young University, Provo, UT, USA 3 Physician, Department of Emergency Medicine, Intermountain Healthcare, Provo, UT, USA 4 MD Candidate, School of Medicine, University of California, San Diego, La Jolla, CA, USA 5 Foundation Professor and Director, Healthcare Delivery and Policy Program, Arizona State University, Tempe, AZ, USA 6 Emeritus President and CEO, Mayo Clinic, Rochester, MN, USA 2
Keywords complexity science, health care policy, health care reform Correspondence Mr D. Justin Larkin Perelman School of Medicine University of Pennsylvania Suite 100 Stemmler Hall Philadelphia, PA 19104-6056 USA E-mail: [email protected] Accepted for publication: 5 September 2014 doi:10.1111/jep.12271
Abstract Rationale, aims and objectives The current health system in the United States is the result of a history of patchwork policy decisions and cultural assumptions that have led to persistent contradictions in practice, gaps in coverage, unsustainable costs, and inconsistent outcomes. In working toward a more efficient health system, understanding and applying complexity science concepts will allow for policy that better promotes desired outcomes and minimizes the effects of unintended consequences. Methods This paper will consider three applied complexity science concepts in the context of the Patient Protection and Affordable Care Act (PPACA): developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels. Results and conclusions Transforming the US health system, or any other health system, will be neither easy nor quick. Applying complexity concepts to health reform efforts, however, will facilitate long-term change in all levels, leading to health systems that are more effective, efficient, and equitable.
Introduction The current health system in the United States is the result of a history of patchwork policy decisions and cultural assumptions that have led to persistent contradictions in practice, gaps in coverage, unsustainable costs, and inconsistent outcomes. The recent debate over health care reform has brought the fragmented, inefficient and inequitable nature of that system into the glare of media attention and under public scrutiny. Discussions, dominated by special interest groups, have typically omitted ‘complexity science’ approaches: those that consider the inherently complex nature of the system as a whole and the interrelations of its subsystems [1]. The process leading the US Congress to pass the Patient Protection and Affordable Care Act [2] (PPACA, see Table 1) illustrated the heart of the problem: legislators substituted polarizing rhetoric in place of serious public dialogue about a shared vision of an ideal US health system. Even the US Supreme Court’s narrow decision in June 2012 to uphold the individual mandate and Medicaid expansion provisions of the PPACA by a vote of 5 to 4 highlights the divided nature of the country.
With that Supreme Court decision on the two controversial issues, there seemed to be a growing consensus that the core provisions of the PPACA would remain intact. In fact, and more recently, the problems with the federal exchange rollout and other delays have generated much scrutiny from opponents of the PPACA, but have done little to slow the momentum of the implementation of the legislation. While the PPACA will likely improve equity through increased insurance coverage [3], there is still a need to address components and processes within the still inefficient health system that make it a large financial burden on US citizens without resulting in the desired population and individual health outcomes. The reductionist and linear views of the biomedical paradigm that drive current policy and reform are insufficient to understand the dynamic and complex interactions of the various actors and stakeholders involved in the health system and to offer solutions that promote lasting change. Complexity approaches offer a different set of solutions [4] that account for the non-linear, complex and multidimensional processes [5] that characterize health systems. In working towards a more efficient health system, understanding and applying complexity science concepts will
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Table 1 Summary of various key provisions included in the Patient Protection and Affordable Care Act Provisions to improve coverage • Require US citizens and legal residents to have health insurance, the so-called ‘individual mandate’. • Create state-level insurance exchanges so that individuals and businesses can purchase insurance. • Require employers to offer coverage. • Expand Medicaid (the government-run health insurance programme for the poor) to 133% of the federal poverty level. • Improve coverage of patients’ pre-existing conditions, and expand dependent coverage. Provisions intended to control health care costs • Minimize administrative costs by standardizing health insurance operating rules and other procedures. • Restructure Medicare payments to discourage fee-for-service payments. • Establish a body of professionals – an Independent Payment Advisory Board – that will submit legislative proposals to control costs. • Create an ‘Innovation Center’ within the Centers for Medicare and Medicaid Services to encourage and test innovative payment structures. • Incentivize the formation of ‘accountable care organizations’, wherein providers share in cost savings if they meet criteria such as: coordinate comprehensive care, improve quality and promote evidence-based medicine. Provisions intended to improve the health care delivery system • Establish an institute to support comparative effectiveness research. • Award grants that propose medical malpractice tort reform. • Establish Medicare and Medicaid pilot programmes based on ‘bundled payments’; payments for episodes of care lasting 30 days for a given condition. • Increase payments to primary care providers. • Establish the National Prevention, Health Promotion and Public Health Council to coordinate federal prevention, wellness and public health activities and make funds available for research around those areas. • Improve payment for preventative measures, and provide grants for wellness programmes. Adapted from Summary of New Health Reform Law [45].
allow for policy that better promotes desired outcomes and minimizes the effects of unintended consequences [6]. Others have utilized concepts of complexity science as a framework for more effective health care reform [7,8] and as a lens to understand the US health care reform in particular [6,9]. We hope to continue that discussion by applying a complexity science lens to various provisions of the PPACA. This is a timely consideration, as many of the most impactful provisions of the bill have gone into effect in 2014 and many more will take effect in the coming years, thus setting the course for the US health care system for the near and distant future. A comprehensive analysis of the legislation in the PPACA is beyond the scope of this paper, as is a detailed overview of complexity. Rather, this paper will provide a brief introduction to complexity concepts and approaches, and consider three applied complexity science concepts in the context of the PPACA: developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels.
Complexity and health: a brief introduction Practices and policies in the US health care system over the past 100 years have largely been based on mechanistic assumptions rooted in scientific reductionism [10]. The randomized, controlled trial – considered by many the ‘gold standard’ in medical research – highlights this dominating perspective: all confounding variables are controlled so that we consider one intervention isolated from all other factors. Our reductionist mindset is not limited to medical research or interventions. For example, we too often work in silos, reimburse for one service and educate and train for a specific 134
patient encounter. Linear causality dominates this perspective; we assume that a particular action will result in a corresponding result. We might suppose that paying providers for their services will result in optimal outcomes, or that prescribing a medication for an illness to treat the underlying pathophysiology of the disease. While this reductionist approach to medicine has resulted in successes in managing certain diseases, ranging from the development of vaccines and antibiotics to the improvement of the art and science of surgical techniques, it is inadequate to address the challenges of our current complex health care system [4]. The health care system has been described as a complex, adaptive system because it has five key characteristics: diverse agents that learn, non-linear interdependencies, emergence, co-evolution, and self-organization [11]. Health care providers, patients, policy makers, citizens and many others are the agents that make up the health care system. All of these individuals have unique perspectives, assumptions, relationships, personality characteristics, experiences and goals that influence the way that they act in the system. They learn from experience in the system to optimize their position locally. A doctor prescribes unnecessary antibiotics to appease her patient [12]. An insurance company limits the drugs on its formulary to prevent the prescription of more expensive drugs [13]. The effects of their actions often have unpredictable outcomes [6,13,14]. A small act can have large effects, such as a rumor resulting in the firing of an administrator. Conversely, a large act, such as requiring blood cultures for pneumonia patients can have relatively small effects; the intervention might not result in improved outcomes [15]. When agents self-organize into structures, those phenomena are described as emergent. The systemic effects of emergence are unpredictable and are decided by how agents adapt in response to the new structures. This principle is illustrated by the increase in
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nosocomial infection rates due to the emergence of resistant bacteria secondary to widespread antibiotic usage [16]. As an example on the health system level, conferences have emerged that train doctors how to document their clinical encounters to maximize their billing under the current fee-for-service (FFS) structure. These, too, are examples of co-evolution: when a complex system changes, its environment changes as well [17]. Reductionist approaches to health often result in significant unintended consequences because of the unpredictable nature of the system [6,14]. No one individual is in charge of the entire system, and no one person or organization can predict how others are going to react because diverse agents self-organize to optimize locally. Indeed, ‘the essence of complexity science is in the study of patterns and relationships, rather than objects and substance’ ([17], emphasis added). By focusing attention on these patterns and relationships, complexity science helps stakeholders to anticipate self-organization and unintended consequences, and in turn to create policy that allows for quick response to changes in the system. We turn our attention to three applied complexity science concepts in the context of the PPACA: developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels.
A shared vision around reimbursement for value A shared vision unites people behind an idea that transcends their different backgrounds and experiences by providing a common motivator for transforming behaviour. It can also be viewed as an ‘attractor’, or a force that naturally influences all aspects of a system [18,19]. A vision owned by all stakeholders is a powerful force for the long-lasting change needed in the US health system as it encourages the self-organizing power of the complex system to work in favour of, rather than against, policy initiatives [20]. Currently, the shared vision in the United States is weak. Patients are motivated to reduce the negative effects of disease; providers to offer as many services as can be justified for their patients; governments to reduce costs and prevalence of specific diseases; and insurance companies to have the highest bottom line. Furthermore, pharmaceutical and biotechnology companies are incentivized to drive up utilization of their products, resist price controls, and protect their patent rights; legislators to use health care as a means to gain the votes necessary for election; lawyers to earn financial gain on mistakes by health care professionals without helping the system learn from those mistakes; and employers to take advantage of the tax free nature of providing insurance benefits (instead of offering higher salaries) and to help their employees be present and productive at work. In short, these attractors are each optimized to financially profit the respective stakeholder – an outcome the US health system achieves quite successfully. The fragmented and divergent nature of these attractors results in a US health system that seems to be working against itself as much as it works together; this limits dynamic adaptation and prevents the health system from effectively reaching its most important goal – producing individual and population health equitably and efficiently.
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Ultimately, performance and accountability in the US health system will only improve once a shared vision unites the interests and activities of all shareholders [21]. One rallying point that has the potential to unite the many stakeholders in the health system is value. Value is simply defined as the outcomes achieved per dollar spent to achieve those outcomes over time [22]. Because higher spending is not currently correlated with improved outcomes [23], there is much room for improving the value of the US health care system. Oftentimes, outcomes and costs are narrowly viewed as specific, final clinical outcomes or the money spent on an individual service rendered to a patient, respectively. Consistent with the reductionist paradigm, these metrics are often poor, overly simplified surrogates that do not accurately reflect system success or failure. For value to act as a unifying attractor, it must encompass a system-wide understanding of outcomes and costs (see Fig. 1). For example, our view of outcomes must include what we as a society value most: population health, the patient’s experience of health, care coordination, patient safety and clinical care [18,24]. At the same time, cost measurement must incorporate the total costs of the full cycle of care for the patient’s medical condition, not the individual services, while also considering the spending over time for a particular condition, population or payer [21,22]. Until the system becomes centred on value, it will constantly adapt and realign itself around other core drivers like disease management or cost containment without adequate consideration of the effects of unintended consequences [18]. An important measure of the PPACA, then, is if it moves us towards unity around payment for value. The polarized passing of the legislation, the tight Supreme Court decision to uphold it and the ensuing political gridlock regarding amendment of its provisions [25] has created a strong division among policymakers and citizens, which inhibits the open, public discourse that catalyses the development of a shared vision [26]. Even though the current political landscape is far from united under a shared vision, the PPACA does include many provisions that focus on improved outcomes and lower costs. One example that just completed its first round of evaluation with mixed results is the pilot-testing programme for Accountable Care Organizations, as reported in the Wall Street Journal [27]. Other examples of provisions in the PPACA that may lead to high-value health care
Figure 1 Definition of value as it applies to health care with examples of patient outcomes and components of total cost. Value can serve as a rallying point for developing a shared vision. Adapted from A Roadmap to High-Value Healthcare Delivery [22].
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include contracting directly with provider groups through riskbased payment; allowing states to test and fully integrate care for Medicare and Medicaid patients (including oversight of all funds); establishing a high-value care collaborative to implement, document and disseminate proven care methods; and rewarding hospitals that provide high-value care [22]. While the PPACA has the potential to nudge the US health system towards more equitable, affordable and high-quality health care, it falls short of uniting diverse stakeholders behind a shared vision of value. One of the greatest impediments to a shared vision around value is the current FFS reimbursement mechanism. The FFS model fragments the health system because it sets each actor in financial conflict with the others. This reimbursement scheme contributes to increasing costs, Medicare and Medicaid fraud, a lack of inter-doctor collaboration, system-wide inefficiency and poor health outcomes [28,29]. Although the PPACA largely maintains the current reimbursement structure, it does provide some development programmes and other incentives to test the pay-forperformance (PFP) model ([2], Sections 3001 and 10326), representing a step in the transition from FFS to one that is more accountable for patient and community outcomes [24]. For example, the PPACA includes three value-based purchasing or PFP, programmes designed to incentivize improved outcomes. One specific programme, hospital value-based purchasing, bases up to 2% of payment on achievement of quality performance standards and patient satisfaction while also rewarding achievement and improvement ([2], Section 10327). Previous literature has shown, however, that PFP, as it is currently being implemented, does not consistently result in higher quality care and better clinical outcomes and can even result in unintended consequences [30–32]. Instead of promoting value, PFP merely incentivizes compliance to certain processes [22]. Because value depends on outcomes, not processes [21], current PFP payment structures may continue to come up short of the goal of high-value health care. Before these programmes can truly incentivize valuedriven health care, stakeholders must increasingly unite behind a shared understanding of value, and outcomes and costs must be measured according to that understanding.
Creating an environment for emergence through simple rules The health system in the United States is characterized by the complex, adaptive interactions of many agents and processes. Such interactions are best directed by simple rules: aims, limits and incentives [6,9]. To make progress towards desired outcomes, simple rules must be based upon the desired common attractor, or shared vision [7]. When simple rules are implemented, which are focused on the common attractor, new system roles and processes emerge, which work towards the established shared vision. In other words, the system has the ability to adapt to new, unforeseen circumstances on its own without being forced or coerced. Instead of attempting to control a complex system through reductionist strategies, stakeholders should unite behind a ‘good enough vision’ and create an environment where an efficient system can self-organize and emerge based on local context and needs [9,33]. The natural tendency within health care reform, however, is to utilize top-down, master plans. Complex systems like health, however, cannot be governed by master plans [34] 136
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because local actors without a shared vision work to ‘game’ the system. When simple rules are replaced with command-andcontrol policies, these top-down reform attempts stifle the innovation, emergence and adaptation found in healthy complex systems that can naturally and efficiently direct the system towards the shared vision [35]. In accordance with this prevailing tendency, the PPACA employs reductionist and command-and-control practices by implementing provisions that attempt to optimize subsystems instead of the system as a whole (see Table 2 for examples from the PPACA). Such reform initiatives too often focus on linear processes – individual components, budgetary concerns or disease-specific initiatives [7] – while not considering the outcomes that these changes will have as the respective subsystems interact, create feedback loops and adapt. Without a shared vision and with aims, incentives and limits that only focus on value within a given subsystem, the PPACA may fall short of creating an environment where high-value system behaviour can emerge. For example, the quality-focused incentives and limits included in the PPACA for providers treating and receiving reimbursement for Medicare patients ([2], Sections 3001–3008) have the potential to improve outcomes and reduce cost for these specific Medicare patients and the Medicare subsystem. However, the PPACA fails to incentivize these same outcomes for all patients and does not consider how this may affect the treatment offered to other patients that the doctor cares for outside of the Medicare system, for good or for bad. Value is surely a focus for many of the aims, limits and incentives in the legislation, but because the various stakeholders and subsystems still have their own fragmented goals and objectives, value may take on a different meaning for each. Aside from lacking a shared understanding of value, the provisions and ‘rules’ in the PPACA are often too prescriptive to enable the complexity of the health system to naturally and efficiently adapt and emerge. Even though the PPACA does offer some room for adaptation and emergence through flexibility given to the states to tailor the provisions to their specific circumstances, like providing grant funds for them to allocate to groups that improve health care quality ([2], Section 4202 and 5303), simple rules are intended to guide the dynamic processes of the system, not to serve as ways to force compliance. Without a shared vision and simple rules as guiding forces for emergence of effective and innovative system components, the PPACA may have limited impact and will likely result in significant unintended consequences [6]. An insightful illustration of this principle is the provision of the PPACA that expands Medicaid to cover approximately 11 million people up to 138% of the Federal Poverty Level [35]. Coupled to the expansion was a limit set on states that did not comply – the loss of federal Medicaid funding. While expanded coverage is an admirable aim, the prescriptive nature of the provision did not allow for local adaptation or innovation. The result was a massive backlash from dissenting states and ultimately in the Supreme Court trial that upheld the expansion, but deemed the limits imposed by this provision to be coercive and provided the states with the option to either to opt-in or opt-out of the expansion. Consequently, nearly half the states have declined to participate, largely as a result of the programme being too expensive to implement [35], thus leaving millions of people in those states without coverage and the system with a huge burden to bear [36].
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Table 2 Examples of ‘simple’ rules (aims, limits and incentives) of the Patient Protection and Affordable Care Act. If simple rules are based on a unified shared vision, they will guide self-adaptation and the emergence of innovative and efficient system components that can help achieve desired system outcomes Aims to [3] 1. Achieve near-universal coverage through shared responsibility among government, individuals and employers. 2. Improve the fairness, quality and affordability of health insurance coverage. 3. Improve health care value, quality and efficiency while reducing wasteful spending and making the health care system more accountable to a diverse patient population. 4. Strengthen primary health care access and preventive health care. 5. Make strategic investments in the public’s health, through both an expansion of clinical preventive care and community investments. Limits on [2] 1. Medicare reimbursement for medical services based on quality standards (Section 3001). 2. Amount and uses of federal funding for demonstration (pilot) projects (Section 2707, 6301). 3. Employers who do not offer employer-sponsored health care coverage (Section 9001). 4. Sharing and use of data (Section 4302). 5. For states that do not comply with Medicaid expansion (Section 2001).* Incentives for [2] 1. Prevention of chronic diseases (Section 4108). 2. Rewarding insurance plan and treatment quality through market-based incentives (Section 1311). 3. Improving health outcomes through: quality reporting, effective case management, care coordination and medication and care compliance initiatives (Section 1311). 4. Implementation of activities to prevent hospital readmission such as education and counseling, planning and reinforcement (Section 1311). 5. Programmes to improve patient safety, reduce medical errors and reduce health and health care disparities (Section 1311). 6. Meeting performance and savings guidelines (ACOs) (Section 2706). *The Supreme Court decision in 2012 revoked the right of HHS to withhold anything but expansion funds to states who did not comply with the expansion, thus reducing the limiting effect of this simple rule [35].
Herein lies the importance for first developing a shared vision, as the combination of a lack of shared vision and a suppression of emergence can lead to a system that is not optimally reaching its potential. Once a shared vision is established on value, and simple rules focused on this shared vision are established, the environment necessary to deliver the desired outcomes through local emergence and innovation without having to ‘force’or ‘control’the system will be in place [7] (see Table 3 for a comparison of the current shared vision and simple rules with those of a future, ideal health system).
Embracing transformational leadership at all levels Since health depends on factors outside of the control of government such as individual behaviour, it is beyond the scope of health reform legislation to create a shared vision or to completely create the environment for emergence [9]. This is up to individuals – leaders – who enact transformational change at all levels. Successful reform of the US health system (or any other health system) along complexity science lines will require change in cultural assumptions about health. This will require that more health professionals become ‘system stewards’ [37], or that they see themselves as responsible for the current status of the health system they are a part of and realize that they have the power to do something about it. These stewards, influential individuals at all levels and even unlikely change agents [26], need to increase their social engagement with and political advocacy for systems level health issues. System stewards from clinical medicine, health education, public health practice, nursing, health policy, community engagement and other disciplines will need to create and disseminate a shared vision around value [38] and establish an environment for efficient system structures to emerge.
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This will not be a discrete process, but rather one that is continuous and iterative. It will require challenging prevailing mental models (see Table 4), considering how their disciplines affect the entire system, communicating and collaborating with colleagues from other disciplines more frequently, planning strategically for opportunities to make lasting structural changes in our health system, and embracing efficient and innovative (though often unanticipated) structures and processes [39]. In other words, systems stewards should adjust perceptions through continuous, interdisciplinary dialogue as they make sense of and adaptively learn from system intricacies and dynamics. Sensemaking, the process of constructing actionable interpretations from many sources of system data [40], can be facilitated by exploratory models and frameworks [41]. By engaging with each other in sensemaking, stewards will be better equipped to react productively and efficiently to system changes [42], attributes that are imperative for an intervention’s success [40]. Indeed, even seemingly small systems-oriented discussions and actions can have larger, unanticipated positive effects [43]. A key to recognizing and challenging prevailing mental models may be found in educating the rising crop of professionals in complexity and systems science principles. In a 2009 report [29], the Medicare Payment Advisory Commission (an independent congressional agency) emphasized that the Medicare programme is the single largest supporter of graduate medical education and strongly encouraged steps towards longterm system changes. This report discusses the importance of reforming medical education even before discussing innovations like the implementation of ACOs and bundled payments, as well as the need for more system-focused courses and programmes throughout a health professional’s education. It advises ‘Reforming medical education will be a key component to transforming 137
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Ideal future system (based on the ‘Triple Aim’ [46])
Shared vision
Maximize profits and other outcomes within siloed professions: • Individualism • Doctor autonomy • Emergency and intensive care • Intolerance for misses • Professional tribalism
Maximize the value of the overall system: • The patient at the centre of health care, not other stakeholders • Optimum population health • Effectiveness • Efficiency • Safety and patient satisfaction • Lower per capita cost of health care
Simple rules
• Reimburse on fee-for-service basis (confounded by price controls and a Relative Value System) • Do as many tests and procedures as needed regardless of cost • Provide more specialty care • Allow doctors, hospitals, insurance and pharmaceutical companies to operate independently
• Reimburse for keeping people healthy (pay for value) • Promote health by focusing on prevention and wellness • Educate and train in interdisciplinary teams • Measure patient outcomes and satisfaction through comprehensive, system-wide metrics • Create learning organizations that drive innovation
Table 3 Comparison of the current shared vision and simple rules with those of a future, ideal health system
Table 4 Some mental models and component beliefs that will need to be challenged for successful health reform • • • • • • • • • •
Health is (is not) a human right. Clinical outcomes should (should not) determine health care delivery practices. Provider payments should (should not) be based on delivery of value. Health care is (is not) best managed by fostering competition. Health is (is not) best improved by trying to prevent diseases and injuries before they happen. End of life care and decisions are (are not) best managed in a facility setting. Clinical medicine and population health approaches should (should not) continue to function relatively independently. All health expertise and responsibility is (is not) vested in professionals with formal training and credentials. Patients and their families can (cannot) take significant responsibilities for their own health. Health providers should (should not) be involved in social mobilization and political advocacy.
the nation’s healthcare delivery system from one that historically has focused on care for acute illness to one that values patientcentered care, quality improvement, and resource conservation. Our medical schools and residency training programs need to emphasize a set of skills and knowledge that will equip students and residents to practice and lead under reformed payment incentives.’ Yet, the PPACA contains little that addresses current professional education curricula and the need for a focus on increasing value in the health system. Limited consideration of education reform makes it more difficult to develop a shared vision and create an environment for emergence as doctors, hospital administrators, public health professionals, insurance providers, nurses, policy makers and lawyers are trained in outdated and inefficient delivery practices. As system stewards embrace complexity science principles and challenge mental models, they begin to see that their everyday actions matter. They begin to see that their actions can result in incremental changes that may eventually lead to ‘tipping points’ and, ultimately, the fundamental change that the US health system needs [44]. 138
Conclusion To reform a complex and self-organizing system such as health requires much more than legislative action. Systems reform will require systems stewards who advance a shared vision around value and create an environment for emergence of efficient system structures within their respective spheres of influence through continuous dialogue, sensemaking and learning. Ultimately, this may lead to a paradigm shift among all stakeholders. The complexity concepts that we apply to the US health care system above can and should be applied by health reformers at all health systems levels – from clinics to communities to nations – around the world to improve efficiency and equity. Systems concepts applied to health reform will foster direct links to policy making, result in better ownership, and enhance and build national capacity in solving health system problems [37]. Transforming the US health system, or any other health system, will be neither easy nor quick. Applying complexity concepts to health reform efforts, however, will facilitate long-term change in all levels, leading to health systems that are more effective, efficient and equitable.
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Acknowledgements We thank Bill Rouse, Stan Finklestein, Joel Moses, Larry Green, Scott Cooper, Patrick Kamba and several anonymous reviewers for contributions to earlier drafts of this document.
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