By Samuel Chimeremueze Anaemeje
Applying Engineering Systems Models to Healthcare Improvement
As health systems worldwide confront increasing complexity—from rising chronic disease burdens to fragmented care coordination and resource inefficiency—traditional approaches to service improvement are proving insufficient. Siloed reforms, reactive interventions, and isolated performance metrics often fail to account for the dynamic, interdependent nature of modern healthcare. To address these shortcomings, the field is witnessing a growing shift toward systems thinking, an approach long used in engineering and now increasingly applied to health service design and transformation.
This article explores how systems thinking, rooted in engineering management and systems science, provides powerful tools to redesign health service delivery. It offers not only a conceptual framework for understanding complexity but also practical models—such as Lean, Six Sigma, and microsystems engineering—for creating resilient, efficient, and patient-centred health systems.
Systems Thinking: A Paradigm for Complexity
Systems thinking emphasizes the relationships, feedback loops, and emergent behaviours that arise from the interaction of system components over time (de Savigny & Adam, 2020). In contrast to linear cause-effect models, it encourages holistic analysis, long-term learning, and adaptive strategy. Healthcare systems, like engineered systems, consist of multiple interacting subcomponents—clinicians, patients, technologies, institutions, and policies—all operating within social, cultural, and economic contexts.
In low-resource settings, where limitations in infrastructure and workforce create additional strain, systems thinking has proven especially valuable (Best, Saul & Greenhalgh, 2021). It enables leaders to identify leverage points—places where small, strategic interventions can lead to large, sustained improvements.
Engineering Models Applied to Healthcare
Borrowed from industrial and systems engineering, models such as Lean, Six Sigma, and Clinical Microsystems have increasingly been applied to health service delivery.
Lean healthcare, adapted from Toyota’s production system, focuses on eliminating waste while maximizing value from the patient’s perspective. This involves streamlining workflows, reducing waiting times, and improving patient flow (Poksinska, Swartling & Drotz, 2021). Although adoption has met some resistance—due to concerns over oversimplification and cultural fit—evidence shows that, when applied thoughtfully, Lean can improve efficiency without compromising care quality (Waring & Bishop, 2020).
Six Sigma, originally developed for precision manufacturing, offers rigorous statistical tools for reducing variation and enhancing quality. In healthcare, this model supports data-driven decision-making, root cause analysis, and continuous process improvement. Combined with Lean, it provides a comprehensive strategy for operational excellence (Kapur & Smith, 2020).
Clinical Microsystems, introduced by Nelson et al. (2020), focus on the small, frontline units of care—where patients, professionals, and systems meet. These microsystems form the building blocks of larger institutions and, when optimized, drive system-wide transformation. Their design considers culture, leadership, data, and service relationships, aligning well with both systems thinking and engineering principles.
From Concept to Implementation
Successful application of systems thinking in healthcare requires more than importing engineering tools—it demands a cultural shift. Health systems are traditionally hierarchical, risk-averse, and fragmented by specialties and departments. Systems thinking encourages cross-functional collaboration, shared learning, and feedback loops that challenge rigid command-and-control structures.
Rees and Gauld (2021) note that hospitals employing systems-based performance management show improved coordination and responsiveness. However, they caution that performance targets must be system-aligned; otherwise, they risk driving unintended behaviours, such as overtreatment or data gaming.
Systems thinking also supports dynamic modelling and simulation, allowing decision-makers to test scenarios before implementation. Kim and Andersen (2020) demonstrate how modelling patient flow in emergency departments using systems dynamics can optimize capacity, reduce bottlenecks, and enhance patient outcomes.
Resilience and Learning in Health Systems
The COVID-19 pandemic revealed systemic vulnerabilities in even the most advanced health systems. Resilience—the ability to absorb shocks and reorganize while maintaining core functions—has emerged as a key objective in health service redesign. WHO (2021) highlights systems thinking as central to building resilient health systems that can adapt to crises, absorb complexity, and continue to serve populations equitably.
This perspective aligns with engineering’s emphasis on fault tolerance, redundancy, and flexibility—design principles that can be intentionally embedded into health service infrastructures.
Van Olmen et al. (2020) further argue that health systems frameworks must reflect political, economic, and contextual realities. Systems thinking does not occur in a vacuum; it must be informed by participatory governance, community input, and health equity objectives.
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Barriers and Enablers
Despite its promise, implementing systems thinking in health service redesign faces significant barriers. These include limited technical expertise, entrenched professional silos, rigid funding mechanisms, and lack of interoperable data systems (Best, Saul & Greenhalgh, 2021). To overcome these, health leaders must invest in systems education, foster interprofessional collaboration, and align incentives with holistic outcomes.
Leadership plays a pivotal role. Without committed leadership capable of navigating complexity and mobilizing cross-sectoral support, systems-based initiatives may falter or revert to traditional paradigms.
Finally, redesigning health service delivery requires more than incremental fixes; it requires a fundamental shift in how health systems are understood and managed. Systems thinking, particularly when integrated with engineering models, offers a robust and adaptive framework for tackling complexity, improving efficiency, and enhancing patient outcomes.
By moving beyond reductionist approaches and embracing interconnection, feedback, and learning, health systems can become more resilient, more responsive, and more aligned with the needs of the populations they serve. The future of healthcare will not be built by isolated reforms, but by systems designed to think, adapt, and thrive.
Engineer Samuel Chimeremueze Anaemeje is a distinguished software engineer, healthcare professional, and expert in engineering management whose interdisciplinary mastery drives innovation across sectors. With a rare blend of clinical insight and advanced technical skill, he develops scalable, human-centered systems that improve both technological performance and healthcare outcomes. Known for his precision, strategic thinking, and integrity, Samuel transforms complex challenges into impactful, sustainable solutions. His work bridges engineering and health with a clear focus on quality, efficiency, and user experience. A visionary leader, he continues to inspire transformative change, setting new standards in digital health and systems design worldwide.
References
Best, A., Saul, J.E. and Greenhalgh, T., 2021. Systems thinking for health systems strengthening in low-income countries: A realist synthesis. BMJ Global Health, 6(3), e005635. https://doi.org/10.1136/bmjgh-2021-005635
de Savigny, D. and Adam, T. (eds.), 2020. Systems Thinking for Health Systems Strengthening. 2nd ed. Geneva: Alliance for Health Policy and Systems Research, World Health Organization. https://www.who.int/alliance-hpsr/resources/9789241563897/en/
Kapur, G.B. and Smith, J.P., 2020. Systems thinking in health care: Lessons from engineering. Journal of Healthcare Engineering, 2020, Article ID 8854390. https://doi.org/10.1155/2020/8854390
Kim, D. and Andersen, D.F., 2020. A systems approach to improving patient flow in emergency departments. Systems Research and Behavioral Science, 37(5), pp.842–855. https://doi.org/10.1002/sres.2683
Nelson, E.C., Batalden, P.B., Godfrey, M.M. and Lazar, J.S., 2020. Value by Design: Developing Clinical Microsystems to Achieve Organizational Excellence. 2nd ed. San Francisco: Jossey-Bass.
Poksinska, B., Swartling, D. and Drotz, E., 2021. The use of Lean in healthcare: A global review. Leadership in Health Services, 34(1), pp.1–20. https://doi.org/10.1108/LHS-04-2020-0028
Rees, G.H. and Gauld, R., 2021. Systems thinking and performance management in public hospitals. Health Policy, 125(4), pp.464–471. https://doi.org/10.1016/j.healthpol.2021.02.004
Van Olmen, J., Marchal, B., Van Damme, W. and Kegels, G., 2020. Health systems frameworks in their political context: Framing divergent agendas. BMC Public Health, 20(1), p.1. https://doi.org/10.1186/s12889-020-08796-0
Waring, J. and Bishop, S., 2020. Lean healthcare: Rhetoric, ritual and resistance. Social Science & Medicine, 260, p.113201. https://doi.org/10.1016/j.socscimed.2020.113201
World Health Organization (WHO), 2021. Health systems resilience toolkit: A WHO global public health good. Geneva: World Health Organization. https://www.who.int/publications/i/item/9789240038310