Better Decisions for Complex Health Systems: Aligning Priorities Through Applied Health Economics

Feature article

By Professor Taha Chaiechi

Dean (Academic), ICMS

Introduction

Healthcare systems around the world are facing mounting and increasingly complex pressures. Ageing populations, escalating costs, workforce shortages, and rising expectations for high-quality care are placing unprecedented demands on decision-makers responsible for resource allocation, funding, and service design at all levels of the system. These pressures are not only intensifying but also interacting in ways that make decision-making more complex and less predictable.

At the same time, many resource allocation, funding, and service design decisions must be made under conditions of uncertainty. Data may be incomplete, outcomes may be difficult to predict, and trade-offs between competing priorities are often unavoidable. Whether allocating limited resources, designing interventions, or prioritising patient care, decision-makers are required to act despite ambiguity, time constraints, and competing stakeholder expectations.

Recent policy debates, particularly reforms to the National Disability Insurance Scheme (NDIS), highlight the challenge of balancing rising demand with constrained public budgets. The 2024–25 federal budget raises concerns about the scheme’s rapid expenditure growth and long-term sustainability, while broader trends show Australia’s health spending exceeding $270 billion amid increasing demand for services[1]. These pressures illustrate how decisions about funding and service priorities directly shape access to care and system sustainability.

In this context, the importance of structured, evidence-based decision-making becomes increasingly clear. Health economics, as a discipline, offers well-established tools to support such decisions by evaluating costs, outcomes, and trade-offs in a systematic way. However, despite decades of development, the integration of these tools into everyday practice remains uneven.

In many real-world settings, decisions continue to rely heavily on experience, intuition, or organisational precedent rather than formal economic evaluation. While professional judgement remains essential, the limited use of structured frameworks can lead to inconsistent, opaque, or suboptimal outcomes, including increased variation in care, diagnostic errors, and delays in treatment[2], [3].

This highlights a critical and ongoing challenge: how can economic reasoning be made more accessible, practical, and embedded in routine decision-making processes across healthcare systems?

From Theory to Practice: A Persistent Gap

Health economics offer a well-established set of frameworks for evaluating costs, outcomes, and trade-offs. Tools such as cost-effectiveness and cost-benefit analysis are widely recognised as critical for informing resource allocation, service design, and policy decisions.

Yet despite their conceptual strength and widespread recognition, their application in practice remains uneven. A key barrier is accessibility. Much of the existing literature is highly technical and often designed for specialist audiences. While these approaches are theoretically robust, they are not always easily translated into the fast-paced, resource-constrained environments in which real-world decisions are made. As a result, clinicians, health service managers (e.g., hospital executives and program directors),  and policymakers (e.g., government health departments and regulatory agencies) frequently rely on experience, judgement, or organisational conventions rather than structured analytical frameworks[4], [5].

This disconnect between theoretical capability and practical application is not unique to health systems. Evidence from broader economic research shows that decision-makers often struggle to apply formal models in complex, uncertain, and rapidly changing environments[6]. Under such conditions, even well-established tools can remain underutilised if they are not accessible, adaptable, and relevant to day-to-day decision-making.

Bridging this gap therefore requires more than methodological refinement. It requires a deliberate shift towards approaches that translate theory into practical, usable tools that can be integrated into routine decision-making processes.

An Applied Approach to Decision-Making

In complex health systems, decision-makers often face uncertainty, competing priorities, and limited resources. While analytical tools exist to support these decisions, many remain underutilised due to their complexity or limited accessibility. This creates a need for practical, applied frameworks that can support real-world decision-making.

Addressing this challenge was a key motivation behind the development of the open-access book ‘Applied Health Economics: Practical Methods for Evidence-Based Health Decisions’ [7]. This work builds on earlier applied contributions in economic decision-making[8], which emphasise the importance of structured yet accessible tools in guiding real-world choices.

The book adopts a deliberately applied perspective. Rather than focusing on abstract modelling, it translates key economic concepts into practical frameworks that can be used by clinicians making treatment decisions, postgraduate students, and researchers developing the analytical skills, managers allocating resources, and policymakers designing interventions. The focus is not on replacing professional judgement, but on strengthening it. In doing so, it aims to reduce reliance on ad hoc or intuition-based decision-making and instead support more consistent, evidence-informed practices across different levels of the system.

By embedding economic reasoning into everyday processes, decision-makers are better equipped to justify choices, communicate rationale to stakeholders, and navigate competing priorities in a more transparent and systematic way. Ultimately, this approach contributes to building organisational capability, enhancing accountability, and improving the resilience of decision-making in complex environments.

In practical terms, this applied approach is particularly valuable in environments where decisions must be made quickly and under pressure. By providing structured yet flexible frameworks, it enables decision-makers to move beyond ad hoc reasoning and instead adopt more consistent, transparent, and defensible approaches. This is especially relevant for institutions seeking to improve accountability, optimise resource use, and respond effectively to growing system complexity.

Why Accessibility Matters for Impact

Access to knowledge remains a critical barrier in many sectors, particularly in applied fields such as healthcare. Traditional publishing models often limit access through institutional subscriptions, reducing the reach of otherwise valuable insights.

By contrast, open-access resources allow knowledge to be shared more widely across institutions, professions, and geographical regions. This is particularly important in healthcare, where improved decision-making can have direct implications for system performance and population outcomes. Making applied tools widely available enhances not only academic visibility but also practical impact.

Decision-Making in a Time of Continuous Disruption

Healthcare systems are no longer operating in stable conditions. Instead, they are navigating overlapping disruptions including economic, technological, environmental, and demographic.

Evidence from broader economic research shows that such conditions require flexible and adaptive decision-making frameworks[9]. Traditional linear approaches are often insufficient when systems are characterised by interdependence and uncertainty. In this context, applied health economics provides a structured way to assess trade-offs, prioritise limited resources, and support transparent decision-making under pressure.

The challenge is not the absence of tools, but their integration into everyday practice. In many cases, existing frameworks remain underutilised because they are not embedded into routine workflows or decision processes. This creates a gap between what is theoretically possible and what is operationally implemented. Bridging this gap requires more than awareness; it demands practical mechanisms, institutional support, and a shift in mindset towards using structured approaches as a normal part of decision-making rather than an exception. Without this integration, even the most robust tools risk remaining peripheral rather than central to how decisions are made.

Strengthening Practice: Moving Forward

To enhance the role of applied health economics in practice, several actions can be considered:

• Embed economic thinking in professional education, particularly for clinicians and health managers to strengthen decision-making capability.
• Integrate economic evaluation into organisational processes Integrate economic evaluation into organisational processes, ensuring it is applied systematically rather than treating it as a specialised function.
• Promote open-access resources, ensuring equitable access to knowledge and tools, supporting broader uptake of evidence-informed approaches across settings .
• Encourage interdisciplinary collaboration, across health services linking economists, practitioners, and policymakers.

These steps can help normalise the use of structured frameworks in decision-making, improving both consistency and accountability.

Conclusion: From Knowledge to Impact

As healthcare systems continue to face complex and evolving challenges, the ability to make well-informed decisions becomes increasingly critical.

Applied health economics offers a pathway to strengthen decision-making, but only if it is accessible, practical, and aligned with real-world needs. By focusing on usability and dissemination, applied approaches can bridge the gap between knowledge and action.

Ultimately, the value of scholarship lies not only in its development, but in its application. Expanding access to applied tools can support better decisions, more efficient systems, and improved outcomes for communities.

Acknowledgement

The author declares no conflict of interest and does not have any financial disclosures.

To cite this article:

Chaiechi, T. (2026, June 17). Better Decisions for Complex Health Systems: Aligning Priorities Through Applied Health Economics. Scholarly Impact. International College of Management, Sydney. https://www.icms.edu.au/scholarly-impact/business-and-management/better-decisions-for-complex-health-systems-aligning-priorities-through-applied-health-economics/

References

Australian Institute of Health and Welfare (AIHW). (2025). Health expenditure Australia 2023–24. https://www.aihw.gov.au/reports/health-welfare-expenditure/health-expenditure

[1] Pennings, S. (2024, June 25). National Disability Insurance Scheme. In Budget Review 2024–25. Parliamentary Library, Parliament of Australia. https://www.aph.gov.au/About_Parliament/Parliamentary_departments/Parliamentary_Library/Research/Budget_Review/2024-25/NDIS

[2] Guenette, J.P., & Lacson, R.(2026). Clinical decision support: Point-closing gaps between evidence and practice to mitigate diagnostic error. American Journal of Roentgenology, 226(2), e2533115. https://doi.org/10.2214/AJR.25.33115

[3] Scott, I. (2009). Errors in clinical reasoning: Causes and remedial strategies. British Medical Journal, 338. https://doi.org/10.1136/bmj.b1860

[4] Hay, M.C., Weisner, T.S., Subramanian, S., Duan, N., Niedzinski, E.J. & Kravitz, R.L. (2008). Harnessing experience: Exploring the gap between evidence-based medicine and clinical practice. Journal of Evaluation in Clinical Practice, 14, 707-713. https://doi.org/10.1111/j.1365-2753.2008.01009.x

[5] Kim, S. Y. (2025). Evidence-based practice and evidence–practice gap: Status, challenges, and solutions. Journal of Evidence-Based Practice, 1(1), 1–6. https://doi.org/10.63528/jebp.2025.00001

[6] Chaiechi, T. (Ed.). (2020). Economic effects of natural disasters: Theoretical foundations, methods, and tools. Academic Press. https://doi.org/10.1016/C2018-0-01357-2

[7] Chaiechi, T. (2026). Applied health economics: Practical methods for evidence-based health decisions. James Cook University. https://doi.org/10.25120/nwpw-zc12

[8] Chaiechi, T. (2025). Cost-benefit analysis: A practical guide for decision-making. https://doi.org/10.25120/9d6c-kx2y

[9] Chaiechi, T. (Ed.). (2020). Economic effects of natural disasters: Theoretical foundations, methods, and tools. Academic Press. https://doi.org/10.1016/C2018-0-01357-2