| Literature DB >> 31839925 |
Joachim P Sturmberg1,2, Johannes Bircher3.
Abstract
Rising healthcare costs are major concerns in most high-income countries. Yet, political measures to reduce costs have so far remained futile and have damaged the best interests of patients and citizen. We therefore explored the possibilities to analyze healthcare systems as a socially constructed complex adaptive system (CAS) and found that by their very nature such CAS tend not to respond as expected to top-down interventions. As CAS have emergent behaviors, the focus on their drivers - purpose, economy and behavioral norms - requires particular attention. First, the importance of understanding the purpose of health care as improvement of health and its experience has been emphasized by two recent complementary re-definitions of health and disease. The economic models underpinning today's healthcare - profit maximization - have shifted the focus away from its main purpose. Second, although economic considerations are important, they must serve and not dominate the provision of healthcare delivery. Third, expected health professionals' behavioral norms - to first consider the health and wellbeing of patients - have been codified in the universally accepted Declaration of Geneva 2017. Considering these three aspects it becomes clear that complex adaptive healthcare systems need mindful top-down/bottom-up leadership that supports the nature of innovation for health care driven by local needs. The systemic focus on improving people's health will then result in significant cost reductions. Copyright:Entities:
Keywords: Complex adaptive systems; Definition of health; Healthcare as complex adaptive system; Healthcare costs; Healthcare financing; Healthcare organization; Norms in healthcare; Philosophy of medicine; Sense or purpose of healthcare; System dynamics
Mesh:
Year: 2019 PMID: 31839925 PMCID: PMC6900806 DOI: 10.12688/f1000research.19414.1
Source DB: PubMed Journal: F1000Res ISSN: 2046-1402
Comparing high income country health system resourcing and achievements (Data Source: OECD - Health at a Glance 2017 [14]).
| OECD | US | UK | Switzerland | Australia | World | |
|---|---|---|---|---|---|---|
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| Distribution of healthcare spending 2014 Public/Private | - | 48%/52% | 81%/17% | 66%/34% | 67%/33% | 60%/40% |
| Per capita spending 2014 | $ 4,003 | $ 9,892 | $ 4,192 | $ 7,919 | $ 4,708 | $ 1,061 |
| Healthcare spending as % of GDP 2016 | 9.0% | 17.2% | 9.7% | 12.4% | 9.6% | |
| Annual per capita healthcare spending increase 2003-09 | 3.6% | 2.5% | 3.9% | 1.4% | 2.7% | |
| Annual per capita healthcare spending increase 2009-16 | 1.4% | 2.1% | 0.9% | 2.8% | 2.7% | |
| Doctors/1,000 population | 3.4 | 2.6 | 2.8 | 4.2 | 3.5 | |
| Nurse/1,000 population | 9.0 | 11.3 | 7.9 | 18.0 | 11.5 | |
| Beds/1,000 population | 4.7 | 2.8 | 2.6 | 4.6 | 3.8 | |
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| Life Expectancy M/F | 77.9/83.1 | 76.3/81.2 | 79.2/82.8 | 80.8/85.1 | 80.4/84.5 | |
| Life Expectancy at age 65 | 19.5 | 19.3 | 19.7 | 20.9 | 20.9 | |
| Ischaemic Mortality, age-standardised rate/100,000 | 112 | 113 | 98 | 78 | 85 | |
| Dementia Prevalence per 1,000 | 14.8 | 11.6 | 17.1 | 17.2 | 14.2 | |
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| Population covered by insurance | 97.9% | 90.9% | 100.0% | 100.0% | 100.0% | |
| Final household consumption to cover out of pocket expenses | 3.0% | 2.5% | 1.5% | 5.3% | 3.1% | |
| Consultations skipped due to cost - age-sex standardised rate
| 10.5% | 22.3% | 4.2% | 20.9% | 16.2% | |
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| Asthma and COPD hospital admission - Age-sex standardised
| 236 | 262 | 303 | 138 | 371 | |
| Antibiotics prescribed - defined daily dose per 1,000
| 20.6 | - | 20.1 | - | 23.4 | |
| Acute Myocardial Infarction mortality - Age-sex standardised
| 7.5 | 6.5 | 7.1 | 5.1 | 4.0 | |
| Obstetric trauma (instrument) - Crude rate per 100 vaginal
| 5.7 | 9.6 | 6.8 | 7.4 | 7.2 | |
| Foreign body left in during procedures/100,000 discharges
| 5.4 | 7.5 | 7.2 | 12.3 | 8.8 | |
| Post-operative DVT or PE following hip and knee
| 357/301 | 209/294 | 202/316 | 237/339 | 1,113/549 | |
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| Diabetes | 7.0% | 10.8% | 4.7% | 6.1% | 5.1% | |
| Obesity | 19.4% | 35.2% | 26.9% | 10.3% | 27.9% | |
| Smokers, age >15 | 18.4% | 11.4% | 16.1% | 20.4% | 12.4% | |
| Alcohol consumption, age >15 in litres | 9.0 | 8.8 | 9.5 | 9.5 | 9.7 | |
| Population eating fruit daily, age >15 | 56.6% | 57.9% | 62.6% | 61.5% | 95.0% | |
| Population eating vegetables daily, age >15 | 59.8% | 92.4% | 65.5% | 68.5% | 99.0% |
The table highlights the differences in health system performance amongst 4 selected OECD-countries with distinctively different health system structures. Performance outcomes arises from the unique dynamic behaviors of the system, i.e. outcomes cannot be attributed to one or two specific features of the system. It also means that direct comparison of outcomes between different systems is difficult as they depend on each system’s unique characteristics and dynamics.
Figure 1. A conceptual model of the implications of top-down versus bottom-up leadership on the function of health systems.
The effects of the top-down policy-driven approach on health care delivery are illustrated by the ever-decreasing size of the inner circles from one organizational level to the next where each level further constrains what the next lower level can achieve – the top-down leadership’s constraints minimize bottom-up feedback (left). The bottom-up approach is illustrated by dotted circles – to emphasize the open and adaptive nature of entities at each level- all focused on the system’s overall goal. Every higher-level circle emerges as a result of various interactions (arrows) at a lower level, resulting in the variance of characteristics and behaviors that depend on unique local circumstances. While each level shows variability in its components, each level component is the best adapted version of this level in its unique environment, and each does uniquely contribute to the achievement of the overall policy goals & settings – leadership minimizes constraints and encourages constant feedback across all levels of the system (right). Note that the complexity of a system arises from the feedback loops between top-down and bottom-up interactions across all the layers of the system. These two approaches are not mutually exclusive, rather – as the figure highlights – reflect the tension in leadership between trust (minimize constraints, maximize contextual adaptation) and distrust (maximize constraints, minimize variability). For a detailed discussion on causation in complex adaptive systems see Ellis [8]; for a discussion on complex adaptive organizations see Laloux [7].
Figure 2. General structure of a CAS.
Complex adaptive systems are open, i.e. they receive inputs from their external environment, and the interactions – especially feedback loop interactions – between its agents result in emergent outcomes that can be shared with external agents or other systems.
Figure 3. General structure of the healthcare system.
The driver of the health system – resulting from its agreed purpose, goals and values – align and limit the potential interactions of its agents in response to diverse inputs. These constraints “determine” the potential outcomes the health system can deliver, both in terms of health outcomes for the patients treated and the economic and resource costs associated with the service delivery.
Comparison of governance in traditional and complex organizations (adapted from Rouse [16])
| Traditional organizational system | Complex adaptive organizational system | |
|---|---|---|
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| Hierarchy | Heterarchy |
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| Management | Leadership |
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| Top-down organization | Bottom-up self-organization |
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| Command and control | Sense, purpose and norms |
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| Contractual | Personal commitment |
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| Efficiency | Problem-orientation |
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| Activities | Outcomes |