General practice as a complex system: a novel analysis of consultation data.

Area of Science:

• Complex Systems Science
• Health Services Research
• General Practice

Background:

• Complex systems exhibit robustness and self-organization due to interacting components, often displaying power law distributions.
• While health systems are theorized as complex, quantitative evidence has been limited.
• This study investigates health system complexity through primary care consultation patterns.

Purpose of the Study:

• To empirically test if primary care consultation patterns align with power law distributions, a hallmark of complex systems.
• To provide quantitative evidence for the complexity of general practice.

Main Methods:

• Analysis of 142,050 non-pathological back pain episodes from New Zealand national data.
• Calculation of consultation duration and frequency distributions per illness episode.
• Secondary analysis of UK general practice data on consultation rates for 44,000 patients.

Main Results:

• Consultation numbers per back pain episode showed an excellent fit to a power law (r2 = 0.96) in New Zealand data.
• Subgroup analyses also demonstrated strong power law fits (r2 = 0.90-0.99).
• UK data revealed suggestive power law distributions for consultation rates (r2 = 0.88-0.93).

Conclusions:

• General practice consultation patterns exhibit measurable characteristics of a complex system.
• The consistent power law distribution across populations indicates system-wide properties.
• Interventions for managing consultations should consider the entire patient system, not just individuals.