Quantification of the resilience of primary care networks by stress testing the health care system.

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ID: 75703
2019
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Ranked #91 of 292 articles by views in Proceedings of the National Academy of Sciences of the United States of America

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Abstract
There are practically no quantitative tools for understanding how much stress a health care system can absorb before it loses its ability to provide care. We propose to measure the resilience of health care systems with respect to changes in the density of primary care providers. We develop a computational model on a 1-to-1 scale for a countrywide primary care sector based on patient-sharing networks. Nodes represent all primary care providers in a country; links indicate patient flows between them. The removal of providers could cause a cascade of patient displacements, as patients have to find alternative providers. The model is calibrated with nationwide data from Austria that includes almost all primary care contacts over 2 y. We assign 2 properties to every provider: the "CareRank" measures the average number of displacements caused by a provider's removal (systemic risk) as well as the fraction of patients a provider can absorb when others default (systemic benefit). Below a critical number of providers, large-scale cascades of patient displacements occur, and no more providers can be found in a given region. We quantify regional resilience as the maximum fraction of providers that can be removed before cascading events prevent coverage for all patients within a district. We find considerable regional heterogeneity in the critical transition point from resilient to nonresilient behavior. We demonstrate that health care resilience cannot be quantified by physician density alone but must take into account how networked systems respond and restructure in response to shocks. The approach can identify systemically relevant providers.
Reference Key
lo-sardo2019quantificationproceedings Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lo Sardo, Donald Ruggiero;Thurner, Stefan;Sorger, Johannes;Duftschmid, Georg;Endel, Gottfried;Klimek, Peter;
Journal Proceedings of the National Academy of Sciences of the United States of America
Year 2019
DOI
10.1073/pnas.1904826116
URL
Keywords
quality of care robustness coevolving networks dynamics of collapse patient-sharing network

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