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Variation of colorectal, breast and prostate cancer screening activity in Switzerland: Influence of insurance, policy and guidelines

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  • Agne Ulyte
  • Wenjia Wei
  • Holger Dressel
  • Oliver Gruebner
  • Viktor von Wyl
  • Caroline Bähler
  • Eva Blozik
  • Beat Brüngger
  • Matthias Schwenkglenks

Abstract

Variation in utilization of healthcare services is influenced by patient, provider and healthcare system characteristics. It could also be related to the evidence supporting their use, as reflected in the availability and strength of recommendations in clinical guidelines. In this study, we analyzed the geographic variation of colorectal, breast and prostate cancer screening utilization in Switzerland and the influence of available guidelines and different modifiers of access. Colonoscopy, mammography and prostate specific antigen (PSA) testing use in eligible population in 2014 was assessed with administrative claims data. We ran a multilevel multivariable logistic regression model and calculated Moran’s I and regional level median odds ratio (MOR) statistics to explore residual geographic variation. In total, an estimated 8.1% of eligible persons received colonoscopy, 22.3% mammography and 31.3% PSA testing. Low deductibles, supplementary health insurance and enrollment in a managed care plan were associated with higher screening utilization. Cantonal breast cancer screening programs were also associated with higher utilization. Spatial clustering was observed in the raw regional utilization of all services, but only for prostate cancer screening in regional residuals of the multilevel model. MOR was highest for prostate cancer screening (1.24) and lowest for colorectal cancer screening (1.16). The reasons for the variation of the prostate cancer screening utilization, not recommended routinely without explicit shared decision-making, could be further investigated by adding provider characteristics and patient preference information. This first cross-comparison of different cancer screening patterns indicates that the strength of recommendations, mediated by specific health policies facilitating screening, may indeed contribute to variation.

Suggested Citation

  • Agne Ulyte & Wenjia Wei & Holger Dressel & Oliver Gruebner & Viktor von Wyl & Caroline Bähler & Eva Blozik & Beat Brüngger & Matthias Schwenkglenks, 2020. "Variation of colorectal, breast and prostate cancer screening activity in Switzerland: Influence of insurance, policy and guidelines," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
    • Handle: RePEc:plo:pone00:0231409
    DOI: 10.1371/journal.pone.0231409
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    1. Klaus Larsen & Jørgen Holm Petersen & Esben Budtz-Jørgensen & Lars Endahl, 2000. "Interpreting Parameters in the Logistic Regression Model with Random Effects," Biometrics, The International Biometric Society, vol. 56(3), pages 909-914, September.
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