Abstract

Introduction: The availability of specialized pulmonary medicine differs considerably between geographical areas in Switzerland. Currently there are 6 tertiary centers supplying the broadest spectrum of pulmonary diagnostics and therapy. The diagnostic diversity is a marker of medical quality in terms of precision medicine. We hypothesize that diagnostic diversity could be lower in more isolated regions. Our aim was to investigate the relationship between the diversity of pulmonary diagnoses and the distance between patients' area of residence and the closest tertiary lung center. Methods: We used a database provided by the Swiss Federal Office for Statistics offering a nation-wide coverage of all hospitalization cases between 2009 and 2015. For each hospitalization case, the data set included one main diagnosis as well as up to 50 additional diagnoses, coded using the International Classification of Disease version 10 (ICD-10-GM) codes. The data set also included patients' area of residence (705 medstat regions). The distance between each region and the closest tertiary lung center was obtained using the finaroute webtool (http://www.finaroute.ch). The Shannon diversity index was used to calculate the diversity of pulmonary diagnoses. The relationship between the diagnostic diversity and the distance to the closest tertiary lung center was investigated using linear regression. Results: There was a significant inverse association between the diagnostic diversity of pulmonary diagnoses and the distance between the area of residence and the closest tertiary lung center (Figure 1). For each 100 km increase of distance there was a decrease of 0.05 points in the Shannon diversity index (estimate: -5.2e-04, se=6.5e-05, p < 0.001). Conclusion: Regions located remotely from tertiary lung centers show lower diagnostic diversity which implicates a possible lower diagnostic precision leading to a higher rate of diagnostic errors. Remote regions should receive more medical support from specialists, e.g., through collaborative networks.

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