Diagnostic diversity - an indicator of institutional and regional healthcare quality

Martin Brutsche, Frank Rassouli, Harald Gallion, Sanjay Kalra, Veronique Lee Roger, Florent Baty

Research output: Contribution to journalArticle

Abstract

AIM: Our aim was to estimate the diagnostic performance of institutions and healthcare regions from a nationwide hospitalisation database. METHODS: The Shannon diversity index was used as an indicator of diagnostic performance based on the International Classification of Disease, 10th revision, German Modification (ICD-10-GM codes). The dataset included a total of 9,325,326 hospitalisation cases from 2009 to 2015 and was provided by the Swiss Federal Office for Statistics. A total of 16,435 diagnostic items from the ICD-10-GM codes were taken as the basis for the calculation of the diagnostic diversity index (DDI). Numerical simulations were performed to evaluate the effect of misdiagnoses in the DDI. We arbitrarily defined the minimum clinically important difference (MCID) as 10% misdiagnoses. The R statistical software was used for all analyses. RESULTS: Diagnostic performance of institutions and healthcare regions as measured by the DDI were strongly associated with caseload and number of inhabitants, respectively. A caseload of >7217 hospitalisations per year for institutions and a population size >363,522 for healthcare regions were indicators of an acceptable diagnostic performance. Among hospitals, there was notable heterogeneity of diagnostic diversity, which was strongly associated with caseload. Application of misdiagnosis-thresholds within each ICD-10-GM category allowed classification of hospitals in four distinct groups: high-volume hospitals with an all-over comprehensive diagnostic performance; high- to mid-volume hospitals with extensive to relevant basic diagnostic performance in most categories; low-volume specialised hospitals with a high diagnostic performance in a single category; and low-volume hospitals with inadequate diagnostic performance in all categories. The diagnostic diversity observed in the 26 Swiss healthcare regions showed relevant heterogeneity, an association with ICD-10-GM code utilisation, and was strongly associated with the size of the healthcare region. The limited diagnostic performance in small healthcare regions was partially, but not fully, compensated for by consumption of health services outside of their own healthcare region. CONCLUSION: Calculation of the DDI from ICD-10 codes is easy and complements the information derived from other quality indicators as it sheds a light on the fitness of the institutionalised interplay between primary and specialised medical inpatient care. &nbsp.

Original languageEnglish (US)
Pages (from-to)w14691
JournalSwiss Medical Weekly
Volume148
StatePublished - Dec 3 2018

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Quality of Health Care
International Classification of Diseases
Delivery of Health Care
Low-Volume Hospitals
Diagnostic Errors
Hospitalization
High-Volume Hospitals
Population Density
Health Services
Inpatients
Software
Databases

ASJC Scopus subject areas

  • Medicine(all)

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Diagnostic diversity - an indicator of institutional and regional healthcare quality. / Brutsche, Martin; Rassouli, Frank; Gallion, Harald; Kalra, Sanjay; Roger, Veronique Lee; Baty, Florent.

In: Swiss Medical Weekly, Vol. 148, 03.12.2018, p. w14691.

Research output: Contribution to journalArticle

Brutsche, Martin ; Rassouli, Frank ; Gallion, Harald ; Kalra, Sanjay ; Roger, Veronique Lee ; Baty, Florent. / Diagnostic diversity - an indicator of institutional and regional healthcare quality. In: Swiss Medical Weekly. 2018 ; Vol. 148. pp. w14691.
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abstract = "AIM: Our aim was to estimate the diagnostic performance of institutions and healthcare regions from a nationwide hospitalisation database. METHODS: The Shannon diversity index was used as an indicator of diagnostic performance based on the International Classification of Disease, 10th revision, German Modification (ICD-10-GM codes). The dataset included a total of 9,325,326 hospitalisation cases from 2009 to 2015 and was provided by the Swiss Federal Office for Statistics. A total of 16,435 diagnostic items from the ICD-10-GM codes were taken as the basis for the calculation of the diagnostic diversity index (DDI). Numerical simulations were performed to evaluate the effect of misdiagnoses in the DDI. We arbitrarily defined the minimum clinically important difference (MCID) as 10{\%} misdiagnoses. The R statistical software was used for all analyses. RESULTS: Diagnostic performance of institutions and healthcare regions as measured by the DDI were strongly associated with caseload and number of inhabitants, respectively. A caseload of >7217 hospitalisations per year for institutions and a population size >363,522 for healthcare regions were indicators of an acceptable diagnostic performance. Among hospitals, there was notable heterogeneity of diagnostic diversity, which was strongly associated with caseload. Application of misdiagnosis-thresholds within each ICD-10-GM category allowed classification of hospitals in four distinct groups: high-volume hospitals with an all-over comprehensive diagnostic performance; high- to mid-volume hospitals with extensive to relevant basic diagnostic performance in most categories; low-volume specialised hospitals with a high diagnostic performance in a single category; and low-volume hospitals with inadequate diagnostic performance in all categories. The diagnostic diversity observed in the 26 Swiss healthcare regions showed relevant heterogeneity, an association with ICD-10-GM code utilisation, and was strongly associated with the size of the healthcare region. The limited diagnostic performance in small healthcare regions was partially, but not fully, compensated for by consumption of health services outside of their own healthcare region. CONCLUSION: Calculation of the DDI from ICD-10 codes is easy and complements the information derived from other quality indicators as it sheds a light on the fitness of the institutionalised interplay between primary and specialised medical inpatient care. &nbsp.",
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