Objective: development of an algorithm to estimate the prevalence of obstructive lung diseases (OLD) through record linkage of administrative health data sources in three Italian areas. Setting: AULSS 12 Veneziana, city of Torino, ASL10 Firenze. Participants: all residents in the three areas in the period 20020-2004 (N = 1. 944.471 on 30th June 2003). Main outcome: crude prevalence, standardized prevalence with 95% confidence intervals. Methods: the following data sources were used to identify OLD cases: hospital discharges (HD), health-tax exemptions HTE), death causes (DC) and drug prescriptions (DP) Allpatients diagnosed with (from HD) or dead because of chronic bronchitis, emphysema and asthma have been included in the analysis. We defined as a prevalent case a subject found in each year in at least one of the four data sources. We reported the absolute and relative contribution of each information system by area, age, gender and year of interest. We performed a sensitivity analysis using more restrictive criteria to identify prevalent cases (two or more DPs per year), Results: DP was the most relevant source in identifying cases (from 86 to 88%). The relative contribution of HD ranged from 3 to 5%. In 2003, standardized prevalence of OLD ranged from 5.35% in Firenze to 6.02% in Venezia. Venezia showed a higher prevalence in children aged 0-14years and a lower prevalence in older age groups (> 64 years) compared to other centers. Overall, the prevalence was higher among males. The use of more restrictive criteria in case identification substantially reduces the estimated prevalence, particularly in younger age-groups and, to a lesser extent, in older age-groups. Conclusions: the algorithm provides estimates with differences between centres. The validity of this algorithm (in terms of sensitivity and positive predictive value) needs to be evaluated through further ad hoc studies.

Obstructive lung disease prevalence estimated using a standard algorithm based on electronic health data in various areas of Italy

CANOVA, CRISTINA;SIMONATO, LORENZO
2008

Abstract

Objective: development of an algorithm to estimate the prevalence of obstructive lung diseases (OLD) through record linkage of administrative health data sources in three Italian areas. Setting: AULSS 12 Veneziana, city of Torino, ASL10 Firenze. Participants: all residents in the three areas in the period 20020-2004 (N = 1. 944.471 on 30th June 2003). Main outcome: crude prevalence, standardized prevalence with 95% confidence intervals. Methods: the following data sources were used to identify OLD cases: hospital discharges (HD), health-tax exemptions HTE), death causes (DC) and drug prescriptions (DP) Allpatients diagnosed with (from HD) or dead because of chronic bronchitis, emphysema and asthma have been included in the analysis. We defined as a prevalent case a subject found in each year in at least one of the four data sources. We reported the absolute and relative contribution of each information system by area, age, gender and year of interest. We performed a sensitivity analysis using more restrictive criteria to identify prevalent cases (two or more DPs per year), Results: DP was the most relevant source in identifying cases (from 86 to 88%). The relative contribution of HD ranged from 3 to 5%. In 2003, standardized prevalence of OLD ranged from 5.35% in Firenze to 6.02% in Venezia. Venezia showed a higher prevalence in children aged 0-14years and a lower prevalence in older age groups (> 64 years) compared to other centers. Overall, the prevalence was higher among males. The use of more restrictive criteria in case identification substantially reduces the estimated prevalence, particularly in younger age-groups and, to a lesser extent, in older age-groups. Conclusions: the algorithm provides estimates with differences between centres. The validity of this algorithm (in terms of sensitivity and positive predictive value) needs to be evaluated through further ad hoc studies.
2008
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2269711
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