Within the OECD Health Care Quality Indicators (HCQI) Project up to 21 countries participated in calculations of six indicators on care for chronic conditions. Those so-called Health Promotion, Prevention and Primary Care Indicators originally had been introduced by the US Agency for Healthcare Research and Quality and rely on the principal diagnoses of an adult hospitalization stored in a hospital administrative database.
2007 age-sex standardized asthma admission rates varied considerably across the countries and ranged from 17 (Italy) to 120 (United States) admissions per 100.000 population (OECD mean: 51). It was concluded that asthma outpatient treatment was not optimal in countries reporting higher rates. Germany provided the third lowest asthma admission rate of 21 (Health at a Glance 2009 OECD Indicators. http://www.oecd.org/health/healthataglance).
As data collections from various countries can differ in, e.g. coding responsibility, incentives for coding, and implementation of coding guidelines, international variations cannot exclusively be explained by differences in health system performance. This study aimed to calculate asthma admission rates separately for all 16 Federal States of Germany, assuming national comparisons are not biased by these factors.
Methods:
Using the 2009 nationwide Diagnosis Related Groups statistic we calculated age-sex standardized asthma admission rates according to the OECD HCQI Data Collection Guidelines.
Results:
Among all adult hospitalizations (15 years or older) we found 14,399 admissions with a principal diagnosis code of asthma. Related to the corresponding population of 70,779,623, the crude rate is 20.34 admissions per 100.000. Age and sex standardized rate is 20.20 (95%Confidence-Interval: 19.86-20.54). Among the 16 Federal States of Germany age-standardized rates ranges from 7.62 in Berlin (95% CI: 6.17-9.08) to 20.26 in North Rhine-Westphalia (95% CI: 19.13-21.39) among men and from 16.15 in Berlin (95% CI: 14.07-18.23) to 36.70 in Bremen (95% CI: 29.89-43.98) among women, respectively.
Conclusions:
Prevention Quality Indicators calculated on national hospital administrative databases might be a useful tool to identify national variations of asthma admission rates reflecting areas with differences in outpatient care. Reasons for the differences found, e.g. a varying regional density of primary care providers or regional differences on asthma prevalence are in focus of further investigations.