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French hospital discharge database (PMSI) and bacterial resistance: Is coding adapted to hospital epidemiology?
L de Léotoing1, F Barbier2, A Dinh3
1HEVA, Lyon, France.
Objective:
A preliminary analysis of data consistency on different types of bacterial resistance by infection site and causative agents was conducted using the French hospital discharge database (French acronym PMSI) to assess the use of the database in a national cartography tool.
Material And Methods:
Hospital stays in medical, surgical, and obstetrical units were extracted from the 2014 PMSI database using the ICD-10 diagnosis codes. Bacterial infections, causative agents, and resistance corresponding to these stays were also identified.
Results:
Data from 1258462 patients, corresponding to a total of 1617893 stays, was extracted. Among these stays, 46% were associated with a bacteria code and 7% with a resistance code. Lower respiratory tract infections were the most frequent infections (32% of stays; pneumonia in 95% of cases), followed by genitourinary infections (26%), intra-abdominal infections and diarrhoeas (24%), and skin and soft tissue infections (15%). Inconsistencies were observed between the types of infection and associated bacteria and between bacteria and associated resistance. These inconsistencies are likely due to initial coding errors.
Conclusion:
The cartography of bacterial infections cannot be developed using the data of the current PMSI coding. These results underline the need to improve the coding of PMSI data for its use as a complementary tool of epidemiological surveillance of bacterial infections.
Insights
The French hospital discharge database (PMSI) shows inconsistencies in bacterial infection and resistance coding. Improvements are needed for accurate national epidemiological surveillance of bacterial infections.
Area of Science:
- Medical Informatics
- Epidemiology
- Infectious Diseases
Background:
- The French hospital discharge database (Programme de Médicalisation des Systèmes d'Information - PMSI) is a valuable source for health data.
- Assessing data consistency is crucial for utilizing such databases for national health surveillance tools.
Purpose of the Study:
- To analyze data consistency regarding bacterial resistance, infection sites, and causative agents within the PMSI database.
- To evaluate the suitability of the PMSI database for developing a national cartography tool for bacterial infections.
Main Methods:
- Extracted hospital stays from the 2014 PMSI database using ICD-10 codes.
- Identified bacterial infections, causative agents, and resistance data associated with these stays.
Main Results:
- Analysis of over 1.6 million hospital stays revealed that 46% had a bacteria code and 7% a resistance code.
- Lower respiratory tract infections were most common, followed by genitourinary and intra-abdominal infections.
- Significant inconsistencies were found between infection types, bacteria, and resistance codes, likely due to coding errors.
Conclusions:
- Current PMSI coding data is insufficient for developing a reliable bacterial infection cartography.
- Enhancements in PMSI data coding are essential for its effective use in epidemiological surveillance of bacterial infections.
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