Higher surgeon’s operation volume might reduce the risk of CABG surgical site infections (SSIs); however, the relationship might impact by definitions and categorization methods of operation volume and correct identification of SSIs. These are the findings of a population-based health insurance claims data in Taiwan led by Dr. Kuo-Piao Chung, of the National Taiwan University, with Dr. Tsung-Hsien Yu as first author. This study has been published online in PLoS ONE since June 8.
The relationship between service volume and outcome is a very interesting issue in the health care services research field. Although there are an enormous number of studies in the literature exploring the volume-outcome issue, the findings are not consistent. In the topic of healthcare-associated infection, the controversial findings can perhaps be attributed to two major issues. Firstly, the identification of infection cases might not have been accurate. Most studies analyzed the relationship between provider volumes and infection on the basis of claims data. Researchers usually have identified infection cases through International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) infection codes. However, several studies have indicated that the ICD-9-CM codes might be inappropriate for identifying such cases in claims data because of insufficient code list and coding bias. These problems might not only over- or under-estimate the infection cases, but also affect the validity of studies, especially in patient-level studies. Secondly, the definition and categorization methods of service or operation volumes are not consistent. In the past, some studies calculated the service/ operation volumes within the study period, while others calculated the service/ operation volumes before the study period (e.g. in the previous one year). Moreover, researchers usually categorized provider volumes using subjective methods.
For exploring the association between provider volume and healthcare-associated infection, Professor Kuo-Piao Chung, project assistant professor Dr. Tsung-Hsien Yu, and colleagues took CABG as an example, and used utilization of antibiotics (e.g. type, dose, second-line antibiotics), length of stay, and number of vessels obstructed etc., to develop alternative models for the identification of cases of CABG SSIs, based on the National Health Insurance claims data and healthcare-associated infection surveillance data from two medical centers in Taiwan, and compared the performance between these models and the ICD-9 CM codes. They found that using the classification and regression tree (CART) model can improve the accuracy SSI cases identification, especially in positive predictive value. After that, they applied this model and ICD-9 CM SSI codes in Taiwan National Health Insurance Research Database, and treated provider’s operation volume into three different way: (1) a continuous variable; (2) a categorical variable based on the quartile; and (3) a data-driven categorical variable based on k-means clustering algorithm. And two definitions of operation volumes, within the study period and in the previous one year before each CABG surgery were used.
They attempted answered whether the association exist between provider’s volume and CABG SSIs in Taiwan via different SSI case identification approaches, different definitions and classification methods of provider’s volume. The results showed surgeon volumes were more important than hospital volumes in exploring the relationship between CABG operation volumes and SSIs in Taiwan. However, the relationships were not robust. Definitions and categorization methods of operation volume and correct identification of SSIs are important issues for future research.