Comparing administrative and clinical data for central line associated blood stream infections in Pediatric Intensive Care Unit and Pediatric Cardiothoracic Intensive Care Unit
AbstractCentral line associated bloodstream infections (CLABSIs) are a frequent source of health complication for patients of all ages, including for patients in the pediatric intensive care unit (PICU) and Pediatric Cardiothoracic Intensive Care Unit (PCTU). Many hospitals, including the University of Michigan Health System, currently use the International Classification of Disease (ICD) coding system when coding for CLABSI. The purpose of this study was to determine the accuracy of coding for CLABSI infections with ICD-9CM codes in PICU and PCTU patients. A retrospective chart review was conducted for 75 PICU and PCTU patients with 90 events of hospital acquired central line infections at the University of Michigan Health System (from 2007-2011). The different variables examined in the chart review included the type of central line the patient had, the duration of the stay of the line, the type of organism infecting the patient, and the treatment the patient received. A review was conducted to assess if patients had received the proper ICD-9CM code for their hospital acquired infection. In addition, each patient chart was searched using Electronic Medical Record Search Engine to determine if any phrases that commonly referred to hospital acquired CLABSIs were present in their charts. Our review found that in most CLABSI cases the hospital’s administrative data diagnosis using ICD-9CM coding systems did not code for the CLABSI. Our results indicate a low sensitivity of 32% in the PICU and an even lower sensitivity of 12% in the PCTU. Using these results, we can conclude that the ICD-9CM coding system cannot be used for accurately defining hospital acquired CLABSIs in administrative data. With the new use of the ICD- 10CM coding system, further research is needed to assess the effects of the ICD-10CM coding system on the accuracy of administrative data.
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Copyright (c) 2016 Jory Bond, Mohamed Issa, Ali Nasrallah, Sheena Bahroloomi, Roland A. Blackwood
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