{'fraction_non_alphanumeric': 0.025941939468807906, 'fraction_numerical': 0.007823759522338892, 'mean_word_length': 5.434437086092715, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Moving to a More Level Playing Field: The Need for Risk Adjustment of Publicly Reported Hospital CLABSI Performance

(See the article by Jackson et al on pages 1019–1024.) Central vascular catheters (CVCs) are commonly used in hospitalized patients, and infections of these devices, known as central line-associated bloodstream infections (CLABSIs), can cause significant morbidity and mortality. A variety of factors can lead to a patient’s increased risk for the development of a CLABSI, including procedural and device-related factors (eg, anatomic placement, CVC type, use of sterile and aseptic insertion and maintenance practices, and CVC duration). In 2006, Pronovost illustrated that much of this risk can be mitigated by following standardized bundles of evidenced-based practices folded into a culture of accountability and safety. In 2011, the Centers for Medicare and Medicaid Services (CMS) began to require acute-care facilities to report performance on key healthcare-associated infection (HAI) outcome metrics, with CLABSIs within intensive care units (ICUs) the first HAI designated for reporting. This was soon followed by other important HAIs, including CLABSIs in units outside of ICUs. Initially, hospitals were only required to report performance, but over the next few years, facility-specific reimbursement was tied to the specific level of performance, with those hospitals with the lowest infection rates receiving the highest monetary incentives. Publicly reported infection performance is defined using surveillance definitions from the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) and is expressed as a standardized infection ratio (SIR) of the observed number of infection cases over the number of predicted events. Historically for CLABSI, pooled mean infection rates (adjusted by unit type) and the total number of device days were used to calculate the predicted number of events. In 2017, new CLABSI logistic regression risk models were introduced, but these include weighting only for specific unit and facility type, bed size, and medical school affiliation to determine the predicted number of events. Patient-specific risk factors are not included in the risk models currently in use. The impact of public reporting of HAI performance has been substantial and largely positive, likely contributing to many important changes surrounding infection prevention, including increased resources, improved awareness among frontline healthcare personnel of the impact and potential preventability of HAIs, and accountability of operational leaders for reduction in HAI-related patient harm. Financial incentives and penalties related to this performance are common and carry increasing consequences. Most importantly, rates of several HAIs have declined, with a number of facilities reporting sustained reductions and even elimination of these events. Despite these important gains, the current reportingmetrics do not fully adjust for important risk differences, resulting in an uneven playing field for interfacility comparisons. One could argue that many, if not all, of the “low” and “middle-hanging fruits” pertaining to CLABSI prevention have been culled. As such, we may be approaching a floor, where variations in performance no longer reflect largely preventable events but instead reflect variations in immitigable patient risk factors between facilities. In this context, we examine the important study by Jackson et al that investigates the effect of adding patient comorbidities to the current NHSN CLABSI risk model. Using ICU-related CLABSI data from 22 hospitals, patient case-mix variables as determined by International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes were included in a modified risk model that was then compared to one similar to the NHSN risk model (pre-2017). The selected comorbid conditions were based on earlier work that used expert opinion to classify the 35 comorbid conditions in the Charlson and Elixhauser comorbidity indices. For bothmodels, predicted probabilities for CLABSI development were estimated and used to generate each model’s C statistic, a measure of predictive ability. They also performed an assessment of the change in risk adjusted rates and facility ranking in the cohort with the use of the enhanced model. The proportion of patients in the study who acquired a CLABSI was a strikingly low, 0.2%. The case-mix model had a significantly better predictability for CLABSI than the ICU-type only model. Even among this small cohort, hospital rankings were impacted with the use of the case-mix enhanced model. Overall, 10 hospitals changed rank, some with relatively pronounced changes in the calculated SIR (between 11% and 16% among those moving more than 1 ranking spot).