A model to forecast central-line-associated bloodstream infection rates in acute care hospital units
Creators: name: Gadala, Avinash
Publisher: name: No Publisher Supplied
Year: 2021

description: Background:Approximately 250,000 CLABSIs occur in the U.S. each year, 80,000 in intensive care units, these infections are associated with over 28,000 deaths each year and cost over $2 billion1. CLABSI increases patient morbidity and mortality as well as healthcare costs2,3. It is estimated that almost 300 million catheters are used each year; nearly 3 million of these are central venous catheters4.In the United States, 15 million occur in intensive care units (ICUs) each year. Bundles of recommended practices for safely inserting and maintaining an intravenous catheter are routinely implemented in the intensive care setting. Other factors, such as safety culture, employee engagement, morale, patient acuity, and staff training/knowledge likely affect the rates of adherence to evidence-based process measures and therefore a hospital areas CLABSI rate.Objective:The aim of this study is to identify the predictors and establish the correlation between the performances on evidence based process measures, Safety Culture, Knowledge, Training and Experience in a hospital unit and build a model to predict the level of risk hospital units have for possible occurrence of Central Line Associated Blood Stream Infections (CLABSI) in the acute care hospital this is to facility the intervene based upon available data. Development and validation of this type of forecasting model would allow proactive interventions to support infection prevention practices and avert patient harm from CLABSI.Design &amp; Setting:A single-center, retrospective cohort study of patients admitted to acute care hospital and have a central Line and are identified for Central line Associated Blood Stream Hospital Acquired Condition – at The Johns Hopkins Hospital urban, academic, 900+ bed hospital from June 1, 2016 until June 30, 2020.The research is divided into three parts. First part, Identify the suitable predictors, Second is data analysis of the patient population at risk in association to the infected patients, and the third part is to build model to predict the level of risk hospital units have for possible occurrence of Central Line Associated Blood Stream Infections (CLABSI).Limitation:• The study was done in a single center with 900+ bed urban hospital.• Missing documentation in the electronic medical records.• Research is conducted in single academic hospital.• Countries of low and middle income generally do not have adequate resources to conduct surveillance of HAIs.• Available data on the global impact of HAIs have been more limited, particularly in many resource-constrained areas.Conclusion:The research is first to address the comparison of the incidence of CLABSI with the Clinical employees Hiring or turnover rates. This study has demonstrated that Hospital risk factors can forecast if a hospital area or a unit can meet the national thresholds. One hypothesis to accurately stratify level of risk in the hospital area is negated based on the limited availability of predictors. CLABSIs are highly disruptive and impacts health systems financially and reputationally and patients financially and clinically. Also, Research has found that there are some of key important predictors that are not available in the medical records or in current electronic system for easy consumption for data analysis and forecasting. This requires alternate measure to collect the information. As a part of the project, there were additional data collection tools and real time feedback data dashboards are created to collect information required for the accurate prediction of the incidence of CLABSIs as discussed in the methodology.