DESIGN/METHODOLOGY/APPROACH: Preinterventional study was conducted in one-month period of January 2019, followed by intervention period from February to March 2019. Postintervention study was conducted from April to July 2019. The CLABSI rates were compared between pre and postintervention periods. A multifaceted intervention bundle was implemented, which comprised (1) educational program for healthcare workers, (2) weekly audit and feedback and (3) implementation of central line bundle of care.
FINDINGS: There was a significant overall reduction of CLABSI rate between preintervention and postintervention period [incidence rate ratio (IRR) of 0.06 (95 percent CI, 0.01-0.33; P = 0.001)].
PRACTICAL IMPLICATIONS: CLABSI rates were reduced by a multifaceted intervention bundle, even in non-ICU and resource-limited setting. This includes a preinterventional study to identify the risk factors followed by a local adaption of the recommended care bundles. This study recommends resources-limited hospitals to design a strategy that is suitable for their own local setting to reduce CLABSI.
ORIGINALITY/VALUE: This study demonstrated the feasibility of a multifaceted intervention bundle that was locally adapted with an evidence-based approach to reduce CLABSI rate in non-ICU and resource-limited setting.
RESULTS AND DISCUSSION: Given the current lack of evidence on quality and safety improvements and on the cost-benefits associated with the introduction of eHealth applications, there should be a focus on implementing more mature technologies; it is also important that eHealth applications should be evaluated against a comprehensive and rigorous set of measures, ideally at all stages of their application life cycle.
METHODS: The agreement indices (or pass rates) for global and local gamma evaluation, maximum allowed dose difference (MADD) and divide and conquer (D&C) techniques were calculated using a selection of acceptance criteria for 429 patient-specific pretreatment quality assurance measurements. Regression analysis was used to quantify the similarity of behavior of each technique, to determine whether possible variations in sensitivity might be present.
RESULTS: The results demonstrated that the behavior of D&C gamma analysis and MADD box analysis differs from any other dose comparison techniques, whereas MADD gamma analysis exhibits similar performance to the standard global gamma analysis. Local gamma analysis had the least variation in behavior with criteria selection. Agreement indices calculated for 2%/2 mm and 2%/3 mm, and 3%/2 mm and 3%/3 mm were correlated for most comparison techniques.
CONCLUSION: Radiation oncology treatment centers looking to compare between different dose comparison techniques, criteria or lower dose thresholds may apply the results of this study to estimate the expected change in calculated agreement indices and possible variation in sensitivity to delivery dose errors.