Transferring knowledge into practice: a multi-modal, multi-centre intervention for enhancing nurses' infection control competency in Bangladesh.

BACKGROUND: Nurses are considered as the key to infection prevention as they play a major role in treatment as well as taking care of patients. AIM: To assess the role of a multi-modal intervention (MMI) in improving nurses' competency and adherence to standard infection control practices in Bangladesh. METHODS: The study adopted a pretest-post-test intervention approach, in three different periods (from 2012 to 2017) in five hospitals (two public, two private, and one autonomous) in Bangladesh. Each study period was divided into three phases: pretest, MMI, and post-test. Data were collected on 642 nurses using direct observation method through a structured checklist. FINDINGS: After implementing the MMI, overall hand hygiene compliance significantly increased before patient contact (from 1.3% to 50.2%; P < 0.000) and after patient contact (from 2.8% to 59.6%; P < 0.000). Remarkable improvements were also achieved in adherence to use of gloves (from 14.6% to 57.6%; P < 0.000), maintaining sterility of equipment during aseptic techniques (from 34.9% to 86%; P < 0.000), biomedical waste segregation (from 1.8% to 81.3%; P < 0.000) and labelling of procedural sites (from 0% to 85.7%; P < 0.000). Moreover, needlestick injury rate notably decreased (from 6.2% to 0.6%; P < 0.000). CONCLUSION: MMI can play a vital role in improving nurses' compliance with the standard infection control practices. Such context-specific interventions, which are crucial for preventing healthcare-associated infections and for decreasing occupational hazards, should be replicated in resource-poor countries for achieving universal health coverage by 2030.

High accuracy multiple scatter modelling for 3D whole body PET.

A new technique for modelling multiple-order Compton scatter which uses the absolute probabilities relating the image space to the projection space in 3D whole body PET is presented. The details considered in this work give a valuable insight into the scatter problem, particularly for multiple scatter. Such modelling is advantageous for large attenuating media where scatter is a dominant component of the measured data, and where multiple scatter may dominate the total scatter depending on the energy threshold and object size. The model offers distinct features setting it apart from previous research: (1) specification of the scatter distribution for each voxel based on the transmission data, the physics of Compton scattering and the specification of a given PET system; (2) independence from the true activity distribution; (3) in principle no scaling or iterative process is required to find the distribution; (4) explicit multiple scatter modelling; (5) no scatter subtraction or addition to the forward model when included in the system matrix used with statistical image reconstruction methods; (6) adaptability to many different scatter compensation methods from simple and fast to more sophisticated and therefore slower methods; (7) accuracy equivalent to that of a Monte Carlo model. The scatter model has been validated using Monte Carlo simulation (SimSET).