Conectar
Adverse events are a major cause of patient harm in the hospitalised setting. Low-income and middle-income countries account for a disproportionate share of the global burden of adverse events. However, patient safety research is still centred around high-income countries and high-resource health systems. The methods and data produced from these efforts are ill-suited to low-income and middle-income systems due to the social and technical differences between these settings. We aim to use our pilot-tested, locally developed methodology to estimate the frequency and characteristics of adverse events in hospitalised patients in a lower-middle-income country to inform patient safety policies and initiatives.
This multi-centre study will employ a two-step chart review methodology to identify adverse events in a representative sample of patients admitted at five hospitals between 1 January 2019 and 31 December 2019. The first step will include assessing patient files against a list of triggers to detect adverse events and the second step will involve an in-depth review of the events to capture pertinent characteristics. The triggers have been adapted from validated tools used in other studies. The reviewing team will be trained on the use of research tools and operational definitions to ensure that data are collected uniformly. The main outcome of interest is the rate at which adverse events occur in hospitalised patients. Further analysis will look to identify and quantify associations between the main outcome of interest and a variety of variables such as patient age and gender using tests of independence and regression techniques.
This study protocol has been approved by the Ethics Review Committee at Aga Khan University (Reference number: 2023-6324-24566). The findings of this study will be published in a peer-reviewed journal and disseminated to the public through national and international conferences, workshops, websites and social media.
by Ayubo Kampango, Fatma Saleh, Peter Furu, Flemming Konradsen, Michael Alifrangis, Karin L. Schiøler, Christopher W. Weldon
There is an increasing awareness of the association between tourism activity and risks of emerging mosquito-borne diseases (MBDs) worldwide. In previous studies we showed that hotels in Zanzibar may play an important role in maintaining residual foci of mosquito vectors populations of public health concern. These findings indicated larval sources removal (LSR) interventions may have a significant negative impact on vector communities. However, a thorough analysis of the response vector species to potential LSM strategies must be evaluated prior to implementation of a large-scale area-wide control campaign. Here we propose a protocol for evaluation of the impact of LSR against mosquito vectors at hotel settings in Zanzibar. This protocol is set to determine the efficacy of LSR in a randomized control partial cross-over experimental design with four hotel compounds representing the unit of randomization for allocation of interventions. However, the protocol can be applied to evaluate the impact of LRS in more than four sites. Proposed interventions are active removal of disposed containers, and installation of water dispenser to replace single use discarded plastic water bottles, which were identified as the most important source of mosquitoes studied hotels. The ideal time for allocating intervention to the intervention arms the dry season, when the mosquito abundance is predictably lower. The possible impact of interventions on mosquito occurrence and abundance risks is then evaluated throughout subsequent rainy and dry seasons. If an appreciable reduction in mosquito abundance and occurrence risks is observed during the trial period, intervention could be extended to the control arm to determine whether any potential reduction of mosquito density is reproducible. A rigorous evaluation of the proposed LRS interventions will inspire large scale trials and provide support for evidence-based mosquito management at hotel facilities in Zanzibar and similar settings.
FreshRSS 