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dc.contributor.authorMulema, Edrine
dc.date.accessioned2024-10-02T08:11:35Z
dc.date.available2024-10-02T08:11:35Z
dc.date.issued2024-09-30
dc.identifier.citationMulema. E. (2024). Optimizing detection and early management of acute kidney injury using trained caregivers on the infectious disease wards of Kiruddu National Referral Hospital. (Unpublished masters dissertation)en_US
dc.identifier.urihttp://hdl.handle.net/10570/13481
dc.descriptionA dissertation submitted to the Department of Medicine in partial fulfilment of the requirements for the Award of the Degree of Master of Medicine in Internal Medicine at Makerere University.en_US
dc.description.abstractBackground: Globally 13.3 million people develop AKI annually, with 85% in LMICs, largely due to infections and sepsis. AKI can be resolved in up to two-thirds of the patients with proper timely management. Current clinical practice rarely uses urine output (UO) monitoring since it is tedious. Due to limited human resources in low and middle-income countries (LMICs), informal active involvement of patient caregivers has proved beneficial. In this study, we used a quality improvement (QI) approach by training caregivers in UO monitoring to optimize the detection and early management of AKI through a task-shift model. Methods: A quasi-experimental pre-post intervention study with a six-month retrospective data review of randomly sampled 121 patient files was done for AKI diagnosis and related outcomes among patients who were admitted on the infectious disease (ID) wards of Kiruddu National Referral Hospital (KNRH) to generate pre-intervention data. The same data was prospectively collected in a review of 119 patient files on the same wards for eight weeks during the implementation of the QI interventions. The QI interventions were implemented in two phases: 1) clinical staff education on AKI detection and early management, and 2) training caregivers on UO monitoring respectively to generate trends in AKI diagnosis. We used Pearson’s chi-square test and Fisher’s exact test to determine trends in UO monitoring and the prevalence of diagnosed AKI during the pre-intervention phase and the two phases of QI intervention. Multilevel models using mixed effects logistic regression were used at a 5% significant level to estimate odds ratios [ORs] for hypothesized correlates of QI interventions. Results: In the pre-intervention phase, 60% of participants were female with a median age of 37 years (IQR: 28-47). During the QI interventions, 36% of participants were female with a median age of 38 years (IQR: 29-48). During the pre-intervention phase, AKI was diagnosed in 12% of cases without UO monitoring. In the first phase of the QI intervention, UO monitoring increased to 12%, and AKI diagnoses rose to 25%. In the second phase, UO monitoring reached 62%, with AKI diagnoses at 31%. Overall, during the QI interventions, UO monitoring increased to 40%, and AKI detection rose to 29%, with 91% of those diagnosed receiving management. Mortality significantly decreased from 41% at baseline to 15% (P < 0.001). Conclusion: Routine clinical practice has less AKI detection.Trained caregivers in UO monitoring, using a multicomponent QI approach, optimized AKI detection and early management on KNRH's ID wards.The QI project was associated with a reduction in mortality on the ID wards of KNRH.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectAcute kidney injuryen_US
dc.subjectTrained caregiversen_US
dc.subjectEarly managementen_US
dc.subjectOptimizing detectionen_US
dc.subjectInfectious disease wardsen_US
dc.subjectKiruddu National Referral Hospitalen_US
dc.titleOptimizing detection and early management of acute kidney injury using trained caregivers on the infectious disease wards of Kiruddu National Referral Hospitalen_US
dc.typeThesisen_US


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