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Background: In diabetes care and management guidelines, shared decision-making (SDM) implementation is explicitly recommended to help patients and health care providers to make informed shared decisions that enable informed choices and the selection of treatments. Despite widespread calls for SDM to be embedded in health care, there is little evidence to support SDM in the management and care of diabetes. It is still not commonly utilized in routine care settings because its effects remain poorly understood. Hence, the current systematic review and meta-analysis aimed to evaluate the effectiveness of SDM for glycaemic control among type 2 diabetes adult patients. Methods: Literature sources were searched in MEDLINE, PubMed, Cochrane library and HINARI bibliographic databases and Google Scholar. When these records were searched and reviewed, the PICO criteria (P: population, I: intervention, C: comparator, and O: outcome) were applied. The extracted data was exported to RevMan software version 5.4 and STATA 17 for further analysis. The mean differences (MD) of glycated hemoglobin (HbA1c) were pooled using a random effect model (REM), and sub-group analysis were performed to evaluate the effect size differences across the duration of the follow-up period, modes of intervention, and baseline glycated hemoglobin level of patient groups. The sensitivity analysis was performed using a leave-one-out meta-analysis to quantify the impact of each study on the overall effect size in mean difference HbA1c%. Finally, the statistically significant MD of HbA1c% between the intervention groups engaged in SDM and control groups received usual care was declared at P ˂0.05, using a 95% confidence interval (CI). Results: In the database search, 425 records were retrieved, with only 17 RCT studies fulfilling the inclusion criteria and were included in the meta-analysis. A total of 5416 subjects were included, out of which 2782(51.4%) were included in trial arms receiving SDM and 2634(48.6%) were included in usual diabetes care. The Higgins (I2) test statistics were calculated to be 59.1%, P = 0.002, indicating statistically significant heterogeneity was observed among the included studies, and REM was used as a remedial to estimate the pooled MD of HbA1c% level between patients who participated in SDM and received usual care. As a result, the pooled MD showed that the SDM significantly lowered HbA1c by 0.14% compared to the usual care (95% CI = [-0.26, -0.02], P = 0.02). SDM significantly decreased the level of HbA1c by 0.14% (95% CI = -0.28, -0.01, P = 0.00) when shared decisions were made in person or face-to-face at the point of care, but there was no statistically significant reduction in HbA1c levels when patients were engaged in online SDM. In patients with poorly controlled glycaemic level (≥ 8%), SDM significantly reduced level of HbA1c by 0.13%, 95% CI = [-0.29, -0.03], P = 0.00. However, significant reduction in HbA1c was not observed in patients with ˂ 8%, HbA1c baseline level. Conclusions: Overall, statistically significant reduction of glycated hemoglobin level was observed among T2DM adult patients who participated in shared decision-making compared to those patients who received diabetes usual care that could lead to improved long-term health outcomes, reducing the risk of diabetes-related complications. Therefore, we strongly suggest that health care providers and policy-makers should integrate SDM into diabetes health care and management, and further study should focus on the level of patients' empowerment, health literacy, and standardization of decision supporting tools to evaluate the effectiveness of SDM in diabetes patients. [ABSTRACT FROM AUTHOR]

Introduction: Discharge of excreta to the environment lead to surface and groundwater contamination and human exposure to disease-causing micro-organisms. There is limitation of evidences regarding the latrine utilization among community-led total sanitation and hygiene implemented and non-implemented districts of the East Wollega Zone. Hence, this study aimed to determine the magnitude and associated factors of latrine utilization among households in community-led total sanitation and hygiene implemented and non-implemented Districts in East Wollega Zone, Western Ethiopia. Methods: A cross-sectional study was conducted. A Multi-stage sampling technique was applied to select the 461 households. Data were collected using interviews and observations guided by a pre-structured questionnaire. Data were entered using Epi Data and exported to SPSS software version 25 for data recording, cleaning, and statistical analysis. Bivariable logistic regression was run to identify the candidate variables at p-value <0.25. Variables that had associations with latrine utilization in the bi-variable analysis were entered together into multivariable logistic regression. An Adjusted odds ratio with a 95% confidence interval was calculated and P-value< 0.05 was used to declare a statistically significant association. Result: The overall prevalence of latrine utilization was found to be 52.7% (95%CI:48%, 57.3%). Religion (AOR = 0.149;95%CI:0.044,0.506), education (AOR = 3.861;95%CI:1.642,9.077), occupation, absence of children <5 years (AOR = 4.724;95%CI:2.313,9.648), toilet cleaning (AOR = 10.662;95%CI:5.571,20.403), frequency of latrine construction (AOR = 6.441;95%CI:2.203,18.826), maintenance need (AOR = 6.446; 95%CI:3.023,13.744), distance from health institution (AOR = 0.987; 95%CI:0.978, 0.996), distance from kebele office (AOR = 6.478; 95%CI:2.137,19.635), and latrine distance from dwelling (AOR = 11.656; 95%CI:2.108, 64.44) were the factors associated with latrine use. Conclusion: The latrine utilization in this study is low as compared to other studies. Religion, education, occupation, absence of children <5 years, toilet cleaning, frequency of latrine construction, maintenance need of the toilet, distance from health institution, distance from kebele, and latrine distance from dwelling are the associated factors of latrine utilization. Both households and health workers have to work together to improve latrine utilization and the safe disposal of children's feces. [ABSTRACT FROM AUTHOR]

Background: Health care disparities (HCD) occur across a broad range of dimensions and achieving equity in health care is a strenuous task. To overcome the disparities, countries worldwide have started implementing varies policies. HCD remains a challenge in the health care system of Ethiopia. Hence, the study aimed to estimate the disparities in health care utilization (HCU) among households. Methods: A community-based cross-sectional study was conducted from February 01 to April 30, 2022, among households in Gida Ayana District, Ethiopia. A single population proportion formula was used to determine the 393sample size, and participants were selected using systematic sampling. Data was entered into Epi-data 4.6 and exported to SPSS 25 for analysis. Descriptive analysis and binary and multivariable logistic regressions were performed. Results: Of the 356 households that participated in the study, 321 (90.2%) of them reported at least one member of their family perceived morbidity in the last six months. The overall level of HCU determined was 207(64.5%), 95% confidence interval (CI),59.0-69.7%. Urban residents (AOR = 3.68, 95% CI = 1.94–6.97), attending secondary school and above (AOR = 2.79, CI = 1.27–5.98), rich (AOR = 2.47, CI = 1.03–5.92), small families (AOR = 2.83, CI = 1.26–6.55), and insured (AOR = 4.27, CI = 2.36–7.71) significantly contributed to HCD. Conclusions: Households' overall level of HCU for perceived morbidity was moderate. However, significant disparities were observed in HCU across place of residence, wealth status, level of education, family size, and health insurance. Hence, strengthening the strategy of financial protection by implementing health insurance that focuses on the socio-demographic and economic status of households is recommended to reduce the disparities. [ABSTRACT FROM AUTHOR]

Background: The significance of effectively using medical equipment has received widespread public attention. Due to its complex effects on healthcare costs and quality, the relationship between hospital features and medical equipment consumption has drawn increased attention. Therefore, the study aimed to evaluate the efficiency of medical equipment utilization and its associated factors. Methods: The study was conducted at public referral hospitals in East Wollega, Oromia Regional National State, Ethiopia, in 2021. A cross-sectional study design was mixed with observation and document review. The study included approximately 192 pieces of equipment. Descriptive statistics and Pearson Chi-square (χ2) were used to identify associations between each independent and dependent variable at p< 0.05 to declare level of significance. Results: Using 95% confidence interval (CI), the level of utilization coefficient was estimated to be 0.49 (0.44– 0.55). As a result, 111 pieces of equipment (57.8%) were used efficiently, while 81 (42.2%) were underutilized. The form in which the hospitals received the equipment (χ2=7.7.2; P=0.005), regular availability (χ2=19.30; P=0.00), equipment breakdown (χ2=11.57; P=0.001), the availability of trained staffs operating the equipment (χ2=26.14; P=0.00), performing preventive maintenance (χ2=91.54; P=0.00), the availability of spare parts (χ2=32.36; P=0.00), and the availability of accessories (χ2=43.91; P=0.00) were statistically significant factors affecting the medical equipment utilization. Conclusion: On average, the utilization coefficient of medical equipment in the study hospitals was low compared to other study findings, which indicated that 2 out of 5 pieces of medical equipment were under-utilized, which could be significantly affected by the form in which the hospital received the equipment, its regular availability, equipment breakdown, availability of trained staff operating the equipment, performing preventive maintenance, and availability of adequate spare parts and accessories. Every hospital should develop an appropriate strategic framework to manage and utilize the available medical diagnostic equipment based on its level and demand. [ABSTRACT FROM AUTHOR]

Background: Ethiopia has received 2.2 million doses of COVID-19 vaccine from the COVID-19 Vaccines Global Access (COVAX) facility and planned to vaccinate 20% of its population by the end of 2021. However, evidence on the current uptake of the vaccine in our country is scanty. Therefore, this study aimed to assess COVID-19 vaccine uptake and associated factors among health professionals in Ethiopia. Methods: A national online cross-sectional E-survey was conducted on COVID-19 vaccine Uptake and associated factors among health professionals in Ethiopia from June 1 to 30, 2021. A semi-structured questionnaire was created on Google forms and disseminated online. The snowball sampling technique through the authors' network with Ethiopian residents on the popular social media like Facebook, telegram, and email was used. Descriptive statistics were performed. Multivariable logistic regression analysis was performed using Statistical Package for Social Sciences version 25, and all variables with P-value < 0.05 and adjusted odds ratio at 95% CI were used to declare the predictors of the outcome variable. Results: A total of 522 health professionals participated in the survey, of which about 324 (62.1%) of them were vaccinated with any of the COVID-19 vaccines at least once. The study indicated that COVID-19 vaccine uptake was associated with age range from 35 to 44 years [AOR = 12.97, 95% CI: 2.36– 71.21], age beyond 45 years [AOR = 18.95, 95% CI = 2.04– 36.29], being male [AOR = 2.91, 95% CI = 1.05,8.09], being only an academician [AOR = 0.23, 95% CI: 0.10– 0.49], academicians working in University hospitals [AOR = 0.19, 95% CI: 0.05– 0.83], perceiving their family as healthy [AOR = 4.40, 95% CI: 2.21– 8.75], no history of receiving other vaccine before as an adult [AOR = 4.07, 95% CI: 2.07– 8.01] and no history of contact with confirmed COVID-19 patients or clients [AOR = 0.42, 95% CI: 0.20– 0.86]. Conclusion: The study found that COVID-19 vaccine uptake among health professionals was low. This was not sufficient to achieve herd immunity as at least nine out of ten health professionals are required for herd immunity. Ages, sex, place of work, perceived family health status, previous experience of receiving a vaccine as an adult and history of contact with COVID-19 clients or patients were the factors that influence the vaccine uptake among health professionals in Ethiopia. Hence, decision makers and health managers should consider instituting mandatory vaccination for health professionals and design strategies for the provision of the vaccine. [ABSTRACT FROM AUTHOR]

Objectives: Breast cancer is the leading cause of cancer morbidity and mortality among women. Still, there is a paucity of studies to know the magnitude of the problem in Ethiopia. Hence, this review was intended to pool the prevalence and identify the determinants of breast cancer in Ethiopia., Design: A systematic review and meta-analysis was conducted., Data Sources: Databases like PubMed/MEDLINE, HINARI, Science Direct, and Google Scholar, as well as websites of organisationsI organizations,rewere searched between 25 February and 6 March 2023., Eligibility Criteria: All observational studies in Ethiopia that reported either the magnitude and/or determinants of breast cancer regardless of publication status were included., Data Extraction and Synthesis: Two authors independently assessed and extracted the data. The Joanna Briggs Institute meta-analysis of statistics assessment and review instrument quality appraisal tool was used to assess the quality of the articles. Effect estimates were done by using the random-effects model. The meta-analysis results were displayed by using forest plots., Results: Seventeen articles were reviewed with 24 435 total participants. The pooled proportion of breast cancer morbidity among patients with cancer was 20. 58% (95% CI 17.25%, 23.90%) in Ethiopia. Consuming packed foods (POR=2.12, 95% CI 1.41, 3.17), presence of high cholesterol (POR=4.08; 95% CI 2.75, 6.07), physical inactivity (POR=3.27; 95% CI 1.80, 5.94), high body mass index (BMI) (POR=2.27; 95% CI 0.85, 6.03), postmenopause (POR=2.25; 95% CI 1.63, 3.10), family history of cancer (POR=3.65; 95% CI 0.85, 15.71) and lack of breastfeeding (POR=2.76; 95% CI 0.90, 7.92) were the determinants of breast cancer., Conclusions: One of five patients with cancer is diagnosed with breast cancer in Ethiopia. Furthermore, more than a quarter of women with cancer suffer from breast cancer. Processed food consumption, high cholesterol in the body, lack of physical activity, high BMI, postmenopause, family history of cancer and lack of breastfeeding were the risk factors for breast cancer. The use of healthy food sources such as fruits and vegetables, and homegrown varieties of crops rather than seeking processed foods would help., Prospero Registration Number: CRD42023417733., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)