Health Facilities’ Readiness to Manage Hypertension and Diabetes Cases at Primary Health Facilities in Bidibidi Refugee Settlement, Yumbe District, Uganda

• Published in: Journal of Tropical Medicine
• Main Authors: Vuchiri Ray Isadru, Rose Clarke Nanyonga, John Bosco Alege
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2021
• Subjects: Arctic medicine. Tropical medicine; RC955-962; Arctic
• Online Access: https://doi.org/10.1155/2021/1415794; https://doaj.org/article/e23faf64f16540a3b42880fa6b99c1f6

Background. NCDs are the greatest global contributors to morbidity and mortality and are a major health challenge in the 21st century. The global burden of NCDs remains unacceptably high. Access to care remains a challenge for the majority of persons living with NCDs in sub-Saharan Africa. In Uganda, 55% of refugee households, including those with chronic illnesses, lack access to health services. Of these, 56% are in the West-Nile region where the Bidibidi settlement is located, with 61% of its refugee households in need of health services especially for NCDs (UNHCR, 2019). Data on NCDs in Bidibidi are scarce. Unpublished health facilities’ (HFs) data indicate that cardiovascular diseases (CVDs) (54.3%) and metabolic disorders (20.6%) were the leading causes of consultation for major NCDs (IRC, 2019). No readiness assessment has ever been conducted to inform strategies for the efficient management of NCDs to avert more morbidity, mortality, and the economic burden associated with NCD management or complications among refugees. This study sought to determine the readiness of HFs in managing hypertension (HTN) and diabetes cases at primary health facilities in the Bidibidi refugee settlement, Yumbe district, Uganda. Methods. The study used facility-based, cross-sectional design and quantitative approach to assess readiness for the management of HTN and diabetes. All the 16 HFs at the Health Centre III (HCIII) level in Bidibidi were studied, and a sample size of 148 healthcare workers (HCWs) was determined using Yamane’s formula (1967). Proportionate sample sizes were determined at each HF and the simple random sampling technique was used. HF data were collected using the Service Availability and Readiness Assessment (SARA) checklist and a structured questionnaire used among HCWs. Data were analyzed using SPSS version 20. Univariate analysis involved descriptive statistics; bivariate analysis used chi-square, Fisher’s exact test, and multivariable regression analysis for readiness of HCWs. Results. 16 HCIIIs were ...