An analysis of health facility preparedness for major incidents in Kampala

Background & Objectives: Major incidents occur commonly in Uganda, but little is known about either local hazards which risk causing major incidents, or health system preparedness for such events. Understanding risk and current preparedness is the first step in improving response. Methods: We undertook a cross - sectional study across four teaching hospitals in Kampala (Mulago National Referral Hospital, Nsambya Hospital, Mengo Hospital and Lubaga Hospital). A local geographic area Hazard Vulnerability Analysis (HVA) f or each site was combined with a key informant questionnaire and standardized facility checklist within the hospitals. Data collected included status of major incident committees, operational major incident plans and facility major incident operation centres, bed capacity, equipment and supplies and staffing. The HVA assessed the human impact, impact on property and on business of the hazards as well as measures for mitigation (preparedness, internal response and external response) in place at the hospitals. Results: Only one of the four hospitals was found to have had an operational major incident plan. The designated coordinator for major incidents across all facilities was mostly a general surgeon; no funds were specifically allocated for planning .All hospitals have procedures for triage, resuscitation, stabilization and treatment. None of the facilities had officially designated a major incident committee. All the facilities had sufficient supplies for daily use but none had specifically stock piled any reserves for major incidents. All hospitals were staffed by at least a medical officer, clinical officers, nurses and a specialist with procedures for mobilizing extra staff s for major incidents. Some staffs had received some emergency care training in courses namely basic life support, advanced trauma life support, primary trauma care and emergency triage and treatment but no team had received training in major incident response. Only one hospital carried out annual simulation exercises. Incidents involving human hazards specifically bomb threats, road crash mass casualty incidents, civil disorder and epidemics posed the highest risk to all four hospitals and yet preparation and response measures were inadequate. Conclusion: Hospitals in Kampala face a wide range of hazards and frequent major incidents but despite this they remain under - prepared to respond. Large gaps were identified in as far as staffing, equipment and infrastructure

Cost-effectiveness analysis of the multi-strategy WHO emergency care toolkit in regional referral hospitals in Uganda.

BackgroundLow- and middle-income countries bear a disproportionate amount of the global burden of disease from emergency conditions. To improve the provision of emergency care in low-resource settings, a multifaceted World Health Organization (WHO) intervention introduced a toolkit including Basic Emergency Care training, resuscitation area guidelines, a trauma registry, a trauma checklist, and triage tool in two public hospital sites in Uganda. While introduction of the toolkit revealed a large reduction in the case fatality rate of patients, little is known about the cost-effectiveness and affordability. We analysed the cost-effectiveness of the toolkit and conducted a budget analysis to estimate the impact of scale up to all regional referral hospitals for the national level.MethodsA decision tree model was constructed to assess pre- and post-intervention groups from a societal perspective. Data regarding mortality were drawn from WHO quality improvement reports captured at two public hospitals in Uganda from 2016-2017. Cost data were drawn from project budgets and included direct costs of the implementation of the intervention, and direct costs of clinical care for patients with disability. Development costs were not included. Parameter uncertainty was assessed using both deterministic and probabilistic sensitivity analyses. Our model estimated the incremental cost-effectiveness of implementing the WHO emergency care toolkit measuring all costs and outcomes as disability-adjusted life-years (DALYs) over a lifetime, discounting both costs and outcomes at 3.5%.ResultsImplementation of the WHO Toolkit averted 1,498 DALYs when compared to standard care over a one-year time horizon. The initial investment of $5,873 saved 34 lives (637 life years) and avoided$1,670,689 in downstream societal costs, resulted in a negative incremental cost-effectiveness ratio, dominating the comparator scenario of no intervention. This would increase to saving 884 lives and 25,236 DALYs annually with national scale up. If scaled to a national level the total intervention cost over period of five years would be $4,562,588 or a 0.09$29,880,949 USD, the equivalent of a 655% return on investment. The model was most sensitive to average annual cash income, discount rate and frequency survivor is a road-traffic incident survivor, but was robust for all other parameters.ConclusionImproving emergency care using the WHO Toolkit produces a cost-savings in a low-resource setting such as Uganda. In alignment with the growing body of literature highlighting the value of systematizing emergency care, our findings suggest the toolkit could be an efficient approach to strengthening emergency care systems

A qualitative study exploring nurses’ attitudes, confidence, and perceived barriers to implementing a traumatic brain injury nursing chart in Uganda

Introduction: In Africa, traumatic brain injuries frequently result from road traffic injuries and assaults. Despite limited resources and the high costs of life-saving neurosurgical interventions, secondary brain injury prevention has the potential for improving outcomes. However, nurses and other medical personnel infrequently monitor vital signs, blood sugar, and pulse oximetry and only sporadically re-assess neurological status. Methods: In one-on-one, semi-structured interviews, 27 nurses from Mulago Hospital’s emergency centre, a tertiary care trauma hospital in Kampala, Uganda, provided feedback regarding a traumatic brain injury-focused education session and use of a nursing chart for detecting secondary brain injury. The interviews explored the nurses’ confidence and perceived barriers to long-term chart implementation and traumatic brain injury care, as well as their ideas for improving this intervention. Interviews were audio recorded, transcribed, and coded using ATLAS.ti: Qualitative Data Analysis and Research Software (Cleverbridge, Inc., Chicago, USA) and Microsoft Word and Excel (Microsoft Office, Redmond, USA) for thematic content analysis. Results: Key findings identified in the interviews included the nurses’ attitudes toward the chart and their feelings of increased confidence in assessing and caring for these patients. The main barriers to continuous implementation included inadequate staffing and resources. Conclusion: Nurses were receptive to the education session and nursing chart, and felt that it increased their confidence and improved their ability to care for traumatic brain injured patients. However, lack of supplies, overwhelming numbers of patients, and inadequate staffing interfered with consistent monitoring of patients. The nurses offered various suggestions for improving traumatic brain injury care that should be further investigated. More research is needed to assess the applicability of a standardised traumatic brain injury nursing education and chart in a broader context. Keywords: Traumatic brain injury, Uganda, Nursing, Nursing chart, Barriers, Emergenc

Incremental cost-effectiveness results.

Incremental cost-effectiveness results.</p

Summary of cost variables for the WHO toolkit intervention in Uganda.

Summary of cost variables for the WHO toolkit intervention in Uganda.</p

Cost-effectiveness plane results of 10,000 samples.

Cost-effectiveness plane results of 10,000 samples.</p

Results of a univariate sensitivity analysis of key variables on cost per DALY averted.

Results of a univariate sensitivity analysis of key variables on cost per DALY averted.</p

Model parameter range and probability distribution.

Model parameter range and probability distribution.</p

Decision tree model.

Decision tree model.</p

Budget impact analysis cost of national scale up to all RRHs.

Budget impact analysis cost of national scale up to all RRHs.</p