Abstract

BackgroundUganda experiences a high morbidity and mortality burden due to conditions amenable to emergency care, yet few public hospitals have dedicated emergency units. As a result, little is known about the costs and effects of delivering lifesaving emergency care, hindering health systems planning, budgeting and prioritization exercises. To determine healthcare costs of emergency care services at public facilities in Uganda, we estimate the median cost of care for five sentinel conditions and 13 interventions.MethodsA direct, activity-based costing was carried out at five regional referral hospitals over a four-week period from September to October 2019. Hospital costs were determined using bottom-up micro-costing methodology from a provider perspective. Resource use was enumerated via observation and unit costs were derived from National Medical Stores lists. Cost per condition per patient and measures of central tendency for conditions and interventions were calculated. Kruskal-Wallis H-tests and Nemyeni post-hoc tests were conducted to determine significant differences between costs of the conditions.ResultsEight hundred seventy-two patient cases were captured with an overall median cost of care of $15.53 USD ($14.44 to $19.22). The median cost per condition was highest for post-partum haemorrhage at $17.25 ($15.02 to $21.36), followed by road traffic injuries at $15.96 ($14.51 to $20.30), asthma at $15.90 ($14.76 to $19.30), pneumonia at $15.55 ($14.65 to $20.12), and paediatric diarrhoea at $14.61 ($13.74 to $15.57). The median cost per intervention was highest for fracture reduction and splinting at $27.77 ($22.00 to $31.50). Cost values differ between sentinel conditions (p < 0.05) with treatments for paediatric diarrhoea having the lowest median cost of all conditions (p < 0.05).ConclusionThis study is the first to describe the direct costs of emergency care in hospitals in Uganda by observing the delivery of clinical services, using robust activity-based costing and time motion methodology. We find that emergency care interventions for key drivers of morbidity and mortality can be delivered at considerably lower costs than many priority health interventions. Further research assessing acute care delivery would be useful in planning wider health care delivery systems development.

Highlights

  • Uganda experiences a high morbidity and mortality burden due to conditions amenable to emergency care, yet few public hospitals have dedicated emergency units

  • This study addresses some of the critical gaps in the economic evidence for Emergency care (EC) in Low-and middle income countries (LMIC) and accompanies ongoing research assessing the effectiveness of the World Health Organization (WHO) Emergency Care Toolkit in Uganda, whose methods are previously described [17]

  • The following criteria were used for site inclusion to the study: a public Regional Referral Hospital (RRH), with an emergency/casualty/A&E unit, which had not received any of the elements of the WHO EC Toolkit

Read more

Summary

Introduction

Uganda experiences a high morbidity and mortality burden due to conditions amenable to emergency care, yet few public hospitals have dedicated emergency units. Data from high-income settings do not accurately reflect the fiscal environment more common in LMICs. Numerous additional research challenges, including: paper-based data management systems, unreliable supply chains with frequent stockouts and highly variable accounting practices, present further challenges in assessing local costs in LMIC environments to provide context-relevant guidance [14]. Numerous additional research challenges, including: paper-based data management systems, unreliable supply chains with frequent stockouts and highly variable accounting practices, present further challenges in assessing local costs in LMIC environments to provide context-relevant guidance [14] Under these circumstances, capturing accurate figures requires resource and time intensive methods such as direct observation via time-motion methodology – a likely reason for the paucity of published data surrounding performance and capability of delivering of EC in LMICs [15]

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call