A complex intervention to improve implementation of World Health Organization guidelines for diagnosis of severe illness in low-income settings: a quasi-experimental study from Uganda

Abstract

BackgroundTo improve management of severely ill hospitalized patients in low-income settings, the World Health Organization (WHO) established a triage tool called “Quick Check” to provide clinicians with a rapid, standardized approach to identify patients with severe illness based on recognition of abnormal vital signs. Despite the availability of these guidelines, recognition of severe illness remains challenged in low-income settings, largely as a result of infrequent vital sign monitoring.MethodsWe conducted a staggered, pre-post quasi-experimental study at four inpatient health facilities in western Uganda to assess the impact of a multi-modal intervention for improving quality of care following formal training on WHO “Quick Check” guidelines for diagnosis of severe illness in low-income settings. Intervention components were developed using the COM-B (“capability,” “opportunity,” and “motivation” determine “behavior”) model and included clinical mentoring by an expert in severe illness care, collaborative improvement meetings with external support supervision, and continuous audits of clinical performance with structured feedback.ResultsThere were 5759 patients hospitalized from August 2014 to May 2015: 1633 were admitted before and 4126 during the intervention period. Designed to occur twice monthly, collaborative improvement meetings occurred every 2–4 weeks at each site. Clinical mentoring sessions, designed to occur monthly, occurred every 4–6 months at each site. Audit and feedback reports were implemented weekly as designed. During the intervention period, there were significant increases in the site-adjusted likelihood of initial assessment of temperature, heart rate, blood pressure, respiratory rate, mental status, and pulse oximetry. Patients admitted during the intervention period were significantly more likely to be diagnosed with sepsis (4.3 vs. 0.4%, risk ratio 10.1, 95% CI 3.0–31.0, p < 0.001) and severe respiratory distress (3.9 vs. 0.9%, risk ratio 4.5, 95% CI 1.8–10.9, p = 0.001).ConclusionsTheory-informed quality improvement programs can improve vital sign collection and diagnosis of severe illness in low-income settings. Further implementation, evaluation, and scale-up of such interventions are needed to enhance hospital-based triage and severe illness management in these settings.Trial registrationSevere illness management system (SIMS) intervention development, ISRCTN46976783 Electronic supplementary materialThe online version of this article (10.1186/s13012-017-0654-0) contains supplementary material, which is available to authorized users.

Clinical and microbiological characterization of sepsis and evaluation of sepsis scores

“…Furthermore, antimicrobial resistance is increasing and contributing to the rise in mortality in the light of limited treatment options. Regarding sepsis in SSA, awareness is limited [ 2 ] and the WHO Global Burden of Diseases Reports do not list sepsis as specific cause of death. Due to various reasons, diagnostic criteria for recognition and prognostic evaluation of sepsis are often not systematically applied in the clinical routine and it has therefore to be assumed that a high number of cases remain unrecognized and unreported.…”

Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings

“…The purpose of these scores is to rapidly identify patients who need urgent care: once identified a complete set of vital signs will become an essential part of their management. Unfortunately, in many low resource settings complete sets of vital signs are often not performed [ 35 , 36 ] and/or cannot be measured because the equipment required was not available [ 35 , 37 ].…”

Do different patient populations need different early warning scores? The performance of nine different early warning scores used on acutely ill patients admitted to a low-resource hospital in sub-Saharan Africa

“…In many studies complete sets of vital signs were often not performed, and/or could not be measured because the equipment required was not available. [17][18][19] In this study a considerable amount of care with vital sign measurement was taken. The READS computer system has been used at Kitovu to collect vital signs at the bedside since 2016, and for this study an electrocardiograph was used to assess heart rate, a computer application to accurately determine respiratory rate measured over 60 seconds, and a well-validated blood pressure machine to record blood pressure.…”