Geographical validation of the Smart Triage Model by age group.

Infectious diseases in neonates account for half of the under-five mortality in low- and middle-income countries. Data-driven algorithms such as clinical prediction models can be used to efficiently detect critically ill children in order to optimize care and reduce mortality. Thus far, only a handful of prediction models have been externally validated and are limited to neonatal in-hospital mortality. The aim of this study is to externally validate a previously derived clinical prediction model (Smart Triage) using a combined prospective baseline cohort from Uganda and Kenya with a composite endpoint of hospital admission, mortality, and readmission. We evaluated model discrimination using area under the receiver-operator curve (AUROC) and visualized calibration plots with age subsets (< 30 days, ≤ 2 months, ≤ 6 months, and < 5 years). Due to reduced performance in neonates (< 1 month), we re-estimated the intercept and coefficients and selected new thresholds to maximize sensitivity and specificity. 11595 participants under the age of five (under-5) were included in the analysis. The proportion with an endpoint ranged from 8.9% in all children under-5 (including neonates) to 26% in the neonatal subset alone. The model achieved good discrimination for children under-5 with AUROC of 0.81 (95% CI: 0.79-0.82) but poor discrimination for neonates with AUROC of 0.62 (95% CI: 0.55-0.70). Sensitivity at the low-risk thresholds (CI) were 85% (83%-87%) and 68% (58%-76%) for children under-5 and neonates, respectively. After model revision for neonates, we achieved an AUROC of 0.83 (95% CI: 0.79-0.87) with 13% and 41% as the low- and high-risk thresholds, respectively. The updated Smart Triage performs well in its predictive ability across different age groups and can be incorporated into current triage guidelines at local healthcare facilities. Additional validation of the model is indicated, especially for the neonatal model.

Transitions from hospital to home: A mixed methods study to evaluate pediatric discharges in Uganda.

The World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) guidelines recognize the importance of discharge planning to ensure continuation of care at home and appropriate follow-up. However, insufficient attention has been paid to post discharge planning in many hospitals contributing to poor implementation. To understand the reasons for suboptimal discharge, we evaluated the pediatric discharge process from hospital admission through the transition to care within the community in Ugandan hospitals. This mixed methods prospective study enrolled 92 study participants in three phases: patient journey mapping for 32 admitted children under-5 years of age with suspected or proven infection, discharge process mapping with 24 pediatric healthcare workers, and focus group discussions with 36 primary caregivers and fathers of discharged children. Data were descriptively and thematically analyzed. We found that the typical discharge process is often not centered around the needs of the child and family. Discharge planning often does not begin until immediately prior to discharge and generally does not include caregiver input. Discharge education and counselling are generally limited, rarely involves the father, and does not focus significantly on post-discharge care or follow-up. Delays in the discharge process itself occur at multiple points, including while awaiting a physical discharge order and then following a discharge order, mainly with billing or transportation issues. Poor peri-discharge care is a significant barrier to optimizing health outcomes among children in Uganda. Process improvements including initiation of early discharge planning, improved communication between healthcare workers and caregivers, as well as an increased focus on post-discharge care, are key to ensuring safe transitions from facility-based care to home-based care among children recovering from severe illness.

Management of preterm birth using protocols in a low resource setting.

BACKGROUND: Preterm birth is the leading cause of neonatal deaths and the second leading cause of death in children under five after pneumonia. The study aimed at improving the management of preterm birth through the development of protocols for standardization of care. METHODS: The study was conducted in Mulago National Referral Labor ward in two phases. A total of 360 case files were reviewed and mothers whose files had missing data interviewed for clarity for both the baseline audit and the re-audit. Chi squares were used to compare results for the baseline and the re-audit. RESULTS: There was significant improvement in four parameters out of the six that were used to assess quality of care and these were 32% increase in administration of Dexamethasone for fetal lung maturity, 27% increase in administration of Magnesium Sulphate for fetal neuroprotection and 23% increase in anti-biotic administration. A 14% reduction noted in patients who received no intervention. However, there was no change in the administration of Tocolytic. CONCLUSION: The results of this study have shown that protocols standardize care and improve the quality of care in preterm delivery to optimize outcomes.

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.

BACKGROUND: To 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. METHODS: We 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. RESULTS: There 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). CONCLUSIONS: Theory-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 REGISTRATION: Severe illness management system (SIMS) intervention development, ISRCTN46976783.