Evaluation of the feasibility and performance of early warning scores to identify patients at risk of adverse outcomes in a low-middle income country setting

Abstract

ObjectiveThis study describes the availability of core parameters for Early Warning Scores (EWS), evaluates the ability of selected EWS to identify patients at risk of death or other adverse outcome and describes the burden of triggering that front-line staff would experience if implemented.DesignLongitudinal observational cohort study.SettingDistrict General Hospital Monaragala.ParticipantsAll adult (age >17 years) admitted patients.Main outcome measuresExisting physiological parameters, adverse outcomes and survival status at hospital discharge were extracted daily from existing paper records for all patients over an 8-month period.Statistical analysisDiscrimination for selected aggregate weighted track and trigger systems (AWTTS) was assessed by the area under the receiver operating characteristic (AUROC) curve.Performance of EWS are further evaluated at time points during admission and across diagnostic groups. The burden of trigger to correctly identify patients who died was evaluated using positive predictive value (PPV).ResultsOf the 16 386 patients included, 502 (3.06%) had one or more adverse outcomes (cardiac arrests, unplanned intensive care unit admissions and transfers). Availability of physiological parameters on admission ranged from 90.97% (95% CI 90.52% to 91.40%) for heart rate to 23.94% (95% CI 23.29% to 24.60%) for oxygen saturation. Ability to discriminate death on admission was less than 0.81 (AUROC) for all selected EWS. Performance of the best performing of the EWS varied depending on admission diagnosis, and was diminished at 24 hours prior to event. PPV was low (10.44%).ConclusionThere is limited observation reporting in this setting. Indiscriminate application of EWS to all patients admitted to wards in this setting may result in an unnecessary burden of monitoring and may detract from clinician care of sicker patients. Physiological parameters in combination with diagnosis may have a place when applied on admission to help identify patients for whom increased vital sign monitoring may not be beneficial. Further research is required to understand the priorities and cues that influence monitoring of ward patients.Trial registration numberNCT02523456.

Association of the Quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) Score With Excess Hospital Mortality in Adults With Suspected Infection in Low- and Middle-Income Countries

“…We conducted a secondary analysis of 9 data sets: 8 cohort studies (5 prospective and 3 retrospective) and 1 randomized clinical trial. [8][9][10][11][12][13][14][15] Of the countries represented in this study (Bangladesh, Haiti, India, Indonesia, Myanmar, Rwanda, Sierra Leone, Sri Lanka, Thailand, and Vietnam), 3 are classified as low income, 6 as lower middle income, and 1 as upper middle income by the World Bank. 16 Patients were recruited to the cohorts from a range of hospital settings, including small community hospitals, military hospitals, rural regional hospitals, national referral hospitals, and specialty infectious disease hospitals.…”

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

“…The few studies performed in low-and middle-income countries have shown a wide variation in the performance of EWS. 1,17,18 In addition to patient population, the performance of any EWS must also depend on the accuracy of the vital sign recordings used to calculate it. 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.…”

“…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.…”

Addressing the information deficit in global health: lessons from a digital acute care platform in Sri Lanka

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“…While there is much in the literature to recommend what data should be collected,7 10 11 there is limited practical advice or examples on how day-to-day clinical information can be successfully captured, especially in overstretched and under-resourced LMIC settings 1. It is noticeable in HIC settings that healthcare providers and researchers have increasingly turned towards technology and digital surveillance in order to achieve the breadth and saturation of continuous information needed to improve care.…”