Dataset Information

Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool.

ABSTRACT: Background: Sepsis is the leading cause of death and disability in children. Every hour of delay in treatment is associated with an escalating risk of morbidity and mortality. The burden of sepsis is greatest in low- and middle-income countries where timely treatment may not occur due to delays in diagnosis and prioritization of critically ill children. To circumvent these challenges, we propose the development and clinical evaluation of a digital triage tool that will identify high risk children and reduce time to treatment. We will also implement and clinically validate a Radio-Frequency Identification system to automate tracking of patients. The mobile platform (mobile device and dashboard) and automated patient tracking system will create a low cost, highly scalable solution for critically ill children, including those with sepsis.

Methods: This is pre-post intervention study consisting of three phases. Phase I will be a baseline period where data is collected on key predictors and outcomes before implementation of the digital triage tool. In Phase I, there will be no changes to healthcare delivery processes in place at the study hospitals. Phase II will involve model derivation, technology development, and usability testing. Phase III will be the intervention period where data is collected on key predictors and outcomes after implementation of the digital triage tool. The primary outcome, time to treatment initiation, will be compared to assess effectiveness of the digital health intervention.

Discussion: Smart technology has the potential to overcome the barrier of limited clinical expertise in the identification of the child at risk. This mobile health platform, with sensors and data-driven applications, will provide real-time individualized risk prediction to rapidly triage patients and facilitate timely access to life-saving treatments for children in low- and middle-income countries, where specialists are not regularly available and deaths from sepsis are common.

Trial registration: Clinical Trials.gov Identifier: NCT04304235, Registered 11 March 2020.

SUBMITTER: Mawji A

PROVIDER: S-EPMC7268489 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool.

Mawji Alishah A Li Edmond E Komugisha Clare C Akech Samuel S Dunsmuir Dustin D Wiens Matthew O MO Kissoon Niranjan N Kenya-Mugisha Nathan N Tagoola Abner A Kimutai David D Bone Jeffrey N JN Dumont Guy G Ansermino J Mark JM

BMC health services research 20200603 1

<h4>Background</h4>Sepsis is the leading cause of death and disability in children. Every hour of delay in treatment is associated with an escalating risk of morbidity and mortality. The burden of sepsis is greatest in low- and middle-income countries where timely treatment may not occur due to delays in diagnosis and prioritization of critically ill children. To circumvent these challenges, we propose the development and clinical evaluation of a digital triage tool that will identify high risk ...[more]

PMID: 32493319

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Project description:BackgroundSepsis is a clinical syndrome characterized by organ dysfunction due to presumed or proven infection. Severe cases can have case fatality ratio 25% or higher in low-middle income countries, but early diagnosis and timely treatment have a proven benefit. The Smart Triage program in Jinja Regional Referral Hospital in Uganda will provide expedited sepsis treatment in children through a data-driven electronic patient triage system. To complement the ongoing Smart Triage interventional trial, we propose methods for a concurrent cost-effectiveness analysis of the Smart Triage platform.MethodsWe will use a decision-analytic model taking a societal perspective, combining government and out-of-pocket costs, as patients bear a sizeable portion of healthcare costs in Uganda due to the lack of universal health coverage. Previously published secondary data will be used to link healthcare utilization with costs and intermediate outcomes with mortality. We will model uncertainty via probabilistic sensitivity analysis and present findings at various willingness-to-pay thresholds using a cost-effectiveness acceptability curve.DiscussionOur proposed analysis represents a first step in evaluating the cost-effectiveness of an innovative digital triage platform designed to improve clinical outcomes in pediatric sepsis through expediting care in low-resource settings. Our use of a decision analytic model to link secondary costing data, incorporate post-discharge healthcare utilization, and model clinical endpoints is also novel in the pediatric sepsis triage literature for low-middle income countries. Our analysis, together with subsequent analyses modelling budget impact and scale up, will inform future modifications to the Smart Triage platform, as well as motivate scale-up to the district and national levels.Trial registrationTrial registration of parent clinical trial: NCT04304235, https://clinicaltrials.gov/ct2/show/NCT04304235. Registered 11 March 2020.

Project description:BackgroundSepsis, characterized by organ dysfunction due to presumed or proven infection, has a case-fatality over 20% in severe cases in low-and-middle income countries. Early diagnosis and treatment have proven benefits, prompting our implementation of Smart Triage at Jinja Regional Referral Hospital in Uganda, a program that expedites treatment through a data-driven triage platform. We conducted a cost-effectiveness analysis of Smart Triage to explore its impact on patients and inform multicenter scale up.MethodsThe parent clinical trial for Smart Triage was pre-post in design, using the proportion of children receiving sepsis treatment within one hour as the primary outcome, a measure linked to mortality benefit in existing literature. We used a decision-analytic model with Monte Carlo simulation to calculate the cost per year-of-life-lost (YLL) averted of Smart Triage from societal, government, and patient perspectives. Healthcare utilization and lost work for seven days post-discharge were translated into costs and productivity losses via secondary linkage data.ResultsIn 2021 United States dollars, Smart Triage requires an annuitized program cost of only $0.05 per child, but results in $15.32 saved per YLL averted. At a willingness-to-pay threshold of only $3 per YLL averted, well below published cost-effectiveness threshold estimates for Uganda, Smart Triage approaches 100% probability of cost-effectiveness over the baseline manual triage system. This cost-effectiveness was observed from societal, government, and patient perspectives. The cost-effectiveness observed was driven by a reduction in admission that, while explainable by an improved triage mechanism, may also be partially attributable to changes in healthcare utilization influenced by the coronavirus pandemic. However, Smart Triage remains cost-effective in sensitivity analyses introducing a penalty factor of up to 50% in the reduction in admission.ConclusionSmart Triage's ability to both save costs and avert YLLs indicates that patients benefit both economically and clinically, while its high probability of cost-effectiveness strongly supports multicenter scale up. Areas for further research include the incorporation of years lived with disability when sepsis disability weights in low-resource settings become available and analyzing budget impact during multicenter scale up.Trial registrationNCT04304235 (registered on 11/03/2020, clinicaltrials.gov).

Project description:Objective: To study warning signs of serious infections in febrile children presenting to PED, ascertain their risk of having sepsis, and evaluate their management. Design: Prospective observational study. Setting: A single pediatric emergency department (PED). Participants: Febrile children, aged 1 month-16 years, with >= 1 warning signs of sepsis. Interventions and Main outcome measures: Clinical characteristics, including different thresholds for tachycardia and tachypnoea, and their association with (1) delivery of pediatric sepsis 6 (PS6) interventions, (2) final diagnosis of invasive bacterial infection (IBI), (3) the risk for pediatric intensive care unit (PICU) admission, and (4) death. Results: Forty-one percent of 5,156 febrile children had warning signs of sepsis. 1,606 (34%) children had tachypnoea and 1,907 (39%) children had tachycardia when using APLS threshold values. Using the NICE sepsis guidelines thresholds resulted in 1,512 (32%) children having tachypnoea (kappa 0.56) and 2,769 (57%) children having tachycardia (kappa 0.66). Of 1,628 PED visits spanning 1,551 disease episodes, six children (0.4%) had IBI, with one death (0.06%), corresponding with 256 children requiring escalation of care according to sepsis guideline recommendations for each child with IBI. There were five additional PICU admissions (0.4%). 121 (7%) had intravenous antibiotics in PED; 39 children (2%) had an intravenous fluid bolus, inotrope drugs were started in one child. 440 children (27%) were reviewed by a senior clinician. In 4/11 children with IBI or PICU admission or death, PS6 interventions were delivered within 60 min after arriving. 1,062 (65%) visits had no PS6 interventions. Diagnostic performance of vital signs or sepsis criteria for predicting serious illness yielded a large proportion of false positives. Lactataemia was not associated with giving iv fluid boluses (p = 0.19) or presence of serious bacterial infections (p = 0.128). Conclusion: Many febrile children (41%) present with warning signs for sepsis, with only few of them undergoing investigations or treatment for true sepsis. Children with positive isolates in blood or CSF culture presented in a heterogeneous manner, with varying levels of urgency and severity of illness. Delivery of sepsis care can be improved in only a minority of children with IBI or admitted to PICU.

Project description:ObjectiveTo demonstrate the incremental benefit of using free text data in addition to vital sign and demographic data to identify patients with suspected infection in the emergency department.MethodsThis was a retrospective, observational cohort study performed at a tertiary academic teaching hospital. All consecutive ED patient visits between 12/17/08 and 2/17/13 were included. No patients were excluded. The primary outcome measure was infection diagnosed in the emergency department defined as a patient having an infection related ED ICD-9-CM discharge diagnosis. Patients were randomly allocated to train (64%), validate (20%), and test (16%) data sets. After preprocessing the free text using bigram and negation detection, we built four models to predict infection, incrementally adding vital signs, chief complaint, and free text nursing assessment. We used two different methods to represent free text: a bag of words model and a topic model. We then used a support vector machine to build the prediction model. We calculated the area under the receiver operating characteristic curve to compare the discriminatory power of each model.ResultsA total of 230,936 patient visits were included in the study. Approximately 14% of patients had the primary outcome of diagnosed infection. The area under the ROC curve (AUC) for the vitals model, which used only vital signs and demographic data, was 0.67 for the training data set, 0.67 for the validation data set, and 0.67 (95% CI 0.65-0.69) for the test data set. The AUC for the chief complaint model which also included demographic and vital sign data was 0.84 for the training data set, 0.83 for the validation data set, and 0.83 (95% CI 0.81-0.84) for the test data set. The best performing methods made use of all of the free text. In particular, the AUC for the bag-of-words model was 0.89 for training data set, 0.86 for the validation data set, and 0.86 (95% CI 0.85-0.87) for the test data set. The AUC for the topic model was 0.86 for the training data set, 0.86 for the validation data set, and 0.85 (95% CI 0.84-0.86) for the test data set.ConclusionCompared to previous work that only used structured data such as vital signs and demographic information, utilizing free text drastically improves the discriminatory ability (increase in AUC from 0.67 to 0.86) of identifying infection.

Dataset Information

Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool.

Publications

Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool.

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