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| Name | Class |
|---|---|
| Kenya Medical Research Institute | OTHER |
| Wellcome Trust | OTHER |
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Sepsis is the leading cause of death and disability in children, every hour of delay in treatment is associated with greater organ damage and ultimately death. The challenges, especially in poor countries, are the delays in diagnosis and the inability to identify children in urgent need of treatment.To circumvent these challenges, we propose the development and clinical evaluation of a trigger tool that will reduce the time to diagnosis and prompt the timely initiation of life-saving treatment. The key innovations are 1) a data-driven approach to rapid diagnosis of sepsis severity and 2) a low- cost digital tagging system to track the time to treatment. The tool will require minimal cost, clinical expertise and training or time to use.
The tool will identify high risk children and reduce time to treatment. The digital platform (mobile device and dashboard) will create a low-cost, highly scalable solution for children with sepsis.
This is a pre-post intervention study involving pediatric patients presenting to the study hospitals in seek of medical care for an acute illness. The study involves three phases: (I) Baseline Period, (II) Interphase Period, (III) Intervention Period.
Phase I (3-6 months) will be a prospective observational cohort at Mbagathi County Hospital in Nairobi, Kenya, and Jinja Regional Referral Hospital in Jinja, Uganda. During this period, there will be no changes to healthcare delivery procedures in the study hospitals. Triage will continue to be performed by hospital staff using Emergency Triage and Treatment (ETAT) guidelines, the system that is currently in effect at the study hospitals. Data collection will be undertaken in the triage waiting area. While participants are waiting for their turn to be seen by the hospital triage nurses, our trained study nurses will collect data on a pre-selected list of predictor variables. These data will be used to develop a clinical prediction model based on the need for hospital admission.
Control Site (Phase I, 12 months): Kiambu County Referral Hospital in Nairobi, Kenya will serve as the control site and no intervention will be implemented. At this site, Phase I will commence for a period of 12 months. There will be no Phase II or Phase III.
Phase II (1-3 months) will involve technology development, usability testing, and training.
Phase IIa: Technology Development. A risk prediction model will be derived using the data collected in Phase I and implemented in a Digital Triaging Platform, along with a digitized version of the ETAT+ guidelines. The Digital Triaging Platform, including vital sign measurement devices (PhoneOx and RRate and the mobile application and clinical dashboard has already been developed and evaluated. Once the digital triage tool has been developed, it will be evaluated in potential users using simulated patient scenarios and a 'Think Aloud' method.
Phase IIb: Usability Testing and Training. The digital triage tool will be evaluated for ease of interface navigation, functionality and basic workflow. A sample of 15 health workers in the study hospitals to represent the primary user groups will be selected for participation in the 60-minute-long usability testing initiatives. Participants will be recruited through word of mouth as there is a very small cadre of potential participants. The objective of the training is to (1) ensure healthcare workers understand how to correctly collect and interpret patient information, and (2) to obtain feedback on the digitization of the tool. Training will use a framework that meets key international norms for testing digital tools, including, the think-aloud method and a questionnaire.
Each training session will be conducted by a moderator and observer. During the evaluation, the observer will be seated next to the participant and will record user interaction with each interface, comments, errors, and duration of each task. Participants will be given 3-5 patient scenarios which will list hypothetical information to be entered into the app. This information will be designed to represent routine data collected during triage examination at the study hospitals. The moderator will provide the fictional charts to participants and instruct them throughout the tasks. During the simulated patient scenarios, participants will be asked to think aloud, in order to assess their thought process as they used the app. Participants will be specifically instructed to comment on the layout of the app screen, the dialogue on each interface, the order of tasks, and any additional observations or opinions. After learning the basics of the digital platform, the participants will be read the think aloud instructions and asked to perform the list of tasks and answer questions. The observer will complete a checklist to ensure that all tasks were completed, questions will be asked to evaluate task comprehension, and notes will be taken about whether help was needed in completing each task. At the end of the training session, participants will complete a triage tool training questionnaire to provide an understanding of the practical benefits and drawbacks of incorporating the digital triage tool into a clinical context. The questionnaire will utilize open ended questions and comment responses. from this evaluation. Responses from the survey will be anonymous. The data generated from the training phase is fictitious and will not be linked to any individual subject.
Transcriptions and Think Aloud observations will be analyzed using the Framework Method to assess attitudes of health workers. Responses will be transcribed and coded for the identification, examination and interpretation of emerging themes and patterns. Results from the analysis, feedback from the questionnaires, and comments on the observer checklists will be used to generate a report with suggested improvements to be shared with the quality improvement implementation team prior to Phase III.
Phase III (3-6 months) will be an interventional period involving routine use of the digital triage tool by the hospital triage nurses at Mbagathi County Hospital in Nairobi, Kenya, and Jinja Regional Referral Hospital in Jinja, Uganda. The digital triage tool will not replace triage policies already in place at the study hospitals, but rather it will supplement and strengthen existing triage systems. As done in Phase I, study nurses will collect data on the pre-selected list of predictor variables in the triage waiting area while participants are waiting to be seen by the hospital triage nurses (who will be using the digital triage tool). Continued collection of predictor variables will allow comparison of participant characteristics in the pre-intervention cohort and the post-intervention cohort. (Funder: Wellcome Trust Innovator Award # 215695/Z/19/Z)
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Kenya intervention baseline | Active Comparator | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
|
| Kenya intervention implementation | Experimental | Hospital nurses will triage participants using the digital triage tool (mhealth intervention). |
|
| Kenya control baseline | Active Comparator | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
|
| Kenya control implementation | Active Comparator | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
|
| Uganda intervention baseline | Active Comparator | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Pediatric Rapid Sepsis Trigger (PRST) tool | Device | The digital platform consists of a mobile application integrating a pulse oximetry sensor attached to this device, with embedded smart algorithms that predict a critically ill state, or level of risk (below) in a child presenting at the hospital. The platform also includes an interactive dashboard located in strategic locations (e.g., laboratory, consultation rooms), which connects to the mobile application through a secure local network and displays the triage data to provide real-time monitoring for the physicians who manage the patients. |
| Measure | Description | Time Frame |
|---|---|---|
| Time to Administration of an Appropriate Antimicrobial | Time in minutes to administer an appropriate antimicrobial, which includes at least one antibiotic or antimalarial (treatment determined and administered by hospital staff). The time is measured from when the child arrives at the facility (time of the first registration) until the antimicrobial administration is started. | 1 day |
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| Measure | Description | Time Frame |
|---|---|---|
| Readmission | The child is readmitted to the hospital after being discharged | 7 days |
| Mortality | Death within 7 days | 7 days |
Inclusion Criteria:
Exclusion Criteria:
-Patients presenting to the outpatient department for elective cases (e.g. elective surgery or change of dressing) or for clinical review appointment.
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| Name | Affiliation | Role |
|---|---|---|
| John M Ansermino | The University of British Columbia | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Kiambu County Referral Hospital | Nairobi | Kenya | ||||
| Mbagathi County Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40063663 | Result | Ansermino JM, Pillay Y, Tagoola A, Zhang C, Dunsmuir D, Kamau S, Kigo J, Agaba C, Aye IA, Hwang B, Novakowski SK, Huxford C, Wiens MO, Kimutai D, Ouma M, Ahmed I, Mwaniki P, Oyella F, Tenywa E, Nambuya H, Toliva BO, Kenya-Mugisha N, Kissoon N, Akech S; Pediatric Sepsis CoLab. Implementation of Smart Triage combined with a quality improvement program for children presenting to facilities in Kenya and Uganda: An interrupted time series analysis. PLOS Digit Health. 2025 Mar 10;4(3):e0000466. doi: 10.1371/journal.pdig.0000466. eCollection 2025 Mar. | |
| 37653477 |
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| ID | Type | URL | Comment |
|---|---|---|---|
| doi.org/10.5683/SP3/SIL | Individual Participant Data Set | View IPD |
After the study period, a de-identified copy of the data will be prepared for deposition in a repository with open access with proper governance mechanisms. We will make every effort to prevent re-identification of subjects by coding data that has the potential of being identifiable. The de-identified study data will be made publicly available using the Harvard Dataverse (https://dataverse.harvard.edu/), which is the data repository for KWTRP, and a URL will be made accessible. To enhance visibility, sharing and collating datasets with other collaborating sites for increased usability/re-use, de-identified will also be shared availed to reputable data hosting service such as the INDEPTH Data Repository (http://www.indepth-ishare.org/index.php/home), or through the newly established Pediatric Sepsis CoLab (sponsored by the World Federation of Pediatric Critical and Intensive care Societies).
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Data will be made available within 12 months following completion of the study.
Sharing and access will be managed and subject to institutional agreements (Kenya Medical Research Institute, The University of British Columbia, Makerere University School of Public Health) that will set terms for how requests and access will be managed. We will ensure that a rigorous data governance structure is used by the data hosting service. The distribution will only occur with agreement from Principal Investigators and the investigators at all of the study sites.
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Non infectious illness, routine clinic visit
Recruitment occurred at hospitals in two countries . Each country had a control and intervention site. A baseline period of data collection occurred at all sites except the control site in Uganda (due to COVID 19 pandemic restrictions).
Kenya: Intervention site Baseline, Kenya Intervention site Implementation, Kenya Control site Baseline, Kenya Control site Implementation
Uganda: Intervention site Baseline, Uganda Intervention site Implementation, Uganda Control site Implementation:
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| ID | Title | Description |
|---|---|---|
| FG000 | Kenya Intervention Baseline | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
| FG001 | Kenya Intervention Implementation | Hospital nurses will triage participants using the digital triage tool (mhealth intervention). Pediatric Rapid Sepsis Trigger (PRST) tool: The digital platform consists of a mobile application integrating a pulse oximetry sensor attached to this device, with embedded smart algorithms that predict a critically ill state, or level of risk (below) in a child presenting at the hospital. The platform also includes an interactive dashboard located in strategic locations (e.g., laboratory, consultation rooms), which connects to the mobile application through a secure local network and displays the triage data to provide real-time monitoring for the physicians who manage the patients. |
| FG002 | Kenya Control Baseline | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
| FG003 | Kenya Control Implementation | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
| FG004 | Uganda Intervention Baseline | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
| FG005 | Uganda Intervention Implementation | Hospital nurses will triage participants using the digital triage tool (mhealth intervention). Pediatric Rapid Sepsis Trigger (PRST) tool: The digital platform consists of a mobile application integrating a pulse oximetry sensor attached to this device, with embedded smart algorithms that predict a critically ill state, or level of risk (below) in a child presenting at the hospital. The platform also includes an interactive dashboard located in strategic locations (e.g., laboratory, consultation rooms), which connects to the mobile application through a secure local network and displays the triage data to provide real-time monitoring for the physicians who manage the patients. |
| FG006 | Uganda Control Implementation | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
|
same as Participant Flow information
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| ID | Title | Description |
|---|---|---|
| BG000 | Kenya Intervention Baseline | Baseline cohort at Kenya intervention site |
| BG001 | Kenya Intervention Implementation | Implementation cohort at Kenya implementation site |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Median |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Time to Administration of an Appropriate Antimicrobial | Time in minutes to administer an appropriate antimicrobial, which includes at least one antibiotic or antimalarial (treatment determined and administered by hospital staff). The time is measured from when the child arrives at the facility (time of the first registration) until the antimicrobial administration is started. | Children presenting to the outpatient department at facility | Posted | Mean | Inter-Quartile Range | minutes | 1 day |
|
7 days
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Kenya Intervention Baseline | Baseline cohort at Kenya intervention site | 29 |
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Simultaneous recruitment across countries disrupted by COVID-19 pandemic.
| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| J Mark Ansermino | The University of British Columbia | 1 604 875 2711 | anserminos@yahoo.ca |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP_ICF | Yes | Yes | Yes | Study Protocol, Statistical Analysis Plan, and Informed Consent Form | Oct 19, 2020 | Aug 1, 2024 | Prot_SAP_ICF_000.pdf |
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| ID | Term |
|---|---|
| D018805 | Sepsis |
| D007239 | Infections |
| ID | Term |
|---|---|
| D018746 | Systemic Inflammatory Response Syndrome |
| D007249 | Inflammation |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D004864 | Equipment and Supplies |
| D013812 | Therapeutics |
| D017408 | Guidelines as Topic |
| ID | Term |
|---|---|
| D011785 | Quality Assurance, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
| D017530 | Health Care Quality, Access, and Evaluation |
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This is a pre-post intervention study involving pediatric outpatients at Jinja Hospital in Jinja, Uganda, and Mbagathi Hospital in Nairobi, Kenya. The study has three phases: (I) Baseline Period: data is collected on key predictors and outcomes before implementation of the digital triage tool, (II) Interphase Period: model/technology development and usability testing, (III) Intervention Period: data is collected on key predictors and outcomes after implementation of the digital triage tool. Patients who present to the study hospitals in seek of medical care for an acute illness during Phase I will be part of the baseline cohort. Patients who present to the study hospitals in seek of medical care for an acute illness during Phase III will be part of the interventional cohort. A third hospital site, Kiambu Hospital in Nairobi Kenya, will serve as a control hospital, and will only participate in Phase I for the entire duration of the study.
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Due to the clinical pre-post intervention design, masking will not be possible.
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|
| Uganda intervention implementation | Experimental | Hospital nurses will triage participants using the digital triage tool (mhealth intervention) |
|
| Uganda control implementation | Active Comparator | Hospital nurses will triage participants using the Emergency Triage and Treatment (ETAT) guidelines, the triage policy that is currently in place at the study hospital sites. |
|
|
| Emergency Triage and Treatment (ETAT) guidelines | Other | These are the triage guidelines currently applied in the study hospital sites. This will be the comparator group. |
|
| Admission | Admission to hospital | 12 hours |
| Clinical Diagnosis | The clinical diagnosis for each participant | 12 hours |
| Length of Stay | Length of stay in hospital for admitted cases | 7 days |
| Nairobi |
| Kenya |
| Jinja Regional Referral Hospital | Jinja | Uganda |
| Derived |
| Li ECK, Tagoola A, Komugisha C, Nabweteme AM, Pillay Y, Ansermino JM, Khowaja AR. Cost-effectiveness analysis of Smart Triage, a data-driven pediatric sepsis triage platform in Eastern Uganda. BMC Health Serv Res. 2023 Aug 31;23(1):932. doi: 10.1186/s12913-023-09977-5. |
| 34788338 | Derived | Li ECK, Grays S, Tagoola A, Komugisha C, Nabweteme AM, Ansermino JM, Mitton C, Kissoon N, Khowaja AR. Cost-effectiveness analysis protocol of the Smart Triage program: A point-of-care digital triage platform for pediatric sepsis in Eastern Uganda. PLoS One. 2021 Nov 17;16(11):e0260044. doi: 10.1371/journal.pone.0260044. eCollection 2021. |
| 32493319 | Derived | Mawji A, Li E, Komugisha C, Akech S, Dunsmuir D, Wiens MO, Kissoon N, Kenya-Mugisha N, Tagoola A, Kimutai D, Bone JN, Dumont G, Ansermino JM. Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool. BMC Health Serv Res. 2020 Jun 3;20(1):493. doi: 10.1186/s12913-020-05344-w. |
Open access to all study materials and data |
| BG002 | Kenya Control Baseline | Baseline cohort at Kenya control site |
| BG003 | Kenya Control Implementation | Implementation cohort at Kenya control site |
| BG004 | Uganda Intervention Baseline | Baseline cohort at Uganda intervention site |
| BG005 | Uganda Intervention Implementation | Implementation cohort at Uganda implementation site |
| BG006 | Uganda Control Implementation | Implementation cohort at Uganda control site |
| BG007 | Total | Total of all reporting groups |
| Months |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Race and Ethnicity Not Collected | Race and Ethnicity were not collected from any participant. | Count of Participants | Participants |
|
| Time to antimicrobial administration | This study is not a randomized trial. Each cohort has bassline observations however the time to antibiotic administration is an outcome. This is reported as an outcome | Median | Inter-Quartile Range | Minutes |
|
| OG002 | Kenya Control Baseline | Baseline cohort at the Kenya control site |
| OG003 | Kenya Control Implementation | Implementation cohort at the Kenya control site |
| OG004 | Uganda Intervention Baseline | Baseline cohort at Uganda intervention site |
| OG005 | Uganda Intervention Implementation | Implementation cohort at the Uganda intervention site |
| OG006 | Uganda Control Implementation | Implementation cohort at Uganda control site |
|
|
| Other Pre-specified | Readmission | The child is readmitted to the hospital after being discharged | All participants | Posted | Count of Participants | Participants | 7 days |
|
|
|
| Other Pre-specified | Mortality | Death within 7 days | All participants | Posted | Count of Participants | Participants | 7 days |
|
|
|
| Other Pre-specified | Admission | Admission to hospital | All enrolled children | Posted | Count of Participants | Participants | 12 hours |
|
|
|
|
| Other Pre-specified | Clinical Diagnosis | The clinical diagnosis for each participant | All participants. | Posted | Count of Participants | Participants | 12 hours |
|
|
|
| Other Pre-specified | Length of Stay | Length of stay in hospital for admitted cases | Posted | Median | Inter-Quartile Range | Days | 7 days |
|
|
|
| Post-Hoc | Number of Intravenous Antimicrobials in Admitted Cases | Number cases receiving antimicrobials in the cohort of admitted cases | Participants admitted to hospital | Posted | Count of Participants | Participants | 24 hours |
|
|
|
| 2,856 |
| 0 |
| 2,856 |
| 0 |
| 2,856 |
| EG001 | Kenya Intervention Implementation | Implementation cohort at Kenya intervention site | 10 | 3,428 | 0 | 3,428 | 0 | 3,428 |
| EG002 | Kenya Control Baseline | Baseline cohort at Kenya control site | 11 | 2,520 | 0 | 2,520 | 0 | 2,520 |
| EG003 | Kenya Control Implementation | Implementation cohort at Kenya control site | 10 | 3,177 | 0 | 3,177 | 0 | 3,177 |
| EG004 | Uganda Intervention Baseline | Baseline cohort at Uganda intervention site | 11 | 1,408 | 0 | 1,408 | 0 | 1,408 |
| EG005 | Uganda Intervention Implementation | Implementation cohort at Uganda intervention site | 4 | 1,903 | 0 | 1,903 | 0 | 1,903 |
| EG006 | Uganda Control Implementation | Implementation cohort at Uganda control site | 2 | 2,855 | 0 | 2,855 | 0 | 2,855 |
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| Male |
|
| Broncholitis |
|
| Diarrhea/ Gastro |
|
| Meningitis |
|
| Malnutrition |
|
| Septicemia |
|
| Neonatal sepsis |
|
| Dehydration |
|
| Other |
|