Infection, Sepsis
Conditions
Keywords
triage, developing countries
Brief summary
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.
Detailed description
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)
Interventions
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.
These are the triage guidelines currently applied in the study hospital sites. This will be the comparator group.
Sponsors
Study design
Masking description
Due to the clinical pre-post intervention design, masking will not be possible.
Intervention model description
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.
Eligibility
Inclusion criteria
* All paediatric outpatients presenting to the study hospitals for medical treatment. The lower age limit will include children aged from 0 days, and the upper age limit will be in accordance to respective hospitals' practice for paediatric admissions (this may be 12, 15 or 19 years). * Informed parental/guardian consent provided. * Assent from children older than 13 years in addition to parental/guardian consent provided.
Exclusion criteria
-Patients presenting to the outpatient department for elective cases (e.g. elective surgery or change of dressing) or for clinical review appointment.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Time to Administration of an Appropriate Antimicrobial | 1 day | 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. |
Other
| Measure | Time frame | Description |
|---|---|---|
| Readmission | 7 days | The child is readmitted to the hospital after being discharged |
| Mortality | 7 days | Death within 7 days |
| Admission | 12 hours | Admission to hospital |
| Clinical Diagnosis | 12 hours | The clinical diagnosis for each participant |
| Length of Stay | 7 days | Length of stay in hospital for admitted cases |
Countries
Kenya, Uganda
Participant flow
Recruitment details
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:
Pre-assignment details
Non infectious illness, routine clinic visit
Participants by arm
| Arm | Count |
|---|---|
| Kenya Intervention Baseline Baseline cohort at Kenya intervention site | 2,856 |
| Kenya Intervention Implementation Implementation cohort at Kenya implementation site | 3,428 |
| Kenya Control Baseline Baseline cohort at Kenya control site | 2,520 |
| Kenya Control Implementation Implementation cohort at Kenya control site | 3,177 |
| Uganda Intervention Baseline Baseline cohort at Uganda intervention site | 1,408 |
| Uganda Intervention Implementation Implementation cohort at Uganda implementation site | 1,903 |
| Uganda Control Implementation Implementation cohort at Uganda control site | 2,855 |
| Total | 18,147 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 | FG002 | FG003 | FG004 | FG005 | FG006 |
|---|---|---|---|---|---|---|---|---|
| Overall Study | incomplete triage data | 0 | 69 | 0 | 0 | 289 | 123 | 65 |
Baseline characteristics
| Characteristic | Kenya Intervention Implementation | Kenya Control Baseline | Kenya Control Implementation | Uganda Intervention Baseline | Uganda Intervention Implementation | Uganda Control Implementation | Total | Kenya Intervention Baseline |
|---|---|---|---|---|---|---|---|---|
| Age, Continuous | 31.2 Months | 17.55 Months | 13.3 Months | 13.55 Months | 15 Months | 17.3 Months | 22.4 Months | 25 Months |
| Race and Ethnicity Not Collected | — | — | — | — | — | — | 0 Participants | — |
| Sex: Female, Male Female | 1466 Participants | 1207 Participants | 1504 Participants | 676 Participants | 908 Participants | 1418 Participants | 8431 Participants | 1252 Participants |
| Sex: Female, Male Male | 1962 Participants | 1313 Participants | 1673 Participants | 732 Participants | 995 Participants | 1437 Participants | 9716 Participants | 1604 Participants |
| Time to antimicrobial administration | 123 Minutes | 239 Minutes | 261 Minutes | 255 Minutes | 239 Minutes | 212 Minutes | 206 Minutes | 115 Minutes |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk | EG004 affected / at risk | EG005 affected / at risk | EG006 affected / at risk |
|---|---|---|---|---|---|---|---|
| deaths Total, all-cause mortality | 29 / 2,856 | 10 / 3,428 | 11 / 2,520 | 10 / 3,177 | 11 / 1,408 | 4 / 1,903 | 2 / 2,855 |
| other Total, other adverse events | 0 / 2,856 | 0 / 3,428 | 0 / 2,520 | 0 / 3,177 | 0 / 1,408 | 0 / 1,903 | 0 / 2,855 |
| serious Total, serious adverse events | 0 / 2,856 | 0 / 3,428 | 0 / 2,520 | 0 / 3,177 | 0 / 1,408 | 0 / 1,903 | 0 / 2,855 |
Outcome results
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.
Time frame: 1 day
Population: Children presenting to the outpatient department at facility
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Kenya Intervention Baseline | Time to Administration of an Appropriate Antimicrobial | 115 minutes |
| Kenya Intervention Implementation | Time to Administration of an Appropriate Antimicrobial | 123 minutes |
| Kenya Control Baseline | Time to Administration of an Appropriate Antimicrobial | 239 minutes |
| Kenya Control Implementation | Time to Administration of an Appropriate Antimicrobial | 261 minutes |
| Uganda Intervention Baseline | Time to Administration of an Appropriate Antimicrobial | 255 minutes |
| Uganda Intervention Implementation | Time to Administration of an Appropriate Antimicrobial | 239 minutes |
| Uganda Control Implementation | Time to Administration of an Appropriate Antimicrobial | 212 minutes |
Admission
Admission to hospital
Time frame: 12 hours
Population: All enrolled children
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Kenya Intervention Baseline | Admission | 581 Participants |
| Kenya Intervention Implementation | Admission | 474 Participants |
| Kenya Control Baseline | Admission | 452 Participants |
Clinical Diagnosis
The clinical diagnosis for each participant
Time frame: 12 hours
Population: All participants.
| Arm | Measure | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| Kenya Intervention Baseline | Clinical Diagnosis | Malaria | 131 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Pneumonia | 139 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Broncholitis | 3 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Diarrhea/ Gastro | 15 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Meningitis | 11 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Malnutrition | 17 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Septicemia | 58 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Neonatal sepsis | 12 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Dehydration | 20 Participants |
| Kenya Intervention Baseline | Clinical Diagnosis | Other | 161 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Dehydration | 12 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Malaria | 100 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Malnutrition | 5 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Meningitis | 6 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Pneumonia | 154 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Other | 123 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Neonatal sepsis | 32 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Broncholitis | 5 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Septicemia | 23 Participants |
| Kenya Intervention Implementation | Clinical Diagnosis | Diarrhea/ Gastro | 12 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Neonatal sepsis | 17 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Diarrhea/ Gastro | 12 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Meningitis | 5 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Malnutrition | 8 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Dehydration | 20 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Septicemia | 75 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Malaria | 85 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Other | 123 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Pneumonia | 104 Participants |
| Kenya Control Baseline | Clinical Diagnosis | Broncholitis | 2 Participants |
Length of Stay
Length of stay in hospital for admitted cases
Time frame: 7 days
| Arm | Measure | Value (MEDIAN) |
|---|---|---|
| Kenya Intervention Baseline | Length of Stay | 4 Days |
| Kenya Intervention Implementation | Length of Stay | 4 Days |
| Kenya Control Baseline | Length of Stay | 4 Days |
Mortality
Death within 7 days
Time frame: 7 days
Population: All participants
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Kenya Intervention Baseline | Mortality | 39 Participants |
| Kenya Intervention Implementation | Mortality | 23 Participants |
| Kenya Control Baseline | Mortality | 14 Participants |
Number of Intravenous Antimicrobials in Admitted Cases
Number cases receiving antimicrobials in the cohort of admitted cases
Time frame: 24 hours
Population: Participants admitted to hospital
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Kenya Intervention Baseline | Number of Intravenous Antimicrobials in Admitted Cases | 512 Participants |
| Kenya Intervention Implementation | Number of Intravenous Antimicrobials in Admitted Cases | 361 Participants |
| Kenya Control Baseline | Number of Intravenous Antimicrobials in Admitted Cases | 406 Participants |
Readmission
The child is readmitted to the hospital after being discharged
Time frame: 7 days
Population: All participants
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Kenya Intervention Baseline | Readmission | 57 Participants |
| Kenya Intervention Implementation | Readmission | 57 Participants |
| Kenya Control Baseline | Readmission | 48 Participants |