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Created on : 04.03.2025 Last modified : 04.03.2025

Dynamic electronic decision trees to manage sick children in Tanzania - Phase 1 cRCT data
Master dataset from "Phase 1" cluster randomized trial

Tanzania, 2021 - 2022
DVMS

Reference ID

10.16909-dataset-58

DOI

Producer(s)

Valerie D'Acremont, Honorati Masanja, Nyanda Ntinginya

Collections

Department of Vulnerabilities and Social Medicine (DVMS)

Metadata

Identification

Survey ID number

10.16909-dataset-58
Title

Dynamic electronic decision trees to manage sick children in Tanzania - Phase 1 cRCT data
Subtitle

Master dataset from "Phase 1" cluster randomized trial
Abbreviation or Acronym

DYNAMIC TZ
Country
Name
Tanzania
Abstract

A pragmatic digital health project to improve quality of care and antibiotic stewardship in primary care level health facilities in Tanzania for the management of sick children less than 15 years of age. The data provided here are from the first open-label parellel group pragmatic cluster randomized trial in 40 health facilities in Tanzania to evaluate the impact of a digital clinical decision support algorithm compared to usual care on antibiotic prescribing and clinical outcome among children with an acute illness presenting to primary care health facilities.
Kind of Data

Clinical data [cli]
Unit of Analysis

Individual consultations

Version

Version Description

version 2: Edited, de-identified dataset, for internal use only
Version Date

2025-01-01

Scope

Notes

Clinical data: Symptoms, signs, test results, diagnoses, treatment, clinical outcome at D7, hospitalization, referral
Demographics: age, sex

Coverage

Geographic Coverage

Mbeya and Morogoro region
Councils in Morogoro region: Ulanga DC, Mlimba DC, Ifakara TC
Councils in Mbeya region: Mbeya CC, Mbeya DC
Semi-urban and rural areas

Producers and sponsors

Primary investigators
Name Affiliation
Valerie D'Acremont Unisanté, Center for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland
Honorati Masanja Ifakara Health Institute
Nyanda Ntinginya Mbeya Medical Research Center - NIMR
Funding Agency/Sponsor
Name Abbreviation Role
Fondation Botnar Funding
Swiss Development Cooperation SDC Funding

Sampling

Sampling Procedure

Sampling, randomization and masking
The 40 health facilities were randomly selected from all eligible health facilities in the participating councils following a 3:2 ratio between health facilities from the Morogoro and Mbeya region (to include more health facilities in the higher malaria transmission area). In addition, to include a representative sample of health centers compared to dispensaries, four health centers per region were included.

The sampled health facilities were then randomized (1:1) to ePOCT+ (intervention) or usual care (control). Randomization was stratified by region, council, level of health facility (health center versus dispensary) and attendance rate. An independent statistician in Switzerland was provided with the list of all eligible health facilities and performed computer-generated sampling and randomization. Intervention allocation by the study team was only shared with study investigators in Tanzania once all council leaders had confirmed the participation of their selected health facilities. The nature of the intervention did not allow for masking of the intervention to health-care providers, patients or study implementers.

Data collection

Dates of Data Collection
Start End
20211201 20221031
Mode of data collection
  • Other [oth]
Data Collection Notes

Overall, 59,875 children were screened for inclusion between 1 December 2021 and 31 October 2022, and 44,306 (74%) consultations were enrolled (23,593 in ePOCT+ health facilities and 20,713 in usual care health facilities). The first health facilities started enrolling patients on 1 December 2021, and the last health facilities started enrolling patients on 13 April 2022. A total of 28,243 unique patients were enrolled with a mean of 1.6 consultations per patient over the duration of the study. Among those enrolled in the intervention health facilities, 17,985 (76.2%) consultations were managed using ePOCT+, and day 7 outcome was ascertained in 20,355 consultations (86.3%). In usual care health facilities, 18,937 (91.4%) consultations had final treatment documented in the electronic case report form (eCRF), and 17,292 consultations (83.5%) had day 7 outcome ascertained. Information technology (IT) problems and power outages were reported by research assistants on respectively 293 (7.3%) and 245 (6.1%) health facility days in ePOCT+ facilities, and 160 (4.1%) and 245 (6.1%) health facility days in usual care facilities. Both issues contributed to children being prevented from enrollment in the study.

Data processing

Data Editing

Demographic information was collected and entered in the eCRF (ePOCT+ for intervention health facilities and eCRFs for usual care facilities within the data collection system medAL-reader) by registration research assistants. Clinical data was entered by the routine clinicians in both study arms, however clinical data limited in the control arm. 7 days after the initial consult research assistants made phone calls to all participants to collect data on clinical outcome, further healthcare use, and further use of additional medications not prescribed.

Access policy

Location of Data Collection

Unisanté Data repository
URL for Location of Data Collection

https://doi.org/10.16909/58

Data Access

Access authority
Name Affiliation Email
Valerie D'Acremont Unisanté, Center for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland valerie.dacremont@unisante.ch
Rainer Tan Unisanté, Center for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland rainer.tan@unisante.ch
Confidentiality
Is signing of a confidentiality declaration required? Confidentiality declaration text
yes All requests for use of data should be directed towards rainer.tan@unisante.ch or valerie.dacremont@unisante.ch
Availability Status

The access and use of this dataset is restricted to the intern team only.

Contacts

Contacts
Name Affiliation Email
Valerie D'Acremont Unisanté, Center for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland valerie.dacremont@unisante.ch
Rainer Tan Unisanté, Center for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland rainer.tan@unisante.ch
Study description in PDF

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