Dynamic electronic decision trees for managing childhood illness (DYNAMIC)
Every year, more than five million children die before the age of five due to preventable or treatable causes, most of them in developing countries. New technologies combined with rapid tests can improve diagnosis and management of sick children and reduce health costs. This collaborative research project makes use of Switzerland’s knowledge in digital technologies to improve the health of children and reduce unnecessary antibiotic prescriptions in low resource settings.
| Paese/Regione | Tema | Periodo | Budget |
|---|---|---|---|
|
Mondo Ruanda Tanzania |
Sanità Altro
Assistenza sanitaria primaria
Sector not specified Servizi medici Rafforzamento dei sistemi sanitari |
15.11.2019
- 31.12.2024 |
CHF 3’910’000
|
- Central State of South East
- Settore privato svizzero
- universitelausanne
-
Settore in base alle categorie del Comitato di Aiuto allo sviluppo (DAC) dell'OCSE SALUTE
Unallocated / Unspecified
SALUTE
SALUTE
Sotto-Settore in base alle categorie del Comitato di Aiuto allo sviluppo (DAC) dell'OCSE Infrastruttura per i servizi sanitari di base
Sectors not specified
Servizi medici
Politica sanitaria e gestione amministrativa
Tipo di aiuto Mandato senza fondo fiduciario
Contributo al progetto e al programma
Numero del progetto 7F10361
| Contesto | Children are a vulnerable population group that suffers most of acute illnesses. In most low and middle-income countries significant improvements in healthcare have been achieved in the last decades. However, the diagnosis and management of sick children at primary care level often remains inadequate. Health professionals have limited skills, diagnostic tools are missing, and practical guidelines are inconsistent and quickly outdated. Digital decision making tools for primary health care workers are very cost-effective instruments that can greatly improve care for sick children, rationalize antibiotic use, and strengthen referral decisions. The safety of a novel electronic point-of-care clinical algorithm (ePOCT) was validated through a first clinical trial conducted in Tanzania and supported by SDC in the framework of its research for development (r4d) programme. Further validation studies are now needed to improve and extend the scope of the ePOCT tool. |
| Obiettivi | To improve the quality of care for children aged 0-12 years in low resource settings by validating and implementing a novel electronic point-of-care clinical algorithm (ePOCT) that guide and train health workers in the diagnosis and management of sick children. |
| Gruppi target |
Primary beneficiaries: sick children aged 0 days to 12 years and their families attending primary health care facilities Secondary beneficiaries: surrounding communities, health workers, health administrators and managers, health ministries |
| Effetti a medio termine |
Outcome 1: Integrated management of children with acute illnesses at primary care level is improved Outcome 2: The national health information system for disease surveillance and early epidemic detection is enhanced Outcome 3. Clinical algorithms are improved and continuously adapted to geographical and seasonal variations using machine-learning Outcome 4: Antimicrobial drug pressure in the community is decreased Outcome 5: The environment for sustainability of electronic clinical decision support algorithms and framework for larger-scale implementation is supportive |
| Risultati |
Risultati fasi precedenti: The safety of ePOCT was asessed and validated through a first clinical trial conducted in urban Tanzania. The use of ePOCT led to an improvement in clinical outcome while reducing by 88% the proportion of antibiotic prescriptions. |
| Direzione/Ufficio responsabile |
DSC |
| Credito |
Cooperazione allo sviluppo |
| Partner del progetto |
Partner contrattuale Economia privata Instituzione statale straniera Instituzione universitaria e di ricerca svizzera |
| Budget | Fase in corso Budget Svizzera CHF 3’910’000 Budget svizzero attualmente già speso CHF 3’843’250 |
| Fasi del progetto | Fase 1 15.11.2019 - 31.12.2024 (Fase in corso) |
