Antimicrobial resistance (AMR) is a major worldwide public health problem, with more than half of children in resource-constrained countries such as Tanzania prescribed antibiotics.
To address this challenge, various nations throughout the world have formulated national-level action plans. For example, clinical decision support algorithms (CDSAs) have demonstrated the ability to minimize antibiotic prescriptions in children between two and 60 months of age.
Study: A digital health algorithm to guide antibiotic prescription in pediatric outpatient care: a cluster randomized controlled trial. Image Credit: vectorfusionart / Shutterstock.com
About the study
In a recent study published in Nature Medicine, researchers assessed the effects of ePOCT+, a digital CDSA, against routine care on antimicrobial prescriptions and one-week clinical outcomes among critically sick children 15 years and younger presenting to primary care centers in Tanzania.
The DYNAMIC Tanzania open-label, pragmatic, parallel-group, cluster-randomized trial was conducted in 40 Tanzanian primary healthcare centers to address diagnoses and syndromes not identified by existing CDSAs. The study recruited 44,306 consultations from 59,875 children between two months and 14 years of age.
The intervention included supplying ePOCT+ facilities with the necessary information and technology infrastructure, a C-reactive protein (CRP) lateral flow test, a pulse oximeter, a hemoglobin test, supportive mentoring, and training.
Previous-generation clinical decision support algorithms, national and international clinical recommendations, and inputs from intra- and international experts were used to develop the algorithm. Moreover, the researchers visited the facilities every two to three months. They communicated with users by phone calls or group texts three or four times each month to solve any reported difficulties.
Dashboard results were shared through group chats to obtain feedback on ePOCT+ use and allow healthcare practitioners to compare antimicrobial prescriptions and uptake with those of other health facilities. Clinical training was offered to healthcare personnel based on Integrated Management of Childhood Illness (IMCI) chartbooks, with special training provided for the ePOCT+ algorithm in interventional centers and the electronic case report form (eCRF) for control-type facilities. The team assessed children needing care for eligibility and obtained their demographic data, which was recorded into eCRF.
The eCRF includes research questions to determine the provision of oral and systemic antibiotics and patient referrals for inpatient hospitalizations or additional outpatient examinations. The clinical signs and symptoms of the participants were documented in the algorithm during consultations.
At the individual patient level, coprimary outcomes included antibiotic prescriptions during the initial consultation and clinical failure on day seven. Secondary outcomes were unscheduled reattendance visits, non-referred secondary hospitalization, mortality, and referral for inpatient hospitalization during the initial consultation. Random effects-type logistic regression modeling was performed for the analysis.
The study included 68 participating councils' 259 health institutions, with 76% of consultations handled by the algorithm and 86% achieving day seven results. About 91% percent of healthcare consultations in regular care health institutions had final treatments recorded in the eCRF, whereas 84% had one-week outcomes determined.
Intervention health institutions had equivalent consultation numbers but significantly lower service availability and readiness assessment (SARA) scores. Malaria frequency was comparable in both research groups.
In the interventional health facilities, young infants below two months of age presented more often with convulsions, lethargy, or fever and less frequently with respiratory diseases. However, patients within this age group had comparable distributions in presenting symptoms.
Over a period of 11 months, 23,593 consultations from 20 ePOCT+ health institutions and 20,713 from 20 usual care facilities were performed. Compared to regular care, ePOCT+ use in intervention facilities reduced the coprimary outcome of antibiotic prescription to 23% compared to 70%.
The adjusted analyses indicated a 65% reduced probability of prescribing antibiotics on day zero. Using a cautious imputation analysis technique, antibiotic prescriptions in ePOCT+ facilities remained fewer than in regular care, with an adjusted absolute-type difference of 34%.
Following reattendance-case inclusion, the reduction in antibiotic prescriptions was comparable with an adjusted absolute-type difference of 45%. The percentage of individuals experiencing clinical failures within one week in ePOCT+ facilities was non-inferior to that in regular care facilities, with an adjusted relative risk (aRR) of 0.97 and no significant differences in secondary safety outcomes. However, on day seven, there was a substantial reduction in unnecessary reattendance visits.
The intervention more profoundly impacted antibiotic prescriptions on day zero among children with respiratory symptoms and in the two to 59-month age group. Antibiotic prescriptions were reduced by at least 25% in all prespecified categories, with infants under two months of age experiencing the lowest reduction.
The ePOCT+ algorithm significantly reduced antibiotic prescriptions for sick children under 15 in Tanzania. The study included 44,306 children and demonstrated a three-fold reduction in the likelihood of unwell children being prescribed antibiotics compared to regular care facilities.
- Tan, R., Kavishe, G., Luwanda, L. B., et al. (2023). A digital health algorithm to guide antibiotic prescription in pediatric outpatient care: a cluster randomized controlled trial. Nature Medicine. doi:10.1038/s41591-023-02633-9
Posted in: Child Health News | Medical Science News | Medical Research News | Medical Condition News | Healthcare News
Tags: Antibiotic, Antimicrobial Resistance, Children, Consultation, C-Reactive Protein, Fever, Frequency, Healthcare, Hemoglobin, Lethargy, Malaria, Medicine, Mortality, Primary Care, Protein, Public Health, Research, Respiratory, Technology
Pooja Toshniwal Paharia
Dr. based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.