A cluster randomized trial assessing the effect of a digital health algorithm on quality of care in Tanzania (DYNAMIC study).

PLOS digital health Pub Date : 2024-12-23 eCollection Date: 2024-12-01 DOI:10.1371/journal.pdig.0000694
Rainer Tan, Godfrey Kavishe, Alexandra V Kulinkina, Sabine Renggli, Lameck B Luwanda, Chacha Mangu, Geofrey Ashery, Margaret Jorram, Ibrahim Evans Mtebene, Peter Agrea, Humphrey Mhagama, Kristina Keitel, Marie-Annick Le Pogam, Nyanda Ntinginya, Honorati Masanja, Valérie D'Acremont
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Abstract

Digital clinical decision support tools have contributed to improved quality of care at primary care level health facilities. However, data from real-world randomized trials are lacking. We conducted a cluster randomized, open-label trial in Tanzania evaluating the use of a digital clinical decision support algorithm (CDSA), enhanced by point-of-care tests, training and mentorship, compared with usual care, among sick children 2 to 59 months old presenting to primary care facilities for an acute illness in Tanzania (ClinicalTrials.gov NCT05144763). The primary outcome was the mean proportion of 14 major Integrated Management of Childhood Illness (IMCI) symptoms and signs assessed by clinicians. Secondary outcomes included antibiotic prescription, counseling provided, and the appropriateness of antimalarial and antibiotic prescriptions. A total of 450 consultations were observed in 9 intervention and 9 control health facilities. The mean proportion of major symptoms and signs assessed in intervention health facilities was 46.4% (range 7.7% to 91.7%) compared to 26.3% (range 0% to 66.7%) in control health facilities, an adjusted difference of 15.1% (95% confidence interval [CI] 4.8% to 25.4%). Only weight, height, and pallor were assessed statistically more often when using the digital CDSA compared to controls. Observed antibiotic prescription was 37.3% in intervention facilities, and 76.4% in control facilities (adjusted risk ratio 0.5; 95% CI 0.4 to 0.7; p<0.001). Appropriate antibiotic prescription was 81.9% in intervention facilities and 51.4% in control facilities (adjusted risk ratio 1.5; 95% CI 1.2 to 1.8; p = 0.003). The implementation of a digital CDSA improved the mean proportion of IMCI symptoms and signs assessed in consultations with sick children, however most symptoms and signs were assessed infrequently. Nonetheless, antibiotics were prescribed less often, and more appropriately. Innovative approaches to overcome barriers related to clinicians' motivation and work environment are needed.

一项评估坦桑尼亚数字健康算法对护理质量影响的聚类随机试验(DYNAMIC研究)。
数字临床决策支持工具有助于提高初级保健一级卫生设施的护理质量。然而,缺乏现实世界随机试验的数据。我们在坦桑尼亚进行了一项集群随机、开放标签试验,评估了在坦桑尼亚因急性疾病到初级保健机构就诊的2至59个月大的患病儿童中,通过护理点测试、培训和指导,与常规护理相比,数字临床决策支持算法(CDSA)的使用情况(ClinicalTrials.gov NCT05144763)。主要结局是临床医生评估的14种主要儿童疾病综合管理(IMCI)症状和体征的平均比例。次要结局包括抗生素处方、提供的咨询以及抗疟药和抗生素处方的适宜性。在9个干预保健设施和9个对照保健设施共观察了450次咨询。干预卫生机构评估的主要症状和体征平均比例为46.4%(范围7.7%至91.7%),而对照卫生机构评估的主要症状和体征平均比例为26.3%(范围0%至66.7%),调整后差异为15.1%(95%可信区间[CI] 4.8%至25.4%)。与对照组相比,使用数字CDSA时,只有体重、身高和苍白被统计地评估得更多。观察到干预机构的抗生素处方率为37.3%,对照机构为76.4%(调整风险比0.5;95% CI 0.4 ~ 0.7;p
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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