UCL Institute of Child Health, Great Ormond Street Hospital for Children, London, UK.
Division of Hospital Medicine, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, California, USA.
BMJ Open. 2021 May 18;11(5):e042124. doi: 10.1136/bmjopen-2020-042124.
To determine whether a panel of neonatal experts could address evidence gaps in local and international neonatal guidelines by reaching a consensus on four clinical decision algorithms for a neonatal digital platform (NeoTree).
Two-round, modified Delphi technique.
Participants were neonatal experts from high-income and low-income countries (LICs).
This was a consensus-generating study. In round 1, experts rated items for four clinical algorithms (neonatal sepsis, hypoxic ischaemic encephalopathy, respiratory distress of the newborn, hypothermia) and justified their responses. Items meeting consensus for inclusion (≥80% agreement) were incorporated into the algorithms. Items not meeting consensus were either excluded, included following revisions or included if they contained core elements of evidence-based guidelines. In round 2, experts rated items from round 1 that did not reach consensus.
Fourteen experts participated in round 1, 10 in round 2. Nine were from high-income countries, five from LICs. Experts included physicians and nurse practitioners with an average neonatal experience of 20 years, 12 in LICs. After two rounds, a consensus was reached on 43 of 84 items (52%). Per experts' recommendations, items in line with local and WHO guidelines yet not meeting consensus were still included to encourage consistency for front-line healthcare workers. As a result, the final algorithms included 53 items (62%).
Four algorithms in a neonatal digital platform were reviewed and refined by consensus expert opinion. Revisions to NeoTree will be made in response to these findings. Next steps include clinical validation of the algorithms.
通过就新生儿数字平台(Neotree)的四个临床决策算法达成共识,确定一组新生儿专家是否能够解决当地和国际新生儿指南中的证据空白。
两轮,改良 Delphi 技术。
参与者为高收入和低收入国家(LICs)的新生儿专家。
这是一项共识生成研究。在第一轮中,专家对四个临床算法(新生儿败血症、缺氧缺血性脑病、新生儿呼吸窘迫、低体温)的项目进行评分,并为其回答提供依据。符合纳入共识的项目(≥80%的一致性)被纳入算法。不符合共识的项目要么被排除,要么在修订后纳入,要么如果它们包含循证指南的核心要素,则纳入。在第二轮中,专家对第一轮未达成共识的项目进行评分。
共有 14 名专家参加了第一轮,10 名参加了第二轮。其中 9 人来自高收入国家,5 人来自 LICs。专家包括医生和执业护士,平均新生儿经验为 20 年,其中 12 人来自 LICs。两轮后,84 项中的 43 项(52%)达成共识。根据专家的建议,与当地和世卫组织指南一致但未达成共识的项目仍被纳入,以鼓励一线医护人员保持一致。因此,最终的算法包括 53 个项目(62%)。
通过共识专家意见审查和完善了新生儿数字平台中的四个算法。将根据这些发现对 Neotree 进行修订。下一步包括对算法进行临床验证。