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数据驱动的健康干预平台对埃塞俄比亚北谢瓦地区卫生办公室工作人员数据决策文化的影响:一项整群随机对照试验。

Effect of the data-informed platform for health intervention on the culture of data use for decision-making among district health office staff in North Shewa Zone, Ethiopia: a cluster-randomised controlled trial.

机构信息

Health System and reproductive health research directorate, Ethiopian Public Health Institute, Addis Ababa, Ethiopia.

London School of Hygiene and Tropical Medicine, London, UK.

出版信息

BMC Med Inform Decis Mak. 2024 Jul 5;24(1):190. doi: 10.1186/s12911-024-02597-x.

Abstract

BACKGROUND

Similar to other low and middle-income countries, Ethiopia faces limitations in using local health data for decision-making.We aimed to assess the effect of an intervention, namely the data-informed platform for health, on the culture of data-based decision making as perceived by district health office staff in Ethiopia's North Shewa Zone.

METHODS

By designating district health offices as 'clusters', a cluster-randomised controlled trial was implemented. Out of a total of 24 districts in the zone, 12 districts were allocated to intervention arm and the other 12 in the control group arms. In the intervention arm district health office teams were supported in four-monthly cycles of data-driven decision-making over 20 months. This support included: (a) defining problems using a health system framework; (b) reviewing data; (c) considering possible solutions; (d) value-based prioritizing; and (e) a consultative process to develop, commit to, and follow up on action plans. To measure the culture of data use for decision-making in both intervention and control arms, we interviewed 120 health management staff (5 per district office). Using a Likert scale based standard Performance of Routine Information System Management tool, the information is categorized into six domains:- evidence-based decision making, emphasis on data quality, use of information, problem solving, responsibility and motivation. After converting the Likert scale responses into percentiles, difference-in-difference methods were applied to estimate the net effect of the intervention. In intervention districts, analysis of variance was used to summarize variation by staff designation.

RESULTS

The overall decision-making culture in health management staff showed a net improvement of 13% points (95% C.I:9, 18) in intervention districts. The net effect of each of the six domains in turn was an 11% point increase (95% C.I:7, 15) on culture of evidence based decision making, a 16% point increase (95% C.I:8, 24) on emphasis on data quality, a 20% point increase (95% C.I:12, 28) on use of information, a 21% point increase (95% C.I:13, 29) on problem solving, and a 10% point increase (95% C.I:4, 16) on responsibility and motivation. In terms of variation by staff designation within intervention districts, statistically significant differences were observed only for problem solving and responsibility.

CONCLUSION

The data-informed platform for health strategy resulted in a measurable improvement in data use and structured decision-making culture by using existing systems, namely the Performance Monitoring Team meetings. The intervention supported district health offices in identifying and solving problems through a structured process. After further research, DIPH intervention could also be applied to other health administration and facility levels.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT05310682, Dated 25/03/ 2022.

摘要

背景

与其他中低收入国家一样,埃塞俄比亚在利用当地卫生数据进行决策方面存在局限性。我们旨在评估干预措施(即数据驱动的卫生平台)对埃塞俄比亚北舍瓦地区卫生办公室工作人员对基于数据的决策文化的影响。

方法

通过将卫生办公室指定为“集群”,实施了一项集群随机对照试验。在该地区总共 24 个区中,有 12 个区被分配到干预组,其余 12 个区被分配到对照组。在干预组的区卫生办公室团队在 20 个月内每四个月进行一次数据驱动的决策。这种支持包括:(a)使用卫生系统框架定义问题;(b)审查数据;(c)考虑可能的解决方案;(d)基于价值的优先排序;(e)制定、承诺和跟踪行动计划的协商过程。为了衡量干预组和对照组中数据用于决策的文化,我们采访了 120 名卫生管理人员(每个区办公室 5 名)。使用基于李克特量表的标准常规信息系统管理工具,信息分为六个领域:-基于证据的决策制定、强调数据质量、信息使用、解决问题、责任和动机。将李克特量表的反应转换为百分位数后,采用差值法估计干预的净效果。在干预区,方差分析用于按员工职位总结差异。

结果

在卫生管理工作人员中,整体决策文化总体上表现出 13%的净改善(95%置信区间:9,18)。每个六个领域的净效应依次为基于证据的决策制定文化增加 11%(95%置信区间:7,15),强调数据质量增加 16%(95%置信区间:8,24),信息使用增加 20%(95%置信区间:12,28),解决问题增加 21%(95%置信区间:13,29),责任和动机增加 10%(95%置信区间:4,16)。就干预区内部员工职位的变化而言,仅在解决问题和责任方面观察到具有统计学意义的差异。

结论

通过使用现有的系统,即绩效监测团队会议,数据驱动的卫生平台战略导致数据使用和结构化决策文化的可衡量改善。该干预措施支持区卫生办公室通过结构化流程识别和解决问题。经过进一步研究,DIPH 干预措施也可以应用于其他卫生管理和设施层面。

试验注册

ClinicalTrials.gov ID:NCT05310682,日期:2022 年 3 月 25 日。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b471/11225382/bc002b823785/12911_2024_2597_Fig1_HTML.jpg

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