评估利用公开数据源确定医疗保健数据差异并加强服务提供的可行性:对四个人类指数得分较低国家的回顾性横截面研究

Alix Boisson-Walsh, Jack Lewis, M. Neilson, Sheila Leatherman
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摘要

尽管全球都在努力推动全民医保,但在人类发展指数(LHDIS)较低的国家,医疗质量(QoC)仍然是一项长期存在的挑战。要在人类发展指数低的国家解决根本原因并系统地实施改善干预措施,就必须更好地理解和使用医疗质量数据。我们旨在描述数据差距,并说明一小部分国家的医疗服务质量状况。我们利用人口健康调查 (DHS) 和服务提供评估 (SPA) 这两个公共数据来源,选择了相关的质量指标,并将其归类到质量控制矩阵中。我们根据脆弱、受冲突影响和易受伤害环境下的医疗质量框架领域和多纳比德模型来选择衡量标准。我们的回顾性横断面研究的标准包括低密度人类发展信息系统,以及为数据相关性而提供的近期人口与健康调查和 SPA 数据。但是,指标矩阵中的某些单元格缺乏 SPA 和 DHS 数据中的合适指标。我们选择了刚果民主共和国、海地、阿富汗和塞内加尔,对这些国家的质量控制情况进行了简要介绍。比较结果表明,这些国家在一些领域取得了积极的成绩,也面临着共同的挑战,但在某些类别中存在明显的差异。塞内加尔的总体排名最高,而阿富汗在所有汇总表类别中排名最低。塞内加尔的数据最为全面,有 94.7% 的指标可用。这些结果清楚地表明,应进一步努力开发标准化、可公开获取、常规收集和验证的数据集,以衡量和公开报告 LHDIS 国家的质量状况,从而引起全球关注并采取行动,实现更显著的健康公平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries
Quality of care (QoC) remains a persistent challenge in countries with low Human Development Index scores (LHDIS) despite global efforts to promote universal health coverage. Addressing root causes and systematically implementing improvement interventions in LHDIS countries require a better understanding and use of QoC data. We aim to describe the data gaps and illustrate the state of quality in health services across a small set of countries. We demonstrate how we can leverage currently available, although imperfect, public data sources to compile quality metrics across multiple LHDIS countries.Using public data sources, the Demographic Health Survey (DHS) and Service Provision Assessment (SPA), we selected relevant quality metrics and categorised them within a QoC matrix. We based the selection of metrics on the quality of care in fragile, conflict-affected and vulnerable settings framework domains and the Donabedian model. Criteria for our retrospective cross-sectional study included a LHDIS and recent availability of both DHS and SPA data for data relevance.The approach was feasible, with relevant indicators distributed across various QoC categories. However, some cells in the indicator matrix lacked suitable indicators from SPA and DHS data. We selected the Democratic Republic of the Congo, Haiti, Afghanistan and Senegal for a snapshot of QoC in LHDIS countries. Comparisons highlighted areas of positive performance and shared challenges across these countries, with notable variability in certain categories. Senegal ranked highest overall, while Afghanistan ranked lowest across all matrix categories. Senegal had the most comprehensive data, with 94.7% of metrics available. Missing data existed for two specific metrics in all four countries, particularly within the improving clinical care domain.The results are a clarion call for advancing efforts to develop standardised, publicly available, routinely collected and validated data sets to measure and publicly report LHDIS countries’ state of quality to marshal global attention and action in pursuit of more significant health equity.
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