Towards good practice for health statistics: lessons from the Millennium Development Goal health indicators.
Towards good practice for health statistics: lessons from the Millennium Development Goal health indicators.
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DOI：
10.1016/s0140-6736(07)60415-2
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发表时间：
2007-03-10
期刊：
影响因子：
--
通讯作者：
Murray CJ
中科院分区：
文献类型：
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作者：
Murray CJ
卫生统计是越来越多的世界卫生争议的中心问题。若干因素加剧了高质量卫生信息供需之间的紧张关系，与卫生有关的千年发展目标提供了一个引人注目的例子。由于建议的指标数以千计，但衡量良好的指标很少，世界卫生界需要集中精力改进对少数优先领域的衡量。优先指标的选择应基于公共卫生的重要性和可测量性的几个方面。卫生统计可分为三种类型：原始统计、修正统计和预测统计。卫生统计是规划和战略决策、方案执行、监测实现目标的进展情况以及评估哪些有效哪些无效的必要投入。有偏见的粗略统计数据在这些步骤中都不起作用；正确的统计数据优先。对于战略决策，当无法获得正确的统计数据时，预测统计数据可以发挥重要作用。但是，为了监测达成商定目标的进展情况和评估哪些有效，哪些无效，不应使用预测的统计数字。减少对卫生统计的争议和鼓励更好地收集初级数据和发展更好的分析方法的最有效方法也许是坚定地承诺提供明确的数据审计跟踪。这项倡议将向公众提供原始数据、所有数据收集后的调整、包括用于预测和预测的协变量在内的模型以及必要的文件。
Health statistics are at the centre of an increasing number of worldwide health controversies. Several factors are sharpening the tension between the supply and demand for high quality health information, and the health-related Millennium Development Goals (MDGs) provide a high-profile example. With thousands of indicators recommended but few measured well, the worldwide health community needs to focus its efforts on improving measurement of a small set of priority areas. Priority indicators should be selected on the basis of public-health significance and several dimensions of measurability. Health statistics can be divided into three types: crude, corrected, and predicted. Health statistics are necessary inputs to planning and strategic decision making, programme implementation, monitoring progress towards targets, and assessment of what works and what does not. Crude statistics that are biased have no role in any of these steps; corrected statistics are preferred. For strategic decision making, when corrected statistics are unavailable, predicted statistics can play an important part. For monitoring progress towards agreed targets and assessment of what works and what does not, however, predicted statistics should not be used. Perhaps the most effective method to decrease controversy over health statistics and to encourage better primary data collection and the development of better analytical methods is a strong commitment to provision of an explicit data audit trail. This initiative would make available the primary data, all post-data collection adjustments, models including covariates used for farcasting and forecasting, and necessary documentation to the public.