加强马来西亚卫生方案死亡率统计:来自实地的经验教训

C. Rao, M. A. Omar, S. Ganapathy, N. I. Tamin
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引用次数: 4

摘要

马来西亚是少数几个拥有长期生命登记系统历史的亚洲国家之一。然而,数据质量问题限制了现有生命统计数据在公共卫生政策、项目评估和研究中的应用[1,2]。虽然马来西亚半岛各州的死亡登记已经完成,但东部沙巴州和沙捞越州仍然存在轻微少报死亡人数的问题。然而,马来西亚国家注册局(Jabatan Pendaftaran Negara, JPN)最近发起了一项倡议,以解决这些州的注册规则和基础设施问题。更令人关切的是,登记的死亡原因质量差。在马来西亚,大约50%的死亡发生在医院,并以医学证明的原因进行登记,这些原因质量良好。然而,其余在家中发生的死亡由家庭成员报告死因进行登记。出于统计目的,这些被称为“非医学证明的死亡”。每年,只有大约三分之一的死亡是由特定原因造成的,其余65-70%的死亡是每年登记的,原因含糊不清,包括“老年”、“心力衰竭”和“猝死”等。在估计2000年和2008年的全国死亡率和疾病负担时,生命登记数据的这些限制要求使用基于通用模型的调整来填补这些数据空白[4,5]。即使在2009年至2017年的最近时期,仍然可以观察到这些持续高比例的不明确原因(图1)。
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Strengthening Mortality Statistics for Health Programs in Malaysia: Lessons from the Field
Malaysia is one of a few Asian countries with a longstanding history of vital registration systems. Yet, issues with data quality have limited the utility of available vital statistics for public health policy, program evaluation, and research [1,2]. Although death registration is complete for states located on Peninsular Malaysia, the problem of marginal underreporting of deaths still persists in the eastern states of Sabah and Sarawak [3]. However, initiatives have been recently launched by the Malaysian National Registration Department [Jabatan Pendaftaran Negara (JPN)] to resolve issues with registration rules and infrastructure in these states. The more significant concern lies with the poor quality of registered causes of death. About 50% of all deaths in Malaysia occur in hospitals and are registered with medically certified causes, which are of good quality. However, the remaining deaths that occur at home are registered with causes reported by family members. For statistical purposes, these are termed as “nonmedically certified deaths.” Each year, only about a third of these deaths are reported to be from specific causes, and the remaining 65–70% of these deaths are registered annually with vague and ill-defined causes including “old age,” “heart failure,” and “sudden death” [3]. These limitations in vital registration data necessitated the use of generic model-based adjustments to fill these data gaps, while estimating national mortality and burden of disease estimation for the years 2000 and 2008 [4,5]. These persistently high proportions of illdefined causes can still be observed even for the most recent period from 2009 to 2017 (Figure 1).
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