Cape Coast Teaching Hospital, Cape Coast, Ghana.
Department of Health Information Management, University of Cape Coast, Cape Coast, Ghana.
PLoS One. 2021 Mar 4;16(3):e0239049. doi: 10.1371/journal.pone.0239049. eCollection 2021.
Cause-specific mortality data are required to set interventions to reduce neonatal mortality. However, in many developing countries, these data are either lacking or of low quality. We assessed the completeness and accuracy of cause of death (COD) data for neonates in Ghana to assess their usability for monitoring the effectiveness of health system interventions aimed at improving neonatal survival.
A lot quality assurance sampling survey was conducted in 20 hospitals in the public sector across four regions of Ghana. Institutional neonatal deaths (IND) occurring from 2014 through 2017 were divided into lots, defined as neonatal deaths occurring in a selected facility in a calendar year. A total of 52 eligible lots were selected: 10 from Ashanti region, and 14 each from Brong Ahafo, Eastern and Volta region. Nine lots were from 2014, 11 from 2015 and 16 each were from 2016 and 2017. The cause of death (COD) of 20 IND per lot were abstracted from admission and discharge (A&D) registers and validated against the COD recorded in death certificates, clinician's notes or neonatal death audit reports for consistency. With the error threshold set at 5%, ≥ 17 correctly matched diagnoses in a sample of 20 deaths would make the lot accurate for COD diagnosis. Completeness of COD data was measured by calculating the proportion of IND that had death certificates completed.
Nineteen out of 52 eligible (36.5%) lots had accurate COD diagnoses recorded in their A&D registers. The regional distribution of lots with accurate COD data is as follows: Ashanti (4, 21.2%), Brong Ahafo (7, 36.8%), Eastern (4, 21.1%) and Volta (4, 21.1%). Majority (9, 47.4%) of lots with accurate data were from 2016, followed by 2015 and 2017 with four (21.1%) lots. Two (10.5%) lots had accurate COD data in 2014. Only 22% (239/1040) of sampled IND had completed death certificates.
Death certificates were not reliably completed for IND in a sample of health facilities in Ghana from 2014 through 2017. The accuracy of cause-specific mortality data recorded in A&D registers was also below the desired target. Thus, recorded IND data in public sector health facilities in Ghana are not valid enough for decision-making or planning. Periodic data quality assessments can determine the magnitude of the data quality concerns and guide site-specific improvements in mortality data management.
需要特定原因死亡率数据来制定干预措施以降低新生儿死亡率。然而,在许多发展中国家,这些数据要么缺乏,要么质量低下。我们评估了加纳公共部门 20 家医院新生儿死因(COD)数据的完整性和准确性,以评估其用于监测旨在改善新生儿生存的卫生系统干预措施效果的可用性。
在加纳四个地区的 20 家公立医院进行了大量质量保证抽样调查。2014 年至 2017 年期间发生的机构内新生儿死亡(IND)分为多个批次,定义为在选定年份在选定机构发生的新生儿死亡。共选择了 52 个合格批次:阿散蒂地区 10 个,布隆阿哈福、东部和沃尔特地区各 14 个。其中 9 个批次来自 2014 年,11 个来自 2015 年,16 个来自 2016 年和 2017 年。从入院和出院(A&D)登记册中提取每个批次 20 例 IND 的死因(COD),并与死亡证明、临床医生记录或新生儿死亡审计报告中记录的 COD 进行核对,以确定一致性。错误阈值设定为 5%,20 例死亡中有 17 例正确匹配的诊断,则该批 COD 诊断准确。通过计算有死亡证明的 IND 比例来衡量 COD 数据的完整性。
52 个合格批次中有 19 个(36.5%)在其 A&D 登记册中记录了准确的 COD 诊断。具有准确 COD 数据的批次的区域分布如下:阿散蒂(4,21.2%)、布隆阿哈福(7,36.8%)、东部(4,21.1%)和沃尔特(4,21.1%)。大多数(9,47.4%)准确数据的批次来自 2016 年,其次是 2015 年和 2017 年,各有 4 个(21.1%)批次。2014 年有 2 个(10.5%)批次的 COD 数据准确。2014 年至 2017 年期间,只有 22%(239/1040)的抽样 IND 完成了死亡证明。
2014 年至 2017 年期间,加纳样本医疗机构的 IND 死亡证明并未可靠填写。A&D 登记册中记录的特定原因死亡率数据的准确性也低于预期目标。因此,加纳公立部门卫生机构记录的 IND 数据不足以用于决策或规划。定期进行数据质量评估可以确定数据质量问题的严重程度,并指导特定地点改善死亡率数据管理。