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提高数据质量以改善印度尼西亚巴布亚省的疟疾监测。

Enhanced data quality to improve malaria surveillance in Papua, Indonesia.

作者信息

Fransisca Liony, Burdam Faustina Helena, Kenangalem Enny, Rahmalia Annisa, Ubra Reynold Rizal, van den Boogaard Christel H A, Ley Benedikt, Douglas Nicholas M, Poespoprodjo Jeanne Rini, Price Ric N

机构信息

Yayasan Pengembangan Kesehatan Dan Masyarakat Papua (YPKMP), Timika, Indonesia.

Menzies School of Health Research, Charles Darwin University, Darwin, Australia.

出版信息

Malar J. 2025 Jun 4;24(1):177. doi: 10.1186/s12936-025-05358-x.

Abstract

BACKGROUND

Papua has a high burden of malaria, with an annual parasite incidence 300 times the national average. A key component of malaria elimination strategies is robust surveillance which is essential for monitoring trends in case numbers, guiding public health interventions, and prioritizing resource allocation. This study aimed to enhance malaria surveillance in Central Papua, Indonesia, by improving data collection, record-keeping, and treatment practices.

METHODS

The study was conducted at five public clinics in Central Papua province, Indonesia, as part of a wider health systems strengthening programme to promote safer and more effective anti-malarial treatment (The SHEPPI Study). Clinical and laboratory details of patients with malaria and their treatment were documented in clinic registers which were digitalized into an electronic database. Automated reports were generated each month and used to provide regular feedback to clinic staff. Continuous Quality Improvement (CQI) workshops were conducted with clinic staff using the Plan-Do-Study-Act approach to address challenges and drive sustained improvements.

RESULTS

Between January 2019 and December 2023, a total of 314,561 patients were tested for malaria, of whom 41.9% (131,948) had peripheral parasitaemia detected. The first round of Continuous Quality Improvement (CQI) workshops were held in May 2019 and improved data quality significantly, increasing data completeness from 46.3% (4540/9802) in the initial period (Jan-May 2019) to 71.5% (9053/12,665) after the first CQI (Jun-Oct 2019), p < 0.001. The second CQI round reduced DHP prescribing errors from 17.1% (1111/6489) in the initial period to 5.7% (607/10,669) after the second CQI (Sep 2019-Jan 2020) and PQ prescribing errors from 17.4% (552/3175) to 3.4% (160/4659) over the same time interval, p < 001. In total, 347 patients were prescribed fewer than the recommended number of PQ tablets during the initial period, 89 (25.6%) of whom were erroneously given only a single dose. Over the 4 year study period, a total of 11 workshops were conducted, driving continuous improvements in data quality and prescribing practices.

CONCLUSION

One or two rounds of CQI, supported by regular follow-up, can enhance the quality of malariometric surveillance, however interventions needed to be tailored to address specific needs of participating clinics. Improvements in data quality and prescribing practices have potential to contribute to better malaria management, improved clinical outcomes, and strengthened trust in healthcare providers.

摘要

背景

巴布亚疟疾负担沉重,年寄生虫发病率是全国平均水平的300倍。疟疾消除战略的一个关键组成部分是强有力的监测,这对于监测病例数趋势、指导公共卫生干预措施以及确定资源分配优先级至关重要。本研究旨在通过改善数据收集、记录保存和治疗实践,加强印度尼西亚巴布亚中部的疟疾监测。

方法

该研究在印度尼西亚巴布亚中部省的五家公立诊所进行,作为更广泛的卫生系统加强计划的一部分,以促进更安全、更有效的抗疟治疗(SHEPPI研究)。疟疾患者的临床和实验室详细信息及其治疗情况记录在诊所登记簿中,并数字化到电子数据库。每月生成自动报告,并用于向诊所工作人员提供定期反馈。使用计划-执行-研究-行动方法与诊所工作人员举办持续质量改进(CQI)研讨会,以应对挑战并推动持续改进。

结果

2019年1月至2023年12月期间,共有314,561名患者接受了疟疾检测,其中41.9%(131,948)检测到外周血寄生虫血症。第一轮持续质量改进(CQI)研讨会于2019年5月举行,显著提高了数据质量,将初始阶段(2019年1月至5月)的数据完整性从46.3%(4540/9802)提高到第一次CQI之后(2019年6月至10月)的71.5%(9053/12,665),p<0.001。第二轮CQI将二氢青蒿素(DHP)处方错误率从初始阶段的17.1%(1111/6489)降低到第二次CQI之后(2019年9月至2020年1月)的5.7%(607/10,669),在同一时间间隔内,哌喹(PQ)处方错误率从17.4%(552/3175)降低到3.4%(160/4659),p<0.001。在初始阶段,共有347名患者的PQ片剂处方少于推荐数量,其中89名(25.6%)仅错误地给予了单剂量。在4年的研究期间,共举办了11次研讨会,推动了数据质量和处方实践的持续改进。

结论

在定期随访的支持下,一到两轮CQI可以提高疟疾监测的质量,然而干预措施需要根据参与诊所的具体需求进行调整。数据质量和处方实践的改善有可能有助于更好地管理疟疾、改善临床结果以及增强对医疗服务提供者的信任。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a2c4/12135496/f7921c59d522/12936_2025_5358_Fig1_HTML.jpg

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