Cook Kayleigh R, Zeleke Zebenay B, Gebrehana Ephrem, Burssa Daniel, Yeshanew Bantalem, Michael Atkilt, Tediso Yoseph, Jaraczewski Taylor, Dodgion Chris, Beyene Andualem, Iverson Katherine R
Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
Department of Surgery, Bahir Dar University, Bahir Dar, Amhara Region, Ethiopia.
PLOS Glob Public Health. 2024 Mar 27;4(3):e0002600. doi: 10.1371/journal.pgph.0002600. eCollection 2024.
In 2015, the Ethiopian Federal Ministry of Health (FMOH) developed the Saving Lives through Safe Surgery (SaLTS) initiative to improve national surgical care. Previous work led to development and implementation of 15 surgical key performance indicators (KPIs) to standardize surgical data practices. The objective of this project is to investigate current practices of KPI data collection and assess quality to improve data management and strengthen surgical systems. The first portion of the study documented the surgical data collection process including methods, instruments, and effectiveness at 10 hospitals across 2 regions in Ethiopia. Secondly, data for KPIs of focus [1. Surgical Volume, 2. Perioperative Mortality Rate (POMR), 3. Adverse Anesthetic Outcome (AAO), 4. Surgical Site Infection (SSI), and 5. Safe Surgery Checklist (SSC) Utilization] were compared between registries, KPI reporting forms, and the DHIS2 (district health information system) electronic database for a 6-month period (January-June 2022). Quality was assessed based on data completeness and consistency. The data collection process involved hospital staff recording data elements in registries, quality officers calculating KPIs, completing monthly KPI reporting forms, and submitting data into DHIS2 for the national and regional health bureaus. Data quality verifications revealed discrepancies in consistency at all hospitals, ranging from 1-3 indicators. For all hospitals, average monthly surgical volume was 57 cases, POMR was 0.38% (13/3399), inpatient SSI rate was 0.79% (27/3399), AAO rate was 0.15% (5/3399), and mean SSC utilization monthly was 93% (100% median). Half of the hospitals had incomplete data within the registries, ranging from 2-5 indicators. AAO, SSC, and SSI were commonly missing data in registries. Non-standardized KPI reporting forms contributed significantly to the findings. Facilitators to quality data collection included continued use of registries from previous interventions and use of a separate logbook to document specific KPIs. Delayed rollout of these indicators in each region contributed to issues in data quality. Barriers involved variable indicator recording from different personnel, data collection tools that generate false positives (i.e. completeness of SSC defined as paper form filled out prior to patient discharge) or missing data because of reporting time period (i.e. monthly SSI may miss infections outside of one month), inadequate data elements in registries, and lack of standardized monthly KPI reporting forms. As the FMOH introduces new indicators and changes, we recommend continuous and consistent quality checks and data capacity building, including the use of routinely generated health information for quality improvement projects at the department level.
2015年,埃塞俄比亚联邦卫生部(FMOH)发起了“通过安全手术拯救生命”(SaLTS)倡议,以改善全国的外科护理水平。此前的工作促成了15项外科关键绩效指标(KPI)的制定与实施,以规范外科数据实践。本项目的目标是调查KPI数据收集的现行做法,并评估质量,以改善数据管理并强化外科系统。研究的第一部分记录了埃塞俄比亚2个地区10家医院的外科数据收集过程,包括方法、工具及有效性。其次,比较了6个月期间(2022年1月至6月)登记处、KPI报告表和DHIS2(地区卫生信息系统)电子数据库中重点KPI[1.手术量,2.围手术期死亡率(POMR),3.不良麻醉结果(AAO),4.手术部位感染(SSI),以及5.安全手术检查表(SSC)使用率]的数据。根据数据完整性和一致性评估质量。数据收集过程包括医院工作人员在登记处记录数据元素、质量管理人员计算KPI、填写月度KPI报告表,并将数据提交给国家和地区卫生局的DHIS2。数据质量核查发现所有医院在一致性方面都存在差异,涉及1至3项指标。所有医院的平均每月手术量为57例,POMR为0.38%(13/3399),住院患者SSI率为0.79%(27/3399),AAO率为0.15%(5/3399),SSC平均每月使用率为93%(中位数为100%)。一半的医院登记处存在不完整数据,涉及2至5项指标。登记处中AAO、SSC和SSI的数据通常缺失。非标准化的KPI报告表对这些结果有显著影响。高质量数据收集的促进因素包括继续使用先前干预措施中的登记处,以及使用单独的日志记录特定KPI。这些指标在每个地区的延迟推出导致了数据质量问题。障碍包括不同人员记录指标的差异、产生假阳性的数据收集工具(如将SSC的完整性定义为患者出院前填写纸质表格)或因报告时间段导致的数据缺失(如每月的SSI可能遗漏一个月以外的感染情况)、登记处数据元素不足,以及缺乏标准化的月度KPI报告表。随着FMOH引入新指标和变革,我们建议进行持续且一致的质量检查和数据能力建设,包括利用常规生成的健康信息开展部门层面的质量改进项目。