Dapkutė Austėja, Trinkūnas Justas, Rastenytė Daiva, Matijošaitis Vaidas, Taroza Saulius, Jatužis Dalius, Baužaitė-Babušienė Sandra, Vilionskis Aleksandras, Klimašauskas Andrius, Juodakis Julius, Jaramavičius Julius, Masiliūnas Rytis
Clinic of Neurology and Neurosurgery, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.
Department of Information Systems, Faculty of Fundamental Sciences, Vilnius Gediminas Technical University, Vilnius, Lithuania.
Front Neurol. 2025 May 23;16:1550539. doi: 10.3389/fneur.2025.1550539. eCollection 2025.
The Lithuanian Stroke Database (StrokeLT) aims to automate data collection and key performance indicator (KPI) monitoring across all stroke-ready hospitals, addressing the limitations of manual processes and facilitating evidence-based improvements in stroke care nationwide. This publication outlines the selection process and target values of the KPIs designed to standardise and enhance stroke care quality in Lithuania.
The database will include all adult patients diagnosed with stroke or transient ischemic attack (TIA), admitted to Lithuanian stroke-ready hospitals, encompassing approximately 9,582 annual stroke and 1,899 TIA admissions based on 2023 data. The database will ensure comprehensive national coverage by integrating data from stroke centres via a centralised electronic health record system.
A total of 53 KPIs were selected through a multi-stage Delphi process involving national experts and guided by international standards. These KPIs include 44 process metrics, such as timeliness metrics, early rehabilitation, and availability of secondary prevention, as well as 8 outcome metrics, including functional recovery, completion of a patient feedback survey and mortality. This framework enables comprehensive monitoring across all stages of patient care, as well as incorporating valuable patient feedback.
The Lithuanian Stroke Database establishes a standardised automated framework for monitoring stroke care using 53 KPIs, selected through a multi-stage Delphi process involving all relevant stakeholders.
立陶宛卒中数据库（StrokeLT）旨在实现所有具备卒中救治能力医院的数据收集和关键绩效指标（KPI）监测自动化，解决手动流程的局限性，并促进立陶宛全国范围内卒中护理基于证据的改进。本出版物概述了为规范和提高立陶宛卒中护理质量而设计的关键绩效指标的选择过程和目标值。
该数据库将包括所有被诊断为卒中或短暂性脑缺血发作（TIA）的成年患者，这些患者入住立陶宛具备卒中救治能力的医院，根据2023年数据，每年约有9582例卒中和1899例TIA入院。该数据库将通过集中式电子健康记录系统整合卒中中心的数据，确保全国范围内的全面覆盖。
通过一个由国家专家参与并以国际标准为指导的多阶段德尔菲过程，共选择了53个关键绩效指标。这些关键绩效指标包括44个过程指标，如及时性指标、早期康复和二级预防的可及性，以及8个结果指标，包括功能恢复、患者反馈调查的完成情况和死亡率。这个框架能够对患者护理的所有阶段进行全面监测，并纳入有价值的患者反馈。
立陶宛卒中数据库建立了一个标准化的自动化框架，使用53个关键绩效指标监测卒中护理，这些指标是通过一个涉及所有相关利益攸关方的多阶段德尔菲过程选定的。
