OPEN Research Unit, Odense Universitetshospital, Odense, Denmark
Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
BMJ Open Qual. 2023 Feb;12(1). doi: 10.1136/bmjoq-2022-002101.
Patient complaints and compensation cases are analysed individually and do not allow for organisational learning. Systematic information on complaint patterns needs evidence-based measures. The Healthcare Complaints Analysis Tool (HCAT) can systematically code and analyse complaints and compensation claims, but whether this information is useful for quality improvement is underexplored. We aim to explore if and how HCAT information is perceived useful to inform healthcare quality gaps.
To explore the HCAT's usefulness for quality improvement purposes, we used an iterative process. We accessed all complaints relating to a large university hospital. Trained HCAT raters systematically coded all cases, using the Danish version of HCAT.
The intervention had four phases: (1) coding of cases, (2) education, (3) selection of HCAT analyses for dissemination, (4) 'dashboard' development and delivery of targeted HCAT reports. To study the interventions and phases, we used quantitative and qualitative approaches. The coding patterns were descriptively displayed on department and hospital level. The educational programme was monitored using passing rates, coding reliability checks and rater feedback. Online interviews recorded dissemination feedback. We used a phenomenological approach with thematised quotations from the interviews to analyse the usefulness of the information from cases coded.
We coded 5217 complaint cases (11 056 complaint points). The average case coding time was 8.5 min (95% CI 8.2 to 8.7). All four raters passed the online test with >80% correct answers. Using rater feedback, we handled 25 cases of doubt. None affected the HCAT structure or categories. Interviews verified the usefulness of analyses after expert group dissemination. Three themes were important: 'overview of complaints', 'learning from complaints' and 'listening to the patients'. Stakeholders perceived the 'dashboard' development as highly relevant.
Through the development process with several adjustments, stakeholders found the systematic approach useful for quality improvement. The hospital management evaluated the approach as promising and decided to test the approach in clinical practice.
患者投诉和赔偿案件是逐个分析的，无法实现组织学习。系统的投诉模式信息需要基于证据的措施。医疗保健投诉分析工具（HCAT）可以对投诉和赔偿要求进行系统编码和分析，但该信息是否有助于质量改进仍未得到充分探索。我们旨在探讨 HCAT 信息是否以及如何被认为有助于发现医疗保健质量差距。
为了探索 HCAT 用于质量改进的用途，我们使用了迭代过程。我们访问了与一家大型大学医院相关的所有投诉。经过培训的 HCAT 评分员使用丹麦版 HCAT 对所有案例进行了系统编码。
该干预措施有四个阶段：（1）案例编码，（2）教育，（3）选择用于传播的 HCAT 分析，（4）“仪表板”开发和提供有针对性的 HCAT 报告。为了研究干预措施和阶段，我们使用了定量和定性方法。在部门和医院层面上对编码模式进行描述性展示。使用通过率、编码可靠性检查和评分员反馈来监测教育计划。在线访谈记录了传播反馈。我们使用现象学方法，从访谈中提取主题化引语来分析编码案例信息的有用性。
我们对 5217 起投诉案件（11056 个投诉点）进行了编码。平均每个案件的编码时间为 8.5 分钟（95%CI 8.2 至 8.7）。所有四名评分员都通过了在线测试，答对率超过 80%。根据评分员的反馈，我们处理了 25 起有疑问的案例。这些案例均未影响 HCAT 的结构或类别。在专家小组传播后，访谈验证了分析的有用性。三个主题很重要：“投诉概述”、“从投诉中学习”和“倾听患者”。利益相关者认为“仪表板”的开发非常重要。
通过具有多次调整的开发过程，利益相关者发现系统方法对质量改进很有用。医院管理层对该方法的评估结果表示有前景，并决定在临床实践中测试该方法。
