Long covid (post covid-19 condition) is a complex condition with diverse manifestations, uncertain prognosis and wide variation in current approaches to management. There have been calls for formal quality standards to reduce a so-called “postcode lottery” of care. The original aim of this study—to examine the nature of quality in long covid care and reduce unwarranted variation in services—evolved to focus on examining the reasons why standardizing care was so challenging in this condition. In 2021–2023, we ran a quality improvement collaborative across 10 UK sites. The dataset reported here was mostly but not entirely qualitative. It included data on the origins and current context of each clinic, interviews with staff and patients, and ethnographic observations at 13 clinics (50 consultations) and 45 multidisciplinary team (MDT) meetings (244 patient cases). Data collection and analysis were informed by relevant lenses from clinical care (e.g. evidence-based guidelines), improvement science (e.g. quality improvement cycles) and philosophy of knowledge. Participating clinics made progress towards standardizing assessment and management in some topics; some variation remained but this could usually be explained. Clinics had different histories and path dependencies, occupied a different place in their healthcare ecosystem and served a varied caseload including a high proportion of patients with comorbidities. A key mechanism for achieving high-quality long covid care was when local MDTs deliberated on unusual, complex or challenging cases for which evidence-based guidelines provided no easy answers. In such cases, collective learning occurred through idiographic (case-based) reasoning, in which practitioners build lessons from the particular to the general. This contrasts with the nomothetic reasoning implicit in evidence-based guidelines, in which reasoning is assumed to go from the general (e.g. findings of clinical trials) to the particular (management of individual patients). Not all variation in long covid services is unwarranted. Largely because long covid’s manifestations are so varied and comorbidities common, generic “evidence-based” standards require much individual adaptation. In this complex condition, quality improvement resources may be productively spent supporting MDTs to optimise their case-based learning through interdisciplinary discussion. Quality assessment of a long covid service should include review of a sample of individual cases to assess how guidelines have been interpreted and personalized to meet patients’ unique needs. NCT05057260, ISRCTN15022307.

中文翻译：

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长期新冠护理的质量如何？国家质量改进协作和多地点民族志的经验教训

Long covid（covid-19 后病症）是一种复杂的病症，具有多种表现、不确定的预后以及当前管理方法的广泛差异。有人呼吁制定正式的质量标准，以减少所谓的“邮政编码彩票”护理。这项研究的最初目的是检查长期新冠护理的质量本质并减少服务中不必要的变化，后来演变为重点研究在这种情况下标准化护理如此具有挑战性的原因。 2021 年至 2023 年，我们在英国 10 个站点开展了质量改进协作。这里报告的数据集大部分是定性的，但并不完全是定性的。它包括有关每个诊所的起源和当前背景的数据、对工作人员和患者的访谈以及对 13 个诊所（50 次咨询）和 45 次多学科团队 (MDT) 会议（244 例患者病例）的人种学观察。数据收集和分析的依据来自临床护理（例如循证指南）、改进科学（例如质量改进周期）和知识哲学的相关视角。参与诊所在某些主题的标准化评估和管理方面取得了进展；仍然存在一些差异，但这通常是可以解释的。诊所具有不同的历史和路径依赖性，在其医疗保健生态系统中占据不同的位置，并服务于不同的病例，其中包括很高比例的患有合并症的患者。实现高质量长期新冠护理的一个关键机制是，当地 MDT 审议不寻常、复杂或具有挑战性的案例，而循证指南无法为这些案例提供简单的答案。在这种情况下，集体学习是通过具体的（基于案例的）推理进行的，实践者从特殊到一般来积累经验教训。这与基于证据的指南中隐含的规则推理形成对比，其中假设推理从一般性（例如临床试验的结果）到特殊性（个体患者的管理）。并非所有长期新冠服务的变化都是没有根据的。主要是因为新冠病毒的表现多种多样，合并症也很常见，通用的“循证”标准需要大量的个体适应。在这种复杂的情况下，质量改进资源可以有效地用于支持 MDT 通过跨学科讨论来优化基于案例的学习。对长期新冠服务的质量评估应包括对个案样本的审查，以评估如何解释和个性化指南以满足患者的独特需求。 NCT05057260、ISRCTN15022307。