• Trisha Greenhalgh, Julie L Darbyshire, Cassie Lee, Emma Ladds, and Jenny Ceolta-Smith.
• Nuffield Department of Primary Care Health Sciences, University of Oxford, Woodstock Rd, Oxford, OX2 6GG, UK. trish.greenhalgh@phc.ox.ac.uk.
• Bmc Med. 2024 Apr 15; 22 (1): 159159.

BackgroundLong 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.MethodsIn 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.ResultsParticipating 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).ConclusionNot 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.Study RegistrationNCT05057260, ISRCTN15022307.© 2024. The Author(s).

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