Health condition at first fit note and number of fit notes: a longitudinal study of primary care records in south London. Issue 3 (26th March 2021)

• Record Type: Journal Article
• Authors: Dorrington, Sarah; Carr, Ewan; Polling, C; Stevelink, Sharon; Ashworth, Mark; Roberts, Emmert; Broadbent, Matthew; Hatch, Stephani; Madan, Ira; Hotopf, Matthew
• Is Part Of: BMJ open. Volume 11:Issue 3(2021)
• Publication Date: 2021-03-26
• Subjects: primary care -- public health -- occupational & industrial medicine -- health policy; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2020-043889
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: The fit note replaced the sick note in the UK in 2010, with the aim of improving support for patients requiring sickness absence, yet there has been very little research into fit note use. This study aims to describe number of fit notes by condition, to improve our understanding of patterns of fit note use in primary care. Previous fit note research has relied on extracting diagnoses directly from fit notes, rather than extracting information from clinical records. In this paper, we extract information from clinical records to explore demographic factors and conditions associated with number of fit notes issued. Design: This is a longitudinal study of clinical data. We analysed individual-level anonymised data from general practitioner consultations, including demographic information and condition recorded at first fit note. The latter encompassed diagnoses, individual symptoms and psychosocial issues. Setting: A database called Lambeth DataNet, containing electronic clinical records on 326 415 adults (ages 16–60) from all 45 general practices within the London Borough of Lambeth from 1 January 2014 to 30 April 2017. Participants: Our analytical sample contained 40 698 people with a condition recorded at first fit note. Primary outcome measure: Predicted number of fit notes in the period January 2014–April 2017 Results: Of all studied diagnostic groups, mental illness had the highest predicted number of fit notes (n=3.3; 95% CI: 3.1 to 3.4) after controlling for demographic factors and long-term conditions. The highest predicted number of fit notes for any condition subgroup was among patients presenting for drug and/or alcohol misuse (n=4.5; 95% CI: 4.1 to 4.8). Conclusions: For the first time, we show drug and/or alcohol misuse at first fit note are associated with the highest number of fit notes. Research is needed to understand the trajectories of individuals at highest risk of long-term sickness absence, in particular, people presenting with drug and/or alcohol misuse.