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HATCHing plans: a qualitative study of how discharge communication can support expert generalist management
Nicholas Boddy1,2, Joanne Reeve3, Rachel A Spencer4
1National Institute for Health and Care Research (NIHR) In-Practice Fellow, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Nottingham, UK nicholas.boddy@doctors.org.uk.
Background:
Standardisation has improved hospital discharge summaries. However, problems remain for recipient GPs, such as inadequate detail for whole-person continuing care. Hospital authors often lack sufficient understanding of expert generalist practice in community post-discharge settings and so may over-rely on generic information standards or simplified summary template headings.
Aim:
To explore how expert generalist GPs practically use discharge information, including the challenges they face, to shape new understanding of what discharge communication should look like.
Design & Setting:
A qualitative exploration of GP perspectives on challenging post-discharge management scenarios.
Method:
Fifteen semi-structured interviews of GPs and GP trainees were conducted with use of a mock vignette and the think aloud method. Thematic analysis was informed by the '4Es of expert generalism'.
Results:
An interpretive process of 'Holistic Adjustment To Context after Hospital discharge' (HATCH) was found to underpin expert generalist GP decision-making in this transitional care phase. The sub-processes of rationalisation and integration exemplified the use of the expert generalist interpretive paradigm. Insufficient communication of explanation and context surrounding key hospital decisions was found to hinder the HATCH process and risk the quality and safety of post-discharge care. GPs could remediate such situations, but this still had hidden risks and costs.
Conclusion:
Understanding the HATCH process and how contextual and explanatory information supports it emerged as key steps for authors to further improve discharge summaries. Adaptations to information standards and summary templates are key opportunities to address this issue, alongside incorporation into AI software and updated training for all parties.
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