How should referrals to consultation-liaison psychiatry be made? A multisite study of consultation-liaison psychiatry clinicians and medical referrers

Objective To investigate views of consultation-liaison psychiatry (CLP) clinicians and medical referrers regarding optimal referral processes, referral form content, responses to unsatisfactory referrals, and referral appropriateness for inpatient CLP services in Australian hospitals. Method A cross-sectional mixed-methods survey was distributed to CLP clinicians ( n = 121) working across Australia and medical referrers ( n = 73) recruited from two hospitals in Victoria and Tasmania. Ratings of referral processes and referral form content were compared between groups. Free-text responses on referral appropriateness were thematically analysed. Results Both groups preferred digital referral systems supplemented by telephone calls, and referral forms combining free-text fields with checkboxes. Cross-group consensus emerged on the five most important referral form fields: patient identification, reason for referral, referrer details, Mental Health Act status, and urgency. CLP clinicians rated 14 of 25 referral form headings as significantly more important than medical referrers. Thematic analysis of referral appropriateness yielded five interpretive themes. A dominant view framed referral appropriateness as a quality threshold, while a minority argued that any genuine clinical uncertainty warrants CLP review. Conclusion These findings provide an empirical foundation for optimal referral systems in CLP. Referral system design should combine hybrid electronic forms with targeted education, low-threshold discussion pathways and co-design with referrers.

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Publication Details

Journal
Australasian Psychiatry
Published
2026-10-13
DOI
https://doi.org/10.1177/10398562261493848
Primary Topic
Healthcare Systems and Technology
Type
article
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article

How should referrals to consultation-liaison psychiatry be made? A multisite study of consultation-liaison psychiatry clinicians and medical referrers

Steven Moylan, Kabir Ahmad, Murray G. Tucker, Julia Hunt et al.
Australasian Psychiatry
Healthcare Systems and Technology
article

How should referrals to consultation-liaison psychiatry be made? A multisite study of consultation-liaison psychiatry clinicians and medical referrers

Steven Moylan, Kabir Ahmad, Murray G. Tucker, Julia Hunt, Emma Nicholson
article en

Abstract

Objective To investigate views of consultation-liaison psychiatry (CLP) clinicians and medical referrers regarding optimal referral processes, referral form content, responses to unsatisfactory referrals, and referral appropriateness for inpatient CLP services in Australian hospitals. Method A cross-sectional mixed-methods survey was distributed to CLP clinicians ( n = 121) working across Australia and medical referrers ( n = 73) recruited from two hospitals in Victoria and Tasmania. Ratings of referral processes and referral form content were compared between groups. Free-text responses on referral appropriateness were thematically analysed. Results Both groups preferred digital referral systems supplemented by telephone calls, and referral forms combining free-text fields with checkboxes. Cross-group consensus emerged on the five most important referral form fields: patient identification, reason for referral, referrer details, Mental Health Act status, and urgency. CLP clinicians rated 14 of 25 referral form headings as significantly more important than medical referrers. Thematic analysis of referral appropriateness yielded five interpretive themes. A dominant view framed referral appropriateness as a quality threshold, while a minority argued that any genuine clinical uncertainty warrants CLP review. Conclusion These findings provide an empirical foundation for optimal referral systems in CLP. Referral system design should combine hybrid electronic forms with targeted education, low-threshold discussion pathways and co-design with referrers.

Australasian Psychiatry
University of Tasmania (AU), Barwon Health (AU), Deakin University (AU), University of Southern Queensland (AU)
Openalex Percentile: Top 6%
Healthcare Systems and Technology
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