ABSTRACT
Objective
The practice of routine outcome monitoring (ROM) – that is, monitoring clinical outcomes using standardized measures at regular intervals – is becoming increasingly ubiquitous for everyday practitioners in mental healthcare. ROM is recommended, if not mandated, by a growing number of professional and governmental bodies internationally, and there are mounting pressures to incorporate ROM practices into mental health services.
Method
This article presents a critical review of the published literature suggestive that the feasibility, utility, and most importantly, efficacy, of ROM is less effusive than is generally portrayed by advocates of the practice, particularly in naturalistic settings.
Results
The 2022 Better Access Evaluation Report is examined as an archetypal case study whereby research findings are grossly misrepresented in order to reach recommendations supportive of implementing ROM into healthcare systems. Reviewed research suggests that both clients and clinicians experience ROM as cumbersome, and real-world efforts to incorporate ROM into public health services have fostered serious ethical violations.
Conclusions
The social, political, and economic forces responsible for the galvanizing ROM movement are examined.
Key Points
What is already known about this topic:
Routine outcome monitoring (ROM) in mental healthcare is recommended by governments and professional bodies internationally.
The empirical literature emphasises that ROM can improve outcomes in clinical practice.
Clinicians still do not use ROM regularly in everyday practice unless they are obliged to by their organisation.
What this topic adds:
This narrative critique of the literature reveals that in naturalistic settings ROM is generally unfeasible and improvements to clinical outcomes are minimal.
Both practitioners and patients perceive ROM to be cumbersome.
Efforts to implement ROM practices on large scales are driven by political and economic forces rather than any identifiable clinical need.
Acknowledgments
The author would like to thank Shannon Webb for proofreading and editing support.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data sharing is not applicable to this article as no new data were collected or analysed in this manuscript.
Notes
1. For reference, a large effect size is classified as d = 0.8, medium as d = 0.5, and small as d = 0.2 (Sullivan & Feinn, Citation2012).
2. For instance, the Australian Psychological Society (APS) offers an on-demand webinar titled “The easy way to implement routine outcome monitoring in private practice” delivered by the Chief Executive Officer and Chief Science and Evaluation Officer of NovoPsych.