Elsevier

Behaviour Research and Therapy

Volume 99, December 2017, Pages 89-97
Behaviour Research and Therapy

Improving the efficiency of psychological treatment using outcome feedback technology

https://doi.org/10.1016/j.brat.2017.09.011Get rights and content

Highlights

  • Outcome feedback (OF) technology was used to guide the treatment of patients with depression and anxiety.

  • OF cases attained similar outcomes to control cases in usual psychological care, but at significantly lower costs.

  • OF technology can help to improve the efficiency of psychological treatment in primary care.

  • Qualitative interviews suggested that using OF in routine practice is acceptable to therapists and patients.

Abstract

Aims

This study evaluated the impact of applying computerized outcome feedback (OF) technology in a stepped care psychological service offering low and high intensity therapies for depression and anxiety.

Methods

A group of therapists were trained to use OF based on routine outcome monitoring using depression (PHQ-9) and anxiety (GAD-7) measures. Therapists regularly reviewed expected treatment response graphs with patients and discussed cases that were “not on track” in clinical supervision. Clinical outcomes data were collected for all patients treated by this group (N = 594), six months before (controls = 349) and six months after the OF training (OF cases = 245). Symptom reductions in PHQ-9 and GAD-7 were compared between controls and OF cases using longitudinal multilevel modelling. Treatment duration and costs were compared using MANOVA. Qualitative interviews with therapists (N = 15) and patients (N = 6) were interpreted using thematic analysis.

Results

OF technology was generally acceptable and feasible to integrate in routine practice. No significant between-group differences were found in post-treatment PHQ-9 or GAD-7 measures. However, OF cases had significantly lower average duration and cost of treatment compared to controls.

Conclusions

After adopting OF into their practice, this group of therapists attained similar clinical outcomes but within a shorter space of time and at a reduced average cost per treatment episode. We conclude that OF can improve the efficiency of stepped care.

Introduction

Several studies have demonstrated that monitoring patients' response to psychological treatment using standardised outcome measures can help to detect difficulties and to improve outcomes for patients (Gondek, Edbrooke-Childs, Fink, Deighton, & Wolpert, 2016). Routine outcome monitoring may be particularly important for certain patients that tend to have a poorer response to treatment (Lambert et al., 2001, Lutz et al., 2015), referred to as ‘signal cases’ or cases that are ‘not on track’ (NOT). Lambert et al. (2003) proposed that providing timely feedback to therapists using psychometric measures to alert them about signal cases could help to improve their outcomes. Typically, outcome feedback (OF) involves entering a patient's symptom measures into a computer system that graphically displays changes from session-to-session, comparing these to clinical norms derived from hundreds of similar cases. Patients with symptoms that do not improve as suggested by these clinical norms are flagged up as NOT. A meta-analysis of controlled trials in USA concluded that NOT cases in usual psychological care were 2.3 times more likely to deteriorate by comparison to NOT cases treated by therapists that apply OF technology (Shimokawa, Lambert, & Smart, 2010). However, this meta-analysis included studies from the same research group which predominantly treated student populations, therefore raising some questions about generalizability (Davidson, Perry, & Bell, 2015). More recently, trials in European countries have replicated these findings in other clinical populations, suggesting that using OF can help to prevent deterioration in NOT cases (e.g., Amble et al., 2015, De Jong et al., 2014, Hansson et al., 2013).

Although the usefulness of outcome feedback has been demonstrated in specialist counselling and psychotherapy centres, these methods have not yet been tested in stepped care psychological services such as those linked to the IAPT (Improving Access to Psychological Therapies) model applied in England (Clark, 2011) and Australia (Cromarty, Drummond, Francis, Watson, & Battersby, 2016). IAPT services are particularly well placed to apply OF methods since they routinely collect standardised outcome measures at every session to monitor clinical outcomes (Clark, 2011). However, the high volume of work and time pressures typical of public healthcare settings may limit therapists' ability to consistently and meaningfully reflect on the results of outcome measures within their treatment sessions. Furthermore, research suggests that IAPT clinicians do not necessarily consider symptom measures in their decisions about treatment planning and some tend to rely on subjective beliefs and attitudes when making decisions about the treatment of non-improving patients (Delgadillo, Gellatly, & Stephenson-Bellwood, 2015). Therefore, there are plausible contextual and attitudinal barriers that may limit the effective utilization of outcome feedback in this setting.

This study presents the first application of outcome feedback technology in an IAPT stepped care context. The primary objective of the study was to evaluate the clinical impact of using OF, quantified in terms of changes in symptoms, treatment duration and cost. A secondary objective was to assess the feasibility and acceptability of discussing OF with patients in weekly therapy sessions.

Section snippets

Setting, interventions and study design

This study was conducted in an IAPT stepped care service in Leeds, a large and socioeconomically diverse city in the north of England. The service offered evidence-based and protocol-driven psychological interventions for depression and anxiety problems, guided by routine session-by-session outcomes monitoring, consistent with clinical guidelines (National Institute for Health and Care Excellence, 2011). According to publicly available data for the period of the study (NHS Digital, 2016), 6410

Quantitative data on clinical impact

Fixed effects of the fully adjusted MLM analysis are shown in Table 2. The cohort * time interaction term represents the main between-group comparison in symptom changes across time. This was not statistically significant in PHQ-9 (B = 0.80, SE = 0.78, p = 0.30) or GAD-7 (B = 0.80, SE = 0.71, p = 0.26) models applied in the full sample, nor in the subsamples of NOT (shown in Table 2) or OT cases.

Case-mix adjusted logistic regressions (Table 3) indicated that RCSI rates were not significantly

Main findings

This study presents the first comprehensive evaluation of outcome feedback technology applied in a stepped care psychological treatment setting. The results indicated that this technology was feasible to adopt in routine care, was minimally burdensome, and was generally seen by therapists and patients as a useful aid to decision-making and clinical supervision processes.

Qualitative interviews with therapists revealed that the outcome feedback signalling technology influenced their

Conflict of interest

None.

Acknowledgements

The Leeds Outcome Feedback Study (NHS REC Reference: 15/NW/0675) was supported by research capability funding awarded by Leeds Community Healthcare NHS Trust. The outcome feedback and signalling technology used in this study was developed by PCMIS at the Department of Health Sciences, University of York (http://www.pc-mis.co.uk). We thank Byron George, Gareth Percival, Colin Robson, Alexander Teahan, Jan Thomson, Simon Day, Anne Briggs, Jan Lewis, Abigail Coe, Sarah West, Caroline Lloyd, Angela

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