Applied Evidence

Revisiting our approach to behavioral health referrals

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References

CASE SCENARIO

Ms. W’s physician asked her to go online using her phone and answer the questions in the Treatment Outcome Package. Her results, which she viewed with her physician, were displayed in graph form (FIGURE). Her scores were represented in Z scores normalized to the general population, with “0” representing the general, nontreatment-seeking population average and positive scores representing the number of standard deviations (SDs) more severe than the general population average.

Visual review of a patient’s multidimensional routine outcome monitoring assessment

Although this assessment scored Ms. W’s clinically elevated depression as mild, it revealed abnormalities in 3 other domains. Sexual functioning issues represented the most abnormal domain at greater than 3 SDs (more severe than the general population), followed by poor life quality and school/work functioning.

After reviewing Ms. W’s report, her physician decided that pharmacologic management alone (for depression) was not the most appropriate treatment course. Therefore, her physician recommended psychotherapy in addition to the SSRI she was taking. Ms. W agreed to a customized referral for psychotherapy.

Data-driven referrals

When psychotherapy is chosen as a treatment, the individual BHP is an active component of that treatment. Consequently, it is essential to customize referrals to match a patient’s most elevated mental health concerns with a therapist who will most effectively treat those domains. It is rare for a BHP to be skilled in treating every mental health domain.9 Multiple studies have shown that BHPs have identifiable treatment skills in specific domains, which physicians should consider when making referrals.9,21,22 These studies demonstrate the utility of aggregating patient-level routine outcome monitoring data to better understand therapist-level (and ultimately clinic- and system-level) outcomes.

It is essential to customize referrals to match a patient’s most elevated mental health concerns with a therapist who will most effectively treat those domains.

Additionally, recent research has tested this idea prospectively. An RCT funded by the Patient-Centered Outcome Research Institute and published in JAMA Psychiatry showed a significant and positive effect on patient outcomes (ie, reductions in general impairment, impairment involving a patient’s most elevated domain, and global distress) using paired-on outcome data matching vs as-usual matching protocols (eg, therapist self-defined areas of specialty).22 In the RCT, the most effective matching protocol was a combination of eliminating harm and matching the patient on their 3 most problematic domains (the highest match level). These patients ended care as healthy as the general population after 16 weeks of treatment. A random 1-year follow-up assessment from the original RCT showed that most patients who had been matched had maintained their improvement.23

Continue to: Therefore, a multidimensional routine outcome...

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