Making Treatment FIT for Improved Outcomes

Outcome studies have clearly demonstrated the effectiveness of addiction treatment. However, despite the proliferation of treatment approaches, supported by meta-analytic studies, outcomes have not changed significantly in forty years (Miller, Hubble, Chow, & Seidel, 2013).  The stabilization of outcomes, referred to as a ceiling effect, over time speaks to another part of the story: a significant number of people do not benefit from treatment. For example, even with scientifically supported treatment methods, evaluated in carefully controlled studies, 30% to 50% of patients do not respond to treatment (Boswell, Kraus, Miller, & Lambert, 2013). For addiction treatment specifically, researchers learned that 38.2% of patients were off-track at some point during treatment, compared to a range from 15% to 40% for mental health treatments (Critis-Christoph, et al., 2012; Hawkins, Lambert, Vermeesch, Slade, & Tuttle, 2004). At best these statistics tell us that a third of patients are not responding to treatment. Even worse, slightly more than 10% of patients deteriorate in treatment (Hansen, Lambert, & Forman, 2002).

This is tragic news. If addiction treatment works and works well, why are a third or more not recovering? What, if anything, could be done to boost outcomes and extend effective treatment to those heading for unfavorable outcomes? Are stakeholders of addiction and co-occurring treatment destined to learn three, six, and twelve months later—typical follow-up periods in outcome research—that a large percentage of patients had a less than favorable outcome? What could be accomplished today, in the present moment, to change the course of outcomes?  Is there an evidence-based method that reduces deterioration and unresponsiveness to treatment, improving outcomes measured months and perhaps years after treatment?

For more than ten years, studies consistently and emphatically support the efficacy of Feedback Informed Treatment (FIT), an evidence-based method that significantly minimizes deterioration and unresponsiveness to treatment. FIT yields nothing short of dramatic results: cutting dropout by half and diminishing deterioration by a third, allowing clinicians to impact outcomes in real-time, and ensuring that more people experience recovery (Miller, 2011). In an environment that increasingly holds treatment programs accountable for outcomes, FIT offers an evidence-based practice not only to improve outcomes, but also to reduce healthcare expenditures and to utilize treatment resources more effectively (Miller, 2011).

How do FIT methods improve upon current evidence-based practices for addiction and co-occurring disorders? FIT enables counselors to identify in the moment, during treatment, patients who may be heading for a less than favorable outcome—because counselors frequently struggle to detect off-track patients (Hannan, et al., 2005; Hatfield, McCullough, Plucinski, & Krieger, 2010). There are, no doubt, complex reasons counselors miss off-track patients, such as demanding caseloads and externally imposed pressures with limited lengths of stay, but research reveals an additional explanation: counselors tend to overestimate their effectiveness with patients (Boswell, Kraus, Miller, & Lambert, 2013; Walfish, McAlister, O'Donnell, & Lambert, 2010). Laboring under exceptional circumstances, but often without authority to act, most especially in organized treatment programs, counselors should not be scapegoated for deteriorating or unresponsive patients.  In fact, clinicians welcome feedback, but it must come in the form of brief assessments that are efficient and relevant—an unparalleled advantage of FIT in the way in which it seamlessly integrates with treatment (Boswell, Kraus, Miller, & Lambert, 2013; Brickman, 2000; Hartfield & Ogles, 2004; Kiefe, et al., 2001).

FIT does more than simply identify patients who are not responding or deteriorating in treatment. An evidence-based practice, FIT relies on normative databases that provide an "expected treatment response," differentiate between "clinical" and "nonclinical" distress, and thus predict the likelihood of change based on the patient's current functioning.  Knowing a patient's expected trajectory as soon as possible makes a difference in shaping outcomes because early engagement in treatment predicts more favorable outcomes (Howard, Kopta, Krause, & Orlinksy, 1986). In this way, FIT empowers counselors to shape outcomes in real-time, in the present moment, long before they become another statistic about which nothing can be done.  

How does FIT improve outcomes in real-time? FIT utilizes psychometric (scientifically tested) scales on a session-by-session basis: evidence indicates that feedback given at each session more likely improves outcomes and reduces dropouts than feedback provided at less frequent intervals. Requiring only minutes to complete, FIT psychometric scales measure the patient's subjective experience of distress and experience of the therapeutic alliance. Some FIT scales are, for example, administered at the beginning (i.e., measures of distress) and at the end (i.e., measures of alliance) of sessions, whether they be individual, group, or relationship therapy sessions. In the name of transparency and collaboration, scale results are reviewed and discussed in the presence of the patient, often graphically depicted on a computer monitor, revealing progress, or the lack thereof, toward a favorable outcome.

FIT promises more than better outcomes. An evidence-based method, focused on progress in treatment, FIT does not dictate a theoretical model of treatment, but scrutinizes obstacles that stand in the way of recovery, regardless of the theory or method, making it easily adaptable to a variety of theories and program philosophies. FIT honors the patient's level of functioning and facilitates appropriate placement in the continuum of care; thus, it endows both administrators and clinicians with the capacity to allocate precious resources and to reduce the overall cost of treatment.  In short, FIT defies what might have been previously unthinkable: a win-win for all stakeholders integral to the treatment of addiction and co-occurring disorders, ultimately promoting outcomes that best serve the system and ultimately the patient.

Daniel C. Frigo, PhD, LICSW, serves as a professor at the Hazelden Betty Ford Graduate School of Addiction StudiesDaniel C. Frigo, PhD, LICSW, serves as a professor at the Hazelden Betty Ford Graduate School of Addiction Studies. Dr. Frigo practiced as a licensed clinical social worker for 19 years. He specialized in chemical dependence and mental health services for adolescents, adults, and physicians in recovery. He provided leadership on several state legislative efforts that affected the licensure of social workers and participated as an officer in the Missouri Society for Clinical Social Work.
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