The unspoken truth about measurement in routine clinical practice today is that it is inherently failure-oriented. It allows us to quantify the all-too-common clinical observation - that a patient, for whatever reason, is not getting better. It serves the purpose of confirming this subjective experience by attaching a number to the fact that things aren’t going as planned. It safeguards against the possibility of missing this information during weekly sessions, and reminds us to get creative with our clinical approach. In short, it reminds us that something needs to change.
However, it also begs the question…what next?
Although traditional measurement-informed care (MIC) is able to inform us that something is going wrong, it does nothing to suggest how we can proactively modify care to effectively meet the needs of the patient. Currently, there are no standardized guidelines for clinicians to follow regarding how and when to modify treatment based on patient response. Moreover, jumping from treatment approach to treatment approach in order to find one that works can actually be contra-indicated, leading to feelings of hopelessness from patient and clinician alike. As a result, measurement is often overlooked and underutilized because of this disconnect from the realities of routine clinical practice.
Fueled by this limitation, the question of when and how to respond to what the data are telling us, be it good or bad, represents the precursor to a new paradigm shift in contemporary MIC - a shift that gives measurement an entirely new purpose: to better understand our patients in order to elevate the care experience. This new approach to MIC pivots the focus from what is going wrong to what can be done. Rather than simply measuring change in broad diagnostic constructs, we can uncover actionable symptom profiles based on in-the-moment experiences. Rather than relying on verbal reports of lifestyle and health behaviors that are notoriously prone to bias, we can passively monitor these behaviors “in the background” using the sensors in our patient’s cell phones. Most importantly, we can become better clinicians by using this data to link personalized insights to evidence-based interventions.
Better understanding our patient’s lived experiences through measurement, above and beyond their levels of psychopathology, provides a proactive framework for personalizing behavioral healthcare at any stage of treatment. For example, the evolution of clinical science and subsequent models for mental health treatment is moving toward a process-based approach, where the focus of treatment is on identifying psychological and behavioral processes that are preventing a patient from getting from where they are in life to where they want to be. One patient may be held back by poor health behaviors and inactivity, whereas another patient may be struggling with cognitive distortions leading to social isolation. In either case, the ability to create a personalized profile based on measurement of these psychological processes, and link these processes to evidence-based interventions, represents the future of behavioral healthcare. Such a future can only be realized through the re-introduction of proactive measurement into routine clinical practice. Re-introducing measurement into routine clinical practice can only be done when we move away from failure-oriented models and begin to unlock the power of using data to set us up for success.