Session Description: Clinical data is all around us. Electronic health records are ubiquitous and can organize vast quantities of patient-level information with ease. Interpreting that data, however, typically mystifies most clinicians and program administrators. Measurement-based care is an approach to clinical practice wherein clinical data is gathered in an intentional, repetitive method to track symptoms, functional outcomes, and overall patient status over time. That clinical data is then used to highlight change in patient status over time, to reduce clinician bias in communication about a patient case, to improve clinician understanding of the patient's clinical presentation, to improve patients' self-reflection and understanding of progress, to guide in-session communication and treatment planning, and to predict deterioration in patient status early in any decompensation process. Measurement-based care can help clinicians better understand their patients and patients understand themselves, ultimately strengthening the therapeutic alliance and allowing for agile and truly personalized care planning. Participants will be provided with recommendations on which psychometrically-validated instruments can be used to build out a comprehensive measurement-based care program. Further, attendees will learn how to aggregate a collection of measures to understand overall patient health status and compare this data to other patients, thereby attending that minority of patients which likely demand the majority of treatment teams' attention at any given time. Finally, attendees will be provided with skills as to how to utilize this data in patient care and with external stakeholders -- disparate groups who are invested in the patient's status but are typically not behavioral health experts themselves. Suggestions for scripting and verbiage will be shared and taught.
Learning Objectives:
After this activity participants should be able to
Apply the concept of "feedback loops" at the individual patient care level, making treatment plan adjustments by using clinical measurement data.
Analyze population-level patient data to inform program design and evaluation.
Describe the concept of "minimum effectiveness thresholds" and be able to communicate how it applies in behavioral health, including how to explain it to laypersons and external stakeholders.