measurement based care mental health is a method of systematically monitoring and measuring the outcomes of psychiatric treatment to bolster clinical decision making and promote patient engagement. It is an evidence-based approach that improves therapeutic efficiency, adherence and outcomes across multiple treatment modalities, populations and settings.
As a component of the mental health assessment process, measurement-based care involves administration of validated self-report assessments, symptom rating scales (e.g., Personal Health Questionnaire-9 or Generalized Anxiety Disorder-7), and feedback of these data to patients on a regular basis. This collaborative evaluation of the patient’s progress is considered critical for enhancing treatment outcomes [6, 7].
The current implementation of measurement-based care is largely focused on symptom-focused questionnaires that are designed to be short and adaptable to clinician workflows, as well as to incorporate in-session patient feedback. Although these synchronous interactions can provide some insight into how patients are responding to therapy, they cannot fully extend this data to real-world daily functioning or the effects of therapeutic interventions [8, 9].
This method has a number of inherent limitations. The first is the tethering of the measurement process to a specific clinical session, limiting observations and data points that are more likely to reflect a limited range of patient functioning or the effects of therapeutic interventions. The second limitation is the lack of a consistent system for patient feedback between sessions that reflects real-world and/or relapse-related symptom changes.
To avoid these pitfalls, digital technology can enhance measurement-based care by offering more representative and expansive real-world data-gathering through passively gathered data and expanding opportunities for experience sampling (also called ecological momentary assessment). Expansion of this type of passive data collection will also provide more opportunities to engage with patients and encourage their involvement in data-driven decisions and treatment planning.
Valant’s Behavioral Health EHR has a built-in set of over 65 rating scales that can be pushed to patients automatically for each visit, reducing the barriers to creating a measurement-based care practice. The information is automatically populated into clinical notes, saving valuable time and supporting higher-level coding when appropriate.
The symptom rating scales can be administered during the session or at the end of the encounter, and the results can be uploaded to the electronic health record for use during subsequent sessions. These ratings can be interpreted and reviewed by the therapist to facilitate informed clinical decision making and drive treatment planning and adjustment.
Patients who receive symptom-based care report that it is effective and useful for them. They perceive it as efficient, complementary to their provider’s clinical judgment, and an indicator that the clinician is taking their mental health problems seriously. In addition, many patients reported that symptom rating scales have made it easier to communicate their symptoms to their providers.
Using this system has been shown to increase patient satisfaction, reduce required appointments, improve clinical response rates and result in more patients in remission. Furthermore, insurance carriers are increasingly willing to pay clinicians more for using outcome measures. This is especially true in the case of mental health.