Baby Steps to a Learning Mental Health Care System: Can we do the Work?
Abstract There are an infinite number of small decisions to be made in routine clinical practice, and most will never be the subject of prospective research studies. Rather than making these decisions arbitrarily, learning health care systems leverage experience represented by electronic health record data and other sources to inform decision making and improve clinical practice. While this approach has been elusive in mental health, Coulombe et al. (AJE-00362-2020.R3) use British National Health Service data to evaluate a decision rule for antidepressant choice created using dynamic weighted survival modeling. Though the results are equivocal in this use case, the work suggests a path forward for data-driven decision making in routine mental health care. Such approaches will be required to set the stage for a learning mental health care system.