Measurement-based care is essential for the future of mental health

Current lack of measurement-based care

If you were to break your arm and go to a hospital, you would see a doctor and receive a standard treatment protocol for your arm that likely wouldn’t be too different from what any other doctor or facility would recommend. Your recovery would be monitored, and you would have the next steps provided for you at each stage of your recovery. Unlike physical medicine, in mental health recovery, the treatment outcomes, protocol, and follow-up procedures are often not measured, precise, or standardized across the field. In fact, it is extremely rare for therapeutic outcomes to be measured by therapists and mental health centers. We believe that mental health should embrace measurement-based care approaches to mental healthcare treatment.

Why aren’t we measuring therapeutic outcomes?

Currently, when outcomes are measured, those measurements are not risk-adjusted or standardized, and so they are only relevant for that single practitioner.

Part of why outcomes are not measured is because they can be very difficult to measure.

There are patient-reported outcome measurement tools such as PHQ-8 or 9, the EDEQ (Eating Disorder Questionnaire), the ASI-LITE (Addiction Severity Index), the OQ-45.2, and many professionals use a patient satisfaction survey. These tools are not perfect, but they have proven to be statistically and clinically reliable. Many of us who are collecting this data wisely use it to measure ourselves.  Where we see internal deficiencies, we try to improve.  If nothing else, the data collected serves as one of several pieces of feedback that we can use to better support our patients. These surveys tell us if their mood has improved over time, if they are satisfied with their relationships, employment, friendships, etc.

Unfortunately, outcomes need to be standardized and risk-adjusted in order to mean much to anyone else outside of an individual practitioner.


Standardization means we are all using (and publishing) the same tools for the same patients in the same way at the same time.  For example, If we are using the EDE-Q and our friends across the street are using the EAT-26 (another tool used to measure eating disorder progress), for instance, the two cannot be compared against one another, and therefore, any comparative analysis is useless.  After we can all agree on which tool to use, we must standardize how we use it. Are we asking questions in an email or in person? Are we asking them at the same time during recovery (2 days post-treatment or 30 or 265?). If these points aren’t standardized, we can assume the results cannot be accurately compared. Agreeing on which tools and how we use them is a process that we hope will happen soon.  Once we all agree, this is fairly straightforward.

Risk Adjustment

Risk adjustment is a bit more complicated.  Risk adjustment takes into consideration the underlying health status of the patient being measured.  The more complicated the patient’s condition, the “riskier” they are, and therefore, the more resources will be needed to treat them effectively.  Further, the more complicated the patient, the less improvement we might expect to see, or at the very least, the improvement in a complex patient will look different.  For example, imagine if an addiction facility publishes a 75% abstinence rate at 360 days post-discharge. However, they generally treat patients who have never been in treatment before, are relatively young, have not struggled with the disease for a long time, and do not have any co-occurring depression, anxiety, or trauma. But what if another provider with older clients, whose patients have generally been in and out of treatment their entire lives and have a host of medical co-morbidities, uses the same tool, measures the same way, and yet shows a 55% abstinence rate? Would we say this provider is producing lower quality work because their abstinence rate is 55% as compared to 75%? Probably, we would not. In fact, we might say the opposite, namely, that the first provider could possibly be doing better. However, at first glance, that 75% might look fantastic.

Some of the ways we can begin introducing risk adjustment can be by asking:

  • What level of care is the patient coming from previously? (Inpatient, outpatient, detox?)
  • How many diagnoses does the patient have? (The more they have, the higher risk they are.)
  • Has the patient been hospitalized for their addiction/mental health issue in the past 5 years?
  • Does the patient have a supportive family?
  • Any history of overdose or suicide attempts?

Once we finally have standardization and eventually some form of risk adjustment model, the outcomes some of us collect will be far more valuable to patients, their families, and their insurance companies. Once we are able to measure value, we can transform our insurance and healthcare system from a system that is centered on quantity (aka fee for service) to quality. This transition has proven in many other areas of medicine at major health institutions to align the interests of the patient, provider, and payer and results in improved quality at a lower cost.

In general, some data is better than no data – however, if you see data published online, take it with a grain of salt. It is likely not a great indicator of the quality of the program. At least for now!

Accreditation for measurement of quality

Because there is a lack of measurement-based care across all mental health centers, it is very challenging to hold providers accountable for providing quality care. Although these centers are often highly regulated, many regulations exist for ensuring the physical safety of clients, which is, of course, essential but is not aimed at the goal of providing high recovery results.

One way we’ve attempted to tell the quality of centers apart is through accrediting institutions such as JCAHO. Making sure the facility you’re attending is JCAHO accredited can be an assurance of the quality of the facility; however, not always!

The future of mental health treatment is measurement-based care.

The lack of measurement-based care in mental health care is contributing to the high cost of care, confusion in care navigation, and diagnostic confusion. Without the ability to track which protocols are working best under what conditions, we aren’t able to enhance the quality of the field. Without data collection, it is challenging to learn from our mistakes and make educated steps forward. Insurance companies are able to get away with extremely low reimbursement rates in part because clinics aren’t able to provide precise metrics. Measurement-based care is the future of our mental health system – introducing even some simple practices could transform our mental health care landscape. We are optimistic that through virtual care, we can begin to innovate in this domain.