By Josh Morgan, PsyD
As we honor Mental Health Month, there are many calls to reduce suffering. Seems reasonable, right? It’s even in California’s Mental Health Services Act (MHSA), where public systems are called to “reduce subjective suffering.” And as we broadly focus more on outcomes in health, measuring suffering (and hopefully its reduction) is crucial.
In order to measure something, we have to define it.
While some definitions of suffering simply refer to the presence of symptoms, does the presence of illness alone necessarily mean suffering? Have you ever seen someone with an illness who is suffering? It’s painful, and we want to help stop it. In contrast, have you ever seen someone with an illness who is not suffering?
Ever since my Dialectical Behavior Therapy (DBT) training, I’ve preferred a more whole person approach to suffering. Dr. Marsha Linehan, the founder of DBT, defines suffering as non-acceptance of our situation. Think back to people you have known with illnesses. Does their acceptance or non-acceptance of their situation impact their ability to cope with it and therefore their suffering? How does this affect quality of life?
Does this really matter, though? Isn’t it easier to just focus on symptoms?
To measure a reduction in suffering, sure, it’s easier to just look at symptoms. Are there negative consequences of this? As I talked about last year, we can unintentionally contribute to stigma and discrimination by only measuring and talking about negatives.
At a broader level, what happens when we assume that people with behavioral health conditions suffer? Does that help give any hope of living in recovery and resilience, even while symptoms are present?
But a more whole person approach to evaluating suffering can pose challenges. Here are two suggestions on how to tackle this subject.
Natural Language Processing
The words we use matter and express a lot about our cognitive and emotional states. When we talk about things like subjective suffering, as framed in the MHSA, a qualitative approach is virtually required. It can be burdensome to conduct a robust qualitative analysis (Believe me, my dissertation was qualitative), but advances in technology, like natural language processing (NLP) can speed up the process while also helping ensure all voices are heard.
As an example, many organizations already get consumer (and family member) feedback via written responses, grievances, compliments and focus groups. Well-established NLP includes sentiment analysis, which provides a quick quantitative sense of how people feel about something. A common tool in retail, sentiment analysis can be useful for stakeholder feedback, public comment periods and experiences of care. Diving deeper, NLP can pull out themes and trends that do not depend upon a person catching the right phrases and interpreting the feedback. Frankly, it can be easy to accidentally skip over a part of a response, misinterpret it, or not catch a subtlety that advanced analytics can assist in identifying. Pair those results with human wisdom in interpreting the meaning of the themes and trends, and more voices have been heard in their own words for greater impact!
In today’s quantitative world, we often shy away from the qualitative for many reasons. NLP can help bridge the gap and give rich life to our understanding of people’s lives. It’s one of the best ways, in my view, of seeing the whole person.
Whole Person Analytics
As the Chief of Behavioral Health Informatics at the San Bernardino County Department of Behavioral Health, I led systemwide strategy to evaluate outcomes. We spent many hours talking about how to tackle subjective suffering. Our solution was to not focus on just a single metric, but at least two data points. Symptom reduction could be one, but there had to be another metric along with it, such as improvements in hope. If someone had improvements in hope AND improved symptoms, for instance, the chances of reducing suffering is likely.
Oftentimes, we focus on a single data point as our metric. There’s good reasons for this. But it can be limiting and inaccurate, especially when we try to get at concepts like suffering. Combining data points together to get a more whole person perspective will give us a better sense of what’s really going on in our communities and with the people we serve.
A major question with these suggestions is how to get the data I suggest. Head over to my LinkedIn article, “Data sources to assess whole person suffering” for initial thoughts on potential data sources.
Stigma and discrimination reduction are major themes of Mental Health Month. Let’s use data for good to tell a more complete, accurate story of people’s lives, suffering, recovery, resilience, and wellness!
Data Sources to Assess Whole Person Suffering
In my latest blog post, I talk about ways to measure a reduction in suffering from a more whole person perspective. In California, we’re asked to evaluate subjective suffering, as described in the Mental Health Services Act. As we honor Mental Health Month, we all want to reduce suffering, but as I discuss in the blog, it’s critical to take a more whole person definition of suffering and not just focus on symptom reduction.
Focus groups, written survey responses and reflections, and progress notes are all potential data sources for Natural Language Processing (NLP) to help assess suffering. And especially in behavioral health, most of these are already collected. So what a great way to use existing data!
The Family Experiences Interview Scale (FEIS) is a semi-structured interview for loved ones to gain a more whole person understanding of their experiences. It quantifies many common data elements and can provide rich context that can enhance understanding of individual and family suffering.
Many states have implemented the Child and Adolescent Needs and Strengths (CANS), especially in child welfare and behavioral health services. The Adult Needs and Strengths Assessment (ANSA) (the adult version) is similar and increasingly popular. One of the things I really like about these tools is they give a more whole person perspective that is quantifiable. The strengths sections, for instance, provide a way to inform a more holistic understanding of people.
In my blog, I mentioned hope as a potential metric. Hope is absolutely critical in health, especially in behavioral health. There are simple tools, like the Beck Hopelessness Scale, that are validated for hope specifically. The CANS and ANSA have some items that get at this idea as well. While hope has a very strong qualitative component (so going back to narrative content as a source), it can be quantified if we want to track changes in hope. For instance, could you tell me on a scale of 1–10, 10 being the most hopeful, how hopeful you are today?
The Substance Abuse and Mental Health Services Administration (SAMHSA) emphasizes the Eight Dimensions of Wellness, which I see in alignment with this whole person suffering approach. Their Wellness Worksheets can be useful not only as an intervention, but as another data source to assess whole person impact.
The What Works Centre for Wellbeing has a series on ways to measure wellbeing. They provide a nice overview across this series that has a very holistic focus, from finances, loneliness, learning disabilities, and even employee assistance programs.
Let’s also not forget about the advantages of data integration. I’m working with several public and private agencies who are working on getting a more whole person perspective by bringing data together across departments and organizations. As we focus on social determinants of health, including non-health data can be valuable in determining whether someone is suffering or not regardless of health symptoms.
Just because some of these concepts are a bit more nebulous and complex doesn’t mean there’s not a way to get at them, both quantitatively and qualitatively. Advances in technology allow us to unlock more data and gain a more whole person view. I call that data for good!
What data sources would you suggest?
About the author:
As SAS’ National Director of Behavioral Health and Whole Person Care, Dr. Josh Morgan helps public health agencies use data and analytics to support a person-centered approach to improving health outcomes. A licensed psychologist, Morgan was previously the San Bernardino County Department of Behavioral Health’s Chief of Behavioral Health Informatics. His clinical work includes adolescent self-injury, partial hospitalization, intensive outpatient programs, psychiatric inpatient units and university counseling centers. Morgan earned his Bachelor of Arts in religious studies from the University of California, Berkeley, and a PsyD (Doctor of Psychology) in clinical psychology with an emphasis in family psychology from Azusa Pacific University. He is also trained in dialectical behavior therapy.