Last week, my colleague Sarah Threnhauser wrote about the issue of loneliness as a social determinant of health—citing recent research findings and the very interesting fact that the United Kingdom created a new position, the “Minister Of Loneliness” (see Is Loneliness The Overlooked Social Determinant?).
The issue of how best to define and measure loneliness was the focus of comments from OPEN MINDS Circle member Scot Adams, the former director of Nebraska Department Of Health and Human Services, Division of Behavioral Health and a senior consultant at the NASMHPD Research Institute. Dr. Adams wrote:
In my experience, one of the issues that caused persons with mental illness to reach crisis point or to seek hospitalization was simple loneliness. No one to share the cold, the darkness, the fear, or the feeling of being unloved. [But] as a concept to build upon, loneliness has a long way to go. The research literature has a variety of definitions about what constitutes loneliness from a measurement standpoint. Without a standard definition, we will be hard pressed to bring this to scale—either in our research or in our interventions.
This is a crucial issue, because if payers and health plans are going to address the issue of loneliness (or any other social determinants of health) estimating the return-on-investment (ROI) for any proposed intervention is essential. This is a process that we’ve written about before: Social Risk & The ‘Value’ Of Health Care, Jumping The ‘Strategy-To-Execution Gap’?, and Social Determinants, Health Care Outcomes, & Health Care Costs – A Look At The Numbers. And to develop that ROI, definitions that allow quantification are essential—definitions of the problem, of the interventions, and of the measures of “return.”
But quantifying social factors is not typical in the health care field. I found the comments in the article, The Need for Comprehensive Health Care Quality Measures for Older Adults, in October’s issue of the journal Population Health Management, very relevant:
In today’s health care system, quality measures typically are designed to assess what providers actually do, rather than what patients want. Regardless of older patients’ priorities, quality measures tend to focus strictly on clinical conditions rather than on their unique psychological and social needs. In addition, existing measures do not comprehensively examine the performance of providers in assessing the burden on older patients and their caregivers. The impact of this complex self-management of health needs is inadequately addressed by current measures, potentially impacting quality of life.
Following up on Dr. Adams comments, we took a look at the literature specific to this issue. If we look at “loneliness” and “social isolation” as examples, we see social determinants of health that include many different (and not mutually exclusive) social relationships and comorbidities. For example, there is a significant overlap between loneliness and social isolation (see Social Isolation, Loneliness And Their Relationships With Depressive Symptoms: A Population-Based Study); social isolation and loneliness are often confounded by associated factors, such as smoking (see Unravelling The Associations Between Social Isolation, Loneliness, And Mortality); and the different dimensions of social relationships are likely to have different implications for health (see Loneliness, Social Isolation And Social Relationships: What Are We Measuring? A Novel Framework For Classifying And Comparing Tools).
What I am reminded of when I read these articles is that while we are moving rapidly to have provider organizations assume more financial risk for consumer outcomes and consumer costs (see Where Are We On The Path To Value-Based Reimbursement?), there is a limited “dashboard” of information for executives to “steer their ship.” We have crude process measures (home visits, medication refills, etc.) and crude measures of outputs (hospital days, emergency room use, etc.). This crude consumer care coordination dashboard leaves lots of room for interpretation—and for misusing precious resources.
The solution, which is emerging, is three-fold: We need better data collection frameworks to integrate consumer information from disparate sources, data analysis tools that provide actionable insights from that data, and the ability to measure the effectiveness of interventions. Unfortunately, we’re building the bicycle while we’re riding it.
For more on meeting these challenge, join my colleague Joe Naughton-Travers, Senior Associate, OPEN MINDS on June 5 at The 2018 OPEN MINDS Strategy & Innovation Institute for the session, “How To Develop A New Service Line: Building A Diversification Strategy & Conducting A Feasibility Analysis,” featuring Teri Herrmann, MA, Chief Executive Officer, SPARC Services and Programs and Eleanor Castillo Sumi, Ph.D., BCBA-D, Vice President of Research and Program Development, Uplift Family Services.