Saturday, May 21, 2016

Population health data science, complexity, and health equity---Reflections from a local health official

I was honored to be invited to speak at the Stanford Center for Population Health Sciences Annual Colloquium on October 26, 2015. They have an exciting new transdisciplinary program to improve the health of populations.

I covered three related areas: population health data science, complex adaptive social systems, and health equity. I ended my talk by focusing on the inter-generational, lifecourse transmission of the effects of trauma to children ages 0 to 5 and how this contributes to racial health inequities.

Here was my thesis:
  1. For the new field of population health data science we must focus on transforming health relevant data into actionable knowledge. To produce actionable knowledge we must integrate methods from the fields of human-centered design, decision sciences, and behavioral economics. In a sense we must start backwards. In the traditional approach we focus on studying populations to discover average solutions ("one size fits most"). Actionable knowledge must be user- and context-centered, and account for individual variation. We use emerging technologies to make this faster, cheaper, better, and actionable.
  2. Human populations are complex adaptive social systems (CASS). To tackle the toughest challenges (e.g., health inequities) requires CASS approaches. How we conceptualize CASS frame how we study and test solutions. To understand CASS we must leverage computational modeling. From this laboratory we learn that simple rules can produce very complex phenomena. We are humbled to know that existing “real world” data are only one realization of many possible realizations. "Off the shelf" solutions do not exist; we must iterate to a solution through community engagement, experimentation, and continuous improvement (e.g., collective impact). 
  3. Our ultimate goal is to mobilize and transform communities. This starts by learning how to transform ourselves, our teams, and our organizations through testing and learning (“continuous improvement”). In public health the approaches we use to transform communities and inform policy decisions include health impact assessment, collective impact, and community-based participatory approaches. These key approaches add capability to our toolbox public health methods. Collective impact for transforming CASS problems has received enormous attention---and deservedly so. Collective impact is continuous improvement methods applied at a social scale for CASS problems. Collective impact embraces the challenges of complexity, and methodically focuses on collaboration and community transformation through a common agenda, shared measurement, mutually-reinforcing activities, continuous communication and improvement, and backbone support.
  4. Our main population health agenda must be to eliminate racial health inequities. Our collective priority must be to interrupt the inter-generational transmission of the effects of trauma (toxic stress) on young children. Toxic stress alters the brains, bodies, and behaviors of young children, thereby permanently affecting memory, judgment, self-regulation, and physiology. This results in higher risk behaviors and adult chronic diseases. Furthermore, Black/African Americans are traumatized throughout their lives by racism and discrimination. This focus---inter-generational transmission of toxic stress---enables us to prioritize and target social policies and social determinants of health with the biggest potential to eliminate the “childhood roots of adult health inequities.”

Summary slide

  1. Population health data science
    1. Start backwards (understand individual and group decision-making!)
    2. Focus on actionable knowledge (Advise--Predict--Discover--Describe)
    3. Focus on human-centered design (“precision public health”)
  2. Transforming complex social systems
    1. Understand complex adaptive systems (requires humility)
    2. Transform self, teams, organizations, communities (in that order:
    3. requires continuous improvement, taking risks, learning from failures)
  3. Tackling population health inequities
    1. Inter-generational transmission of trauma
    2. Toxic stress alters brain, body, and behavior
    3. Life course of trauma, racism, and discrimination
    4. 4Ps of public health: prevent, protect, prepare, promote
    5. 6Ps of complex systems: people, policy, place, program, provider, parents

Slide presentation




Video presentation

Saturday, May 14, 2016

Saturday, May 7, 2016

What Stephen Curry can teach us about the science of improvement

The Golden State Warriors can teach us a few things (actually a lot!) about leadership, organizational culture, teamwork, and performance improvement (also called continuous quality improvement). Performance improvement consists of improving processes to deliver better results. Improvement can be incremental or breakthrough. The science of improvement is best understood by understanding the theory of knowledge creation (plan-do-study-act) and single-loop and double-loop learning (Maccoby 2013).

On April 16, 2016, the New York Times published a graphic (Figure 1) depicting "752 lines---one for each NBA player who finished in the top 20 in 3-point attempts made in each season since 1980. Sitting atop it is the Golden State Warriors's Stephen Curry, who finished the regular season with a record 402 3-pointers" (Aisch, 2016).

Figure 1: Stephan Curry's 3-point record in context is "off the charts." "This chart contains 752 lines --- one for each NBA player who finished in the top 20 in 3-point attempts made in each season since 1980. Sitting atop it is the Golden State Warriors's Stephen Curry, who finished the regular season with a record 402 3-pointers." (Source: [])

Incremental performance improvement occurs by improving practices, and practices are based on accepted theories. A theory is an explanatory (or causal) model that can explain observed phenomena. Theories are not always explicit; they can be assumptions or mental models, sometimes they are hidden. The typical approach is to use PDSA cycles to test and adjust practice improvements (Figure 2). We plan to test a practice innovation, we test (do) the practice innovation, we study the results, and we act on what we learned, leading to incremental improvements.

Figure 2: Plan-Do-Study-Act (PDSA) cycle of experimentation and continuous improvement
Chris Argyris called this single-loop learning (Maccoby, 2013). He recognized that PDSA can also be used for double-loop learning which can lead to new theories and breakthrough performance improvements. Figure 3 depicts PDSA with single-loop and double-loop learning.

Figure 3: PDSA with singe-loop and double-loop learning

For example, when we are dissatisfied with the results of a practice we have two choices:
  1. Improve the practice (single-loop learning; possible incremental improvements), or 
  2. Improve the theory (double-loop learning; possible breakthrough improvements)
Double-loop learning makes these possibilities explicit and encourages innovative (breakthrough) thinking.

I propose that before Stephen Curry, we witnessed primarily single-loop learning and incremental improvements in making 3-pointers. Note that the cumulative improvements over three decades is very impressive! 

Also, I propose that with Stephen Curry (supported by an amazing team and organization), we are witnessing primarily double-loop learning and breakthrough improvements in making 3-pointers. Curry is changing the physics of shooting, and the Warriors are changing how basketball is played. The Warriors are developing new theories of shooting and playing. Many articles have been written about the Warriors's record setting year in basketball.

I often use sports to illustrate continuous improvement. I now use Figure 1 to teach not just PDSA, but also single-loop and double-loop learning. After all, single-loop and double-loop learning makes PDSA much more powerful, practical, and fun. Double-loop learning enables us to always question our assumptions, and is most productive when we use diverse, transdisciplinary teams.

References

Aisch G and Quealy K. Stephen Curry's 3-point Record in Context: Off the Charts. New York Times. April 16, 2016. Available from: http://nyti.ms/1SJHEvc

Maccoby M, Norman CL, Norman CJ, Margolies R. Transforming Health Care Leadership. 1st ed. Jossey-Bass; 2013. Available from: http://amzn.com/1118505638