Building of the global movement for health equity: what health care can do

ScienceDirect – The Lancet : Building of the global movement for health equity: from Santiago to Rio and beyond – Thanks to @katellington for sending this my way.

Contained within is a concise statement of where health care fits into social determinants. Worth a read to see what’s new in social determinants. And from the read, social determinants is more new than I thought….

…. there are three important roles for the health-care system (webappendix p 1). First is to ensure universal access to high-quality care, with increased focus on prevention and health promotion.13 Second, people in the health sector—from the Minister of Health to primary care professionals and medical and health organisations—should be the advocates for action on social determinants of health. There are good examples of cooperative working between health and other sectors. Third, ensure that routine monitoring systems are in place for health equity and the social determinants of health, undertake evaluation of policies on these topics, and increase the knowledge base.

Now Reading: Understanding the science of life expectancy #SDOH

The concept of tracking life expectancy as a measure of a society’s health hasn’t been a part of my (should I say most?) physician’s experience – it’s just been a yearly announcement on a news show. When I went to England in 2010 I was impressed that it’s much more deeply thought of (see below), and more recently in my social determinants reading, as a key metric to understand social determinants of health.

It’s done in the lead in on this paper:

In the Washington, D.C., metropolitan area, for example, there is a nine-year increase in life expectancy as one takes the subway ride on the Blue Line from downtown Washington to Fairfax County, Virginia.

I decided to dig deeper and reviewed the paper referenced in this post, and I was immediately taken aback by this piece of information:

Tracking county disparities after 2002 until 2009 was impossible, because the US government did not release county-level mortality data during this time period.

The paper doesn’t say why this is, other papers from this time period (by these same authors) confirm this lack of access, but none say why (if anyone knows, post in the comments).

What they did here is look at the life expectancy “frontier,” which is the expectation of where the life expectancy of a particular county was compared to the life expectancy trajectory of the countries with the highest life expectancy. And,

  • there’s huge variation in US counties around life expectancy
  • US counties are mostly behind the frontiers of peer nations
  • US counties have been falling behind from 2000-2007

In 2007, county-level life expectancies range from 15 years ahead of the international frontier to over 50 years behind for men and 16 years ahead to over 50 years behind for women.

There’s a nice discussion at the end of what to do about this and how the health system fits in to this issue. Data point: 1.8% of US deaths annually are attributed to lack of health insurance coverage, and there isn’t a difference in access to health care between people in the lowest and the highest life expectancy tiers. It’s worth reading this section because a person can interpret the health system’s role in multiple ways when looking at this data.

As a comparison example, I did some searching around online (okay, a lot of searching around online), to compare the England experience to ours, and the concept of watching life expectancy seems much more ingrained. See: Mortality Monitoring bulletin: Life expectancy and all-age-all-cause mortality, and mortality from selected causes, overall and inequalities . And within a Primary Care Trust (most closely equivalent to a US Health Plan), a thorough analysis of the trend, and causative factors. See page 5 of “Joint Director of Public Health Anuual Report 2011 – Warwickshire NHS” ). There’s even an animated map showing the increase in life expectancy across England.

I don’t know for sure what our health system should be doing differently. Life expectancy is tracked within the United States’ HealthyPeople 2020 under General Health status. What would it be like if we started with life expectancy (or disability free life expectancy) in our health planning and innovation, though? Would people (patients) identify better with “the health system is allowing me to live a longer healthier life” than “the health system is lowering my cholesterol level”?

Of course, I looked up the data for Washington, DC, and in the appendix of this paper, it shows that the 2007 life expectancy of a Washington, DC male and female are 31 and 28 years behind the international frontier. At least this is better than 49 years in 2000 for men, a little better than 29 years for women in 2000. But far worse than Montgomery County, Maryland, just a few miles away that’s 12 years ahead of the international frontier for men, 3 years ahead for women. If you’d like to see a more graphical version, tied to DC metro maps, check out A Short Distance to Large Disparities in Health.

Now Reading: “Behavior is not the whole story” – Social and Economic Determinants are where Health Disparity Begins

Social Determinants – they are the difficult stuff to change, however they may be more influential than all of the individually directed approaches that are out there. I covered a much more thorough analysis in my reading of the Marmot Review (see: Now Reading: Why a focus on lifestyle behavior change may not improve health: The Marmot Review), and this paper is a more concise version of the concepts and research presented there.

Social determinants of health (hashtag: #sdoh), is defined nicely here as:

Exposure to these determinants [of health] is influenced by “upstream” social determinants of health – personal resources such as education and income and the social environments in which people live, work, study, and engage in recreational activities.

The health differences tied to these social differences are huge, trumping what we could do by advising/informing people to change individual decisions they make on a regular basis (if you take into account readiness, uptake, mastery, etc.).

I perceive that there’s been a change in thinking from 1993, to 2002, (and now 2011?) from the landmark studies of their era, as shown below. You can tell the progression from “diseases cause people to die,” to “what people do and who they are cause them to die,” to maybe, “the social milieu that they are a part of causes them to die.” See what you think from the charts I created below, stimulated by the references in this piece:

SDOH Studies Eytan 7659 SDOH Studies Eytan 7660 SDOH Studies Eytan 7661

There are data points in here that are so impressive I went to track them down (and they are real), such as the fact that white households have 20 times the net worth of black households. That’s kind of an “unmentionable” that could come up in an encounter with the health system that makes anything we do less effective.

The authors talk about “health in all policies” – the idea that all social policy has health impacts. We shouldn’t forget those, they may be more important than all the work that the health system does, or the choices people make in their lives. See what you think.

Community Need Index – is this what Health 3.0 is?

Community Need Index – This is another (second of two) useful GIS-based resource that illustrates social determinants of health (again, hashtag #SDOH), this time from Catholic Healthcare West, and sent my way via Richard Roth (@rich_roth), who’s active in the Innovation Learning Network (@HealthcareILN).

As I did with Community Commons, from the last post, I attempted to retrieve two numbers of interest to me, life expectancy, and disability-free life expectancy, for Washington, DC. Here’s what I came up with:

The results are a little different here because this is more of a general index of community need than a peek into multiple health databases. Serves a different need, but also shows the disparities in Washington, DC, that tend to be glossed over in national data (incorrectly, unfortunately).

I think both resources are useful. CNI might be useful to get a snapshot of areas of need (or “deprivation” as they say in the UK) in your community, and Community Commons for deeper investigation into specific data points AND resources active in a particular area that are working to address problems.

And then there’s also County Health Rankings, from the Robert Wood Johnson Foundation.

Clearly the social determinants of health space is getting some attention, is this Health 3.0? If it is, I am supportive, I believe this is work is harder and it is where we’ll make a difference.

Community Commons – A learning utility to create healthy, equitable, and sustainable communities

Community Commons – A learning utility to create healthy, equitable, and sustainable communities – This is one of a pair of resources that was sent my way by smart people who know that I am interested in social determinants of health (hashtag: #SDOH). This one came to me from Tyler Norris, who I met at the Kaiser Permanente Care Management Institute Annual Meeting recently.

Both resources have interactive, graphical information system-type interfaces. I decided to take each one for a test drive to examine two data points, life expectancy, and disability-free life expectancy, in Washington, DC. These data points are important to me based on my read of the Marmot Review, which I blogged about previously.

I couldn’t find disability-free life expectancy, but I did find life expectancy for Washington, DC. This map does show the approximately 7-year difference in life expectancy between a person in Washington, DC and Southern Maryland.

My 3×3 presentation from the #73cents Salon : past, present, future

The video above is the 3×3 presentation I gave at the 73 cents salon on Friday. As I mentioned previously, this was an opportunity for a small group that got together in 2009 to reconnect.

We customized the format of the presentation to be the following (credit, again, to Aaron Hardisty (@aaronhardisty) from the Kaiser Permanente Garfield Center for Healthcare Innovation ( @KPGarfield ))

3 Slides in 3 minutes – Telling the story of YOU

– You will be timed! (in a loving and supportive, yet equal, way)

Slide 1: The Past

– A success or a failure you’ve experienced since 2009
– What did you learn?

Slide 2: The Present

– What is the most exciting thing you are involved in today?
– How are you making an impact?

Slide 3: The Future

– How do you envision yourself making a bigger impact in the future?
– How can the people in this room help you? 

I decided to think broadly about what success means to me. See what you think above, (make your own if you’d like)

If you’re like me and have trouble sitting through 3 minutes of video, the images from the presentation are below. Just click to enlarge. And, thank you 73 cents alums and new alums!