In this post, we're going to look at how data can tell us how 'healthy' our community is. Collecting and analyzing health data is important—it gives us a benchmark (or baseline) to measure improvements or declines in a community's state of health from. It also helps us compare communities and the social, economic, and environmental factors that serve to influence a community's overall state of health—for example, is living in a warmer climate associated with better health? What are the effects of air polluting smog? Lax regulations on the sale of cigarettes and alcohol? Unemployment due to the loss of a significant employer in the community? A tax on sugary beverages?
You can quickly see that without access to population health data, we wouldn't be able to answer these questions very well. And while we can make inferences on the state of a community's health through simple observation—for example, by seeing members of our community engaged in physical activity—we may not want to make any assumptions on how truly active our community is without actually counting, recording, and reporting how many people we see being physically active over a period of time. And there are certain measures of health that are not so easily observed; for example, the rates of chronic diseases, like diabetes, within a community. In this case, to get an accurate number of those afflicted with diabetes, medical laboratory testing and a central database and reporting process is needed to track this data.
Data collection helps us make informed decisions on how to improve the state of health in our communities; it provides the 'hard numbers' or facts that can inspire social and economic actions, like those seen in the examples described in my previous post (courtesy of the Robert Wood Johnson Foundation's website on the subject). How would we know if our strategies to reduce the rates of smoking among young people worked if we hadn't first surveyed their smoking habits?
Let's look at some simple examples of data collection, like marking when a baby was born or how old a person was when he or she died. In the former, the data we’re talking about is the birth rate; in the latter, we’re talking about the mortality or death rate. With the birth rate, we can measure if a population is growing or shrinking and by how much; and if it's growing, it suggests a need to ramp up services for new mothers and young families and build new schools. When looking at the death rate, we learn how often and from what causes people are dying from. If the rate is unusually high, we should be concerned and investigate the reasons why. Data like this is typically measured over a period of time, so that we can track trends. And the tracking of this data needs to be consistent too; if the tracking wasn’t, we wouldn't be able to rely on the data we've collected to make informed decisions on how to improve our community's state or standard of health.
And who's in charge of recording this information? For births, hospitals could be one obvious place where this data is recorded. Government registration offices is another, when applying for official government identification for a newborn (where circumstances merit doing so). For deaths, funeral homes or hospital morgues could be a source for this information. Typically, family or friends or the police inform governing authorities to make sure that a death is properly recorded (as there are legal and tax implications related to a person's death). This data has to flow somewhere to be stored, analyzed and reported, and typically it's a governing authority that does that on a municipal, provincial (state) or federal level. Some data may only be collected by special interest groups, non-profits, or private organizations and this data may not flow to a governing authority to be recorded and reported. Data collected by these groups is still important as this data can sometimes enhance or highlight gaps in government collected data.
Other health data? If we want to know how long people in our community are living to, we could look at life expectancy. High life expectancy implies that a population is living longer, but it doesn't tell us how well people are living as they age. So we look at quality of life measures to understand how well—or not well—people are living as they age. Some data can be more specific—in addition to measuring the rates of chronic diseases, like diabetes, we can also record the rates of various cancers or transmissible diseases, like polio, smallpox, and HIV. We can measure how a population interacts with the health care system, like how many surgeries are performed on a specific body part (think of heart or knee surgeries, for example) or how many doctors there are for a given population. We can also measure how long it takes for health or social services to deliver their services: wait times for emergency department visits or the time it takes to process social support applications, for example, can tell us how quickly health and social needs are being met in the community.
These are just a few of many examples of health and health related data that can be collected. And I could spend more time writing about it, but I think exploring the examples and links below will be more helpful to you.
From the lovely folk at the Robert Wood Johnson Foundation (RWJF), see this link for health data visualized for different counties within U.S. states. Choose a state (or your own state, if you are living in the U.S.) and see the list of measures that are brought forward. I've taken a few screenshots to get you started:
On the page, you can choose a state:
Now choose a state (or, click the Measures tab for data on the entire state). I chose Tennessee for this example:
There are more than a few counties in Tennessee, so I chose Shelby County to investigate (it is, after all, where Elvis was born...) You can see the first category of health data that the RWJF provides on the county under the category of Health Outcomes, telling us how long residents are living to and how they view their quality of life:
In the next category, we look at Health Factors. Health Behaviours are listed below, like smoking and obesity rates:
Clinical Care is the next category. Here, we see data on the ease of access to the health care system and for some specific chronic disease and screening measures:
Following that, Social & Economic Factors is the next category. Here are non-health specific measures that influence a community's state of health (remember the 'social determinants of health'?):
Lastly, we see the Physical Environment category. Here we see environmental or urban design data that influence health:
So that's the RWJF and their site on the topic. As a non-profit, the RWJF provides this information for those looking to compare health data across the U.S. and at the county level.
Each level of government will collect some or all of this data too, and it would be hosted on their individual websites. For example, you can look at the Centers for Disease Control and Prevention's page on national health statistics for data that is collected by the U.S. government. Some of the data collected there will be different from the data that is shown on the RWJF's page on the subject.
I'll stop here :) And happy searching!