The right person, at the right moment: precision health promotion

A campaign reaches everyone at the same time, with the same message, through the same channel. Those who need it most are often the ones who see it least, or see it at the worst moment. It is not a problem of effort. It is a problem of aim.

Precision health promotion seeks to improve that aim: reaching the right person, in the right place, at the right moment. And the piece almost always missing is the last one.

From health promotion to precision

In 1986, the Ottawa Charter defined health promotion as the process of enabling people to increase control over, and to improve, their health. The idea still holds. What has changed is how much information is available to decide where and how to act.

On that foundation came precision public health. Muin Khoury and colleagues described it as providing the right intervention to the right population at the right time. In practice, it means using data that already exist (clinical records, surveys, public sources, geography) to describe a population and its surroundings in more detail, and to prioritize.

Three kinds of precision: who, where and when

Who

With data that already exist, a whole population can be ranked by risk, without new tests. In our type 2 diabetes example, an interpretable scorecard shows that contacting 6 of every 100 adults reaches more than half (54%) of future cases. It is an illustrative example, with data generated from an anonymized real-world profile, and a prediction model: it shows associations, not cause and effect.

Where

Risk is not spread evenly across a territory, and neither are services. In our Texas shortage map, 124 of 254 counties have no community health center (FQHC) site, and 1.6 million Texans live more than 30 km in a straight line from one. Knowing where need concentrates changes where it makes sense to open, recruit or fund.

When

Who is at risk is usually known. When a person is ready to act almost never is. People act when three things line up: their circumstances, a real opportunity to act, and their own readiness. When all three meet, the moment to reach out appears.

Research on so-called teachable moments has studied this: there are events (a diagnosis, a new job, the birth of a child) when many people are more open to change. It does not work the same for everyone, which is why we are building tools to analyze those conditions over time, from clinical records to digital health apps.

The same message, at another moment, is a different message.

Precision is not individualism

It is easy to read «precision» as ever more personalized messages. But precision health promotion is not only about talking better to each person. It also means changing what surrounds the decision: clinic hours that match the end of a shift, transport that gets there, a service closer by. People decide; their surroundings tilt the odds.

What precision cannot promise

• The data are not the population. People who don’t seek care, lack insurance or live far away tend to appear less in the data. A model can leave out exactly those who need it most unless it is checked with that in mind.
• Predicting is not explaining. A model identifies who and when. Showing that an intervention changed something requires an evaluation with the right method.
• Validated where it is used. A model built in one population needs validation, and usually recalibration, before it is used in another.
• Privacy and trust. More data means more responsibility. Without trust, no precision lasts.

What changes for a prevention program

1. Start with the question, not the data. Whom do we want to reach, where, and for what?
2. Combine who, where and when. Each helps on its own; together they change the aim.
3. Design the surroundings, not just the message. Sometimes the most precise intervention is moving a schedule.
4. Evaluate with the right method. Tell association from effect. It is part of program design and evaluation.
5. Look after those missing from the data. Always ask who is not there.

Precision does not guarantee better outcomes on its own. It is a way to prioritize with the information at hand. Whether a program improves depends on how it is designed, delivered and evaluated in each context. Figures in the examples are illustrative or come from public sources with a stated cut-off date.

If your program needs to know whom to reach first, where and when, let’s talk.

Further reading

1. World Health Organization. Ottawa Charter for Health Promotion. 1986.
2. Khoury MJ, Iademarco MF, Riley WT. Precision public health for the era of precision medicine. American Journal of Preventive Medicine. 2016;50(3):398–401.
3. Dowell SF, Blazes D, Desmond-Hellmann S. Four steps to precision public health. Nature. 2016;540:189–191.
4. McBride CM, Emmons KM, Lipkus IM. Understanding the potential of teachable moments: the case of smoking cessation. Health Education Research. 2003;18(2):156–170.
5. Buckeridge DL. Precision, equity, and public health and epidemiology informatics: a scoping review. Yearbook of Medical Informatics. 2020;29(1):226–230.
6. Seeking precision in public health. Nature Medicine. 2019;25:1177.