Target Setting Guide: Approaches for Target Setting

States may use a variety of target setting approaches1 and must clearly and completely explain their rationale and methods. The following information provides an overview of methods states may want to consider. For more details on each of the methods, see Additional Guidance on Target Setting Approaches.

Percent or Percentage Point Improvement

Percent or percentage point improvements are common methods for setting targets. The following list includes several different ways of determining and applying these changes over time to target-setting methods.

  • Average year-over-year growth/change. Using historical data, calculate the average growth/change from year to year. This change can be calculated as a percent improvement or a percentage point improvement.
  • Overall growth/change. Calculate the overall growth from two historical points in time (e.g., from year 1 to year 5) using either percent or percentage point improvement. Increase the end target five years out, by that total growth.
  • Moving (rolling) average. If the historical data are not stable, a moving average can be calculated and added to each of the future years. The moving average may be based on a period of two, three, or four years, depending on the number of years of historical data available.
  • New baseline (or no historical data). If historical data are not available or if a new baseline has been established (e.g., due to changes in data collection methods), start with the new baseline (or most recent year of actual data) and increase that by a certain percentage or number of percentages points each year.

Start with the End Goal

Decide on the target for the last year of the SPP/APR cycle. One approach to setting that end goal is by determining a meaningful/statistically different value from baseline or current data.

Trend Analysis and Forecasting

A trendline, also referred to as a line of best fit, is a straight or curved line on a chart that shows the general pattern or overall direction of the data. Trend analysis is most often used to show data movement over time, particularly to estimate data in future years. You can decide on a target based on the trendline projection. An important consideration in trend analysis is how far back to go; that is, when to start the trendline.

Tools like Excel can be used to add a trendline to a chart and extend the trendline to future years (forecast). There are different options for doing trend analysis and forecasts in Excel, depending on the type of data you have.

Statistical Modeling/Analysis

Statistical analysis can be used to help predict future results and thus, targets, using additional data such as population data, regional data, or outliers.

Additional Considerations

For each of the approaches, consider changes in state circumstances that may impact performance in any given year, such as data quality issues or the scope and status of improvement initiatives. There may be legitimate reasons for maintaining stability for a few years, and targets may remain the same for several years. Similarly, targets in the intervening years may increase incrementally, but not by the same amount each year. However, targets must show improvement from the baseline in the end.

An effective way to engage stakeholders in the target-setting process is to present multiple options for targets, explain the rationale for each, and solicit feedback. Presenting these options visually, e.g., all on one graph, allows stakeholders to see the impact of each approach. An example is presented in Figure 8 in the Examples of Data Visualization section.


1Hubbard, K., Makram, T., Klein, R., & Huang, D. 2020. Target-Setting Methods in Healthy People 2030. Healthy People Statistical Notes.