About the asthma data

This page provides general information about asthma data and measures developed by the Minnesota Tracking Program. For more information about these data,contact us.

Information on this page:

What these data tell us:

  • The numbers and rates of asthma hospitalizations and emergency department (ED) visits in Minnesota by year, age group and gender.
  • If an asthma measure is going up or down over time.
  • If a segment of a population is at higher risk for hospitalization or a visit to the ED due to asthma.

How we can use these data:

  • To inform the public about asthma hospitalizations and ED visits.
  • For program planning and evaluation by state and local partners.

What these data can not tell us:

  • What causes asthma, or what leads to asthma hospitalizations and ED visits.
  • The total burden of asthma in a population.
  • The number of people who are hospitalized or who visited the ED due to asthma. Because personal identifiers are removed from the hospital discharge data before analysis, individuals who have multiple hospitalizations or ED visits cannot be identified.

The source of the data:

  • Hospitalization and ED data are extracted from Minnesota Hospital Discharge Data (MNHDD), which is maintained by the Minnesota Hospital Association (MHA).
    • MHA represents Minnesota's hospitals and health systems. Hospitals submit inpatient discharge data to MHA using a standardized billing form. In 2010, 99.3% of all hospitals in the state report hospital discharge data to the MHA, representing 99.4% of all licensed beds in the state.
    • MHA began data-sharing agreements with several states in 2005. Minnesota residents receiving care from hospitals from the participating border states of North Dakota, South Dakota and Iowa are also included in hospitalization measures beginning in 2005. Minnesota residents receiving care from emergency departments from North Dakota are also included in emergency department measures beginning in 2005.
    • MHA data are periodically revised by the MHA to reflect more complete and accurate discharge information.
  • Rates are calculated using denominator counts from the US Census. Data from 2000 and 2010 are from the Decennial Census. Data from 2001-2009 and 2011 are from intercensal population estimates.

How asthma hospitalizations and Emergency Department (ED) visits are identified:

  • Hospitalizations visits are defined as Minnesota residents who are discharged from a hospital in Minnesota or the bordering states of North Dakota, South Dakota, or Iowa. Emergency Department visits are defined as Minnesota residents who are treated and released or subsequently admitted to a facility in Minnesota or North Dakota.
  • Asthma hospitalizations have a primary discharge diagnosis of asthma. Asthma ED visits have asthma as the first-listed diagnosis. Asthma is defined as the International Classification of Disease 9th Revision, Clinical Modification (ICD-9-CM) codes 493.0-493.9. ED visits include both patients treated and released from the ED as well as those that enter the ED and are admitted to the hospital.
  • Records with missing county are included in the state count but excluded from county counts.

The difference between a number, rate, age-adjusted rate, and age-specific rate, and how to use them:

Number:

  • If you want to understand the magnitude or how big the overall burden is, then use the number.
  • The number indicates the total number of hospitalizations or ED visits due to asthma, but not the number of unique individuals hospitalized or who visited the ED.
  • To protect an individual's privacy, counts from 1 to 5 are suppressed if the underlying population is less than or equal to 100,000.

Rate:

  • If you want to understand the probability or what is the underlying risk in a population, then use a rate and confidence interval. A rate is a ratio between two measures with different units. In our analysis a rate is calculated using a numerator, the number of asthma hospitalizations during a period of time, divided by a denominator, the number of people at risk in a population during the same period of time. This fraction is then multiplied by a constant (in this case 10,000) to make the number more legible.
  • To protect an individual's privacy, counts from 1 to 5 and rates based on counts from 1 to 5 are suppressed if the underlying population is less than or equal to 100,000.
  • Rates based on counts of 20 or less are flagged as unstable and should be interpreted with caution. These rates are unstable because they can change dramatically with the addition or subtraction of one case.
  • Age-adjusted rate:
    • Age-adjusted rates are useful when comparing the rates of two population groups that have different age distributions
    • A weighted average, called the direct method, is used to adjust for age in this analysis. Age specific rates in a given population are adjusted to the age distribution in a standard population by applying a weight. The U.S. 2000 Standard population is used as the basis for weight calculations.
  • Age-specific rate:
    • A rate of an event (such as disease or death) measured within a particular age group. It is similar to a crude rate but is calculated within an age group (e.g. an age-specific rate of asthma hospitalizations in adults 35-44 years of age).

How to tell if the underlying rate or percent differs compared to another rate or percent:

  • Assessing the confidence interval for the percent or rate is one approach to determine whether there are differences over time or compared to another location. If they do not 'overlap' then they 'differ.' Although it is not a 'true' statistical test, it is a commonly accepted way to compare percents or rates and tends to be more conservative than statistical testing.
  • A confidence interval for a rate is a measure of reliability. In this analysis, 95% confidence intervals were calculated. A 95% confidence intervals is the interval within which the true value of the rate would be expected to fall 95 times out of 100. When the number of events is fewer than 100, the 95% confidence interval is calculated based on the inverse gamma distribution in this analysis. When the number of events is 100 or greater, the 95% confidence interval is calculated based on normal approximation.

The limitations of the data:

  • Multiple hospitalizations or ED visits by the same patient cannot be identified, and are not excluded.
  • These data are not appropriate for estimating the total burden of asthma.
  • Minnesota residents discharged from Wisconsin hospitals are not included, so hospitalization and ED visit rates for counties in which residents are likely to receive care from Wisconsin may be underestimated. Rates for counties in which residents are likely to visit hospitals that do not submit data to the Minnesota Hospital Association (e.g., Veteran's Administration or Indian Health Services hospitals) may also be artificially low.
  • There is usually a two year lag period before hospitalization and ED visit data are available.

More technical information about the data:

To learn more about asthma, contact the MDH Asthma Program. For more about the asthma hospitalization data and measures developed by the MN Tracking Program, contact us.