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Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Prevalence is the proportion of individuals in a population who have the disease at a point in time or during a given time period.

Prevalence is computed by dividing the number of existing cases at a particular point or period in time by the total population from which the cases came. In this report, prevalence estimates are generated in the analysis of data from the Behavioral Risk Factor Surveillance System, School Health Education Profiles, Youth Tobacco Survey, Sentinel Event Notification System of Occupational Risk, and Health Plan and Employer Data and Information Set from the National Committee for Quality Assurance.

The binomial test is very similar to the t-test for comparing prevalence measures between two groups and is interpreted the same way. The average estimates a "typical" value for a given continuous variable in a specific population.

In this report, average estimates are generated in the analysis of data from the Behavioral Risk Factor Surveillance System, Sentinel Event Notification System of Occupational Risk, and Healthcare Cost and Utilization Project. The incidence rate expresses the rate at which events occur in a population at risk at any given point in time during a defined time period. The numerator of the incidence rate is the number of new events in the population during a given time period.

The population at the midpoint of a given time interval is used to estimate the average population over the entire interval.

Incidence rates are generally multiplied by a factor of 10 so that they can be better understood in terms of a population.

In this report, incidence rates are generated in the analysis of data from the Michigan Inpatient Database, Michigan Resident Death File, and Sentinel Event Notification System of Occupational Risk. Populations often differ in their distribution of age, which may in turn affect the overall rate of events in that population. An age-adjusted rate is a weighted average of age group specific rates in the population under study.

To compute an age-adjusted incidence rate, the first step is to compute the comprising age specific rates. In this report, age-adjusted rates are generated in the analysis of data from the Michigan Inpatient Database and the Michigan Resident Death File. The purpose of a confidence interval (CI) is to estimate the statistical uncertainty around a particular measure.

In this report, 95% confidence intervals are provided for estimates of prevalence and average annual incidence rates.

The confidence interval formula for an estimate of prevalence is based on the binomial distribution. The confidence interval formula for a crude incidence rate is based on the Poisson distribution.

The confidence interval formula for an age-adjusted incidence rate is based on the Poisson distribution. Confidence intervals can be used as a method to test whether a specific measure is statistically different between groups. Incidence rate estimates calculated with a small number of events or population sizes are statistically unstable. To determine if Michigan has experienced an overall trend in asthma hospitalization and mortality rates over the 12-year period 1990-2001, the Spearman Correlation Coefficient and its accompanying statistical Rank Correlation Test were utilized. If there is a statistically significant increase in asthma hospitalization rates over time, the Spearman Correlation Coefficient will be positive and the p-value for the test will be less than 0.05. If there is a statistically significant decrease in asthma hospitalization rates over time, the Spearman Correlation Coefficient will be negative and the p-value for the test will be less than 0.05.

IMPORTANT: This is a crude analysis that simply identifies whether there is an overall increase or decrease in the asthma hospitalization or mortality rates. For example, if one population has a larger number of young children than another, it could demonstrate a higher asthma hospitalization rate simply due to its age structure.

Prevalence is computed by dividing the number of existing cases at a particular point or period in time by the total population from which the cases came. In this report, prevalence estimates are generated in the analysis of data from the Behavioral Risk Factor Surveillance System, School Health Education Profiles, Youth Tobacco Survey, Sentinel Event Notification System of Occupational Risk, and Health Plan and Employer Data and Information Set from the National Committee for Quality Assurance.

The binomial test is very similar to the t-test for comparing prevalence measures between two groups and is interpreted the same way. The average estimates a "typical" value for a given continuous variable in a specific population.

In this report, average estimates are generated in the analysis of data from the Behavioral Risk Factor Surveillance System, Sentinel Event Notification System of Occupational Risk, and Healthcare Cost and Utilization Project. The incidence rate expresses the rate at which events occur in a population at risk at any given point in time during a defined time period. The numerator of the incidence rate is the number of new events in the population during a given time period.

The population at the midpoint of a given time interval is used to estimate the average population over the entire interval.

Incidence rates are generally multiplied by a factor of 10 so that they can be better understood in terms of a population.

In this report, incidence rates are generated in the analysis of data from the Michigan Inpatient Database, Michigan Resident Death File, and Sentinel Event Notification System of Occupational Risk. Populations often differ in their distribution of age, which may in turn affect the overall rate of events in that population. An age-adjusted rate is a weighted average of age group specific rates in the population under study.

To compute an age-adjusted incidence rate, the first step is to compute the comprising age specific rates. In this report, age-adjusted rates are generated in the analysis of data from the Michigan Inpatient Database and the Michigan Resident Death File. The purpose of a confidence interval (CI) is to estimate the statistical uncertainty around a particular measure.

In this report, 95% confidence intervals are provided for estimates of prevalence and average annual incidence rates.

The confidence interval formula for an estimate of prevalence is based on the binomial distribution. The confidence interval formula for a crude incidence rate is based on the Poisson distribution.

The confidence interval formula for an age-adjusted incidence rate is based on the Poisson distribution. Confidence intervals can be used as a method to test whether a specific measure is statistically different between groups. Incidence rate estimates calculated with a small number of events or population sizes are statistically unstable. To determine if Michigan has experienced an overall trend in asthma hospitalization and mortality rates over the 12-year period 1990-2001, the Spearman Correlation Coefficient and its accompanying statistical Rank Correlation Test were utilized. If there is a statistically significant increase in asthma hospitalization rates over time, the Spearman Correlation Coefficient will be positive and the p-value for the test will be less than 0.05. If there is a statistically significant decrease in asthma hospitalization rates over time, the Spearman Correlation Coefficient will be negative and the p-value for the test will be less than 0.05.

IMPORTANT: This is a crude analysis that simply identifies whether there is an overall increase or decrease in the asthma hospitalization or mortality rates. For example, if one population has a larger number of young children than another, it could demonstrate a higher asthma hospitalization rate simply due to its age structure.

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