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BRFSS Data Analysis Software - Details



A. Introduction
B. How Vitalnet Handles BRFSS Complexities
C. Vitalnet BRFSS Key Attributes
D. Examples of Vitalnet BRFSS output
E. Vitalnet BRFSS Outcome Measures
F. Vitalnet Compared with Generic Stat Packages
G. Vitalnet Compared with Home-Grown BRFSS Systems
H. Additional Information
 


A. Introduction
 
BRFSS data are valuable: The BRFSS is a rich source of public health data. From the CDC BRFSS web site: The Behavioral Risk Factor Surveillance System (BRFSS) is the world's largest, on-going telephone health survey system, tracking health conditions and risk behaviors in the United States yearly since 1984.
 
fruit BRFSS data are underutilitized: BRFSS data are currently underutilized. The basic reason is that BRFSS data are so complex. It is tedious, error-prone and expensive to analyze BRFSS data by hand using generic stats software. And the complexity has prevented the creation of adequate home-grown BRFSS query systems, despite large amounts of time and money spent on the effort.
 
Vitalnet BRFSS makes best use of the data: Vitalnet BRFSS Table and Map Maker handles all the complexities. Vitalnet BRFSS provides the needed combination of flexibility, ease-of-use, and output capabilities, in a professional software system. Vitalnet makes it much easier and more reliable to analyze BRFSS data, and greatly lowers costs. The result is much better use of BRFSS data for improving US public health, and better use of agency resources.
 
Try out VitalWeb for free (Vitalnet browser platform).
 


B. How Vitalnet Handles BRFSS Complexities
 
1) Weighted data: BRFSS data are of necessity weighted. Epidemiological analyses of the data must take the weighting into account. That rules out "normal" methods of data analysis. The solution: Vitalnet is specially designed to correctly analyze weighted BRFSS data. Vitalnet is much more than a generic stats software: Vitalnet "knows" all the details about BRFSS weighting, and takes care of all the details to ensure correct results.
 
2) Many questions: There are literally hundreds of BRFSS questions. This is confusing to the analyst trying to analyze BRFSS data by hand with generic stats software. And it makes developing home-grown analysis software more difficult. The solution: The special Vitalnet internal database and data dictionary store and integrate data from the many questions. The Vitalnet interface cleanly displays and provides access to the large number of questions.
 
3) Question combinations: Often, several questions need to be combined for analysis, or several responses to a question need to combined. So analysis by hand using generic stats software is tedious and error-prone. And designing a home-grown analysis program is more difficult. The solution: The Vitalnet internal data dictionary "knows about" BRFSS variables and how they interact, so the data are correctly imported and tabulated.
 
4) Wording changes: Question wording can (and does) change over the years. This makes BRFSS results subject to misinterpretation, unless the output is clearly documented. This is tedious and error-prone to do by hand, or to incorporate within a home-grown BRFSS query system. The solution: The Vitalnet internal data dictionary keeps track of the question wording changes. Vitalnet BRFSS output is documented to show how questions might change over time.
 
5) Sub-populations: Many BRFSS questions are only asked of a sub-population. This makes analysis by hand with generic stats software more tedious and error-prone. Misinterpretation results if the output is not clearly documented. And the development of home-grown BRFSS query software is made more difficult. The solution: The Vitalnet internal data dictionary keeps track of sub-population questions. So Witalnet correctly imports and analyzes the data. Vitalnet BRFSS output is documented to show the sub-population.
 
6) Questions not asked: Many questions are not asked some years. This makes analysis with generic stats software tedious and confusing. And it leads to awkward home-grown single-year query systems. To analyze data for a different year, the user has to "back out" of the year, start over again. Also, the single-year system does not let the user combine years to increase the number of responses, or do a time trend analysis. The solution: The Vitalnet internal data dictionary keeps track of which years for each variable. The multi-year Vitalnet interface lets the user easily combine years, and easily do time trend analyses.
 
7) Similar questions: Questions from different modules can be confusingly similar. This can easily lead to analysis errors when the data are analyzed by hand, and again makes development of home-grown software more difficult. The solution: The Vitalnet internal data dictionary keeps track of the exact question wordings, and prevents the wrong variable being used.
 
8) Split surveys: Split surveys lead to multiple weights for each record. This makes analysis by hand tedious and error-prone. It also greatly complicates the development of any home-grown automated system. The solution: The Vitalnet internal data dictionary keeps track of which weight applies to which variable, so Vitalnet automatically produces correct results.
 
9) State-added questions: Each State may add State-added questions. These questions can be confusingly similar to CDC questions, and add even more questions to the number available. This is confusing for analyzing the data by hand, and complicates development of a home-grown query system. The solution: Vitalnet handles State-added questions like any other question.
 
10) Data dictionaries: Data dictionaries (BRFSS codebook) may be incomplete or have errors. Even in the best of circumstances, poring through a data dictionary is tedious and error-prone. The solution: Vitalnet automatically produces correct results. The user never needs to refer to the data dictionary.
 
11) Age-adjusted percents: Calculating age-adjusted percents by hand using generic stats software is tedious and error-prone. The solution: Vitalnet automatically produces correct age-adjusted percents.
 
12) Confidence intervals: Calculating confidence intervals by hand using generic stats software is tedious and error-prone. Doing jack-knife replication is even more difficult and time-consuming. The solution: Vitalnet automatically and quickly produces correct confidence intervals, based on jack-knife replication.
 


C. Vitalnet BRFSS Key Attributes
 
Standards-Based: Before tackling the more complex BRFSS data, we had years of experience analyzing and displaying other public health data. As a first step for developing the Vitalnet BRFSS module, we carefully reviewed CDC and State BRFSS reports, and the extensive technical documentation on the CDC BRFSS web site. physical activity We also spoke with CDC and State staff.
 
Optimized database: We designed a novel record-level database architecture specially optimized for BRFSS data. This was a key step. The special database design results in low disk space requirements, rapid analyses, and retention of record-level detail.
 
Internal BRFSS data dictionary: Vitalnet BRFSS has it's own special internal data dictionary, in database format. It includes question wordings, responses, file layouts, and many other other details. It includes all the information from BRFSS codebooks, and much more, all the metadata needed to make Vitalnet BRFSS run.
 
BRFSS database engine: Vitalnet BRFSS has a special internal "database engine" to correctly read the database and automatically produce the correct results, based on user selections.
 
Data importing included: Next, Vitalnet data importing routines were modified, to rapidly and reliably import BRFSS data into the Vitalnet data warehouse. We import any new data for you. Importing the data takes three days to one week, mostly to modify the internal data dictionary to reflect the new data. Checking the results to ensure correctness takes a few more days.
 
Special BRFSS interface: The BRFSS module uses the same "look and feel" as other Vitalnet modules, making it easy for users to switch between data sets. The interface is customized to handle special features of BRFSS data, such as the large number of questions.
 
Best mapping capabilities: Vitalnet makes png and pdf maps. Each map is publication ready. Each map can be easily and extensively customized by the user.
 
Over 100 BRFSS questions: Currently, over 150 BRFSS variables and "overall questions" are incorporated into the Vitalnet BRFSS module. innovation State-added variables can be added, you just let us know.
 
Easy age-adjusted percents: Vitalnet easily and correctly does age-adjusted outcome measures, which historically have been under-utilized with BRFSS results.
 
Validated to be correct: The program has been extensively verified and tested, both for internal consistency and in comparison with printed reports from the CDC BRFSS web site, State web sites, and CDC WEAT.
 
Customizable: Vitalnet BRFSS can be customized to add other capabilities or analyses. Let us know if anything you might suggest today.

Try out VitalWeb for free (Vitalnet browser platform).
 


D. Examples of Vitalnet BRFSS output
 
The whole point of Vitalnet BRFSS is to let the user easily and reliably make tables, maps, and charts. Vitalnet output formats correctly handle BRFSS numerical results, and include BRFSS-specific documentation. Below are links to examples of output produced by the Vitalnet BRFSS module. Each example took a minute or less to design and produce. The examples are just a sample of what is possible with Vitalnet BRFSS. If you'd like us to add something you find useful, let us know.
 
Tables: The fundamental Vitalnet output type is cross-tabulations. Essentially, Vitalnet lets you compare "anything with anything", make the rows and columns exactly as needed, select any of eight or so "outcome measures", analyze the subpopulation needed, prevent invalid analyses. Here are a few table examples:

  • Typical cross-tabulation
  • Example of combining areas
  • Example of comparing areas
  • Example of comparing regions

  • Body mass index prevalence analysis
  • Last checkup interval prevalence analysis

  • More examples of Vitalnet tables
 
Time trends: A key use of BRFSS data is to tell whether a problem is getting better or worse. Vitalnet BRFSS allows this to be done quickly and easily:

  • Look for trend: Binge drinking in Texas
  • Look for trend: Smoking in Nevada
  • Look for trend: Obesity in AL, CO, DE
 
Charts: To better understand and visualize comparisons, charts are generally easier and more effective than just tables of numbers. Vitalnet BRFSS automatically makes easily customized bar charts, line charts, and pie charts:

  • Pie chart: General health
  • Line plot: Obesity by year and sex
  • Bar chart: Binge drinking by race
 
Confidence intervals: Vitalnet BRFSS automatically and quickly produces correct confidence intervals, using jack-knife replication:

  • Obesity by race: 95% confidence interval
  • Obesity by race: 98% confidence interval
  • Obesity by race: Omit confidence interval

Maps: Along with the tables and charts described above, Vitalnet BRFSS has a complete mapping system. The Vitalnet mapping flexibility and output are much better than any alternative. Each map below was designed and produced in less than a minute:

  • CT map example #1
  • CT map example #2

  • US map example #1
  • US map example #2

  • TX map example #1
  • TX map example #2

  • More examples of Vitalnet maps

  • Try out VitalWeb for free (Vitalnet browser platform).
 


E. Vitalnet BRFSS Outcome Measures
 
From a single simple menu, you can select from select from all the outcomes measures you might need to analyze BRFSS data.
 
Unweighted counts simply tabulate the number of responses.

  • Unweighted number of valid interviews
  • Unweighted number 'yes' for an overall question
  • Unweighted number 'no' for an overall question
 
Weighted counts adjust the number of responses to reflect the actual population size. You can easily select one of the following outcome measures:

  • Weighted number of valid interviews
  • Weighted number 'yes' for an overall question
  • Weighted number 'no' for an overall question
 
Weighted percents compare risk between different populations and years. You can easily select one of the following outcome measures:

  • Weighted percent 'yes' for an overall question
  • Weighted percent 'no' for an overall question

Age-adjusted weighted percents prevent misleading results if an age effect (eg, more diabetes in older people) and a difference in age structure between two populations (eg, UT younger than FL). Vitalnet BRFSS lets the user easily and reliably produce age-adjusted output. Compare the following two outputs with the previous two:

  • Age-adjusted weighted % 'yes' for an overall question
  • Age-adjusted weighted % 'no' for an overall question
 


F. Vitalnet Compared with Generic Stat Packages
 
Vitalnet Table and Map Maker provides much better value than the generic stat packages that have historically been used to analyze BRFSS data.
 
Motivation for GSP - BRFSS data have historically been analyzed using certain commercial generic stat packages (GSP), because there was no alternative. "Generic stat packages" include SAS, SPSS, SUDAAN, and Stata.
 
GSP shortcomings - Using a GSP is far beyond the capability of the great majority of users. Even in expert hands, using a GSP is quite complex, error-prone, awkward, and time-consuming, especially for complex survey data such as BRFSS data. The user needs to understand many details about BRFSS file layouts, BRFSS variables, and how to use the complex software. Also, a GSP is typically not cheap, can easily cost thousands of dollars. Also, the needed training is expensive and time-consuming.
 
Vitalnet provides much better value - Vitalnet is a new and fundamentally different kind of stats package. Vitalnet is specifically and totally customized for analyzing BRFSS data (or some other data set of interest to you), for a particular jurisdiction. Vitalnet "knows" all about the data set.
 
Vitalnet is much easier, more reliable, and more useful. Instead of the confusing array of statistical tests offered by a GSP, Vitalnet offers exactly the options the user might need, in a fully menu-driven format. Instead of the arduous, error-prone task of setting up a GSP analysis, you merely choose options from self-explanatory menus and press "Go". Vitalnet training is mostly focused on understanding data analysis in general, instead of struggling with details of using a GSP.

Here are some ways Vitalnet is better than a GSP for analyzing BRFSS data:

Vitalnet BRFSS ModuleGeneric Stat Package (GSP)
Results in seconds or minutes.
For both casual and expert users.
Is easy-to-use and reliable.
"Knows" details of BRFSS files.
Output is publication-ready.
Takes hours or days.
Requires expert user.
Difficult and error-prone.
User must learn file details.
Output needs reformatting.

 


G. Vitalnet Compared with Home-Grown BRFSS Systems
 
Vitalnet Table and Map Maker provides much better value than home-grown BRFSS analysis systems States and the CDC have tried to develop.
 
Motivation for HGS - Most realize a general statistics package (GSP) is impractical for the great majority of users to analyze BRFSS and other public health data. Web-based home-grown systems (HGS), as developed by the CDC and some States, have been produced to make BRFSS and other data easier to access and analyze.
 
HGS shortcomings - However, in practice the HGS have failed to meet the need. Developing and maintaining data warehouse software is very complex. The results lack many needed capabilities, are buggy, have awkward interfaces, and cost too much to develop and maintain.
 
Vitalnet provides much better value - Vitalnet provides the needed combination of analytical flexibility, ease-of-use, and output capabilities, in a professional software system. With Vitalnet, government agencies can get out of trying to be in the software development business, and get back to their public health mission. Vitalnet allows government agencies to smoothly and efficiently make best use of their data, at much lower cost.
 
Each HGS is somewhat different, with it's own strengths, weaknesses, and quirks. However, none of them adequately meet user needs for analyzing and visualizing BRFSS data. Here are some ways Vitalnet differs from home-grown systems we have used:
 
Vitalnet BRFSS ModuleHome-Grown System (HGS)
Clean, professional interface.
Makes most needed results.
Output is very customized.
User never needs to "back out".
A professional software system.
Can customize data groupings.
Customized charts and graphs.
Output is fully documented.
Output is publication-ready.
Interface has rough edges.
Only makes subset of needed results.
Only limited output customization.
User must "back out" to make a change.
Has rough edges and missing parts.
Data groupings fixed or not accessible.
Charting is missing or works poorly.
Output subject to misinterpretation.
Output needs reformatting.

 


H. Additional Information
 
Cost comparison - Compare what you pay for a "home-grown" system. $10,000 to $30,000 per year for software licenses and hardware costs. $50,000 to $200,000 per year for personnel costs (system analysts, programmers, documentation writers, managers). These costs will vary from State to State, and are hard to find. But they are at least in the $50,000 to $200,000 range, and can easily be more. And that's assuming that the "home-grown" system works well. They typically don't. We guarantee a better solution, at a lower cost.
 
Hassle comparison - Do you want to be in the software development business, or do public health? Also, consider that 1) development takes years, 2) "home-grown" costs in succeeding years may go down some, but not much in practice, and 3) "technology transfer" has not worked well in practice. We guarantee a better solution, with no hassles. satisfied user
 
General information - Vitalnet is a professional data warehouse solution, the product of over 10 years of development. Besides BRFSS data, it can analyze any data set of your choosing, including birth, death, pregnancy, hospital discharge, and many more. Vitalnet runs on a PC desktop and over the internet in a web browser.
 
If you would like more information about Vitalnet BRFSS module, please fill out feedback form or call us. Vitalnet can be rapidly and reliably customized for use by your State. We welcome your requests and suggestions. We will customize your Vitalnet software as required to make better use of the data. We want to help you accomplish your goals, succeed, and enjoy your work.
 
Try out VitalWeb for free (Vitalnet browser platform).
 
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