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Smoking PaST Framework


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The newly released Smoking Prevalence, Savings, and Treatment (SmokingPaST) Framework is a tool designed to calculate the impact of investments in tobacco treatment programs on health and medical cost savings.  The framework combines what is already known about the medical costs of smoking, the health benefits of quitting and the effectiveness of different quit methods.  It can be used to help guide employers, city, state and national policymakers in making decisions about how to invest funds in tobacco treatment efforts. 

 

An article published in the September/October, 2011 issue American Journal of Health Promotion describes the use of the framework for specific populations and quantifies the significant drops in smoking rates that can be achieved and medical cost savings that can be captured by employers as well as state and federal governments through tobacco treatment and prevention programs.  The article is available here 

 

We envision two types of users of the Framework:

 

  • Program leaders and policy makers.  We expect that most users will be program leaders and policy makers who use the Framework to make decisions for their own populations.  They will plug in values relevant to their own populations and accept the results as presented.  We encourage you to let us know how you used the Framework and feedback on its usefulness.

 

  • Scientists and model builders.  We expect that some users will be scientists and model builders who enjoy looking at spreadsheets and are good at building models.  We encourage you to look for faults in our logic, errors in our formula and broken links in the spreadsheet. We hope that you can help us improve the Framework, and use it to build or enhance their own Framework or model.  All we ask is that you give us credit when appropriate and share your insights with us. We retain ownership of the Framework.

 

Tips on how to use the The SmokingPaST Framework

Below are a few tips on how to use the The SmokingPaST Framework:

 

  • Read the article (available here).  Read the article for a basic description of the Framework, the rationale behind the assumptions, the formulae, and the meaning of the outputs.

 

  • Not fancy.  We are posting the spreadsheet in the rough format with all the warts and dimples that resulted from the organic way in which we developed it.  We added new formulae for new output variables as we they occurred to us.  The result is arms and trees flowing every which way.

 

  • One page for each population application.  The spreadsheet has four sheets, one for each employer, county, state and national applications.  All the sheets have the same formulae; we did this to help us sort through different population applications at the same time. The names of some the variable in the employer level population are different from the other populations.

 

  • Current and possible scenario.  Each sheet includes formula for a current and possible scenario.  The possible scenario formulae are shown in red.  We added this second set of formulae for each page to allow users to show results side by side given different  assumptions for the population level variables.

 

  • Insert your own values. The numbers shown in blue are values you may wish to change for your population.   You may choose to insert your own values for these numbers.  They include current adult population, smoking rates of current adults, new adults,  smoking rates of new adults, adult immigrants, smoking rates of adult immigrants, adult emigrants, smoking rates of adult emigrants,  percent of current adults attempting to quit smoking, percent of quit attempters quitting cold turkey, pharma therapy only, behavioral therapy only and pharma plus behavioral therapy,  success rate by quit method, cost by quit method and medical cost/smoker/year.

 

  • Primary results.  The numbers shown in green are the primary output results of the Framework.  These include smoking prevalence rates at the end of each of the years illustrated, projected years of life saved, projected medical costs  saved, medical care cost savings/quitter, cost /quitter, program costs. cost/year of life saved, and return on investment on medical costs.

 

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