How To Make Sure You're Getting The Very Most Out Of Your Critical Prescription Data
So, when it comes to analyzing prescription data & xponent data that is available from IMS Health or Verispan, this often becomes a lower priority even though this data, combined with your own operations data, can be incredibly valuable. Or, if you are a smaller pharma company and don’t subscribe to this data, single cuts of the data that can be much less expensive can also prove to be valuable, even many months after the purchase.
There are three main points this series of articles will present.
(1) Is this data really that important? What benefits are there to analyzing this data, combined with our own internal sales operations data?
(2) Once our organization has decided that “yes”, this data is very important, how best to analyze it? What tools are out there? Should I outsource?
(3) What type of organization should I be dealing with if I choose to go the outsourcing route?
In our first article on this topic, we're going to focus on the following question:
Is the data important?
Absolutely. Medium and large pharmaceutical companies must have it because compensation is often based on how many scripts are written in a territory, and because the organization does not sell directly to its customers, this third party data is critical.
Smaller organizations, especially startups, don’t necessarily see the value of spending money for this data on a monthly basis and will try to craft compensation plans based on other criteria such as calls, sample drops, recruitment of doctors to speaker’s bureaus or events, and other methods thought to show a salesperson’s effectiveness. While this may work for the short term, the data gathered (calls, samples, recruitment) needs to be assimilated with prescription data to really know the effectiveness of various campaigns.
One example is an actual case with one of our medium sized customers. This customer ran a registry, and had doctors on their advisory board. When all of this data was merged and a query was run to see the script writing habits of doctors on the board, they found one key board member actually wrote no scripts of that company’s drugs and concentrated mostly on a competitor. Without the script data, a compensation plan based on calls, samples, and recruitments would have erroneously rewarded a rep for this particular “bad” doctor.
Medium and larger organizations usually have group management operations. With group plan track information, programs and support for these operations can become very important.
Most pharmas have some sort of relationship with insurance providers that provide for discounts at various levels of script writing. But how are these verified? With this data and tools to mine this data. And remember that these groups expend a great deal of effort to to continually get best pricing, so frequent queries must be run to make sure large groups are not changing policies and switching to competitors.
Continual monitoring of plan track data allows a company to make sure various insurance groups are meeting their obligations.
With the right tools in place you can streamline your presciption data mining and analysis efforts.
So, when it comes to analyzing prescription data & xponent data that is available from IMS Health or Verispan, this often becomes a lower priority even though this data, combined with your own operations data, can be incredibly valuable. Or, if you are a smaller pharma company and don’t subscribe to this data, single cuts of the data that can be much less expensive can also prove to be valuable, even many months after the purchase.
There are three main points this series of articles will present.
(1) Is this data really that important? What benefits are there to analyzing this data, combined with our own internal sales operations data?
(2) Once our organization has decided that “yes”, this data is very important, how best to analyze it? What tools are out there? Should I outsource?
(3) What type of organization should I be dealing with if I choose to go the outsourcing route?
In our first article on this topic, we're going to focus on the following question:
Is the data important?
Absolutely. Medium and large pharmaceutical companies must have it because compensation is often based on how many scripts are written in a territory, and because the organization does not sell directly to its customers, this third party data is critical.
Smaller organizations, especially startups, don’t necessarily see the value of spending money for this data on a monthly basis and will try to craft compensation plans based on other criteria such as calls, sample drops, recruitment of doctors to speaker’s bureaus or events, and other methods thought to show a salesperson’s effectiveness. While this may work for the short term, the data gathered (calls, samples, recruitment) needs to be assimilated with prescription data to really know the effectiveness of various campaigns.
One example is an actual case with one of our medium sized customers. This customer ran a registry, and had doctors on their advisory board. When all of this data was merged and a query was run to see the script writing habits of doctors on the board, they found one key board member actually wrote no scripts of that company’s drugs and concentrated mostly on a competitor. Without the script data, a compensation plan based on calls, samples, and recruitments would have erroneously rewarded a rep for this particular “bad” doctor.
Medium and larger organizations usually have group management operations. With group plan track information, programs and support for these operations can become very important.
Most pharmas have some sort of relationship with insurance providers that provide for discounts at various levels of script writing. But how are these verified? With this data and tools to mine this data. And remember that these groups expend a great deal of effort to to continually get best pricing, so frequent queries must be run to make sure large groups are not changing policies and switching to competitors.
Continual monitoring of plan track data allows a company to make sure various insurance groups are meeting their obligations.
With the right tools in place you can streamline your presciption data mining and analysis efforts.
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