A Job for Predictive Analytics; increased cost for Prescription Drugs

Posted on January 12, 2010 by Jeffrey Newman

The steady and significant increases in the price of medicines, which has no indication of slowing, cries out for an extrapolation of costs going forward. Statheads come forth. Between October 2008 and September 2009, the brand-named medications most commonly used by Medicare beneficiaries rose an average of 9.3 percent. Interestingly, this was a period when there was no inflation and when consumer prices actually dropped. Those drugs that spiked their prices the most included Seroquel (to treat psychosis) 16.1%; Aricept(for dimentia), 17.2% increase; Ambien (for insomnia) 18.8% increase and Flomax (prostate) a 19.7% increase. If you analyze the drug industry answers to why such stark (and obscene) increases in prices of these and other medications, they say that it costs more to make drugs now. 18% per year more? BS! Of course the startling increases affect those on fixed incomes and those who are disabled and those who won’t get cost of living increases. Here’s where the statheads come in. The use of predictive analysis tools that have been developed including machine learning would allow us to predict with a high degree of probability the cost of most drugs separately as they will increase for the next five, ten and twenty years based on historical figures. This information, it seems to me, would be quite valuable in the hands of economists who can also predict the percentage of the population who will and will not be able to afford their medications. There are public databases of information with all information needed to determine the trend. Anyone game?