data in healthcare economics

Healthcare economics impacts everyone as we will all need medical care at some point in our life. A substantial subsection of this is prescription drugs and the affect their prices have on consumers, employers and insurance companies. Prescription medications are a major reason that overall healthcare costs are rising.

The American Association of Retired Persons (AARP) monitors drug prices because these costs effect its members greatly. The AARP Public Policy Institute studies drug prices, as most elder Americans take at least one drug on a regular basis. The Institute’s study of drug prices between 2006 and 2013 showed that prices of the most common drugs increased substantially over this period, so much so that the average cost for a year’s supply of a prescription drug is more than $11,000, which is about 75 percent of the average yearly Social Security benefit. Cumulatively, drug prices increased 81% during the eight-year study while inflation was 18.4%.

How Do They Know?

Collecting data for a study like this takes careful and long-term planning. To collect their data, the Public Policy Institute created “market baskets” of drugs in three categories: brand names, specialty drugs and generic drugs. A total of 662 drugs were studied: 227 brand names, 115 specialty and 280 generic drugs. During the period of study, 397 of the 622 drugs were on the market for the entire period. If a drug was taken off the market, it was removed from the market basket and the previous years’ data adjusted to exclude those drugs. Data was collected from Truven Health MarketScan Research Databases.

A large portion of the data collection process was devoted to defining and organizing the data into the proper categories (brand, specialty and generic drugs). The report explains this in detail, but the important thing to remember is that when you are sorting data, each piece of data can only belong to one category, so well-defined categories are a must.

Analyzing the Data

Once the costs of the market basket drugs were gathered, analysis could begin. The report shows the percentage of each category of drugs as part of the total number of prescriptions for the drugs in the basket of 622 drugs (p. 9) and the percentage of expenditures for the drugs in those categories. Pie charts can be used to show the disparities in the values for each category.

Further analysis of the data was based on comparing prices from month to month and year to year and interpreting the trends. This is how the Institute describes their method: “We calculate the change in prescription drug prices for each month compared with the same month in the previous year (referred to as an annual point-to-point change). We then average all the annual point-to-point price changes for each of the 12 months to produce a rolling average change” (p. 4).

Using this method, the Institute determined that brand name and specialty drugs increased in price substantially (compared to inflation), while generic drugs decreased in price. However, they also found that the rate of decrease in generic drug prices slowed down in 2013. (See p. 5 of the report to see the trend lines.) The Institute analyzed the effects of each category of drugs and found that specialty drug prices outdistanced brand name and generic drugs by far and that these drugs prices led to the $11,000+ annual drug costs. The study reports that “the recent acceleration in overall prescription drug price growth could be an indication that we can no longer rely on lower-priced generics to counterbalance the price trends seen in the brand name and specialty prescription drug markets” (p. 8).


As with all studies, there are some limitations to the Institute’s drug-price study. One important limitation of this study is that the drugs included in the market baskets were the drugs used most by the AARP’s clientele – Americans over 50 years old. A study that includes all drugs would give an even better picture of the overall cost of drugs in America. When you are conducting your own research studies, it is important that you describe limitations such as this and only interpret your results within the limits you have set. AARP has done this having made no claim that their study represents the entire prescription drug market.

If you are interested in better understanding how insightful analysis can be used in overcoming the assumptions, consider pursuing a degree in data science