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Descriptive statistics involves describing and organizing data collected in a research. It is used by researchers and consumers of research reports, to understand more about the research data.

The statistics assist in understanding how the data is distributed across possible range of values; in order to know whether or not the shape of the variable is normal; and understanding whether one’s subjects tend to cloud in one point on the distribution, or if they are widely scattered throughout the possible range of values (Mc Tarvish & Loather, 2002). In health care, it is commonly used in evidence-based research.

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Mostly, descriptive statistic forms an end of analysis of data or a beginning of testing hypothesis in experimental research (Mc Tarvish & Loather, 2002).

In the healthcare research, the ultimate goal is to develop knowledge and evidence-based practices there by supporting scientific research. The analysis of results, interpretation, and generalization that a researcher generates provides an important piece of research.

Introduction

This Statistical Brief provides descriptive statistics on expenditures for the top five therapeutic classes of outpatient prescription drugs in 2007 (ranked by total expenses) for Medicare beneficiaries age 65 and older in the U.S. civilian no institutionalized population. MEPS uses prescription drugs therapeutic classes as defined by the Multum Lexicon. In 2007, 17 broad therapeutic classifications were identified.

The estimates presented are derived from the Household and Pharmacy Components of the 2007 Medical Expenditure Panel Survey. Expenditures include payments for Medicare beneficiaries age 65 and older, from all sources (e.g., out of pocket, private and public insurance sources) for outpatient prescription drug purchases during 2007.

Insulin and diabetic supplies and equipment are also included in MEPS prescribed medicines estimates. Over-the-counter medicines are excluded from these estimates as are prescription medicines administered in an Inpatient setting or in a clinic or physician’s office. All differences discussed in the text are statistically significant at the 0.05 level or better.

Findings

In 2007, the top five therapeutic classes of prescribed drugs purchased by Medicare beneficiaries age 65 and older (ranked by total expense) were metabolic agents, cardiovascular agents, central nervous system agents, gastrointestinal agents, and hormones. These classes together accounted for 66.2 percent of the $81.7 billion total prescription drug expenses by these adults.

Metabolic agents had the highest total expenses ($18.6 billion) among the top five therapeutic classes for Medicare beneficiaries age 65 and older. This was more than three times the expense for hormones ($5.4 billion), the fifth highest therapeutic class.

Expenditures on cardiovascular agents ($14.7 billion), the second highest class, were also notably higher than the other three classes. When expressed as percentages of all prescribed medicine expenses for Medicare beneficiaries, these classes ranged from 6.6 percent for hormones to 22.7 for metabolic agents.

Among Medicare beneficiaries, age 65 and older with a prescribed drug expense, just over three-quarters (77.3 percent) purchased cardiovascular agents, more than half (57.9 percent) purchased metabolic agents, and nearly half (48.5 percent) purchased central nervous system agents. Smaller proportions of persons purchased hormones (36.2 percent) or gastrointestinal agents (29.8 percent).

In terms of average expense per prescription, gastrointestinal agents had the highest average ($114) followed by metabolic agents ($94) (figure 5). Among the other three classes, the averages for central nervous system agents ($65) and hormones ($62) were both higher than for cardiovascular agents ($40).

Data Source

The estimates shown in this Statistical Brief are based on data from the MEPS HC-113: 2007 Full Year Consolidated Data File and the MEPS HC-110A: 2007 Prescribed Medicines. arch project.

REFERENCE

Mc Tarvish, G. ; Loather, J. (2002). Descriptive and inferential statistics: an introduction. New York: NY. Allyn and Bacon.

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