Arthroplasty Utilization in the United States is Predicted by Age-Specific Population Groups

Bronislava Bashinskaya,Valentin Antoci,Ryan M Zimmerman,Brian P Walcott

doi:10.5402/2012/185938

Bronislava Bashinskaya, Valentin Antoci + Show 2 more

Open Access

https://doi.org/10.5402/2012/185938

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Abstract

Osteoarthritis is a common indication for hip and knee arthroplasty. An accurate assessment of current trends in healthcare utilization as they relate to arthroplasty may predict the needs of a growing elderly population in the United States. First, incidence data was queried from the United States Nationwide Inpatient Sample from 1993 to 2009. Patients undergoing total knee and hip arthroplasty were identified. Then, the United States Census Bureau was queried for population data from the same study period as well as to provide future projections. Arthroplasty followed linear regression models with the population group >64 years in both hip and knee groups. Projections for procedure incidence in the year 2050 based on these models were calculated to be 1,859,553 cases (hip) and 4,174,554 cases (knee). The need for hip and knee arthroplasty is expected to grow significantly in the upcoming years, given population growth predictions.

Highlights

As the post-World War II “baby boom” generation ages, a growing percentage of Americans will be living into their eighth decade and beyond [1]
An accurate assessment of current trends in healthcare utilization as they relate to arthroplasty may predict the needs of a growing elderly population in the United States
Projections for procedure incidence in the year 2050 based on these models were calculated to be 1,859,553 cases and 4,174,554 cases

Summary

Introduction

As the post-World War II “baby boom” generation ages, a growing percentage of Americans will be living into their eighth decade and beyond [1]. To test our first hypothesis, we identified three population groups based on available United States Census data: total population, population over 64 years of age, and population over 84 years of age. These values were used to generate individual scatterplots to allow for a visual interpretation between the variables. To analyze the ability of population trends to predict future arthroplasty incidence, linear regression analysis, fitted using the least squares approach, was utilized. Using the regression formula, arthroplasty trends in future years were predicted using estimated population data from the United States Census Bureau [15]

Results

Discussion

Conclusion