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. 2007 Feb;55(2):221-6.
doi: 10.1111/j.1532-5415.2007.01063.x.

Epidemiology of Medicare abuse: the example of power wheelchairs

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Epidemiology of Medicare abuse: the example of power wheelchairs

James S Goodwin et al. J Am Geriatr Soc. 2007 Feb.

Abstract

Objectives: To determine the effect of neighborhood ethnic composition on power wheelchair prescriptions.

Design: The 5% noncancer sample of Medicare recipients in the Surveillance, Epidemiology and End Results (SEER)-Medicare linked database, from 1994 to 2001.

Setting: SEER regions.

Participants: Individuals covered by Medicare living in SEER regions without a cancer diagnosis.

Measurements: Individual characteristics (age, sex, ethnicity, justifying diagnosis, and comorbidity), primary diagnoses, neighborhood characteristics (percentage black, percentage Hispanic, percentage with <12 years education, and median income), and SEER region.

Results: The rate of power wheelchair prescriptions was 33 times greater in 2001 than in 1994, with a shift over time from justifying diagnoses more closely tied to mobility impairment, such as strokes, to less-specific medical diagnoses, such as osteoarthritis. In multilevel, multivariate analyses, individuals living in neighborhoods with higher percentages of blacks or Hispanics were more likely to receive power wheelchairs (odds ratios=1.09 for each 10% increase in black residents and 1.23 for each 10% increase in Hispanic residents) after controlling for ethnicity and other characteristics at the individual level.

Conclusion: These results support allegations that marketers promoting power wheelchairs have specifically targeted minority neighborhoods.

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Figures

Figure 1
Figure 1
Rate of Wheelchair Prescriptions for Medicare Enrollees in the 5% Non-cancer Sample Residing in SEER Areas, and also Stratified by Whether the Justifying Diagnosis was Medical or Neurologic/Orthopedic. The change in rate for wheelchair prescriptions justified by a medical diagnosis was significantly greater than that for a neurologic/orthopedic diagnosis (p<0.001 by Chi Square).

References

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