Literature DB >> 21417935

Prevalence, healthcare utilization, and costs of breast cancer in a state Medicaid fee-for-service program.

Rahul Khanna1, S Suresh Madhavan, Abhijeet Bhanegaonkar, Scot C Remick.   

Abstract

OBJECTIVE: The purpose of this study was to determine the prevalence, medical services and treatment utilization, and costs associated with breast cancer in a socioeconomically underprivileged population covered by a state Medicaid fee-for-service (FFS) program.
METHODS: We analyzed the West Virginia (WV) Medicaid FFS administrative claims data for women recipients 21-64 years of age enrolled continuously in the program during the calendar year 2005. Breast cancer-related medical services and treatment use and costs were calculated for women recipients with breast cancer. The excess burden of breast cancer was calculated by comparing the all-cause healthcare utilization and costs among women recipients with breast cancer to a matched control group of women recipients without breast cancer. Healthcare costs incurred during the 1-year study period were calculated from the perspective of state Medicaid. Cost estimates in the study excluded out-of-pocket expenses and indirect costs of breast cancer.
RESULTS: In 2005, the prevalence of breast cancer in the WV Medicaid FFS program was 22.7/1000. More than 98% of breast cancer-related medical services utilization occurred in the office setting. Approximately 73% of women recipients with breast cancer had at least one claim for breast cancer treatment, with hormone therapy being the most common (55.1%) treatment. The all-cause healthcare costs were significantly higher for women recipients with breast cancer compared to those without breast cancer ($16,345 vs. $13,027, p<0.001).
CONCLUSIONS: Consistent with our expectations, breast cancer diagnosis among women recipients in the WV Medicaid FFS program was found to be associated with higher all-cause healthcare use and costs compared to women recipients in the matched control group. The excess cost burden associated with breast cancer could be attributed to higher office visit, emergency room visit, and prescription medication use among recipients with breast cancer.

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Year:  2011        PMID: 21417935     DOI: 10.1089/jwh.2010.2298

Source DB:  PubMed          Journal:  J Womens Health (Larchmt)        ISSN: 1540-9996            Impact factor:   2.681


  8 in total

1.  Medical costs of treating breast cancer among younger Medicaid beneficiaries by stage at diagnosis.

Authors:  Justin G Trogdon; Donatus U Ekwueme; Diana Poehler; Cheryll C Thomas; Katherine Reeder-Hayes; Benjamin T Allaire
Journal:  Breast Cancer Res Treat       Date:  2017-07-12       Impact factor: 4.872

2.  Enrollment factors and bias of disease prevalence estimates in administrative claims data.

Authors:  Elizabeth T Jensen; Suzanne F Cook; Jeffery K Allen; John Logie; Maurice Alan Brookhart; Michael D Kappelman; Evan S Dellon
Journal:  Ann Epidemiol       Date:  2015-03-21       Impact factor: 3.797

3.  Treatment Costs of Breast Cancer Among Younger Women Aged 19-44 Years Enrolled in Medicaid.

Authors:  Donatus U Ekwueme; Benjamin T Allaire; Gery P Guy; Sarah Arnold; Justin G Trogdon
Journal:  Am J Prev Med       Date:  2016-02       Impact factor: 5.043

4.  Estimation of Breast Cancer Incident Cases and Medical Care Costs Attributable to Alcohol Consumption Among Insured Women Aged <45 Years in the U.S.

Authors:  Donatus U Ekwueme; Benjamin T Allaire; William J Parish; Cheryll C Thomas; Diana Poehler; Gery P Guy; Arnie P Aldridge; Sejal R Lahoti; Temeika L Fairley; Justin G Trogdon
Journal:  Am J Prev Med       Date:  2017-09       Impact factor: 5.043

5.  Determining Breast Cancer Treatment Costs Using the Top Down Cost Approach.

Authors:  Rukiye Numanoğlu Tekin; Meltem Saygılı
Journal:  Eur J Breast Health       Date:  2019-10-01

6.  Breast cancer attributable costs in Germany: a top-down approach based on sickness funds data.

Authors:  Emil Victor Gruber; Stephanie Stock; Björn Stollenwerk
Journal:  PLoS One       Date:  2012-12-10       Impact factor: 3.240

7.  Productivity losses and public finance burden attributable to breast cancer in Poland, 2010-2014.

Authors:  Błażej Łyszczarz; Ewelina Nojszewska
Journal:  BMC Cancer       Date:  2017-10-10       Impact factor: 4.430

8.  Insure Me Cancer Free: An Intervention Utilizing a Dynamic Communication Model.

Authors:  Kimberly M Kelly; Brandon Dolly; Stephenie Kennedy; Elvonna Atkins; Michelle Coon; Kemi King; Yves Mbous; Shelly Rouse
Journal:  Health Behav Res       Date:  2019-03
  8 in total

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