Literature DB >> 31107629

Spending for Advanced Cancer Diagnoses: Comparing Recurrent Versus De Novo Stage IV Disease.

Michael J Hassett1,2, Matthew Banegas3, Hajime Uno1,2, Shicheng Weng1, Angel M Cronin4, Maureen O'Keeffe Rosetti3, Nikki M Carroll5, Mark C Hornbrook3, Debra P Ritzwoller5.   

Abstract

PURPOSE: Spending for patients with advanced cancer is substantial. Past efforts to characterize this spending usually have not included patients with recurrence (who may differ from those with de novo stage IV disease) or described which services drive spending.
METHODS: Using SEER-Medicare data from 2008 to 2013, we identified patients with breast, colorectal, and lung cancer with either de novo stage IV or recurrent advanced cancer. Mean spending/patient/month (2012 US dollars) was estimated from 12 months before to 11 months after diagnosis for all services and by the type of service. We describe the absolute difference in mean monthly spending for de novo versus recurrent patients, and we estimate differences after controlling for type of advanced cancer, year of diagnosis, age, sex, comorbidity, and other factors.
RESULTS: We identified 54,982 patients with advanced cancer. Before diagnosis, mean monthly spending was higher for recurrent patients (absolute difference: breast, $1,412; colorectal, $3,002; lung, $2,805; all P < .001), whereas after the diagnosis, it was higher for de novo patients (absolute difference: breast, $2,443; colorectal, $4,844; lung, $2,356; all P < .001). Spending differences were driven by inpatient, physician, and hospice services. Across the 2-year period around the advanced cancer diagnosis, adjusted mean monthly spending was higher for de novo versus recurrent patients (spending ratio: breast, 2.39 [95% CI, 2.05 to 2.77]; colorectal, 2.64 [95% CI, 2.31 to 3.01]; lung, 1.46 [95% CI, 1.30 to 1.65]).
CONCLUSION: Spending for de novo cancer was greater than spending for recurrent advanced cancer. Understanding the patterns and drivers of spending is necessary to design alternative payment models and to improve value.

Entities:  

Year:  2019        PMID: 31107629      PMCID: PMC6804885          DOI: 10.1200/JOP.19.00004

Source DB:  PubMed          Journal:  J Oncol Pract        ISSN: 1554-7477            Impact factor:   3.840


  33 in total

1.  Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population.

Authors:  Joan L Warren; Carrie N Klabunde; Deborah Schrag; Peter B Bach; Gerald F Riley
Journal:  Med Care       Date:  2002-08       Impact factor: 2.983

2.  Antineoplastic Treatment of Advanced-Stage Non-Small-Cell Lung Cancer: Treatment, Survival, and Spending (2000 to 2011).

Authors:  Cathy J Bradley; K Robin Yabroff; Angela B Mariotto; Christopher Zeruto; Quyen Tran; Joan L Warren
Journal:  J Clin Oncol       Date:  2017-01-03       Impact factor: 44.544

3.  Challenges and opportunities in measuring cancer recurrence in the United States.

Authors:  Joan L Warren; K Robin Yabroff
Journal:  J Natl Cancer Inst       Date:  2015-05-12       Impact factor: 13.506

4.  Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management.

Authors:  Michael J Hassett; Hajime Uno; Angel M Cronin; Nikki M Carroll; Mark C Hornbrook; Debra Ritzwoller
Journal:  Med Care       Date:  2017-12       Impact factor: 2.983

5.  Economic burden of cancer in the United States: estimates, projections, and future research.

Authors:  K Robin Yabroff; Jennifer Lund; Deanna Kepka; Angela Mariotto
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-10       Impact factor: 4.254

6.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

Authors:  M E Charlson; P Pompei; K L Ales; C R MacKenzie
Journal:  J Chronic Dis       Date:  1987

7.  Development, Validation, and Dissemination of a Breast Cancer Recurrence Detection and Timing Informatics Algorithm.

Authors:  Debra P Ritzwoller; Michael J Hassett; Hajime Uno; Angel M Cronin; Nikki M Carroll; Mark C Hornbrook; Lawrence C Kushi
Journal:  J Natl Cancer Inst       Date:  2018-03-01       Impact factor: 13.506

8.  Patients' expectations about effects of chemotherapy for advanced cancer.

Authors:  Jane C Weeks; Paul J Catalano; Angel Cronin; Matthew D Finkelman; Jennifer W Mack; Nancy L Keating; Deborah Schrag
Journal:  N Engl J Med       Date:  2012-10-25       Impact factor: 91.245

9.  Use of posttreatment imaging and biomarkers in survivors of early-stage breast cancer: Inappropriate surveillance or necessary care?

Authors:  Erin E Hahn; Tania Tang; Janet S Lee; Corrine E Munoz-Plaza; Ernest Shen; Braden Rowley; Jared L Maeda; David M Mosen; John C Ruckdeschel; Michael K Gould
Journal:  Cancer       Date:  2015-12-09       Impact factor: 6.860

10.  Stage, age, comorbidity, and direct costs of colon, prostate, and breast cancer care.

Authors:  S H Taplin; W Barlow; N Urban; M T Mandelson; D J Timlin; L Ichikawa; P Nefcy
Journal:  J Natl Cancer Inst       Date:  1995-03-15       Impact factor: 13.506

View more
  1 in total

1.  Benchmark Method for Cost Computations Across Health Care Systems: Cost of Care per Patient per Day in Breast Cancer Care.

Authors:  Douglas W Blayney; Tina Seto; Nhat Hoang; Craig Lindquist; Allison W Kurian
Journal:  JCO Oncol Pract       Date:  2021-03-01
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.