Cost drivers for breast, lung, and colorectal cancer care in a commercially insured population over a 6-month episode: an economic analysis from a health plan perspective. Sagar, B., Lin, Y. S., & Castel, L. D. Journal of medical economics, 20:1018–1023, October, 2017.
doi  abstract   bibtex   
In the absence of clinical data, accurate identification of cost drivers is needed for economic comparison in an alternate payment model. From a health plan perspective using claims data in a commercial population, the objective was to identify and quantify the effects of cost drivers in economic models of breast, lung, and colorectal cancer costs over a 6-month episode following initial chemotherapy. This study analyzed claims data from 9,748 Cigna beneficiaries with diagnosis of breast, lung, and colorectal cancer following initial chemotherapy from January 1, 2014 to December 31, 2015. We used multivariable regression models to quantify the impact of key factors on cost during the initial 6-month cancer care episode. Metastasis, facility provider affiliation, episode risk group (ERG) risk score, and radiation were cost drivers for all three types of cancer (breast, lung, and colorectal). In addition, younger age (p < .0001) and human epidermal growth factor receptor-2 oncogene overexpression (HER2+)-directed therapy (p < .0001) were associated with higher costs in breast cancer. Younger age (p < .0001) and female gender (p < .0001) were also associated with higher costs in colorectal cancer. Metastasis was also associated with 50% more hospital admissions and increased hospital length of stay (p < .001) in all three cancers over the 6-month episode duration. Chemotherapy and supportive drug therapies accounted for the highest proportion (48%) of total medical costs among beneficiaries observed. Value-based reimbursement models in oncology should appropriately account for key cost drivers. Although claims-based methodologies may be further augmented with clinical data, this study recommends adjusting for the factors identified in these models to predict costs in breast, lung, and colorectal cancers.
@Article{Sagar2017,
  author          = {Sagar, Bhuvana and Lin, Yu Shen and Castel, Liana D.},
  title           = {Cost drivers for breast, lung, and colorectal cancer care in a commercially insured population over a 6-month episode: an economic analysis from a health plan perspective.},
  doi             = {10.1080/13696998.2017.1339353},
  issn            = {1941-837X},
  issue           = {10},
  pages           = {1018--1023},
  pubstate        = {ppublish},
  volume          = {20},
  abstract        = {In the absence of clinical data, accurate identification of cost drivers is needed for economic comparison in an alternate payment model. From a health plan perspective using claims data in a commercial population, the objective was to identify and quantify the effects of cost drivers in economic models of breast, lung, and colorectal cancer costs over a 6-month episode following initial chemotherapy. This study analyzed claims data from 9,748 Cigna beneficiaries with diagnosis of breast, lung, and colorectal cancer following initial chemotherapy from January 1, 2014 to December 31, 2015. We used multivariable regression models to quantify the impact of key factors on cost during the initial 6-month cancer care episode. Metastasis, facility provider affiliation, episode risk group (ERG) risk score, and radiation were cost drivers for all three types of cancer (breast, lung, and colorectal). In addition, younger age (p < .0001) and human epidermal growth factor receptor-2 oncogene overexpression (HER2+)-directed therapy (p < .0001) were associated with higher costs in breast cancer. Younger age (p < .0001) and female gender (p < .0001) were also associated with higher costs in colorectal cancer. Metastasis was also associated with 50% more hospital admissions and increased hospital length of stay (p < .001) in all three cancers over the 6-month episode duration. Chemotherapy and supportive drug therapies accounted for the highest proportion (48%) of total medical costs among beneficiaries observed. Value-based reimbursement models in oncology should appropriately account for key cost drivers. Although claims-based methodologies may be further augmented with clinical data, this study recommends adjusting for the factors identified in these models to predict costs in breast, lung, and colorectal cancers.},
  chemicals       = {Antineoplastic Agents, ERBB2 protein, human, Receptor, ErbB-2},
  citation-subset = {IM},
  completed       = {2018-06-04},
  country         = {England},
  issn-linking    = {1369-6998},
  journal         = {Journal of medical economics},
  keywords        = {Adolescent; Adult; Age Factors; Aged; Antineoplastic Agents, economics; Breast Neoplasms, economics; Colorectal Neoplasms, economics; Comorbidity; Female; Health Expenditures, statistics & numerical data; Hospitalization, economics; Humans; Insurance Claim Review, statistics & numerical data; Insurance, Health, Reimbursement, statistics & numerical data; Lung Neoplasms, economics; Male; Middle Aged; Models, Economic; Neoplasm Metastasis; Neoplasms, economics, pathology, therapy; Radiotherapy, economics; Receptor, ErbB-2, biosynthesis; Regression Analysis; Retrospective Studies; Risk Factors; Sex Factors; United States; Young Adult; Breast neoplasms; colorectal neoplasms; economics; lung neoplasms; risk adjustment},
  month           = oct,
  nlm-id          = {9892255},
  owner           = {NLM},
  pmid            = {28581874},
  pubmodel        = {Print-Electronic},
  revised         = {2018-06-04},
  year            = {2017},
}
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