title: Productivity savings from colorectal cancer prevention and control strategies.
abstract: BACKGROUND
  Lost productivity represents a considerable portion of the total economic burden of colorectal cancer (CRC), but cost-effectiveness studies of CRC prevention and control have not included these costs and therefore underestimate potential savings from CRC prevention and control.
  
  
  OBJECTIVE
  To use microsimulation modeling study to estimate and project productivity costs of CRC and to model the savings from four approaches to reducing CRC incidence and mortality: risk factor reduction, improved screening, improved treatment, and a simultaneous approach where all three strategies are implemented.
  
  
  METHODS
  A model was developed to project productivity losses from CRC using the U.S. population with CRC incidence and mortality projected through the year 2020. Outcome measures were CRC mortality, morbidity, and productivity savings.
  
  
  RESULTS
  With 2005 levels in risk factors, screening, and treatment, 48,748 CRC deaths occurred in 2010, amounting to $21 billion of lost productivity. Using prevention and treatment strategies simultaneously, 3586 deaths could have been avoided in 2010, leading to a savings of $1.4 billion. Cumulatively, by 2020, simultaneous strategies that reduce risk factors and increase screening and treatment could result in 101,353 deaths avoided and $33.9 billion in savings in reduced productivity loss. Improved screening rates alone led to nearly $14.7 billion in savings between 2005 and 2020, followed by risk factor reduction ($12.4 billion) and improved treatment ($8.4 billion).
  
  
  CONCLUSIONS
  The savings in productivity loss from strategies to reduce CRC incidence and mortality are substantial, providing evidence that CRC prevention and control strategies are likely to be cost-saving.
authors.affiliation: Department of Healthcare Policy and Research, Virginia Commonwealth University, Richmond, Virginia 23113, USA. cjbradley@vcu.edu
authors.forename: Cathy J
authors.initials: CJ
authors.lastname: Bradley
authors.forename: Iris
authors.initials: I
authors.lastname: Lansdorp-Vogelaar
authors.forename: K Robin
authors.initials: KR
authors.lastname: Yabroff
authors.forename: Bassam
authors.initials: B
authors.lastname: Dahman
authors.forename: Angela
authors.initials: A
authors.lastname: Mariotto
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Feuer
authors.forename: Martin L
authors.initials: ML
authors.lastname: Brown
mesh_terms: D015179:Colorectal Neoplasms / Q000191:economics* / Q000401:mortality / Q000503:physiopathology / Q000517:prevention & control*; D003198:Computer Simulation; D017046:Cost Savings; D017281:Cost of Illness; D003362:Cost-Benefit Analysis; D004526:Efficiency; D005260:Female; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000191:economics* / Q000379:methods; D018803:Models, Economic; D012307:Risk Factors; D014481:United States