Forecasting Participants in the All Women Count! Mammography Program

Details

• Alternative Title:
  Prev Chronic Dis
• Personal Author:
  Holzhauser, Calla ; Da Rosa, Patricia ; Michael, Semhar
• Description:
  Introduction
  
  The All Women Count! (AWC!) program is a no-cost breast and cervical cancer screening program for qualifying women in South Dakota. Our study aimed to identify counties with similar socioeconomic characteristics and to estimate the number of women who will use the program for the next 5 years.
  
  Methods
  
  We used AWC! data and sociodemographic predictor variables (eg, poverty level [percentage of the population with an annual income at or below 200% of the Federal Poverty Level], median income) and a mixture of Gaussian regression time series models to perform clustering and forecasting simultaneously. Model selection was performed by using Bayesian information criterion (BIC). Forecasting of the predictor variables was done by using an autoregressive integrated moving average model.
  
  Results
  
  By using BIC, we identified 5 clusters showing the groups of South Dakota counties with similar characteristics in terms of predictor variables and the number of participants. The mixture model identified groups of counties with increasing or decreasing trends in participation and forecast averages per cluster.
  
  Conclusion
  
  The mixture of regression time series model used in this study allowed for the identification of similar counties and provided a forecasting model for future years. Although several predictors contributed to program participation, we believe our forecasting analysis by county may provide useful information to improve the implementation of the AWC! program by informing program managers on the expected number of participants in the next 5 years. This, in turn, will help in data-driven resource allocation.
  
  
• Subjects:
  Bayes Theorem Breast Neoplasms Early Detection Of Cancer Female Forecasting Health Promotion Humans Mammography Mass Screening Original Research Papanicolaou Test Poverty Program Evaluation Uterine Cervical Neoplasms

  More +
• Source:
  Prev Chronic Dis. 15
• Pubmed ID:
  30367718
• Pubmed Central ID:
  PMC6219850
• Document Type:
  Journal Article
• Funding:
  U01 DP006293/DP/NCCDPHP CDC HHS/United States ; U01DP006293/ACL HHS/ACL HHS/United States
• Place as Subject:
  South Dakota
• Volume:
  15
• Collection(s):
  Preventing Chronic Disease
• Main Document Checksum:
  urn:sha-512:fbfc4258deda2b54a2cfe6674c40c2f23a02513ed3216c6494a8b9da264a6f8edf4c40fb5d703cd1e99457fe0deeb1d6982cb6c26248a1105ccb4413bf48ae00
• Download URL:
  https://stacks.cdc.gov/view/cdc/60932/cdc_60932_DS1.pdf
• File Type:
  [PDF - 389.49 KB ]