Background and objectives: This paper presents a dynamic model aimed at predicting nursing manpower requirements for cancer care over the next ten years. The proposed model, based on the Taiwan Health Insurance Database (2000 to 2010), is meant to serve as a reference in establishing policy for government health units. Methods: The proposed prediction model uses fuzzy sets to replace definite values with interval values in order to account for uncertainties in real-world data and enhance the flexibility of prediction results. Results: Our results suggest that the demand for nursing manpower for cancer care will grow steadily in the foreseeable future. The gap between the demand for nursing staff and the supply is expected to peak in 2027. By then, the number of oncologists is expected to reach 7,083 (54.32% of the total number of in-hospital physicians), but the number of oncology nurses will be less than 26,297 (56.5% of the total healthcare manpower). It is also expected that there will be fewer than 1,613 outpatient physicians (71.81% of the total number of physicians) and fewer than 4,967 outpatient nurses (68.46% of the total nursing manpower). Conclusions: This paper provides a valuable reference for government agencies involved in the nursing manpower planning to improve the quality of nursing care.

Original languageEnglish
Article number105967
JournalComputer Methods and Programs in Biomedicine
Publication statusPublished - Apr 2021


  • Cancer disease
  • Forecasting
  • Fuzzy sets
  • Nursing manpower
  • System dynamic

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics


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