Subject. Voice assistant is a developing digital healthcare tool that arouse great interest due to its ease of use. In the literature, there is insufficient data on its use in oncology, the cost of development, and experience in domestic platforms application. Objectives. The study aims to develop an approach to calculating the cost of creating a skill in the Alice voice assistant system for patients with skin cancer. Methods. The experience of creating a skill for patients with breast cancer is taken as a basis. We used the methodology for calculating the cost of software product under the calculation method by item. To estimate actual programming costs, we conducted a timekeeping experiment. The model contained 50 scripts with 50,000 lines of code. To evaluate the productivity of IT developers, we applied the volume of software texts, and the number of lines was taken as the number of operators. Results. The total cost of developing a skill for "Alice" is 2,097,190.76 RUB, including the salary fund of the core staff (61%), overhead costs (33.2%), electricity cost (0.2%), depreciation (0.2%). In the total share of labor cost of the core staff, programming costs prevail (61%). Conclusions. The approach to cost calculation for creating a skill for "Alice" is proposed for the first time. We simulated and predicted costs of developing a voice assistant for patients with skin cancer. The development of the skill scenario and the format of the dialog tree are critical and require creating a working group of specialists who contact patients at different stages. The development of the "Alice" skill using the Python can be classified as medium type of complexity, as model solutions and standard algorithms are used in the process.
Philpot L.M., Dugani S.B., Singla A. et al. Digital Care Horizon: A Framework for Extending Health Care Through Digital Transformation. Mayo Clinic Proceedings: Digital Health, 2023, vol. 1, iss. 3, pp. 210–216. URL: Link
Dutsinma F.L.I., Pal D., Funilkul S., Chan J.H. A Systematic Review of Voice Assistant Usability: An ISO 9241-11 Approach. SN Computer Science, 2022, vol. 3, iss. 4. URL: Link
Singh B., Olds T., Brinsley J. et al. Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours. npj Digital Medicine, 2023, vol. 6, iss. 1. URL: Link
Hong G., Folcarelli A., Less J. et al. Voice Assistants and Cancer Screening: A Comparison of Alexa, Siri, Google Assistant, and Cortana. The Annals of Family Medicine, 2021, vol. 19, iss. 5, pp. 447–449. URL: Link
Bibault J.-E., Chaix B., Nectoux P. et al. Healthcare ex Machina: Are conversational agents ready for prime time in oncology? Clinical and Translational Radiation Oncologyl, 2019, vol. 16, pp. 55–59. URL: Link
Milne-Ives M., de Cock C., Lim E. et al. The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review. Journal of Medical Internet Research, 2020, vol. 22, iss. 106. URL: Link
Perez M., Abisaad J.A., Rojas K.D. et al. Skin cancer: Primary, secondary, and tertiary prevention. Journal of the American Academy of Dermatology, 2022, vol. 87, iss. 2, pp. 255–268. URL: Link
Ferlay J., Colombet M., Soerjomataram I. et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. International Journal of Cancer, 2019, vol. 144, iss. 8, pp. 1941–1953. URL: Link
