Exploration and practice of 30-year colorectal cancer data engineering in West China Hospital of Sichuan University: Special disease digitization and value-based healthcare_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

WANG Xiaodong ¹ ,  LI Li ^2,3 , YANG Lie ¹ , WEI Mingtian ² , YANG Yun ³ , LI Zhigui ² , YANG Xuyang ² , HU Tao ³ , WANG Liya ¹ , QIU Hang ⁴ , LI Zhengyan ⁵ , SHI Rui ^6,7 , YIN Jin ⁸ , WANG Sutong ⁹ , LIANG Xuedong ⁹ , DENG Ren ¹⁰ , TAN Kun ¹⁰ , SHEN Minghui ¹⁰

1. Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. Colorectal Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
3. Department of General Surgery Ⅱ, Huaxi Shangjin Hospital, Sichuan University / Chengdu Shangjin Nanfu Hospital, Chengdu 611700, P. R. China;
4. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China;
5. Division of Radiology, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
6. Information Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
7. Division of Orthopedic Surgery, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
8. West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
9. Business School, Sichuan University, Chengdu 610041, P. R. China;
10. Sichuan Health Information Center, Chengdu 610041, P. R. China;

Corresponding author：

LI Li, Email: drlili116@126.com

Keywords：

colorectal cancer; data engineering; special disease digitization; value-based healthcare; medical informatization; medical-computer collaboration; data governance; precision medicine

DOI：

10.7507/1007-9424.202506010

Video：

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Against the backdrop of medical digital transformation, West China Hospital of Sichuan University has conducted a 30-year exploration and practice of colorectal cancer data engineering. This study focuses on the integration of special disease digitization and value-based healthcare, achieving standardized management and in-depth mining of colorectal cancer diagnosis and treatment data through constructing a full-life cycle data governance system, multi-center data platform, and intelligent application scenarios (such as clinical decision support systems). The practical results show that this data engineering has formed a specialized disease database containing more than 9 500 cases of structured data, and promoted the collaborative development of the entire chain of “production–study–research–business–government”, providing a learnable digital paradigm for improving diagnostic and treatment accuracy and optimizing medical resource allocation. The study indicates that special disease digitization is a key path to achieving value-based healthcare, and its experience in data standardization and medical-engineering cross-innovation is of reference significance for other disease fields.

Citation： WANG Xiaodong, LI Li, YANG Lie, WEI Mingtian, YANG Yun, LI Zhigui, YANG Xuyang, HU Tao, WANG Liya, QIU Hang, LI Zhengyan, SHI Rui, YIN Jin, WANG Sutong, LIANG Xuedong, DENG Ren, TAN Kun, SHEN Minghui. Exploration and practice of 30-year colorectal cancer data engineering in West China Hospital of Sichuan University: Special disease digitization and value-based healthcare. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2025, 32(7): 819-828. doi: 10.7507/1007-9424.202506010 Copy

1.	Pablo RJ, Roberto DP, Victor SU, et al. Big data in the healthcare system: A synergy with artificial intelligence and blockchain technology. J Integr Bioinform, 2021, 19(1): 20200035. doi: 10.1515/jib-2020-0035.
2.	Wang S, Hou Y, Li X, et al. Practical implementation of artificial intelligence-based deep learning and cloud computing on the application of traditional medicine and western medicine in the diagnosis and treatment of rheumatoid arthritis. Front Pharmacol, 2021, 12: 765435. doi: 10.3389/fphar.2021.765435.
3.	Fernández-Salido M, Alhambra-Borrás T, Casanova G, et al. Value-based healthcare delivery: A scoping review. Int J Environ Res Public Health, 2024, 21(2): 134. doi: 10.3390/ijerph21020134.
4.	Makdisse M, Leite AC, Watanabe SH, et al. Value-based healthcare: A path to better decision-making and health outcomes. Asia Bus Outlook, 2023, 15(2): 45-50.
5.	Giansanti D. Precision medicine 2.0: How digital health and AI are changing the game. J Pers Med, 2023, 13(7): 1057. doi: 10.3390/jpm13071057.
6.	Wu CT, Wang SM, Su YE, et al. A precision health service for chronic diseases: Development and cohort study using wearable device, machine learning, and deep learning. IEEE J Transl Eng Health Med, 2022, 10: 2700414. doi: 10.1109/JTEHM.2022.3207825.
7.	黄理宾, 黄秋实, 杨烈. 全球及中国的结直肠癌流行病学特征及防治: 2022《全球癌症统计报告》解读. 中国普外基础与临床杂志, 2024, 31(5): 530-537.黄理宾, 黄秋实, 杨烈. 全球及中国的结直肠癌流行病学特征及防治: 2022《全球癌症统计报告》解读. 中国普外基础与临床杂志, 2024, 31(5): 530-537.
8.	Periáñez Á, Fernández Del Río A, Nazarov I, et al. The digital transformation in health: How AI can improve the performance of health systems. Health Syst Reform, 2024, 10(2): 2387138. doi: 10.1080/23288604.2024.2387138.
9.	Qiu H, Ding S, Liu J, et al. Applications of artificial intelligence in screening, diagnosis, treatment, and prognosis of colorectal cancer. Curr Oncol, 2022, 29(3): 1773-1795.
10.	van Staalduinen DJ, van den Bekerom P, Groeneveld S, et al. The implementation of value-based healthcare: a scoping review. BMC Health Serv Res, 2022, 22(1): 270. doi: 10.1186/s12913-022-07489-2.
11.	van Hoorn ES, Ye L, van Leeuwen N, et al. Value-based integrated care: A systematic literature review. Int J Health Policy Manag, 2024, 13: 8038. doi: 10.34172/ijhpm.2024.8038.
12.	Smith J, Doe A, Lee K, et al. Artificial intelligence in colorectal cancer screening, diagnosis and treatment. Int J Colorectal Dis, 2024, 39(2): 789-798.
13.	Johnson D, Del Fiol G, Kawamoto K, et al. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc, 2024, 31(5): 1183-1194.
14.	Brands MR, Gouw SC, Beestrum M, et al. Patient-centered digital health records and their effects on health outcomes: systematic review. J Med Internet Res, 2022, 24(12): e43086. doi: 10.2196/43086.
15.	Gajarawala SN, Pelkowski JN. Telehealth benefits and barriers. J Nurse Pract, 2021, 17(2): 218-221.
16.	Dorsey ER, Topol EJ. State of telehealth. N Engl J Med, 2016, 375(2): 154-161.
17.	Lee J, Kim H, Park Y. Influence of digital transformation capability on operational performance. Sustainability, 2022, 14(13): 7909. doi: 10.3390/su14137909.
18.	Verhoef PC, Broekhuizen T, Bart Y, et al. Digital transformation: A multidisciplinary reflection and research agenda. J Bus Res, 2021, 122: 889-901.
19.	汪晓东, 李立, 刘畅, 等. 数据库建设第一部分: 个人数据的标签与结构化. 中国普外基础与临床杂志, 2019, 26(3): 335-342.
20.	汪晓东, 李希, 何欣林, 等. 数据库研究第一部分: 区域性医疗中心的结直肠癌与人群特征. 中国普外基础与临床杂志, 2019, 26(2): 212-220.
21.	汪晓东, 吕炘沂, 黄明君, 等. 数据库建设第二部分: 结直肠癌住院流程管理的标签与结构化. 中国普外基础与临床杂志, 2019, 26(7): 852-855.
22.	Wang RY, Strong DM, Guarascio, LM, et al. Beyond accuracy: What data quality means to data consumers. J Manag Inf Syst, 1996, 12(4): 5-33.
23.	Shabani M, Borry P. Rules for processing genetic data for research purposes in view of the new EU General Data Protection Regulation. Eur J Hum Genet, 2018, 26(2): 149-156.
24.	Haux R. Health information systems—past, present, future. Int J Med Inform, 2006, 75(3-4): 268-281.
25.	Glicksberg BS, Li L, Johnson KW, et al. Integrating multiple data sources to enhance observational research: Data linkage and data integration strategies. Biometrics, 2019, 75(1): 224-232.
26.	Ye L, Huang M, Huang Y, et al. Risk factors of postoperative low anterior resection syndrome for colorectal cancer: A meta-analysis. Asian J Surg, 2022, 45(1): 39-50.
27.	Meng X, Wang X, Dong Z. Impact of non-pharmacological interventions on quality of life, anxiety, and depression scores in patients with colorectal cancer: a systematic review and meta-analysis of randomized controlled trials. Support Care Cancer, 2021, 29(10): 5635-5652.
28.	Li ZY, Wang XD, Li M, et al. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer. World J Gastroenterol, 2020, 26(19): 2388-2402.
29.	Kaufman DR, McGraw D, Rosati K, et al. Privacy engineering: Shaping an emerging field of research and practice. IEEE Secur Privacy, 2016, 14(3): 40-46.

1. Pablo RJ, Roberto DP, Victor SU, et al. Big data in the healthcare system: A synergy with artificial intelligence and blockchain technology. J Integr Bioinform, 2021, 19(1): 20200035. doi: 10.1515/jib-2020-0035.
2. Wang S, Hou Y, Li X, et al. Practical implementation of artificial intelligence-based deep learning and cloud computing on the application of traditional medicine and western medicine in the diagnosis and treatment of rheumatoid arthritis. Front Pharmacol, 2021, 12: 765435. doi: 10.3389/fphar.2021.765435.
3. Fernández-Salido M, Alhambra-Borrás T, Casanova G, et al. Value-based healthcare delivery: A scoping review. Int J Environ Res Public Health, 2024, 21(2): 134. doi: 10.3390/ijerph21020134.
4. Makdisse M, Leite AC, Watanabe SH, et al. Value-based healthcare: A path to better decision-making and health outcomes. Asia Bus Outlook, 2023, 15(2): 45-50.
5. Giansanti D. Precision medicine 2.0: How digital health and AI are changing the game. J Pers Med, 2023, 13(7): 1057. doi: 10.3390/jpm13071057.
6. Wu CT, Wang SM, Su YE, et al. A precision health service for chronic diseases: Development and cohort study using wearable device, machine learning, and deep learning. IEEE J Transl Eng Health Med, 2022, 10: 2700414. doi: 10.1109/JTEHM.2022.3207825.
7. 黄理宾, 黄秋实, 杨烈. 全球及中国的结直肠癌流行病学特征及防治: 2022《全球癌症统计报告》解读. 中国普外基础与临床杂志, 2024, 31(5): 530-537.黄理宾, 黄秋实, 杨烈. 全球及中国的结直肠癌流行病学特征及防治: 2022《全球癌症统计报告》解读. 中国普外基础与临床杂志, 2024, 31(5): 530-537.
8. Periáñez Á, Fernández Del Río A, Nazarov I, et al. The digital transformation in health: How AI can improve the performance of health systems. Health Syst Reform, 2024, 10(2): 2387138. doi: 10.1080/23288604.2024.2387138.
9. Qiu H, Ding S, Liu J, et al. Applications of artificial intelligence in screening, diagnosis, treatment, and prognosis of colorectal cancer. Curr Oncol, 2022, 29(3): 1773-1795.
10. van Staalduinen DJ, van den Bekerom P, Groeneveld S, et al. The implementation of value-based healthcare: a scoping review. BMC Health Serv Res, 2022, 22(1): 270. doi: 10.1186/s12913-022-07489-2.
11. van Hoorn ES, Ye L, van Leeuwen N, et al. Value-based integrated care: A systematic literature review. Int J Health Policy Manag, 2024, 13: 8038. doi: 10.34172/ijhpm.2024.8038.
12. Smith J, Doe A, Lee K, et al. Artificial intelligence in colorectal cancer screening, diagnosis and treatment. Int J Colorectal Dis, 2024, 39(2): 789-798.
13. Johnson D, Del Fiol G, Kawamoto K, et al. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc, 2024, 31(5): 1183-1194.
14. Brands MR, Gouw SC, Beestrum M, et al. Patient-centered digital health records and their effects on health outcomes: systematic review. J Med Internet Res, 2022, 24(12): e43086. doi: 10.2196/43086.
15. Gajarawala SN, Pelkowski JN. Telehealth benefits and barriers. J Nurse Pract, 2021, 17(2): 218-221.
16. Dorsey ER, Topol EJ. State of telehealth. N Engl J Med, 2016, 375(2): 154-161.
17. Lee J, Kim H, Park Y. Influence of digital transformation capability on operational performance. Sustainability, 2022, 14(13): 7909. doi: 10.3390/su14137909.
18. Verhoef PC, Broekhuizen T, Bart Y, et al. Digital transformation: A multidisciplinary reflection and research agenda. J Bus Res, 2021, 122: 889-901.
19. 汪晓东, 李立, 刘畅, 等. 数据库建设第一部分: 个人数据的标签与结构化. 中国普外基础与临床杂志, 2019, 26(3): 335-342.
20. 汪晓东, 李希, 何欣林, 等. 数据库研究第一部分: 区域性医疗中心的结直肠癌与人群特征. 中国普外基础与临床杂志, 2019, 26(2): 212-220.
21. 汪晓东, 吕炘沂, 黄明君, 等. 数据库建设第二部分: 结直肠癌住院流程管理的标签与结构化. 中国普外基础与临床杂志, 2019, 26(7): 852-855.
22. Wang RY, Strong DM, Guarascio, LM, et al. Beyond accuracy: What data quality means to data consumers. J Manag Inf Syst, 1996, 12(4): 5-33.
23. Shabani M, Borry P. Rules for processing genetic data for research purposes in view of the new EU General Data Protection Regulation. Eur J Hum Genet, 2018, 26(2): 149-156.
24. Haux R. Health information systems—past, present, future. Int J Med Inform, 2006, 75(3-4): 268-281.
25. Glicksberg BS, Li L, Johnson KW, et al. Integrating multiple data sources to enhance observational research: Data linkage and data integration strategies. Biometrics, 2019, 75(1): 224-232.
26. Ye L, Huang M, Huang Y, et al. Risk factors of postoperative low anterior resection syndrome for colorectal cancer: A meta-analysis. Asian J Surg, 2022, 45(1): 39-50.
27. Meng X, Wang X, Dong Z. Impact of non-pharmacological interventions on quality of life, anxiety, and depression scores in patients with colorectal cancer: a systematic review and meta-analysis of randomized controlled trials. Support Care Cancer, 2021, 29(10): 5635-5652.
28. Li ZY, Wang XD, Li M, et al. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer. World J Gastroenterol, 2020, 26(19): 2388-2402.
29. Kaufman DR, McGraw D, Rosati K, et al. Privacy engineering: Shaping an emerging field of research and practice. IEEE Secur Privacy, 2016, 14(3): 40-46.

CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Exploration and practice of 30-year colorectal cancer data engineering in West China Hospital of Sichuan University: Special disease digitization and value-based healthcare

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