Towards Evidence-Based Analysis of Palliative Treatments for Stomach and Esophageal Cancer Patients: a Process Mining Approach

被引:5
|
作者
Pijnenborg, Pam [1 ]
Verhoeven, Rob [1 ,3 ]
Firat, Murat [2 ]
van Laarhoven, Hanneke [3 ]
Genga, Laura [4 ]
机构
[1] Netherlands Comprehens Canc Org, Dept Res & Dev, Utrecht, Netherlands
[2] Open Univ, Carou Inst, Heerlen, Netherlands
[3] Amsterdam Univ Med Ctr, Dept Med Oncol, Amsterdam, Netherlands
[4] Eindhoven Univ Technol, Eindhoven, Netherlands
关键词
Local Process Mining; Predictive Process Monitoring; Healthcare Processes; PATTERNS;
D O I
10.1109/ICPM53251.2021.9576880
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Stomach and esophageal cancer are in the top ten most common cancers worldwide, both with high mortality rate. Approximately one-third of these patients have metastases at initial diagnosis and should receive personalized palliative care to improve their remaining life time. However, there is a lack of consensus about personalized palliative care options. This often leads to difficulties in determining the right treatment pathway for individual patients. This study investigates the application of process mining techniques on palliative care pathways for stomach and esophageal cancer to obtain an evidence-based understanding of which palliative treatments are commonly carried out in clinical practice and how they are associated with patients' survival time. Given the high variability of the treatment pathways, 'local models' are derived, rather than end-to-end process models, which are then validated with the aid of physicians. In addition, this study also investigates the use of predictive process monitoring techniques to predict patients' life expectancy. The results show the benefit of taking the process-flow into account in predicting the outcome of the palliative treatments.
引用
收藏
页码:136 / 143
页数:8
相关论文
共 50 条
  • [31] Towards evidence-based response criteria for cancer immunotherapy
    Garralda, Elena
    Laurie, Scott A.
    Seymour, Lesley
    de Vries, Elisabeth G. E.
    NATURE COMMUNICATIONS, 2023, 14 (01)
  • [32] Towards evidence-based response criteria for cancer immunotherapy
    Elena Garralda
    Scott A. Laurie
    Lesley Seymour
    Elisabeth G. E. de Vries
    Nature Communications, 14
  • [33] A Systematic Review of Prognostic Factors in Patients with Cancer Receiving Palliative Radiotherapy: Evidence-Based Recommendations
    Tam, Alexander
    Scarpi, Emanuela
    Maltoni, Marco Cesare
    Rossi, Romina
    Fairchild, Alysa
    Dennis, Kristopher
    Vaska, Marcus
    Kerba, Marc
    CANCERS, 2024, 16 (09)
  • [34] Symposium "Towards evidence-based management of hereditary cancer"
    Vasen, HFA
    NETHERLANDS JOURNAL OF MEDICINE, 1998, 53 (02): : A1 - A2
  • [35] Barriers to Implementing Evidence-Based Practice in Critical Care: A Process Analysis Approach
    Rentes, V. C.
    Dibble, E. R.
    Ausmus, A. L.
    Haas, C. F.
    Weirauch, A.
    Dammeyer, J.
    Gong, M. N.
    Sales, A. E.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2020, 201
  • [36] Practice review: Evidence-based quality use of corticosteroids in the palliative care of patients with advanced cancer
    Hardy, Janet
    Haywood, Alison
    Rickett, Kirsty
    Sallnow, Libby
    Good, Phillip
    PALLIATIVE MEDICINE, 2021, 35 (03) : 461 - 472
  • [37] Screening for cervical cancer - an evidence-based approach
    Fraser, A
    Hellmann, S
    Leibovici, L
    Levavi, H
    EUROPEAN JOURNAL OF GYNAECOLOGICAL ONCOLOGY, 2005, 26 (04) : 372 - 375
  • [38] Evidence-based approach to cancer of unknown primary
    Porzsolt, F
    Sellenthin, C
    Schmoll, HJ
    Illiger, HJ
    EUROPEAN JOURNAL OF CANCER, 1999, 35 : S368 - S368
  • [39] Prognosis in terminal cancer:: An evidence-based approach
    Viganò, A
    Dorgan, M
    JOURNAL OF PALLIATIVE CARE, 2000, 16 (03) : 67 - 67
  • [40] Towards standardisation of evidence-based clinical care process specifications
    McLachlan, Scott
    Kyrimi, Evangelia
    Dube, Kudakwashe
    Hitman, Graham
    Simmonds, Jennifer
    Fenton, Norman
    HEALTH INFORMATICS JOURNAL, 2020, 26 (04) : 2512 - 2537