title: A sharable cloud-based pancreaticoduodenectomy collaborative database for physicians: emphasis on security and clinical rule supporting.
abstract: BACKGROUND
  Pancreaticoduodenectomy (PD) is a major operation with high complication rate. Thereafter, patients may develop morbidity because of the complex reconstruction and loss of pancreatic parenchyma. A well-designed database is very important to address both the short-term and long-term outcomes after PD.
  
  
  OBJECTIVE
  The objective of this research was to build an international PD database implemented with security and clinical rule supporting functions, which made the data-sharing easier and improve the accuracy of data.
  
  
  METHODS
  The proposed system is a cloud-based application. To fulfill its requirements, the system comprises four subsystems: a data management subsystem, a clinical rule supporting subsystem, a short message notification subsystem, and an information security subsystem. After completing the surgery, the physicians input the data retrospectively, which are analyzed to study factors associated with post-PD common complications (delayed gastric emptying and pancreatic fistula) to validate the clinical value of this system.
  
  
  RESULTS
  Currently, this database contains data from nearly 500 subjects. Five medical centers in Taiwan and two cancer centers in Mongolia are participating in this study. A data mining model of the decision tree analysis showed that elderly patients (>76 years) with pylorus-preserving PD (PPPD) have higher proportion of delayed gastric emptying. About the pancreatic fistula, the data mining model of the decision tree analysis revealed that cases with non-pancreaticogastrostomy (PG) reconstruction - body mass index (BMI)>29.65 or PG reconstruction - BMI>23.7 - non-classic PD have higher proportion of pancreatic fistula after PD.
  
  
  CONCLUSIONS
  The proposed system allows medical staff to collect and store clinical data in a cloud, sharing the data with other physicians in a secure manner to achieve collaboration in research.
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan University, Taiwan.
authors.forename: Hwan-Jeu
authors.initials: HJ
authors.lastname: Yu
authors.forename: Hong-Shiee
authors.initials: HS
authors.lastname: Lai
authors.forename: Kuo-Hsin
authors.initials: KH
authors.lastname: Chen
authors.forename: Hsien-Cheng
authors.initials: HC
authors.lastname: Chou
authors.forename: Jin-Ming
authors.initials: JM
authors.lastname: Wu
authors.forename: Sarangerel
authors.initials: S
authors.lastname: Dorjgochoo
authors.forename: Adilsaikhan
authors.initials: A
authors.lastname: Mendjargal
authors.forename: Erdenebaatar
authors.initials: E
authors.lastname: Altangerel
authors.forename: Yu-Wen
authors.initials: YW
authors.lastname: Tien
authors.forename: Chih-Wen
authors.initials: CW
authors.lastname: Hsueh
authors.forename: Feipei
authors.initials: F
authors.lastname: Lai
mesh_terms: D000368:Aged; D000465:Algorithms; D015992:Body Mass Index; D003199:Computer Systems; D003625:Data Collection; D016208:Databases, Factual; D005746:Gastric Emptying; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008490:Medical Informatics / Q000379:methods; D008986:Mongolia / Q000453:epidemiology; D010185:Pancreatic Fistula / Q000175:diagnosis / Q000453:epidemiology; D016577:Pancreaticoduodenectomy / Q000009:adverse effects / Q000379:methods*; D012042:Registries; D015203:Reproducibility of Results; D012984:Software; D013624:Taiwan / Q000453:epidemiology; D014584:User-Computer Interface
keywords: Clinical database; Cloud; Pancreaticoduodenectomy