Methods Inf Med 2022; 61(05/06): 185-194
DOI: 10.1055/a-1911-9088
Original Article

Self-Service Registry Log Builder: A Case Study in National Trauma Registry of Iran

Mansoureh Yari Eili
1   Department of Computer Engineering and IT, Faculty of Technology and Engineering, University of Qom, Qom, Iran
,
Safar Vafadar
2   Laboratory of Biological Complex Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
,
Jalal Rezaeenour
3   Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran
,
Mahdi Sharif-Alhoseini
4   Sina Trauma and Surgery Research Center, Neurotrauma Department, Tehran University of Medical Sciences, Tehran, Iran
› Author Affiliations

Abstract

Background Although the process-mining algorithms have evolved in the past decade, the lack of attention to extracting event logs from raw data of databases in an automatic manner is evident. These logs are available in a process-oriented manner in the process-aware information systems. Still, there are areas where their extraction is a challenge to address (e.g., trauma registries).

Objective The registry data are recorded manually and follow an unstructured ad hoc pattern; prone to high noises and errors; consequently, registry logs are classified at a maturity level of one, and extracting process-centric information is not a trivial task therein. The experiences made during the event log building from the trauma registry are the subjects to be studied.

Results The result indicates that the three-phase self-service registry log builder tool can withstand the mentioned issues by filtering and enriching the raw data and making them ready for any level of process-mining analysis. This proposed tool is demonstrated through process discovery in the National Trauma Registry of Iran, and the encountered challenges and limitations are reported.

Conclusion This tool is an interactive visual event log builder for trauma registry data and is freely available for studies involving other registries. In conclusion, future research directions derived from this case study are suggested.



Publication History

Received: 01 January 2022

Accepted: 25 July 2022

Accepted Manuscript online:
28 July 2022

Article published online:
15 November 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
  • References

  • 1 WHO. Fact sheet on injuries and violence. Accessed March 19, 2021 at: https://www.who.int/news-room/fact-sheets/detail/injuries-and-violence
  • 2 Papadakos PJ, Gestring ML. Trauma Registry. In: Papadakos PJ, Gestring ML. ed. Encyclopedia of Trauma Care. Springer Berlin Heidelberg; 2015: 1658-1704
  • 3 Kavousi K, Bagheri M, Behrouzi S. et al. IAMPE: NMR-assisted computational prediction of antimicrobial peptides. J Chem Inf Model 2020; 60 (10) 4691-4701
  • 4 Diba K, Batoulis K, Weidlich M. et al. Extraction, correlation, and abstraction of event data for process mining. Wires Data Min Knowl 2020; 10: 1346
  • 5 Watson HJ, Wixom BH. The current state of business intelligence. Computer 2007; 40: 96-99
  • 6 de Murillas EGL, Hoogendoorn GE, Reijers HA. Redo log process mining in real life: data challenges & opportunities. Paper presented at: International Conference on Business Process Management; September 10–15, 2017; Barcelona, Spain.
  • 7 de Murillas EGL, Reijers HA, Van Der Aalst WM. Connecting databases with process mining: a meta model and toolset. SoSyM 2019; 18: 1209-1247
  • 8 Reijers HA, Küng J. Audit Trails in OpenSLEX: paving the road for process mining in healthcare. Paper presented at: Information Technology in Bio-and Medical Informatics; August 28–31, 2017; Lyon, France.
  • 9 Emamjome F, Andrews R, ter Hofstede AHM. A case study lens on process mining in practice. Paper presented at: OTM Confederated International Conferences on the Move to Meaningful Internet Systems; October 21–25, 2019; Rhodes, Greece.
  • 10 IEEE Standard for eXtensible Event Stream (XES) for Achieving Interoperability in Event Logs and Event Streams. IEEE Std 1849–2016. New York, NY: The Institute of Electrical and Electronics Engineers; 2016: 1-50
  • 11 Ingvaldsen JE, Gulla JA. Preprocessing support for large scale process mining of SAP transactions. Paper presented at: International Conference on Business process management; September 24, 2007; Brisbane, Australia.
  • 12 Verbeek HMW, Buijs JC, Van Dongen BF. et al. Xes, xesame, and prom 6. Paper presented at: International Conference on Advanced Information Systems Engineering; June 8–12, 2010; Melbourne, Australia.
  • 13 Günther CW, van der Aalst WM. A generic import framework for process event logs. Paper presented at: In International Conference on Business Process Management; September 13–18, 2006; Vienna, Austria.
  • 14 de Murillas E, van der Aalst WM, Reijers A. Process mining on databases: Unearthing historical data from redo logs. Paper presented at: International Conference on Business Process Management; September 18–22, 2016; Rio de Janeiro, Brazil
  • 15 Dallagassa MR, dos Santos Garcia C, Scalabrin EE. et al. Opportunities and challenges for applying process mining in healthcare: a systematic mapping study. J Ambient Intell Humaniz Comput 2021; 8: 1-18
  • 16 Remy S, Pufahl L, Sachs JP. et al. Event log generation in a health system: a case study. Paper presented at: International Conference on Business Process Management; September 13–18, 2020; Seville, Spain
  • 17 Rojas E, Munoz-Gama J, Sepúlveda M, Capurro D. Process mining in healthcare: a literature review. J Biomed Inform 2016; 61: 224-236
  • 18 Durojaiye AB, Puett LL, Levin S. et al. Linking electronic health record and trauma registry data: assessing the value of probabilistic linkage. Methods Inf Med 2018; 57 (5-06): 261-269
  • 19 Durojaiye AB, McGeorge NM, Puett LL. et al. Mapping the flow of pediatric trauma patients using process mining. Appl Clin Inform 2018; 9 (03) 654-666
  • 20 Yang S, Li J, Tang X, Chen S, Marsic I, Burd RS. Process mining for trauma resuscitation. IEEE Intell Inform Bull 2017; 18 (01) 15-19
  • 21 Yang S, Zhou Y, Guo Y. et al. Semi-synthetic trauma resuscitation process data generator. Paper presented at: International Conference on Healthcare Informatics; August 23–26, 2017; Park City, United States.
  • 22 Andrews R, Wynn MT, Vallmuur K. et al. Pre-hospital retrieval and transport of road trauma patients in Queensland. Paper presented at: International Conference on Business Process Management; September 9–14, 2018; Sydney, Australia.
  • 23 American College of Surgeons. National Trauma Data Standard , Data Dictionary 2020 Admissions; 2020. Available at: https://www.facs.org/media/mkxef10z/ntds_data_dictionary_2022.pdf 2020
  • 24 Nwomeh BC, Lowell W, Kable R, Haley K, Ameh EA. History and development of trauma registry: lessons from developed to developing countries. World J Emerg Surg 2006; 1: 32
  • 25 Sharif-Alhoseini M, Zafarghandi M, Rahimi-Movaghar V. et al. National trauma registry of Iran: a pilot phase at a major trauma center in Tehran. Arch Iran Med 2019; 22 (06) 286-292
  • 26 Saeednejad M, Zafarghandi M, Khalili N. et al. Evaluating mechanism and severity of injuries among trauma patients admitted to Sina Hospital, the National Trauma Registry of Iran. Chin J Traumatol 2021; 24 (03) 153-158
  • 27 Sharif-Alhoseini M, Azadmanjir Z, Sadeghi-Naini M. et al. National Spinal Cord Injury Registry of Iran (NSCIR-IR) - a critical appraisal of its strengths and weaknesses. Chin J Traumatol 2019; 22 (05) 300-303
  • 28 Ghodsi Z, Moghaddam SS, Saadat S. et al. Trend of fatal poisoning at national and provincial levels in Iran from 1990 to 2015. Public Health 2019; 170: 78-88
  • 29 Zehtabchi S, Nishijima DK, McKay MP, Mann NC. Trauma registries: history, logistics, limitations, and contributions to emergency medicine research. Acad Emerg Med 2011; 18 (06) 637-643
  • 30 van Der Aalst W, Adriansyah A, De Medeiros AKA. et al. Process mining manifesto. Paper presented at: International Conference on Business Process Management; August 29, 2011; Clermont-Ferrand, France.
  • 31 Hamming RW. Error detecting and error correcting codes. Bell Syst Tech J 1950; 29: 147-160
  • 32 van der Aalst WMP, Dustdar S. Process mining put into context. IEEE Internet Comput 2012; 16: 82-86
  • 33 Yari Eili M, Rezaeenour J. A Survey on Recommendation in Process mining. Concurr Comput 2021; e7304
  • 34 Microsoft. Excel specifications and limits. Accessed August 8, 2022 at: https://support.microsoft.com/en-us/office/excel-specifications-and-limits-1672b34d-7043-467e-8e27-269d656771c3
  • 35 Roest A. A Practitioner's Guide for Process Mining on ERP Systems: the Case of SAP Order to Cash [Master's thesis]. Eindhoven, The Netherlands: Technische Universiteit Eindhoven; 2012
  • 36 Mahendrawathi ER, Astuti HM, Wardhani IRK. Material movement analysis for warehouse business process improvement with process mining: a case study. Paper presented at: Asia-Pacific Conference on Business Process Management; June 24–26, 2015; Busan, Korea.
  • 37 Štolfa J, Kopka M, Štolfa S. et al. An application of process mining to invoice verification process in sap. Paper presented at: Innovations in Bio-inspired Computing and Applications; June 25, 2014; Ostrava, Czech Republic.
  • 38 Mueller-Wickop N, Schultz M. ERP event log preprocessing: timestamps vs. accounting logic. Paper presented at: International Conference on Design Science Research in Information Systems; June 2013; Berlin, Heidelberg, Germany
  • 39 Calvanese D, Montali M, Syamsiyah A. et al. Ontology-driven extraction of event logs from relational databases. Paper presented at: International Conference on Business Process Management; September 18–22, 2016; Rio de Janeiro, Brazil