Advertisement

Toward a decision support system for the clinical pathways assessment

  • Simona Bernardi
  • Cristian MahuleaEmail author
  • Jorge Albareda
Article
  • 14 Downloads

Introduction

Public healthcare system is managed by national or local governments, who define the purpose and targets of the service together with policies and financial resources. However, because of the complexity of understanding, planning and controlling the system behavior, governments struggle to make good short-term and long-term decisions. This struggle is the same all through the management hierarchy, down to the daily work with patients. This means that the implementation of new legislation is often expensive, can have a long delay and is prone to fail.

This paper proposes a method for the management of the healthcare systems, in particular hospital management, based on clinical pathways (Field and Lohr 1992) developed and used by the medical staff in the hospitals. We consider as case study the Clinical Hospital “Lozano Blesa” of Zaragoza, in particular the Orthopedic Department of this hospital. As all the other departments of the hospital, for each disease, treatment or...

Keywords

Healthcare systems Clinical pathways Unified modeling language Petri nets 

Notes

Acknowledgments

This work has been partially supported by CICYT - FEDER (Spain-EU) under Grant DPI2014-57252-R and by the Aragonese Government (Spain) under grant T94 (DisCo group). The authors want to thank José Manuel Colom, co-author of the conference paper on which is based this manuscript, for all his help during the initial version.

References

  1. Aggarwal V (2002) The application of the unified modeling language in Object-Oriented analysis of healthcare information systems. J Med Syst 26(5):383–397Google Scholar
  2. Aristovnik A (2012) Measuring relative efficiency in health and education sector: The case of East European countries. Actual Probl Econ 136:305–314Google Scholar
  3. Ashiffman RN, Karras BT, Agrawal A, Chen R, Marenco L, Nath S (2000) GEM: a proposal for a more comprehensive guideline document model using XML. J Amer Med Inf Assoc 7 (5):488–498Google Scholar
  4. Augusto V, Xie X (2014) A modeling and simulation framework for health care systems. IEEE Trans Syst Man Cybern: Syst 44(1):30–46Google Scholar
  5. Bernardi S, Donatelli S, Horvȧth A (2001) Implementing compositionality for stochastic Petri nets. STTT 3(4):417–430zbMATHGoogle Scholar
  6. Bernardi S, Campos J (2009) Computation of Performance Bounds for Real-Time systems using Time Petri Nets. IEEE Trans Ind Inf 5(2):168–180Google Scholar
  7. Bernardi S, Campos J (2013) A min-max problem for the computation of the cycle time lower bound in interval-based Time Petri Nets. IEEE Trans Syst Man Cybern: Syst 43(5):1167–1181.  https://doi.org/10.1109/TSMCA.2012.2226442 Google Scholar
  8. Bosilj-Vuksic V, Giaglis G, Hlupic V (2001) IDEF diagrams and petri nets for business process modeling: suitability, Efficacy, and Complementary Use. In: Sharp B, Filipe J, Cordeiro J (eds) Enterprise information systems II. Springer, Dordrecht, pp 143–148Google Scholar
  9. Boxwala AA, Peleg M, Tu S, Ogunyemi O, Zeng QT, Wang D, Patel VL, Greenes RA, Shortliffe EH (2004) Glif3: a representation format for sharable computer-interpretable clinical practice guidelines. J Biomed Inf 37(3):147–161Google Scholar
  10. Brailsford SC, Harper PR, Patel B, Pitt M (2009) An analysis of the academic literature on simulation and modelling in health care. J Simul 3(3):130–140Google Scholar
  11. Büyüközkan G, Çifçi G, Güleryüz S (2011) Strategic analysis of healthcare service quality using fuzzy {AHP} methodology. Expert Syst Appl 38(8):9407–9424Google Scholar
  12. Barros C-P, Vieira JC (2013) Measurement of hospital efficiency, using a latent class stochastic frontier model. Appl Econ 45(1):47–54Google Scholar
  13. Campos J, Silva M (1992) Structural techniques and performance bounds of stochastic Petri net models. Lect Notes Comput Sci 609:352–391MathSciNetGoogle Scholar
  14. Chiola G, Franceschinis G (1991) A structural colour simplification in well-formed coloured nets. In: Proceedings of the 4th International Workshop on Petri Nets and Performance Models, pp 144–153Google Scholar
  15. Chiola G, Dutheillet C, Franceschinis G, Haddad S (1993) Stochastic well-formed colored nets and symmetric modeling applications. IEEE Trans Comput 42(11):1343–1360Google Scholar
  16. Chiola G, Anglano C, Campos J, Colom J, Silva M (1994) Operational analysis of timed Petri nets and application to the computation of performance bounds. In: Boxma O, Koole G (eds) Performance evaluation of parallel and distributed systems: Solution methods, tract, vol 106. Centrum voor Wiskunde en Informatica, Amsterdam, pp 197–213Google Scholar
  17. Connelly LG, Bair AE (2004) Discrete event simulation of emergency department activity: a platform for system-level operations research. Acad Emerg Med 11(11):1177–1185Google Scholar
  18. Coyle RG, Morecroft JDW (1999) Guest editor’s introduction. J Oper Res Soc 50(4):294–294Google Scholar
  19. Davies R (1985) An assessment of models of a health system. J Oper Res Soc 36(8):679–686Google Scholar
  20. Dotoli M, Epicoco N, Falagario M, Sciancalepore F (2015) A cross-efficiency fuzzy data envelopment analysis technique for performance evaluation of decision making units under uncertainty. Comput Ind Eng 79:103–114zbMATHGoogle Scholar
  21. Fanti MP, Iacobellis G, Ukovich W (2010) A Metamodelling Approach to Healthcare System management. In: Testi A, Ivaldi E, Carello G, Aringhieri R, Fraghelli V (eds) XXXVI ORHAS conference, Operation Research for Patient- Centered health care delivery, pp 110–121Google Scholar
  22. Fanti MP, Mangini AM, Dotoli M, Ukovich W (2013) A three-level strategy for the design and performance evaluation of hospital departments. IEEE Trans Syst Man Cybern: Syst 43 (4):742–756Google Scholar
  23. Field MJ, Lohr K (1992) Guidelines for clinical practice: from development to use. National Academy Press, WashingtonGoogle Scholar
  24. Fone D, Hollinghurst S, Temple M, Round A, Lester N, Weightman A (2003) Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Publ Health Med 24(4):325–335Google Scholar
  25. Forrester JW (1960) The impact of feedback control concepts on the Management Sciences. In: Collected Papers of j.w. Forrester. Wright-Allen Press, pp 45–60Google Scholar
  26. Fruggiero F, Lambiase A, Fallon D (2008) Computer simulation and swarm intelligence organisation into an emergency department: a balancing approach across ant colony optimisation. Int J Serv Oper Inf 3(2):142–161Google Scholar
  27. Gao S, Krogstie J (2009) A Combined Framework for Development of Business Process Support Systems. In: Persson A, Stirna J (eds) The practice of enterprise modeling. Lecture notes in business information processing, vol 39. Springer, Berlin, pp 115–129Google Scholar
  28. GreatSPN (2002) http://www.di.unito.it/greatspn. University of Torino, TorinoGoogle Scholar
  29. Günal MM, Pidd M (2010) Discrete event simulation for performance modelling in health care: a review of the literature. J Simul 4(1):42–51Google Scholar
  30. Harper PR (2002) A framework for operational modelling of hospital resources. Health Care Manag Sci 5(3):165–173Google Scholar
  31. IBM (2011) ILOG CPLEX OptimizerGoogle Scholar
  32. Jun JB, Jacobson SH, Swisher JR (1999) Applications of discrete event simulation in health care clinics: a survey. J Oper Res Soc 50(2):109–123zbMATHGoogle Scholar
  33. Kosanke K, Vernadat F, Zelm M (1997) CIMOSA process model for enterprise modelling. In: Goossenaerts J, Kimura F, Wortmann H (eds) Information infrastructure systems for manufacturing. IFIP — the international federation for information processing. Springer, Boston, MA, pp 59–68Google Scholar
  34. Lagarde F, Espinoza H, Terrier F, Gérard S (2007) Improving UML profile design practices by leveraging conceptual domain models. In: Stirewalt REK, Egyed A, Fischer B (eds) 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007). ACM, Atlanta, pp 445–448Google Scholar
  35. Lehaney B, Hlupic V (2008) Simulation modelling for resource allocation and planning in the health sector. J R Soc Health 115(6):382–385Google Scholar
  36. Mahulea C, Mahulea L, Garcia-Soriano J, Colom J (2018) Modular Petri Net Modeling of Healthcare Systems. Flex Serv Manuf J 30(1-2):329–357Google Scholar
  37. Martin J, Odell J (1997) Object-Oriented Methods: a Foundation, 2nd edn. Prentice Hall, Englewood CliffsGoogle Scholar
  38. Mens T, Gorp PV (2006) A taxonomy of model transformation. Electron Notes Theor Comput Sci 152:125–142Google Scholar
  39. OMG (2011a) Business Process Model and Notation. Object Management Group. Version 2.0, formal/11-01-03Google Scholar
  40. OMG (2011b) A UML profile for Modeling and Analysis of Real Time Embedded Systems (MARTE). Object Management Group. Document formal/11-06-02Google Scholar
  41. OMG (2015) Unified Modelling Language: Superstructure. Object Management Group. Version 2.5, formal/15-03-01Google Scholar
  42. Parrilla L, García J, Albareda J, Mahulea C (2017) HEAT: A Tool to Develop, Analyze and Monitor Clinical Pathways. In: ICNSC’2017: 14Th IEEE International Conference on Networking, Sensing and Control. CalabriaGoogle Scholar
  43. Recalde L, Teruel E, Silva M (2001) Structure theory of multi-level deterministically synchronized sequential processes. Theor Comput Sci 254(1):1–33MathSciNetzbMATHGoogle Scholar
  44. Rohleder TR, Lewkonia P, Bischak DP, Duffy P, Hendijani R (2011) Using simulation modeling to improve patient flow at an outpatient orthopedic clinic. Health Care Manag Sci 14 (2):135–145Google Scholar
  45. Roux O, Combes C, Duvivier D (2006) A modeling methodology dedicated to simulation and based on generic meta-models using MDA-UML: an application to a chronic renal dialysis unit. In: International Conference on service systems and service management, vol 1, pp 692–697Google Scholar
  46. Selic B (2007) A systematic approach to Domain-Specific language design using UML. In: Tenth IEEE international symposium on object-oriented real-time distributed computing (ISORC2007). IEEE Computer Society, pp 2–9Google Scholar
  47. Silingas D, Vitiutinas R, Armonas A, Nemuraite L (2009) Domain-Specific modeling environment based on UML profiles. In: Proceedings of 15th International Conference on Information and Software Technologies (IT 2009), pp 167–177Google Scholar
  48. Swisher JR, Jacobson SH, Jun JB, Balci O (2001) Modeling and analyzing a physician clinic environment using discrete-event (visual) simulation. Comput Oper Res 28(2):105–125zbMATHGoogle Scholar
  49. Tricas F, García-Valles F, Colom J, Ezpeleta J (2005) A Petri net Structure-Based Deadlock Prevention Solution for Sequential Resource Allocation Systems. In: International Conference on robotics and automation. BarcelonaGoogle Scholar
  50. Wang T, Guinet A, Belaidi A, Besombes B (2009) Modelling and simulation of emergency services with ARIS and Arena. Case study: the emergency department of Saint Joseph and Saint Luc Hospital. Prod Plann Control 20(6):484–495Google Scholar
  51. Wells L (2006) Performance analysis using CPN tools. In: Lenzini L, Cruz RL (eds) Proceedings of the 1st International Conference on Performance Evaluation Methodolgies and Tools, VALUETOOLS 2006, vol 180. ACM International Conference Proceeding Series, Pisa, p 59Google Scholar
  52. Whittaker SJ, Rudie K, Mclellan J (2015) An Augmented Petri Net Model for Health-Care Protocols. IEEE Transactions on Automatic Control 60(9):2362–2377MathSciNetzbMATHGoogle Scholar
  53. Zimmermann A (2012) Modeling and Evaluation of Stochastic Petri Nets With timeNET 4.1. In: VALUETOOLS12: 6th International Conference on Performance Evaluation Methodologies and Tools, Cargese, pp 1–10Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science and Systems EngineeringUniversity of ZaragozaZaragozaSpain
  2. 2.Orthopedic Surgery DepartmentUniversity Hospital “Lozano Blesa”ZaragozaSpain

Personalised recommendations