Skip to main content
SpringerLink
Log in

Design Approaches for Executable Clinical Pathways at the Point of Care in Limited Resource Settings to Support the Clinical Decision Process: Review of the State of the Art

  • Conference paper
  • First Online:
Wireless Mobile Communication and Healthcare (MobiHealth 2021)

  • 436 Accesses

Abstract

Decision support clinical pathways are used to improve the performance of the health-care management system. An effective clinical pathway (CP) helps to know the optimal treatment route that patients will follow. The extent of the CP goes from the first contact in the health-center (or hospital) to the completion of the treatment until the patient is dismissed. Up to now, far too little attention has been paid to a systematic review, the research and the development of CPs in a low resource setting (LRS). The main focus has been primarily on data-intensive environments where there is no shortage of resources. A systematic search in PubMed and Web of Science was conducted for bundling and categorizing the relevant approaches for LRS. Of 45 full reviewed articles, 25/45(55.6%) and 20/45(44.4%) of the studies were conducted using knowledge-based and data-driven approaches respectively. Among the knowledge-based studies, 9/25(36%) were reporting a stand-alone applications, 10/25(40%) attempting to deliver a paper-based CP, and the remaining focus was on web-based applications. In the data-driven approaches, 15/20(75%) tried to integrate with the electronic health record. The paper identifies the approaches for executing CPs and highlights key considerations for building LRS-compatible CPs. Data-driven CPs do not only resolve the challenges of improving the quality of existing knowledge-based CPs, but also enable evidence-based practice, improve outcomes, and reduce cost and delay.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lee, B.X., et al.: Transforming our world: implementing the 2030 agenda through sustainable development goal indicators. J. Public Health Policy 37, 13–31 (2016)

    Article  Google Scholar 

  2. Marker, P., McNamara, K., Wallace, L.: The Significance of Information and Communication Technologies for Reducing Poverty. DFID, London (2002)

    Google Scholar 

  3. Wootton, R., Patil, N.G., Scott, R.E., Ho, K.: Telehealth in the Developing World. (IDRC) (2009)

    Google Scholar 

  4. Shiferaw, F., Zolfo, M.: The role of information communication technology (ICT) towards universal health coverage: the first steps of a telemedicine project in Ethiopia. Glob. Health Action 5, 15638 (2012)

    Article  Google Scholar 

  5. Mengesha, G.H., Garfield, M.J.: A contextualized it adoption and use model for telemedicine in Ethiopia. Inf. Technol. for Dev. 25, 184–203 (2019)

    Article  Google Scholar 

  6. Lawal, A.K., et al.: What is a clinical pathway? Refinement of an operational definition to identify clinical pathway studies for a Cochrane systematic review. BMC Med. 14(1), 1–5 (2016)

    Article  MathSciNet  Google Scholar 

  7. Abrahams, E., et al.: Clinical pathways: recommendations for putting patients at the center of value-based care. Clin. Cancer Res. 23, 4545–4549 (2017)

    Article  Google Scholar 

  8. Siwicki, B.: Flagler Hospital uses AI to create clinical pathways that enhance care and slash costs (2018). https://www.healthcareitnews.com/news/flagler-hospital-uses-ai-create-clinical-pathways-enhance-care-and-slash-costs. Accessed June 2019

  9. Huang, Z., et al.: Discovery of clinical pathway patterns from event logs using probabilistic topic models. J. Biomed. Inform. 47, 39–57 (2014)

    Article  Google Scholar 

  10. Schrijvers, G., van Hoorn, A., Huiskes, N.: The care pathway: concepts and theories: an introduction. Int. J. Integr. Care 12 (2012)

    Google Scholar 

  11. Huang, Z., Lu, X., Duan, H.: Using recommendation to support adaptive clinical pathways. J. Med. Syst. 36(3), 1849–1860 (2012)

    Article  Google Scholar 

  12. Butow, P., et al.: Clinical pathway for the screening, assessment and management of anxiety and depression in adult cancer patients: Australian guidelines. Psycho-Oncology 24(9), 987–1001 (2015)

    Article  Google Scholar 

  13. Chung, S.-B., et al.: Implementation and outcomes of a critical pathway for lumbar laminectomy or microdiscectomy. J. Korean Neurosurg. Soc. 51(6), 338 (2012)

    Article  Google Scholar 

  14. Sou, V., et al.: A clinical pathway for the management of difficult venous access. BMC Nurs. 16(1), 64 (2017)

    Article  Google Scholar 

  15. Gesme, D.H., Wiseman, M.: Strategic use of clinical pathways. J. Oncol. Pract. 7, 54 (2011)

    Article  Google Scholar 

  16. Rotter, T., et al.: The effects of clinical pathways on professional practice, patient outcomes, length of stay, and hospital costs: Cochrane systematic review and meta-analysis. Eval. Health Prof. 35, 3–27 (2012)

    Article  Google Scholar 

  17. Ellis, P.G., et al.: Clinical pathways: management of quality and cost in oncology networks in the metastatic colorectal cancer setting. J. Oncol. Pract. 13, e522–e529 (2017)

    Article  Google Scholar 

  18. Wylde, V., et al.: Clinical- and cost-effectiveness of the STAR care pathway compared to usual care for patients with chronic pain after total knee replacement: study protocol for a UK randomised controlled trial. Trials 19(1), 132 (2018). https://doi.org/10.1186/s13063-018-2516-8

    Article  Google Scholar 

  19. Jones, A.: Implementation of hospital care pathways for patients with schizophrenia. J. Nurs. Manag. 8(4), 215–225 (2000)

    Article  Google Scholar 

  20. Rickard, J., et al.: Critical care management of peritonitis in a low-resource setting. World J. Surg. 42(10), 3075–3080 (2018). https://doi.org/10.1007/s00268-018-4598-6

    Article  Google Scholar 

  21. Chen, K.S., et al.: Utilizing clinical pathways and web-based conferences to improve quality of care in a large integrated network using breast cancer radiation therapy as the model. Radiat. Oncol. 13(1), 44 (2018). https://doi.org/10.1186/s13014-018-0995-0

    Article  Google Scholar 

  22. Vukoja, M., et al.: A survey on critical care resources and practices in low- and middle-income countries. Glob. Heart 9(3), 337–342 (2014). https://doi.org/10.1016/j.gheart.2014.08.002

    Article  Google Scholar 

  23. Böckmann, B., Heiden, K.: Extracting and transforming clinical guidelines into pathway models for different hospital information systems. Heal. Inf. Sci. Syst. 1, 13 (2013)

    Article  Google Scholar 

  24. Hu, S.-C.: Computerized monitoring of emergency department patient flow. Am. J. Emerg. Med. 11(1), 8–11 (1993)

    Article  Google Scholar 

  25. Hilario, A.L., et al.: Utilization of clinical pathway on open appendectomy: a quality improvement initiative in a private hospital in the Philippines. Int. J. Health Sci. 12(2), 43 (2018)

    Google Scholar 

  26. Dixon, C.A., et al.: Patient flow analysis in resource-limited settings: a practical tutorial and case study. Glob. Health: Sci. Pract. 3(1), 126–134 (2015). https://doi.org/10.9745/GHSP-D-14-00121

    Article  Google Scholar 

  27. Aspland, E., Gartner, D., Harper, P.: Clinical pathway modelling: a literature review. Health Syst. 10, 1–23 (2019)

    Article  Google Scholar 

  28. Liberati, A., et al.: The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J. Clin. Epidemiol. 62(10), e1–e34 (2009)

    Google Scholar 

  29. Groot, G., et al.: Development of a program theory for shared decision-making: a realist review protocol. Syst. Rev. 6(1), 114 (2017). https://doi.org/10.1186/s13643-017-0508-5

    Article  Google Scholar 

  30. Middleton, B., Sittig, D., Wright, A.: Clinical decision support: a 25 year retrospective and a 25 year vision. Yearb. Med. Inform. 25, S103–S116 (2016)

    Article  Google Scholar 

  31. Chu, S.: Reconceptualising clinical pathway system design. Collegian 8, 33–36 (2001)

    Article  Google Scholar 

  32. Chu, S., Cesnik, B.: Improving clinical pathway design: lessons learned from a computerised prototype. Int. J. Med. Inform. 51(1), 1–11 (1998)

    Article  Google Scholar 

  33. Miller, T.W., Ryan, M., et al.: Utilizing algorithms and pathways of care in allied health practice. Internet J. Allied Heal. Sci. Pract. 3, 7 (2005)

    Google Scholar 

  34. DiJerome, L.: The nursing case management computerized system: meeting the challenge of health care delivery through technology. Comput. Nurs. 10, 250–258 (1992)

    Article  Google Scholar 

  35. Khodambashi, S., Slaughter, L.A., Nytrø, Ø.: Computer-interpretable clinical guidelines: a review and analysis of evaluation criteria for authoring methods. In: MedInfo, p. 954 (2015)

    Google Scholar 

  36. Chu, S.: Computerised clinical pathway management systems and the implications. Collegian 8, 19–24 (2001)

    Article  Google Scholar 

  37. Donald, M., et al.: Development and implementation of an online clinical pathway for adult chronic kidney disease in primary care: a mixed methods study. BMC Med. Inform. Decis. Making 16(1), 109 (2016). https://doi.org/10.1186/s12911-016-0350-z

    Article  Google Scholar 

  38. Gibbs, J., et al.: The eclinical care pathway framework: a novel structure for creation of online complex clinical care pathways and its application in the management of sexually transmitted infections. BMC Med. Inform. Decis. Making 16, 98 (2016)

    Article  Google Scholar 

  39. Yang, H., Li, W., Liu, K., Zhang, J.: Knowledge-based clinical pathway for medical quality improvement. Inf. Syst. Front. 14, 105–117 (2012)

    Article  Google Scholar 

  40. Bouamrane, M.M., Mair, F.S.: Implementation of an integrated preoperative care pathway and regional electronic clinical portal for preoperative assessment. BMC Med. Inform. Decis. Making 14, 93 (2014)

    Article  Google Scholar 

  41. Peleg, M., et al.: Comparing computer-interpretable guideline models: a case-study approach. J. Am. Med. Informatics Assoc. 10, 52–68 (2003)

    Article  Google Scholar 

  42. GonzáLez-Ferrer, A., Ten Teije, A., Fdez-Olivares, J., Milian, K.: Automated generation of patient- tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks. Artif. Intell. Med. 57, 91–109 (2013)

    Article  Google Scholar 

  43. Heiden, K.: Model-based integration of clinical practice guidelines in clinical pathways. In: CAiSE (Doctoral Consortium). (Citeseer) (2012)

    Google Scholar 

  44. Rebbeck, T., et al.: Implementation of a guideline-based clinical pathway of care to improve health outcomes following whiplash injury (whiplash impact): protocol of a randomised, controlled trial. J. Physiotherapy 62, 111 (2016)

    Article  Google Scholar 

  45. Djulbegovic, B., Hozo, I., Dale, W.: Transforming clinical practice guidelines and clinical pathways into fast-and-frugal decision trees to improve clinical care strategies. J. Eval. Clin. Pract. 24(5), 1247–1254 (2018). https://doi.org/10.1111/jep.12895

    Article  Google Scholar 

  46. Ethiopian primary healthcare clinical guidelines: Care of children 5–12 years and Adults 15 years or older in Health Centers. Practical Approach to Care Kit (2017)

    Google Scholar 

  47. Bettencourt-Silva, J.H., Mannu, G.S., de la Iglesia, B.: Visualisation of integrated patient-centric data as pathways: enhancing electronic medical records in clinical practice. In: Holzinger, A. (ed.) Machine Learning for Health Informatics. LNCS (LNAI), vol. 9605, pp. 99–124. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-50478-0_5

    Chapter  Google Scholar 

  48. Zhang, Y., Padman, R.: An interactive platform to visualize data-driven clinical pathways for the management of multiple chronic conditions. Stud. Health Technol. Inform. 672–676 (2017)

    Google Scholar 

  49. Bettencourt-Silva, J.H., et al.: Building data-driven pathways from routinely collected hospital data: a case study on prostate cancer. JMIR Med. Inform. 3, e26 (2015)

    Article  Google Scholar 

  50. Zhang, Y., Padman, R.: Data-driven clinical and cost pathways for chronic care delivery. Am. J. Managed Care 22, 816–820 (2016)

    Google Scholar 

  51. Funkner, A.A., Yakovlev, A.N., Kovalchuk, S.V.: Data-driven modeling of clinical pathways using electronic health records. Procedia Comput. Sci. 121, 835–842 (2017)

    Article  Google Scholar 

  52. Perer, A., Wang, F., Hu, J.: Mining and exploring care pathways from electronic medical records with visual analytics. J. Biomed. Inform. 56, 369–378 (2015)

    Article  Google Scholar 

  53. Zhang, Y., Padman, R., Patel, N.: Paving the cowpath: learning and visualizing clinical pathways from electronic health record data. J. Biomed. Inform. 58, 186–197 (2015)

    Article  Google Scholar 

  54. Ye, Y., Jiang, Z., Yang, D., Du, G.: A semantics-based clinical pathway workflow and variance management framework. In: 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, vol. 1, pp. 758–763. IEEE (2008)

    Google Scholar 

  55. Hu, Z., et al.: Modeling of clinical pathways based on ontology. In: 2009 IEEE International Symposium on IT in Medicine & Education, vol. 1, pp. 1170–1174. IEEE (2009)

    Google Scholar 

  56. Alexandrou, D., Xenikoudakis, F., Mentzas, G.: Adaptive clinical pathways with semantic web rules. In: HEALTHINF (2), pp. 140–147 (2008)

    Google Scholar 

  57. Wang, H., Zhou, T., Tian, L., Qian, Y., Li, J.: Creating hospital-specific customized clinical pathways by applying semantic reasoning to clinical data. J. Biomed. Inform. 52, 354–363 (2014). https://doi.org/10.1016/j.jbi.2014.07.017

    Article  Google Scholar 

  58. Hurley, K.F., Abidi, S.S.R.: Ontology engineering to model clinical pathways: towards the computerization and execution of clinical pathways. In: Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007), pp. 536–541. IEEE (2007)

    Google Scholar 

  59. Liu, R., et al.: Pathway-finder: an interactive recommender system for supporting personalized care pathways. In: 2014 IEEE International Conference on Data Mining Workshop, pp. 1219–1222. IEEE (2014)

    Google Scholar 

  60. Tsoukalas, A., Albertson, T., Tagkopoulos, I.: From data to optimal decision making: a data-driven, probabilistic machine learning approach to decision support for patients with sepsis. JMIR Med. Inform. 3, e11 (2015)

    Article  Google Scholar 

  61. Yang, X., et al.: Modelling and performance analysis of clinical pathways using the stochastic process algebra pepa. BMC Bioinform. 13, S4 (2012)

    Article  Google Scholar 

  62. Du, G., Jiang, Z., Diao, X., Ye, Y., Yao, Y.: Variances handling method of clinical pathways based on TS fuzzy neural networks with novel hybrid learning algorithm. J. Med. Syst. 36, 1283–1300 (2012)

    Article  Google Scholar 

  63. Yazid, M.H.A., et al.: Clinical pathway variance prediction using artificial neural network for acute decompensated heart failure clinical pathway. Malays. J. Fundamental Appl. Sci. 14, 116–124 (2018)

    Google Scholar 

  64. De-Arteaga, M., Herlands, W., Neill, D.B., Dubrawski, A.: Machine learning for the developing world. ACM Trans. Manag. Inf. Syst. 9(2), 1–14 (2018). https://doi.org/10.1145/3210548

    Article  Google Scholar 

  65. Ethiopian Federal Ministry of Health: Pathways to Improve Health Information Systems in Ethiopia. Analysis of report on the stage of continuous improvement - Defining the Current Status, Goal and Improvement roadmap of the HIS (2021)

    Google Scholar 

Download references

Acknowledgments

The NASCERE (Network for Advancement of Sustainable Capacity in Education and Research in Ethiopia) program has assisted us in the work to date and will continue to assist us as we move forward with the planned activities.

Author information

Authors and Affiliations

  1. Department of Electronics and Informatics ETRO, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050, Brussel, Belgium

    Geletaw Sahle Tegenaw, Frank Verbeke, Jan Cornelis & Bart Jansen

  2. Department of Obstetrics and Gynecology, College of Health Science, Jimma University, Jimma, Ethiopia

    Demisew Amenu

  3. Faculty of Computing, JIT, Jimma University, Jimma, Ethiopia

    Geletaw Sahle Tegenaw & Girum Ketema

  4. iMEC, Kapeldreef 75, 3001, Leuven, Belgium

    Bart Jansen

Authors
  1. Geletaw Sahle Tegenaw
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Demisew Amenu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Girum Ketema
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Frank Verbeke
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jan Cornelis
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bart Jansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Geletaw Sahle Tegenaw .

Editor information

Editors and Affiliations

  1. Chongqing University of Posts and Telecommunications, Chongqing, China

    Xinbo Gao

  2. The University of Sydney, Sydney, NSW, Australia

    Abbas Jamalipour

  3. Chongqing University of Posts and Telecommunications, Chongqing, China

    Lei Guo

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tegenaw, G.S., Amenu, D., Ketema, G., Verbeke, F., Cornelis, J., Jansen, B. (2022). Design Approaches for Executable Clinical Pathways at the Point of Care in Limited Resource Settings to Support the Clinical Decision Process: Review of the State of the Art. In: Gao, X., Jamalipour, A., Guo, L. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-031-06368-8_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06368-8_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06367-1

  • Online ISBN: 978-3-031-06368-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation