Research Article

Healthcare supply chain risk assessment KPIs: an empirical study using PLS-SEM

Pedro Senna; Augusto Reis; Julio de Guimarães; Lino Guimarães Marujo; Ana Carla de Souza Gomes dos Santos; Eliana Andrea Severo

Downloads: 2
Views: 357


Paper aims: This study has the objective of mapping and empirically validating KPIs that can be used to assess healthcare supply chain risks.

Originality: We combined two methodological approaches: i) we conducted a systematic literature review to identify the healthcare supply chain risk assessment KPIs and ii) We grouped these KPIs into five constructs and validated their relations using PLS-SEM.

Research method: This is the only study that presents a systematic literature review to identify KPIs that measure healthcare supply chain risks, groups the KPIs into a theoretical framework, and presents a PLS-SEM validation. This study used data from Brazil, from a variety of healthcare supply chain organizations (suppliers, OEMs, clinics, and hospitals), therefore we cannot guarantee that the study can be generalized.

Main findings: The systematic literature review identified 27 KPIs which were grouped into five constructs. The structural model supported by the PLS-SEM technique revealed that reliability, responsiveness, costs, and agility are antecedents to healthcare supply chain quality.

Implications for theory and practice: Managers may rely upon this study to understand that healthcare supply chain reliability and responsiveness are antecedents to healthcare supply chain costs and agility, which are antecedents to healthcare supply chain quality.


KPI, Healthcare supply chain risk management, Supply chain resilience, PLS-SEM


Al-Kassab, Z. J., Ouertani, M., Schiuma, G., & Neely, A. (2014). Information visualization to support management decisions. International Journal of Information Technology & Decision Making, 13(2), 407-428.

Antonelli, D., & Bruno, G. (2015). Application of process mining and semantic structuring towards a lean healthcare network. In L. M. Camarinha-Matos, F. Bénaben & W. Picard (Eds.), Risks and resilience of collaborative networks: 16th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2015, Albi, France, October 5-7, 2015, Proceedings (Vol. 463, pp. 497-508). Cham: Springer.

Aoun, M., & Hasnan, N. (2013). Lean production and TQM: complementary or contradictory driving forces of innovation performance? International Journal of Innovation Science, 5(4), 237-252.

Arnaboldi, M., Lapsley, I., & Steccolini, I. (2015). Performance management in the public sector: the ultimate challenge. International Journal of Public Sector Management, 31(1), 1-22.

Barroso, A. P., Machado, V. H., Barros, A. R., & Cruz-Machado, V. (2010, December 7-10). Toward a resilient supply chain with supply disturbances. In Institute of Electrical and Electronics Engineers (Org.), 2010 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 245-249). New York, United States: IEEE.

Bhamra, R., Dani, S., & Burnard, K. (2011). Resilience: the concept, a literature review and future directions. International Journal of Production Research, 49(18), 5375-5393.

Cai, J., Liu, X., Xiao, Z., & Liu, J. (2009). Improving supply chain performance management: a systematic approach to analyzing iterative KPI accomplishment. Decision Support Systems, 46(2), 512-521.

Cardoso, S. R., Barbosa-Póvoa, A. P., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega, 56, 53-73.

Carvalho, H., Cruz-Machado, V., & Tavares, J. G. (2012). A mapping framework for assessing supply chain resilience. International Journal of Logistics Systems and Management, 12(3), 354-373.

Cavalcante, P. D. S., Rossaneis, M. A., Haddad, M. C. L., & Gabriel, C. S. (2016). Indicadores de qualidade utilizados no gerenciamento da assistência de enfermagem hospitalar. Revista Enfermagem UERJ, 23(6), 787-793.

Chan, C., & Green, L. (2013). Improving access to healthcare: models of adaptive behavior. In T. D. Brian (Ed.), Handbook of healthcare operations management. New York: Springer.

Coelho, L. C., Follmann, N., & Rodriguez, C. M. T. (2009). O impacto do compartilhamento de informações na redução do efeito chicote na cadeia de abastecimento. Gestão & Produção, 16(4), 571-583.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale: Erlbaum.

Crema, M., & Verbano, C. (2015). How to combine lean and safety management in health care processes: a case from Spain. Safety Science, 79, 63-71.

Croxton, K., García-Dastugue, S. J., Lambert, D. M., & Rogers, D. S. (2001). The supply chain management processes. International Journal of Logistics Management, 12(2), 13-36.

De Meyer, A., Snoeck, M., Cattrysse, D., & Van Orshoven, J. (2016). A reference data model to support biomass supply chain modelling and optimisation. Environmental Modelling and Software, 83, 1-11.

Díaz, A., Pons, J., & Solís, L. (2012). Improving healthcare services: lean lessons from Aravind. International Journal of Business Excellence, 5(4), 413.

Efe, B., & Efe, Ö. F. (2016). An application of value analysis for lean healthcare management in an emergency department. International Journal of Computational Intelligence Systems, 9(4), 689-697.

Eiro, N. Y., & Torres-Junior, A. S. (2015). Comparative study: TQ and lean production ownership models in health services. Revista Latino-Americana de Enfermagem, 23(5), 846-854. PMid:26487134.

Erdem, S., Kizilelma, T. T., & Vural, C. A. (2016). Supporting healthcare executive managers’ decisions through dashboards. Journal of Information & Knowledge Management, 15(1), 1650005.

Fan, W., Gu, J., Tang, H., & Gao, X. (2011, August 14-17). Risk management in end-to-end global supply chains. In American Society of Civil Engineers (Org.), 11th International Conference of Chinese Transportation Professionals (ICCTP) (pp. 3772-3782). Reston, United States: ASCE.

Fang, D., & Weng, W. (2010, August 16-20). KPI evaluation system of location decision for plant relocation from the view of the entire supply chain optimization. In Institute of Electrical and Electronics Engineers (Org.), 2010 IEEE International Conference on Automation and Logistics (pp. 659-663). New York, United States: IEEE.

Fiksel, J. (2007). Sustainability and resilience: toward a systems approach. IEEE Engineering Management Review, 35(3), 5.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equations models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

Gu, X., & Itoh, K. (2016). Performance indicators: healthcare professionals’ views. International Journal of Health Care Quality Assurance, 29(7), 801-815. PMid:27477935.

Günal, M. M., & Pidd, M. (2011). DGHPSIM: generic simulation of hospital performance. ACM Transactions on Modeling and Computer Simulation, 21(4), 1-22.

Habidin, N. F., Khaidir, N. A., Shazali, N. A., Ali, N., & Jamaludin, N. H. (2015). The development of process innovation and organizational performance in Malaysian healthcare industry. International Journal of Business Innovation and Research, 9(2), 148-162.

Hair Junior, J. F., Black, W. C., Bardin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). New York: Pearson.

Hair Junior, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks: Sage.

Hair Junior, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: a workbook (Classroom Companion: Business). Cham: Springer. The SEMinR package, pp. 49-74.

Hammadi, L., Ouahman, A. A., De Cursi, J. E. S., & Ibourk, A. (2015, July 27-29). An approach based on FMECA methodology for a decision support tool for managing risk in customs supply chain: a case study. In Z. Zhang, R. Zhang, V. Fernandez & S. Liu (Eds.), 2015 International Conference on Logistics, Informatics and Service Sciences (LISS) (pp. 1-6). New York, United States: IEEE.

Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk – definition, measure and modeling. Omega, 52, 119-132.

Jones, P., Shepherd, M., Wells, S., Le Fevre, J., & Ameratunga, S. (2014). Review article: what makes a good healthcare quality indicator? A systematic review and validation study. Emergency Medicine Australasia, 26(2), 113-124. PMid:24707999.

Juttner, U. (2005). Supply chain risk management. International Journal of Logistics Management, 9(2), 120-141.

Jüttner, U., Peck, H., & Christopher, M. (2003). Supply chain risk management: outlining an agenda for future research. International Journal of Logistics: Research and Applications, 6(4), 197-210.

Kahraman, U. A. (2021). Analysis of interactions between performance indicators with fuzzy decision making approach in healthcare management. Journal of Intelligent Manufacturing, 32(3), 913.

Kanamori, S., Castro, M. C., Sow, S., Matsuno, R., Cissokho, A., & Jimba, M. (2016). Impact of the Japanese 5S management method on patients’ and caretakers satisfaction : a quasi-experimental study in Senegal. Global Health Action, 9(1), 32852. PMid:27900932.

Kannengiesser, U., Neubauer, M., & Heininger, R. (2016, April 7-8). Integrating business processes and manufacturing operations based on S-BPM and B2MML. In J. L. Sanz (Ed.), S-BPM '16: Proceedings of the 8th International Conference on Subject-oriented Business Process Management (pp. 1-10). New York, United States: Association for Computing Machinery.

Khalili, S. M., Jolai, F., & Torabi, S. A. (2016). Integrated production–distribution planning in two-echelon systems: a resilience view. International Journal of Production Research, 7543, 1-25.

Khan, O., & Burnes, B. (2007). Risk and supply chain management: creating a research agenda. International Journal of Logistics Management, 18(2), 197-216.

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press.

Kolotzek, C., Helbig, C., Thorenz, A., Reller, A., & Tuma, A. (2018). A company-oriented model for the assessment of raw material supply risks, environmental impact and social implications. Journal of Cleaner Production, 176, 566-580.

Kouvelis, P., Dong, L., & Boyabatli, R. L. O. (2011). Handbook of integrated risk management in global supply chains. Hoboken: John Wiley & Sons.

Lavastre, O., Gunasekaran, A., & Spalanzani, A. (2012). Supply chain risk management in French companies. Decision Support Systems, 52(4), 828-838.

Lehoux, N., Lebel, L., & Elleuch, M. (2016). Benefits of inter-firm relationships: application to the case of a five sawmills and one paper mill supply chain. Information Systems and Operational Research, 54(3), 192-209.

Li, Z. P., Lim, L. H., Chen, X. S., & Tan, C. S. (2015, December 6-9). Supplier selection decision-making in supply chain risk scenario using agent based simulation. In Institute of Electrical and Electronics Engineers (Org.), 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 900-904). New York, United States: IEEE.

Lorenzo-Seva, U., Timmerman, M. E., & Kiers, H. A. (2011). The Hull method for selecting the number of common factors. Multivariate Behavioral Research, 46(2), 340-364. PMid:26741331.

Mardia, K. V. (1971). The effect of nonnormality on some multivariate tests and robustness to non-normality in the linear model. Biometrika, 58(1), 105-121.

Mason, R. (2006). Coping with complexity and turbulence — an entrepreneurial solution. Journal of Enterprising Culture, 14(4), 241-266.

McIntosh, B., Sheppy, B., & Cohen, I. (2014). Illusion or delusion – Lean management in the health sector. International Journal of Health Care Quality Assurance, 27(6), 482-492. PMid:25115051.

Minami, C. A., Sheils, C. R., Bilimoria, K. Y., Johnson, J. K., Berger, E. R., Berian, J. R., Englesbe, M. J., Guillamondegui, O. D., Hines, L. H., Cofer, J. B., Flum, D. R., Thirlby, R. C., Kazaure, H. S., Wren, S. M., O’Leary, K. J., Thurk, J. L., Kennedy, G. D., Tevis, S. E., & Yang, A. D. (2016). Process improvement in surgery. Current Problems in Surgery, 53(2), 62-96. PMid:26806271.

Neiger, D., Rotaru, K., & Churilov, L. (2009). Supply chain risk identification with value-focused process engineering. Journal of Operations Management, 27(2), 154-168.

Norrman, A., & Jansson, U. (2004). Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident. International Journal of Physical Distribution & Logistics Management, 34(5), 434-456.

Pettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring supply chain resilience. Development and Implementation of an Assessment Tool, 34(1), 46-76.

Pujawan, I. N., & Geraldin, L. H. (2009). House of risk: a model for proactive supply chain risk management. Business Process Management Journal, 15(6), 953-967.

Rajesh, R. (2016). Forecasting supply chain resilience performance using grey prediction. Electronic Commerce Research and Applications, 20, 42-58.

Reijula, J., Nevala, N., Lahtinen, M., Ruohomäki, V., & Reijula, K. (2014). Lean design improves both health-care facilities and processes: a literature review. Intelligent Buildings International, 6(3), 170-185.

Robinson, S., Radnor, Z. J., Burgess, N., & Worthington, C. (2012). SimLean: utilising simulation in the implementation of lean in healthcare. European Journal of Operational Research, 219(1), 188-197.

Saen, R. F., Fisher, R., & Mahdiloo, M. (2016). Sustainable supply chain modeling and optimization. Transportation Research Part D, Transport and Environment, 48, 409-410.

Santos, A. C. S. G., Reis, A., Souza, C. G., Santos, I. L., Ferreira, L. A. F., & Senna, P. (2022). Measuring the current state-of-the-art in lean healthcare literature from the lenses of bibliometric indicators. Benchmarking. In press.

Sedevich-Fons, L. (2014). Financial indicators in healthcare quality management systems. The TQM Journal, 26(4), 312-328.

Senna, P., Pinha, D., Ahluwalia, R., Guimarães, J. C., Severo, E., & Reis, A. (2016). A three-stage stochastic optimization model for the Brazilian biodiesel supply chain. Production, 26(3), 501-515.

Senna, P., Reis, A. C., Castro, A., & Dias, A. C. (2020). Promising research fields in supply chain risk management and supply chain resilience and the gaps concerning human factors: a literature review. Work, 67(2), 487-498. PMid:33074212.

Senna, P., Reis, A., Dias, A., Coelho, O., Guimarães, J., & Severo, E. (2023). Healthcare supply chain resilience framework: antecedents, mediators, consequents. Production Planning and Control, 34(3), 295-309.

Senna, P., Reis, A., Santos, I. L., Dias, A. C., & Coelho, O. (2021). A systematic literature review on supply chain risk management: is healthcare management a forsaken research field? Benchmarking, 28(3), 926-956.

Senna, P., Reis, A., Santos, I., & Dias, A. (2022). Healthcare supply chain risk management in Rio de Janeiro, Brazil: what is the current situation? Work, 72(2), 511-527. PMid:35527591.

Shohet, I. M. (2006). Key performance indicators for strategic healthcare facilities maintenance. Journal of Construction Engineering and Management, 132(4), 345-352.

Silva, C. S., Gabriel, C. S., Bernardes, A., & Evora, Y. D. M. (2009). Opinião do enfermeiro sobre indicadores que avaliam a qualidade na assistência de enfermagem. Revista Gaúcha de Enfermagem, 30(2), 263-271. PMid:20027959.

Soni, U., & Jain, V. (2011, December 6-9). Minimizing the vulnerabilities of supply chain: a new framework for enhancing the resilience. In Institute of Electrical and Electronics Engineers (Org.), 2011 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 933-939). New York, United States: IEEE.

Souter, G. (2000). Risks from supply chain also demand attention. Business Insurance, 34, 26-28.

Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53-55. PMid:28029643.

Thun, Ã., & Hoenig, D. (2011). An empirical analysis of supply chain risk management in the German automotive industry. International Journal of Production Economics, 131(1), 242-249.

Torabi, S. A., Baghersad, M., & Mansouri, S. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E, Logistics and Transportation Review, 79, 22-48.

VanVactor. (2011). Cognizant healthcare logistics management: ensuring resilience during crisis. International Journal of Disaster Resilience in the Built Environment, 6(1), 102-116.

Vugrin, E. D., Warren, D. E., & Ehlen, M. A. (2011). A resilience assessment framework for infrastructure and economic systems: quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane. Process Safety Progress, 30(3), 280-290.

Wu, J., Wang, S., Chao, X., Ng, C. T., & Cheng, T. C. (2010). Impact of risk aversion on optimal decisions in supply contracts. International Journal of Production Economics, 128(2), 569-576.

Yildiz, Ö., & Demirors, O. (2014). Healthcare quality indicators – a systematic review. International Journal of Health Care Quality Assurance, 27(3), 209-222. PMid:25786185.

Zepeda, E. D., Nyaga, G. N., & Young, G. J. (2016). Supply chain risk management and hospital inventory: Effects of system affiliation. Journal of Operations Management, 44(1), 30-47.

Submitted date:

Accepted date:

649ac9a3a95395699b246772 production Articles
Links & Downloads


Share this page
Page Sections