EVALUATING SUPPLY CHAIN MANAGEMENT PERFORMANCE IN PUBLIC HEALTH CARE: AN MCDA APPROACH

Marube, Newton; Longaray, André Andrade; Ensslin, Leonardo; Ensslin, Sandra Rolim; Dutra, Ademar

doi:10.1590/0101-7438.2023.043.00275847

Newton Marube

Graduate Program in Computational Modeling, Federal University of Rio Grande, RS, Brazil - E-mail: nyamasege@gmail.com

https://orcid.org/0000-0003-3732-1329

André Andrade Longaray ^**Corresponding author

Graduate Program in Computational Modeling, Federal University of Rio Grande, RS, Brazil - E-mail: andrelongaray@gmail.com

https://orcid.org/0000-0002-2908-9390

Leonardo Ensslin

Graduate Program in Administration, University of Southern Santa Catarina, SC, Brazil - E-mail: leonardoensslin@gmail.com

https://orcid.org/0000-0001-7963-4679

Sandra Rolim Ensslin

Graduate Program in Production Engineering, Federal University of Santa Catarina, SC, Brazil - E-mail: sensslin@gmail.com

https://orcid.org/0000-0001-7420-8507

Ademar Dutra

Graduate Program in Administration, University of Southern Santa Catarina, SC, Brazil - E-mail: ademar.unisul@gmail.com

https://orcid.org/0000-0001-5289-9482

*Corresponding author

Phase	Stage	Description
Structuring	Soft approach to problem structuring	This step aims at explaining the context and achieving an understanding of the decision problem. The actors involved in the context are identified
	Family of Viewpoints	The Primary Assessment Elements (PAEs) are identified through brainstorming with the context actors. Through interviews with the actors, the PAEs are transformed into one or more action-oriented concepts. Finally, the concepts are grouped into Fundamental Points of View (FPV)
	Construction of descriptors	For each FPV the cognitive maps are developed together with the context actors. The cognitive maps seek to expand the knowledge about the means and ends relationships of the concepts built in the previous step and this process generates the rest of the Hierarchical Value Structure (HVS). For the concepts at the base of the hierarchical structure ordinal descriptors (scales) are constructed, establishing the performance levels ”good” and ”neutral”
Evaluation	Independence analysis	MCDA-C uses a compensatory model to build the global evaluation model. This model assumes that the compensation rates used in integration are constant. To achieve this condition, the criteria must be independent
	Construction of value functions and compensation rates	Ordinal scales are transformed into cardinal scales and compensation rates are identified using MACBETH software
	Identifying the impact profile of alternatives	Identifying the impact profile of alternatives: the status quo performance and the impact of actions are evaluated
	Sensitivity analysis	Sensitivity analysis is used to evaluate the robustness of the valuation model
Recommendations	Elaboration of recommendations	The recommendations phase is intended to support the decision-maker in identifying improvement actions, as well as understanding the consequences of these actions on the strategic objectives

Actor	Role
Decision maker	Administrative manager.
Interveners	Superintendent, Expenses Authorizer, Head of Administration Sector, Head of Supplies.
Facilitator	Authors of the study.
The acted	Community of the Southern Region of RS, other employees of the company, and suppliers.

PAE	CONCEPT
Information system management	1. Reducing rework due to diverse data sources ... Find errors in the flow of information
University support	2. Receive support from the University ... Have difficulty solving problems
Competencies	3. Adapt professional expertise to the needs of the sector ... Ignore the employee’s professional training
Group order items	4. Make the group attractive ... Lack supplier for that group
Involvement and Responsibility	5. Stimulate the commitment of employees ... have unproductive employees at the workplace
Institution Growth	6. Lead uniform growth in all areas ... Focus only in some specific areas

Descriptor of EPV 1.1.2.1 - % of achievement of projected number of collaborators
REFERENCE LEVELS	LEVELS OF IMPACT	ORDINAL SCALE
	L5	100%
GOOD	L4	95%
GOOD	L3	90%
NEUTRAL	L2	85%
NEUTRAL	L1	80%

Indicator in present study	Indicator in literature	Authors
Screening/stay	no delay in treatment	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
Installed capacity	overcrowding	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
Mapping costs	total cost per patient	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
screening	total waiting time of patient	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
stay	patient throughput or turnaround time	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
Access time and distance	Accessibility to services	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
Mapping costs	cost of inventory	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
Ideal Quantity	obsolete stock cost/overstocking cost	(Supeekit et al., 2016SUPEEKIT T, SOMBOONWIWAT T & KRITCHANCHAI D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102: 318-330.)
Standardization Commission	Standardization	(Lega et al., 2013LEGA F, MARSILIO M & VILLA S. 2013. An evaluation framework for measuring supply chain performance in the public healthcare sector: evidence from the Italian NHS. Production Planning & Control, 24(10-11), 931-947.)
	Staff specialization	(Lega et al., 2013LEGA F, MARSILIO M & VILLA S. 2013. An evaluation framework for measuring supply chain performance in the public healthcare sector: evidence from the Italian NHS. Production Planning & Control, 24(10-11), 931-947.)
	Safety	(Lega et al., 2013LEGA F, MARSILIO M & VILLA S. 2013. An evaluation framework for measuring supply chain performance in the public healthcare sector: evidence from the Italian NHS. Production Planning & Control, 24(10-11), 931-947.)
Investment in IT	Technological Investment	(Lega et al., 2013LEGA F, MARSILIO M & VILLA S. 2013. An evaluation framework for measuring supply chain performance in the public healthcare sector: evidence from the Italian NHS. Production Planning & Control, 24(10-11), 931-947.; Yazdani et al., 2020YAZDANI M, TORKAYESH AE & CHATTERJEE P. 2020. An integrated decision-making model for supplier evaluation in public healthcare system: the case study of a Spanish hospital. Journal of Enterprise Information Management, 33(5): 965-989.)
Supplier satisfaction	Supplier relationship management	(Lega et al., 2013LEGA F, MARSILIO M & VILLA S. 2013. An evaluation framework for measuring supply chain performance in the public healthcare sector: evidence from the Italian NHS. Production Planning & Control, 24(10-11), 931-947.)
Information flow	accessibility and flow of information	(Longaray et al., 2018LONGARAY AA, ENSSLIN L, ENSSLIN S, ALVES G, DUTRA A & MUNHOZ P. 2018. Using MCDA to evaluate the performance of the logistics process in public hospitals: the case of a Brazilian teaching hospital. International transactions in operational Research, 25(1): 133-156. https://doi.org/10.1111/itor.12387 https://doi.org/10.1111/itor.12387... )
Integration of systems	Computerization of stock control systems	(Longaray et al., 2018LONGARAY AA, ENSSLIN L, ENSSLIN S, ALVES G, DUTRA A & MUNHOZ P. 2018. Using MCDA to evaluate the performance of the logistics process in public hospitals: the case of a Brazilian teaching hospital. International transactions in operational Research, 25(1): 133-156. https://doi.org/10.1111/itor.12387 https://doi.org/10.1111/itor.12387... )
Suppliers with Best Practice Certification	Suppliers’ capabilities	(Hamid Abu Bakar et al., 2009HAMID ABU BAKAR A, LUKMAN HAKIM I, CHOY CHONG S & LIN B. 2009. Measuring supply chain performance among public hospital laboratories. International Journal of Productivity and Performance Management, 59(1): 75-97.)
Suppliers with Best Practice Certification	Supplier evaluation	(Kumar et al., 2005KUMAR A, OZDAMAR L & PENG NGC. 2005. Procurement performance measurement system in the health care industry. International journal of health care quality assurance, 18(2): 152-166. doi: 10.1108/09526860510588179 https://doi.org/10.1108/0952686051058817... )
Resolvability	Solvability rate	(Kumar et al., 2005KUMAR A, OZDAMAR L & PENG NGC. 2005. Procurement performance measurement system in the health care industry. International journal of health care quality assurance, 18(2): 152-166. doi: 10.1108/09526860510588179 https://doi.org/10.1108/0952686051058817... )
Resolvability	Efficiency of IT system	(Kumar et al., 2005KUMAR A, OZDAMAR L & PENG NGC. 2005. Procurement performance measurement system in the health care industry. International journal of health care quality assurance, 18(2): 152-166. doi: 10.1108/09526860510588179 https://doi.org/10.1108/0952686051058817... )
Effectiveness of Terminals	Effectiveness of IT system	(Kumar et al., 2005KUMAR A, OZDAMAR L & PENG NGC. 2005. Procurement performance measurement system in the health care industry. International journal of health care quality assurance, 18(2): 152-166. doi: 10.1108/09526860510588179 https://doi.org/10.1108/0952686051058817... )
Trained users	Training utilization rate	(Kumar et al., 2005KUMAR A, OZDAMAR L & PENG NGC. 2005. Procurement performance measurement system in the health care industry. International journal of health care quality assurance, 18(2): 152-166. doi: 10.1108/09526860510588179 https://doi.org/10.1108/0952686051058817... )

V_{P E H U} (a) = 0.1101 \times V_{F P V 1} (a) + 0.1222 \times V_{F P V 2} (a) + 0.0919 \times V_{F P V 3} (a) + 0.0858 \times V_{F P V 4} (a) + 0.0797 \times V_{F P V 5} (a) + 0.1040 \times V_{F P V 6} (a) + 0.0979 \times V_{F P V 7} (a) + 0.0641 * V_{F P V 8} (a) + 0.0615 \times V_{F P V 9} (a) + 0.0667 \times V_{F P V 10} (a) + 0.1161 \times V_{F P V 11} (a)

\begin{matrix} V_{A c t i v i t i e s} (a) = 0.6471 \times V_{B e s t P r a c t i c e s} (a) + 0.3521 \times V_{N e t w o r k s} (a) \\ V_{S u c c e s s i o n} (a) = 0.5385 \times V_{T e a m M a i n t e n a n c e} (a) + 0.4615 \times V_{C o n t i n u i t y O f A c t i o n s} (a) \\ V_{S t a b i l i t y} (a) = 0.6250 \times V_{S t r e n g t h e n i n g} (a) + 0.3750 \times V_{E x t e r n a l P r e s s u r e} (a) \end{matrix}

[1] *Corresponding author

Critical performance factors to be improved:	EPV 4.3.1 Integration
Descriptor:	% of integrated systems
Proposed Actions:	- Create a multidisciplinary working group (WG) to map all candidate Integration processes.
	- Establish a schedule for the working group findings and final report.
	- Request the IT sector to support the WG.
	- Implement the integration of all the organization processes in the system.
	- Encourage the staff to actively participate in the system tests;
Responsible:	Head of the IT Sector
Deadline:	First semester of following year
Supervision Frequency:	Monthly
How it will be supervised:	Monitoring the Schedule with the working group
Responsible for supervising:	General Manager
Expected result:	Change from ‘<80% Integration of systems’ to ‘80% Integration of systems’
Descriptor Impact:	Improving from L1 (-133.33) to L4 (100)

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EVALUATING SUPPLY CHAIN MANAGEMENT PERFORMANCE IN PUBLIC HEALTH CARE: AN MCDA APPROACH

ABSTRACT