Identifying and Prioritizing Effective Factors on Outsourcing in Public Hospitals Using Fuzzy BWM

Rowshan, Mansooreh; Shojaei, Payam; Askarifar, Kazem; Rahimi, Hamed

doi:10.1080/00185868.2019.1711482

Cited by 8 publications

(3 citation statements)

References 28 publications

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“…Economic and financial factors with a path coefficient of 0.709 directly affect about 70% of outsourcing decision changes. Many studies confirm this finding [ 14 , 16 , 18 , 19 ]. This includes freeing up resources to invest in other activities, comparing contractors’ offers, costs during contract execution (inflation, unforeseen costs), service costs, projected financial and budgetary resources, cost-benefit analysis and the projected benefits of services.…”

Section: Discussionmentioning

confidence: 58%

Developing decision model for the outsourcing of medical service delivery in the public hospitals

Khosravizadeh

Maleki

Ahadinezhad

et al. 2022

BMC Health Serv Res

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Background The decision to outsource an activity is one of the most complex organizational decisions. This decision is also influenced by several factors and components. In order to facilitate and optimize it, for the first time in this study, a decision model for outsourcing medical service delivery in public hospitals has been developed. Methods We conducted this cross-sectional study in 3 stages: 1) We identified the factors affecting the outsourcing decisions, 2) an expert panel identified the influential factors. After standardization, we distributed 220 questionnaires among university staff managers and heads, nursing managers, and managers of the research units, and 3) Structural Equation Model applied to evaluate the relationship between the variables on AMOS22, at 0.05 significant level. Results Findings indicated the optimal level of all fit indices. The path coefficient between all identified factors with the outsourcing decision was positive (t > 1.96). Factors ranging from the most effective to least effective included monitoring and control, service type, human resource, economic and financial, executive capability, external environment, and terms and conditions. Conclusion The proposed model provides unit evaluation to make the appropriate decision on outsourcing or non-outsourcing. Control and monitoring were the most determining factors. We recommend performing monitoring continuously as a guide and deterrent to error. We also recommend continuous monitoring and control over the quality of outsourced units and stakeholder satisfaction.

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Section: Discussionmentioning

confidence: 58%

Developing decision model for the outsourcing of medical service delivery in the public hospitals

Khosravizadeh

Maleki

Ahadinezhad

et al. 2022

BMC Health Serv Res

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“…Also, one of the solutions that the world economy has achieved to avoid costs is outsourcing [ 42 ]. Because outsourcing helps shift fixed costs to variable costs [ 43 ]. While this strategy has been successful in reducing costs of many organizations, but many believe that applying this strategy to clinical services is associated with risks [ 44 ].…”

Section: Discussionmentioning

confidence: 99%

Cost-benefit analysis of Intensive Care Unit with Activity-Based Costing approach in the era COVID-19 pandemic: A case study from Iran

et al. 2023

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Background Providing intensive care to acute patients is a vital part of health systems. However, the high cost of Intensive Care Units (ICU) has limited their development, especially in low-income countries. Due to the increasing need for intensive care and limited resources, ICU cost management is important. This study aimed to analyze the cost-benefit of ICU during COVID-19 in Tehran, Iran. Methods This cross-sectional study is an economic evaluation of health interventions. The study was conducted in the COVID-19 dedicated ICU, from the provider’s point of view and within one-year horizon. Costs were calculated using a top-down approach and the Activity-Based Costing technique. Benefits were extracted from the hospital’s HIS system. Benefit Cost ratio (BCR) and Net Present Value (NPV) indexes were used for cost-benefit analysis (CBA). A sensitivity analysis was performed to evaluate the dependence of the CBA results on the uncertainties in the cost data. Analysis was performed with Excel and STATA software. Results The studied ICU had 43 personnel, 14 active beds, a 77% bed occupancy rate, and 3959 occupied bed days. The total costs were $2,372,125.46 USD, of which 70.3% were direct costs. The highest direct cost was related to human resources. The total net income was $1,213,314.13 USD. NPV and BCR were obtained as $-1,158,811.32 USD and 0.511 respectively. Conclusion Despite operating with a relatively high capacity, ICU has had high losses during the COVID-19. Proper management and re-planning in the structure of human resources is recommended due to its importance in the hospital economy, provision of resources based on needs assessment, improvement of drugs management, reduction of insurance deductions in order to reduce costs and improve ICU productivity.

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“…Soner et al (2022) assessed several ecological effects of the ship recycling process. Rowshan et al (2020) identified factors for outsourcing in public hospitals. Kumar et al (2022) solved a flowline problem.…”

Section: Studies On Fbwm and Fmarcosmentioning

confidence: 99%

A fuzzy BWM and MARCOS integrated framework with Heronian function for evaluating cryptocurrency exchanges: a case study of Türkiye

Ecer,

Murat,

Dinçer

et al. 2024

Financ Innov

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Crypto assets have become increasingly popular in recent years due to their many advantages, such as low transaction costs and investment opportunities. The performance of crypto exchanges is an essential factor in developing crypto assets. Therefore, it is necessary to take adequate measures regarding the reliability, speed, user-friendliness, regulation, and supervision of crypto exchanges. However, each measure to be taken creates extra costs for businesses. Studies are needed to determine the factors that most affect the performance of crypto exchanges. This study develops an integrated framework, i.e., fuzzy best–worst method with the Heronian function—the fuzzy measurement of alternatives and ranking according to compromise solution with the Heronian function (FBWM’H–FMARCOS’H), to evaluate cryptocurrency exchanges. In this framework, the fuzzy best–worst method (FBWM) is used to decide the criteria’s importance, fuzzy measurement of alternatives and ranking according to compromise solution (FMARCOS) is used to prioritize the alternatives, and the Heronian function is used to aggregate the results. Integrating a modified FBWM and FMARCOS with Heronian functions is particularly appealing for group decision-making under vagueness. Through case studies, some well-known cryptocurrency exchanges operating in Türkiye are assessed based on seven critical factors in the cryptocurrency exchange evaluation process. The main contribution of this study is generating new priority strategies to increase the performance of crypto exchanges with a novel decision-making methodology. “Perception of security,” “reputation,” and “commission rate” are found as the foremost factors in choosing an appropriate cryptocurrency exchange for investment. Further, the best score is achieved by Coinbase, followed by Binance. The solidity and flexibility of the methodology are also supported by sensitivity and comparative analyses. The findings may pave the way for investors to take appropriate actions without incurring high costs.

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Identifying and Prioritizing Effective Factors on Outsourcing in Public Hospitals Using Fuzzy BWM

Cited by 8 publications

References 28 publications

Developing decision model for the outsourcing of medical service delivery in the public hospitals

Developing decision model for the outsourcing of medical service delivery in the public hospitals

Cost-benefit analysis of Intensive Care Unit with Activity-Based Costing approach in the era COVID-19 pandemic: A case study from Iran

A fuzzy BWM and MARCOS integrated framework with Heronian function for evaluating cryptocurrency exchanges: a case study of Türkiye

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