ORIGINAL_ARTICLE
Forecasting Surgical Outcomes Using a Fuzzy-Based Decision System
Background and objectives: The kidneys of chronic kidney disease (CKD) patients do not have enough function and hemodialysis (HD) is a common procedure for their treatment. HD requires vascular access surgery (VAS) and arteriovenous fistula (AVF) is a low-complication method in VAS. However, different rates of AVF failure have been reported worldwide which can cause repeating surgeries and patient hospitalization. The goal of this study was to provide a system with the ability to predict VAS outcomes to reduce failures of surgeries. Methods: The data of created AVF for 195 CKD patients – consisting 131 males (67.18%) and 64 females (32.82%), and aged from 15 to 87 years - were studied. Our provided system is based on “Fuzzy Inference System” (FIS) and learns rules by extracted results of decision tree algorithm. Results: The number of diabetic patients was 73 and 117 persons had hypertension. Their hemoglobin range was 4.9 to 16. Their systolic blood pressure (BP) and diastolic BP were in the ranges [95-230] and [60-120], respectively. Using provided fuzzy control system, these results were investigated: (i) When the systolic BP increases, the AVF maturation improves (ii) In the young patients, the rate of AVF failure is higher than older patients; (iii) Growing patient from “Young” to “Middle-aged” causes switching from “AVF failure” status to “late Maturation”; (iv) In aged patients, high systolic BP with low diastolic BP, shifts from “late” AVF maturation to better statuses namely “good” and “excellent”. Conclusion: Using FIS can forecast surgery outcomes and thus reduce risk factors of patients. In the present developed fuzzy system, surgeons can configure the risk ranges of patient’s parameters before vascular surgery and configure changeable factors based on estimating postoperative outcomes.
https://ijhr.iums.ac.ir/article_87050_a521a18b8f7cd5343273f7c9be456800.pdf
2018-02-01
1
11
Fuzzy inference system
Data mining
Postoperative Outcomes
Vascular Access Surgery
Mohammad
Rezapour
mrezapour@srbiau.ac.ir
1
PhD Candidate; Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, IR Iran
LEAD_AUTHOR
ORIGINAL_ARTICLE
Investigating the Prevalence of Enteric Opportunistic Parasitic Infections among Cancer Patients of a Teaching Hospital
Background and objectives: Cancer patients treated with chemotherapy and other immunosuppressive drugs are always prone to various infections including opportunistic parasites. Since detection of infections in immunocompromised patients are frequently imperfect and the usual symptoms such as pyrexia are missing or hidden due to leukopenia, the importance of detection of opportunistic parasitic infections is well justified. Therefore, we aimed in this study to investigating the prevalence of enteric opportunistic parasitic infections among cancer patients of a Selected Teaching Hospital Affiliated to Iran University of Medical Sciences. Methods: This descriptive-analytical cross-sectional study was carried out on 150 cancer patients admitted to the oncology ward of a selected teaching hospital affiliated to Iran University of Medical Sciences in Iran from July 2016 to December 2017. Patients for this study were chosen by simple random selection method. Fecal samples from these patients were gathered and intestinal parasites were identified using direct wet mount, formalin-ether, chromotrope 2R staining and acid-fast staining methods. The obtained data from patients were analyzed using ANOVA, t-test and chi-square test. All statistical analyses were carried out through SPSS version 17.0. Results: Among 150 samples investigated with direct wet mount method, 23 were reported positive for parasites with the most frequent parasite being Blastocystis (14%). Investigation of slides stained by hot acid-fast method revealed no cases contaminated by Cryptosporidium spp. or Isospora belli, yet in fecal samples stained with chromotrope 2R method 9 Microsporidia sp. infection cases were reported. Conclusion: It was believed that due to immunosuppressive effect of chemotherapeutic agents, the treated patients are more prone to opportunistic infections. Contrary to this belief our study showed lower prevalence of infections in these patients which could be related to more prophylactic drug use that are antibacterial as well as antiparasitic.
https://ijhr.iums.ac.ir/article_90646_9a8c787f4c7d7b374987913c1de08a8a.pdf
2018-02-01
12
22
Opportunistic parasites
cancer
Chemotherapy
Teaching Hospital
Soudeh
Salehi
soudesalehi567@gmail.com
1
Firoozgar hospital, Iran University of Medical Science, Tehran, Iran
AUTHOR
Taher
Elmi
elmi1364@yahoo.com
2
Department of Parasitology and Mycology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
AUTHOR
Ahmad Reza
Meamar
ahmadrezameamar@yahoo.com
3
School of Medicine, Iran University of Medical Sciences, Tehran, Iran
AUTHOR
Ali
Basi
alibasi@yahoo.com
4
Hematology - Oncology, Iran University of Medical Sciences, Tehran, Iran
AUTHOR
Amirhosein
Mirhosseini
mirhosseini43@yahoo.com
5
Firoozgar hospital, Iran University of Medical Science, Tehran, Iran
AUTHOR
Mehdi
Najm
6
Department of Parasitology and Mycology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
AUTHOR
Hoda
Namdari
7
Microbiology medical laboratory of Firoozgar hospital,Iran University of Medical Sciences, Tehran, Iran.
AUTHOR
Mitra
Ranjbar
mitraranjbar@yahoo.com
8
Department of Infectious Diseases, Iran University of Medical Sciences. Tehran. Iran
LEAD_AUTHOR
ORIGINAL_ARTICLE
Error Management Culture and Its Impact on Hospital Performance: A Case Study in Iran
Background and Objectives: In recent decades medical errors have become a major issue for scientific investigation to avoid potential harmful failures threatening patients’ health and safety. Developing risk management culture has been considered not only to play an important role in detecting and coping effectively with such errors but also lead to high level of organizational performance. This study aimed to examine the impact of risk management culture on the performance of training hospitals affiliated by Yazd University of Medical Sciences (YUMS). Methods: This descriptive analytical study was conducted in three training hospitals affiliated by YUMS. Research sample consisted of 150 nurses working in the hospitals who’ve been selected by proportional randomized sampling method. Data were collected using a standard questionnaire developed by Dyck et al. Collected data were entered in SPSS version 20 and analyzed through descriptive analysis methods (Mean, Standard deviation), and Pearson correlation coefficient. Results: the highest mean score related to error management and performance belonged to hospital A (3.84+0.32, 3.49+0.49). In both hospitals A and B, a significant statistical relationship between error management culture and organizational performance was approved. Conclusion: Study findings suggested that improvement in error management culture would lead to higher level of performance. In fact supportive culture in error management could be translated to high organizational performance through decreasing negative error consequences.
https://ijhr.iums.ac.ir/article_90651_fc5aab5cd7dce2f0dd1155a8af7c10e0.pdf
2018-02-01
23
35
Error management culture
Hospital Performance
Nurse
Teaching Hospital
Mohammad
Ranjbar
ranjbar3079@gmail.com
1
School of Public health, Yazd University of Medical Sciences
AUTHOR
Ameneh
Khosravi
m.khosravi@yahoo.com
2
Health Policy and Management Research Center, School of Public Health, Shahid Saoughi University of Medical Sciences, Yazd, Iran
AUTHOR
Mohammad amin
Bahrami
aminbahrami1359@gmail.com
3
Mirzasadeghi A. Performance-based management. Tehran: Ministry of Health and Medical Education; 2001. 50 p.
AUTHOR
Sima
Rafiei
sima.rafie@gmail.com
4
Department of Health Management, School of Health, Qazvin University of Medical Sciences, Qazvin, Iran
LEAD_AUTHOR
ORIGINAL_ARTICLE
Providing a model based on Recommender systems for hospital services (Case: Shariati Hospital of Tehran)
Background and objectives: In the increasingly competitive market of the healthcare industry, the organizations providing health care services are highly in need of systems that will enable them to meet their clients' needs in order to achieve a high degree of patient satisfaction. To this end, health managers need to identify the factors affecting patient satisfaction focus. The purpose of this study is to provide a model based on recommender systems in order to increase patient satisfaction with the quality of hospital services, in which patients were clustered based on personal information and then dimensions of services were weighted to determine the most important dimensions. Methods: Information technology can provide the possibility of moving towards better services by analyzing customer preferences and tailoring the content and process of service provision according to customer needs. On the other hand, the personalization of products and services is one of the most important factors affecting customer satisfaction. Findings: In order to conduct the model, the data related to satisfaction forms of 556 discharged patients from Shariati Hospital in Tehran was used. By estimating the accuracy of the predictions of the model based on the mean absolute error criterion and the mean squared error, the values were respectively obtained as 40% and 49%. Conclusions: In this study, through weighting the characteristic for different groups of patients, the more important services were identified where considering the number of 148 test data, it was determined that the model of the most important dimensions of the service for each cluster are correctly determined. Therefore, the hospital can decrease dissatisfaction of the new patients in each group through reinforcing the important services in each group, after discharge.
https://ijhr.iums.ac.ir/article_90863_6fae220e5f63dd22792bce488291850e.pdf
2018-02-01
36
56
Patient Satisfaction
Service Quality
Personalization
Recommender systems
Clustering
Feature Weighing
Mehrdad
Kargari
m_kargari@modares.ac.ir
1
Faculty of Systems and Industrial Engineering , Tarbiat Modares University, Tehran, Iran
LEAD_AUTHOR
Kobra
Akbari
kobra_k7108a22@yahoo.com
2
Faculty of Systems and Industrial Engineering , Tarbiat Modares University, Tehran, Iran
AUTHOR
ORIGINAL_ARTICLE
The effect of Health System Evolution Plan on the performance indices in public hospitals in Iran
Background and Objectives: The Health System Evolution Plan was developed to improve quality and accessibility of health care services and reduce the costs to protect people from catastrophic out of pocket payments. The aim of current study is investigatation of Health System Evolution Plan effects on performance indices of governmental hospitals affiliated to Iran University of Medical Sciences, in Iran.Methods: This was a descriptive analytic study with retrospective approach based on extracted data from 16 hospitals of Iran University of Medical Sciences in Iran. Specific indices comprising income and expenses, paraclinical evaluations, bed performance indices and reform instructional indices were collected in 5 categories before (April , 2013) and after(May ,2014 to March, 2016 ) implementation of Health System Evolution Plan. Data were analyzed with SPSS software version 22, using paired t-test and Pearson’s correlation coefficient.Results: After implementation of Health System Evolution Plan, indices of bed turnover rate, bed occupancy percentage, average active bed, number of emergency patients, the average length of stay of the patient, percentage of normal delivery, cash income, cost of consumables and equipment, percentage of armed forces insurance deductibles and percentage of social security insurance deductibles increased.Conclusion: The Health System Evolution Plan imposed high economic burden on insurance companies due to increased tariffs with no plan to control them; however, it has improved utilization and accessibility of services. It is necessary to supply consistant financial resources and apply effective supervising on continous performance of project to meet the objectives.
https://ijhr.iums.ac.ir/article_90820_391c590ff1d2c271cbff44e326bbbf51.pdf
2018-02-01
57
81
Health System Evolution Plan (HSEP)
health system
Performance Indicators
public hospitals
esmaeil
mohammadi yazani
esmaeilmohammadi92@gmail.com
1
Gastroenterology and Liver Disease Research Center, Firoozgar Hospital, Iran University of Medical Sciences, Tehran, Iran
LEAD_AUTHOR
Behrooz
Ghanbari
g.behrooz@gmail.com
2
Research Center for Gastroenterology and Liver Diseases, Firoozgar Hospital, Iran University of Medical Sciences, Tehran, Iran.
AUTHOR
Maryam
Biglari Abhari
dr.maryam54@gmail.com
3
Clinical Research Development Center of Firoozgar Hospital, Iran University of Medical Sciences, Tehran, Iran.
AUTHOR
ORIGINAL_ARTICLE
Selection of Sustainable Supplier for Medical Centers with Data Envelopment Analysis (DEA) & Multi-Attributed Utility Theory (MAUT) Approaches
Background and Objectives: The selection of the sustainable supplier is important for any industry. Medical centers are not an exception in this case, and selecting the best sustainable supplier is a major step towards increasing their productivity. This paper, using the Data Envelopment Analysis and then using Multi-Attributed Utility Theory as a backup approach to fix errors, attempts to introduce the most important criteria and sub criteria for selecting the best sustainable supplier of medical equipment among domestic and foreign suppliers.Methods: After reviewing the previous papers, the 13 most important sub-criteria are extracted based on the 3 social, environmental and economic criteria. At first a Data Envelopment Analysis (DEA) model is used to find the initial ranking for sustainable suppliers. Then the Multi-Attributed Utility Theory (MAUT) is employed as a secondary and backup approach to find the utility function. The data obtained are first examined in DEA and then by MAUT and the results are presented in the form of figures, tables and analytical results in the relevant section.Findings: Based on the 13 sub-criteria introduced at the end of the two-stage ranking, supplier C is selected as the best sustainable supplier.Conclusion: For initial ranking, DEA is a good method, but to find the utility function of the ranking, the use of MAUT is an effective method with a high degree of proximity.
https://ijhr.iums.ac.ir/article_91548_005b3164fbead14e352427496137cd6d.pdf
2018-08-01
82
96
Sustainable supplier selection
Multiple Criteria Decision Making
Data Envelopment Analysis
Multi-Attributed Utility Theory
Ali
Rezahoseini
ali_rezahoseini@ind.iust.ac.ir
1
Department of industrial engineering, Iran University of science and technology, Tehran, Iran
AUTHOR
Seyed Farid
Ghannadpour
ghannadpour@iust.ac.ir
2
Department of industrial engineering, Iran University of science and technology, Tehran, Iran
AUTHOR
Elmira
Ahmadi
e_ahmadi@du.ac.ir
3
School of Industrial Engineering, Damghan University, Damghan, Iran
AUTHOR
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5. Memari, A., et al. Scenario-based simulation in production-distribution network under demand uncertainty using ARENA. in 2012 7th International Conference on Computing and Convergence Technology (ICCCT). 2012. IEEE.
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6. Goh, M., Z. Shuya, and R. de Souza. Operational Framework for Healthcare Supplier Selection Under a Fuzzy Multi-Criteria Environment. in 23rd International Symposium on Logistics (ISL 2018) Big Data Enabled Supply Chain Innovations. 2018.
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16. Torkzad, A. and M.A. Beheshtinia, Evaluating and prioritizing hospital service quality. International journal of health care quality assurance, 2019. 32(2): p. 332-346.
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20. Samani, M.R.G. and S.-M. Hosseini-Motlagh, An enhanced procedure for managing blood supply chain under disruptions and uncertainties. Annals of Operations Research, 2018: p. 1-50.
20
21. Asadi, R., F. Semnani, and P. Shadpour, Factors Influencing Prioritization of Hospital Services for Outsourcing: A Fuzzy Analytic Hierarchy Process Ranking Model. International Journal of Hospital Research, 2017. 6(2): p. 97-103.
21
22. Asadi, R. and P. Shadpour, Designing the Hybrid Model of Balanced Scorecard and Analysis of Hierarchical Process for Evaluation of the Outsourced Services Suppliers in Supply Chain of Teaching Hospital. International Journal of Hospital Research, 2017. 6(4): p. 49-62.
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23. Bhattacharya, A., J. Geraghty, and P. Young, Supplier selection paradigm: An integrated hierarchical QFD methodology under multiple-criteria environment. Applied Soft Computing, 2010. 10(4): p. 1013-1027.
23
24. Gold, S. and A. Awasthi, Sustainable global supplier selection extended towards sustainability risks from (1+ n) th tier suppliers using fuzzy AHP based approach. Ifac-Papersonline, 2015. 48(3): p. 966-971.
24
25. Beheshtinia, M. and V. Nemati-Abozar, A Novel Hybrid Fuzzy Multi-Criteria Decision-Making Model for Supplier Selection Problem (A Case Study in Advertising industry). Journal of Industrial and Systems Engineering, 2017. 9(4): p. 65-79.
25
26. Beheshtinia, M.A. and M. Ahangareian Abhari, A New Hybrid Decision Making Method for Selecting Roller Concrete Road Pavement Technology Transfer Method. International Journal of Transportation Engineering, 2018. 5(3): p. 229-242.
26
27. Sanayei, A., S.F. Mousavi, and A. Yazdankhah, Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Systems with Applications, 2010. 37(1): p. 24-30.
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28. Chang, T.-H., Fuzzy VIKOR method: a case study of the hospital service evaluation in Taiwan. Information Sciences, 2014. 271: p. 196-212.
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29. Hamid, M., et al., Operating room scheduling by considering the decision-making styles of surgical team members: a comprehensive approach. Computers & Operations Research, 2019. 108: p. 166-181.
29
30. Gul, M., et al., Emergency department performance evaluation by an integrated simulation and interval type-2 fuzzy MCDM-based scenario analysis. European Journal of Industrial Engineering, 2016. 10(2): p. 196-223.
30
31. Beheshtinia, M.A. and S. Omidi, A hybrid MCDM approach for performance evaluation in the banking industry. Kybernetes, 2017. 46(8): p. 1386-1407.
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33. Braglia, M. and A. Petroni, A quality assurance-oriented methodology for handling trade-offs in supplier selection. International Journal of Physical Distribution & Logistics Management, 2000. 30(2): p. 96-112.
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34. Shafaghat, T., et al., Efficiency Determination of Hospitals of Shiraz University of Medical Sciences using Simple and Super Efficiency DEA Models. International Journal of Hospital Research, 2017. 6(3): p. 55-68.
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35. Al-Refaie, A., et al., Applying simulation and DEA to improve performance of emergency department in a Jordanian hospital. Simulation Modelling Practice and Theory, 2014. 41: p. 59-72.
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36. Tseng, F.-M., Y.-J. Chiu, and J.-S. Chen, Measuring business performance in the high-tech manufacturing industry: A case study of Taiwan's large-sized TFT-LCD panel companies. Omega, 2009. 37(3): p. 686-697.
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38. Fallahpour, A., et al., An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach. Neural Computing and Applications, 2016. 27(3): p. 707-725.
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42. Ghayebloo, S., et al., Developing a bi-objective model of the closed-loop supply chain network with green supplier selection and disassembly of products: the impact of parts reliability and product greenness on the recovery network. Journal of Manufacturing Systems, 2015. 36: p. 76-86.
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51
ORIGINAL_ARTICLE
A New Fuzzy AHP- Fuzzy VIKOR Approach in Control and Management of The Angiography Procedure to Prevent Disruptions: A Case Study
Background and objectives - A hybrid MCDM approach is presented to evaluate and prioritize the disruptions in the angiography process, in a fuzzy environment. The proposed approach is applied to a real case in a public hospital.Methods – In this study, a new approach is utilized based on fuzzy MCDM methods. The disruptions are identified using the experts' opinions. Then, the FMEA risk factors are compared in pairs and given weights by experts, using fuzzy AHP. The Experts were then asked to rate the disruptions according to the risk factors. Finally, the disruptions were ranked using Fuzzy VIKOR.Results and Conclusion - Results show that the risk factor occurrence has the most importance among the three risk factors. They also suggest that the top three disruptions in the angiography process are ‘absence of manual’ and ‘guideline on angiography procedure’, ‘inadequate training of personnel and exhaustion’, respectively.Practical implications - Results of this study may be may help hospital managers and practitioners avoid disruptions in the process and the improve healthcare service quality.Originality/value - The recent studies in the related literature were thoroughly investigated and it was found that no studies considered the disruptions identification and analysis in the angiography process. Therefore, the disruptions in the angiography process are investigated for the first time. Moreover, the efficiency and applicability of the proposed method and the rankings are validated by the experts.
https://ijhr.iums.ac.ir/article_91549_0898668ef6b630a4100841cb42d3997a.pdf
2018-08-01
97
108
MCDM
FMEA
fuzzy AHP
Fuzzy VIKOR
Angiography
Healthcare system
Mahziar
Rezvani
m.rezvani@semnan.ac.ir
1
Industral engineering department, Semnan university, Semnan, Iran
AUTHOR
Mohammadali
Beheshtinia
beheshtinia@semnan.ac.ir
2
Industrial engineering department, Semnan university,Semnan, Iran
AUTHOR
Mohammad
Forozeshfard
mff45@yahoo.com
3
Cancer Research Center, Anesthesiology Department, Semnan University of Medical Sciences
AUTHOR
Yaghoubi, A., et al., Quality of Life in Cardiovascular Patients in Iran and Factors Affecting It: A Systematic Review. Journal of cardiovascular and thoracic research, 2012. 4(4): p. 95-101.
1
2. Moradi, B., et al., Factors Associated With Failure to Complete Phase II Cardiac Rehabilitation: Survey Registry in Rajaie Cardiovascular Medical and Research Center. Int Cardiovasc Res J, 2011. 5(4): p. 139-142.
2
3. Jamshidi, A., et al., A comprehensive fuzzy risk-based maintenance framework for prioritization of medical devices. Applied Soft Computing, 2015. 32: p. 322-334.
3
4. Raghavan, V., et al., Reengineering the Cardiac Catheterization Lab Processes: A Lean Approach. Journal of Healthcare Engineering, 2010. 1(1).
4
5. Gupta, U., et al., Failure Mode Effect Analysis in Healthcare - Preventing An Error before any Harm is Done. Apollo Medicine, 2004. 1(1): p. 64-68.
5
6. Beheshtinia, M.A. and S. Omidi, A hybrid MCDM approach for performance evaluation in the banking industry. Kybernetes, 2017. 46(8): p. 1386-1407.
6
7. Sedady, F. and M.A. Beheshtinia, A novel MCDM model for prioritizing the renewable power plants’ construction. Management of Environmental Quality: An International Journal, 2019. 30(2): p. 383-399.
7
8. Beheshtinia, M. and V. Nemati-Abozar, A Novel Hybrid Fuzzy Multi-Criteria Decision-Making Model for Supplier Selection Problem (A Case Study in Advertising industry). Journal of Industrial and Systems Engineering, 2017. 9(4): p. 65-79.
8
9. Rezaee, M.S., A. Haeri, and S. Noori, Using data envelopment analysis to evaluate the performances of food production companies based on EFQM's criteria and to present an improvement plan. International Journal of Business Excellence, 2018. 14(2): p. 256-274.
9
10. Haeri, A. and K. Rezaie, Using data envelopment analysis to investigate the efficiency of resource utilisation and to develop an improvement plan. International Journal of Productivity and Quality Management, 2014. 13(1): p. 39-66.
10
11. Haeri, A., K. Rezaie, and M.-S. Amalnick, Developing a novel approach to assess the efficiency of resource utilisation in organisations: a case study for an automotive supplier. International Journal of Production Research, 2014. 52(10): p. 2815-2833.
11
12. Shafii, M., et al., Performance analysis of hospital managers using fuzzy AHP and fuzzy TOPSIS: Iranian Experience. Global journal of health science, 2016. 8(2): p. 137.
12
13. Chang, T.-H., Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Information Sciences, 2014. 271: p. 196-212.
13
14. Chanamool, N. and T. Naenna, Fuzzy FMEA application to improve decision-making process in an emergency department. Applied Soft Computing, 2016. 43: p. 441-453.
14
15. Liu, H.-C., et al., Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 2012. 39(17): p. 12926-12934.
15
16. Liu, H.-C., et al., A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method. Applied Soft Computing, 2015. 28: p. 579-588.
16
17. Torkzad, A. and M.A. Beheshtinia, Evaluating and prioritizing hospital service quality. International Journal of Health Care Quality Assurance, 2019. 32(2): p. 332-346.
17
18. Al-Hakim, L., Surgical disruption: information quality perspective. International Journal of Information Quality, 2008. 2(2): p. 192-204.
18
19. Abuzeid, W., et al., Radiation safety in the cardiac catheterization lab: A time series quality improvement initiative. Cardiovascular Revascularization Medicine, 2017. 18(5, Supplement 1): p. S22-S26.
19
20. Jayakar, J.P. and D.A. Alter, Music for anxiety reduction in patients undergoing cardiac catheterization: A systematic review and meta-analysis of randomized controlled trials. Complementary Therapies in Clinical Practice, 2017. 28: p. 122-130.
20
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ORIGINAL_ARTICLE
Increasing Operating Room Profits and Decreasing Wait Lists by Use of a Data-Driven Overbooking Model
Background and Objectives: Operating rooms (ORs) are precious resources in hospitals, as they constitute more than 40% of the hospital revenues.As such, surgical cancellations are very costly to hospitals. Same-day surgery cancellations or no-shows were found to be the main contributing factor to underutilization of operating rooms (ORs) in a public-sector hospital despite the existence of long surgical wait lists. Method: To demonstrate the feasibility of overbooking surgical procedures, a Monte-Carlo simulation model to predict unused OR time was built and validated using six months of historical data. We first fitted statistical distributions to the random parameters, using Easyfit©software. Then, a surgical case-mix optimization problem was formulated to prescribe the surgeries for overbooking that maximize the profits over the predicted unused OR time. The optimization model was solved both deterministically based on average historical surgery durations using Lingo Software Package and heuristically by taking into account the random nature of surgical durations using Risk Solver Platform© add-on to Microsoft Excel. Findings: We conducted simulation-optimization of the stochastic model for the three selected date. Results show significant improvements over the base case of no overbooking. The increases in the average surgical profits due to overbooking on three randomly selected dates were 89%, 36%, 93%. Conclusions: To the best of our knowledge, this study is the first applied demonstration of descriptive, predictive, and prescriptive analytics to improve surgical operations through overbooking. The analysis shows significant opportunities in generating surgical profits (36%-93% on randomly selected validation dates) and reducing average wait times (by 4.16 weeks) without risking OR overtime.
https://ijhr.iums.ac.ir/article_87072_e578d4aed938363df6d217ff0e598166.pdf
2018-02-01
109
129
Case-Mix problem
No-shows
Surgical Overbooking
Monte Carlo simulation
Wait Times
Hajar
Sadeghzadeh
sadaf.sadeghzadeh1389@gmail.com
1
Health systems engineering, Faculty of Industrial and Systems Engineering, Tarbiat modares university, Tehran, Iran.
AUTHOR
Somayeh
Sadat
somayeh.sadat@alumni.utoronto.ca
2
Health systems engineering, Faculty of Industrial and Systems Engineering, Tarbiat modares university, Tehran, Iran.
LEAD_AUTHOR
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