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Identifying Improvement Projects Based on Energy Consumption Management in Hospital and Prioritizing Them Using Fuzzy Analytic Hierarchy Process (FAHP)
Dr Bakhtiar Ostadi, Ms Asrin Navidi,
Volume 15, Issue 2 (6-2016)
Abstract

Background: Since, energy consumption per square meter in hospitals is much higher than other types of service institutions; in this study, some actions performed toward optimizing energy consumption improvement projects based on the definition and prioritization in hospital.

Materials and Methods: The necessity of optimizing energy consumption in hospitals were described according to some scales including the average consumption and cost of water, electricity and gas for bed days and active bed, and these indices calculated in the case. Then, improvement actions were identified using energy audit, interviews with hospital experts and conducted studies in hospitals. Next, projects with high importance were extracted regarding to impact on energy consumption indices, expert opinion, aggregation, feasibility, and limitations such as prerequisite, synchronicity and post-requisite. Finally, specific criteria were identified in three dimensions, i.e., factors affecting the level of energy consumption, trying to execute project and risk and the projects were prioritized using questionnaire and FAHP.

Results: The study results revealed that energy consumption was higher than the world standards in the studied hospital; this confirmed the necessity of optimizing energy consumption and using energy management systems. The results of prioritization also showed the first four priorities.

Conclusion: It seems necessary to save energy consumption through improvement projects implementation in the hospitals. Regarding the number and resources limitation, hospitals can choose to implement some low risk and payback period projects based on existing priority and budget annually.


A Developed Method for Handling Uncertainty in Activity - Based Costing for Hospital Services Using Fuzzy Approach
Dr Bakhtiar Ostadi, Reza Mokhtarian Daloie, Dr Mohamad Mahdi Sepehri,
Volume 17, Issue 4 (2-2019)
Abstract
Background: Today, hospitals have faced many requests for quality services, while their costs are increasingly growing as well. These facts; Therefore, necessitate much more attention from hospital mangers in order to reduce healthcare costs. Moreover, the urgent need for a precise costing approach is more evident. Activity-based costing provides useful information on the activities required to achieve services with desirable quality. However, given that the basic information for ABC system is provided under conditions of certainty, the possibility of using this approach in terms of uncertainty would be greatly decreased. This study aims to propose a new framework called FL-ABC.
Materials and Methods: Since, costing processes environment happen under conditions of uncertainty in the hospital, fuzzy logic in the ABC model was used in order to make more accurate estimates of hospital costs and increase the reliability of the results.
Results: This proposed model was used in a hospital lab unit and the results were compared with the standard ABC system. The results showed that the maximum difference in the prescribed costs was 77708951.89 and 67508112.57 IRR in serology and parasitology tests, respectively, mostly due to uncertainty in the assigned costs to each activity.
Conclusion: The FL-ABC system, in terms of taking into account the uncertainty in the parameters of cost, provides more accurate estimates of the cost of activities under conditions of uncertainty which estimates the costs of health care services more accurately.

Developing a Model for Dynamic Schedule of Heart Surgery based on Patient's Maximum Delay
Iman Dehghan, Dr Bakhtiar Ostadi, Dr Saeid Hosseini,
Volume 17, Issue 4 (2-2019)
Abstract
Background: The operating rooms in each health center are one of the most sensitive units in the center, whereas scheduling and scheduling operations are in particular importance and their optimization has a significant effect on the optimization of the whole complex. The scheduling of heart surgery in addition to the limitations of manpower, time, and facilities includes the limitation of the patient's surgical deadline, which is the purpose of the surgical scheduling given this parameter.
Materials and Methods: In this quantitative study, an algorithm containing 3 + 1 function was proposed. This algorithm also addresses uncertainty while monitoring the limitations of available resources and the maximum delay for surgery. In this study, patients categorize to emergency and non-emergency patients which only the scheduling of non-emergency patients is considered. In this study 343 patient was studied.
Results: Based on a six-month period information reviewing from Shahid Rajaie Cardiovascular Center in Tehran, a 11% improvement has been made in respecting the maximum delay for the patient's referral process. The optimization rate is often related to the difference in patient selection based on their deadline for surgery, which in the present algorithm has been a major contributor to the denial of service patients. Another advantage of the proposed algorithm is the dynamic process of the algorithm and appropriate response to the changes.
 Conclusion: The longer the length of the queue, the lower the chance of accepting non-emergency patients with the shorter maximum delays.
Appointment process of open-heart surgery in Shahid Rajaei Heart Hospital using a discrete event simulation approach
Bahare Rahmani Manshadi, Bakhtiar Ostadi, Amirhosein Jalali,
Volume 20, Issue 2 (9-2021)
Abstract
Background: The waiting list is a list of selected patients in the surgical queue. If demand exceeds capacity, the waiting list grows rapidly, which may lead to unacceptable waiting for patients, especially those in need of acute medical care. Patients waiting for heart surgery are placed on the waiting list for surgery, and sometimes the waiting time is longer than patients expect. Reducing the waiting time for medical services, including heart surgery, is one of the challenges of the health system. In this regard, the present study was performed by identifying an effective solution to reduce the queue length of patients undergoing cardiac surgery.
 
Materials and Methods: In this article, the process of scheduling open heart surgery at Shahid Rajaei Hospital was reviewed and improved with a discrete event simulation approach in Arena simulation software. After designing the process, the existing bottlenecks leading to the long waiting time of the patients were identified. The waiting time and the number of patients visited were determined as the objective function and the patient flow was improved by presenting improvement scenarios and selecting the best scenario.
 
Results: Simulation results on 66 selected patients in 7 months from October 2020 to May 27, 2021 show that Scenario number 10 has the most improvement in performance criteria but is not applicable in practice. Therefore, due to system limitations, Scenario 2 was selected as the best scenario. Implementing Scenario 2 could reduce the waiting time by 40 percent and increase the number of patients visited by 21 percent.
 
Conclusion: Patient prioritization methods allow patients with higher needs to receive more services than those with lower urgent needs, although they also have longer waiting times for patients with lower urgent needs.
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