جستجوی مقالات مرتبط با کلیدواژه "healthcare" در نشریات گروه "مدیریت"

With the emergence industry 4.0, many industrial and service sectors have moved towards using it to improve their effectiveness and efficiency. This transformation has been done slowly in Iran's healthcare sector, so it is necessary to identify the factors affecting its acceptance. The requirement to start this movement is to accept it. Considering the existing research gaps, this research has been conducted to identify, model and analyze the scenario of Industry 4.0 acceptance factors in Iran's healthcare supply chain. This research was done in 2 stages with a mixed approach. The first stage with a qualitative approach seeks to identify acceptance factors and the second stage with a quantitative approach seeks to model and analyze their scenarios. The statistical population in both stages are experts in the healthcare supply chain and sampling methods is judgmental and snowball. In the first stage, semi-structured interviews and thematic analysis were used, and in the second stage, a researcher-made questionnaire and fuzzy cognitive map were used. The results of the first stage show 23 acceptance factors, which were classified into 4 categories: "personality factors", "organizational behavior", "organizational hardware" and "management". The results of the second phase indicate that "emotional intelligence", "organizational culture", "social responsibility" and "stakeholders' awareness of I4.0 technologies" are drivers and "organizational openness" is the recipient. The results of the analysis of forward and backward scenarios show the importance of "effective change management", "trust", "stakeholders' awareness of I4.0 technologies", "financial capability" and "optimism towards technology".

The maturity of business intelligence, which is the main goal of this research, plays an important role in intelligent decision-making, planning, control and monitoring in the field of health care. In order to identify the effective factors, the Delphi method was used and experts' opinions were, and in order to determine the effectiveness and effectiveness of the indicators and finally to prioritize them, used the DANP method. The statistical sample includes 20 targeted academic experts and health care experts. According to the results of the Delphi section, 26 main indicators finalized in the research were identified, which are divided into three main categories including organizational, process and judgment criteria. According to the results of the DANP process, flexible and expandable technical infrastructure criteria, data and system quality and the correct definition of business intelligence problems and processes were prioritized as the three criteria with the highest ranking in the maturity of business intelligence. The business intelligence maturity model proposed by the research can be a road map for the successful implementation of business intelligence in the field of health care.

Developing efficient and effective health care systems has become a major concern for governments and health care decision makers. In-time supply of medicine and efficiency of the inventory and distribution system play a vital role in the hospital supply chain and require a proper decision-making process in inventory management. This study suggests a two-objective model of mixed-integer, linear programming to manage medicine and information flow. The main goals of this model are to minimize the costs of purchasing, maintaining, manpower, and medicine expiration, and to minimize medicine shortages. Uncertainty parameters are related to demand, storage, and supply capacity, as well as the aspiration level of each goal. The initial model is first transformed into a fuzzy mixed-integer, goal programming model. Then, the resulting model is transformed into a one-objective model using methods suggested by Torabi and Hassini and solved in GAMS. The supply chain of Shahid Beheshti Hospital in Kashan is used to explain the proposed approach. The results indicate that decisions related to the purchase and logistics of medicine have a great impact on medicine shortages and control various costs relating to medicine inventory in this hospital.

The employee scheduling seeks to find an optimal schedule for employees according to the amount of demand (workload), employee availability, labor law, employment contracts, etc. The importance of this problem in improving the quality of service, health and satisfaction of employees and reducing costs, including in hospitals, military or service centers, has encouraged researchers to study. In this regard, nurse rostering problem is a scheduling that determines the number of nurses required with different skills and the time of their services on the planning horizon. In this research, by adding the nurses' shift preferences and number of consecutive working days constraints, an attempt has been made to make the problem more realistic. The objective function of the problem is to minimize the total cost of allocating work shifts to nurses, the cost of the number of nurses required to reserve, the cost of overtime from a particular shift, the cost of underemployment from a particular shift, the cost of overtime on the planning horizon, the cost of underemployment on the planning horizon and the cost of absence shift-working and non-working days preferred by nurses. To solve problem, after modeling the problem as a mixed-nteger program and due to the complexity of the problem, the differential evolutionary algorithm is used with innovation in its crossover operator. To validate the proposed algorithm, its output was compared with the genetic algorithm. The results show that the differential evolutionary algorithm has good performance in problem-solving. Keywords: Nurse Rostering Problem, Deferential Evolution Algorithm

Risk Adjusted Cumulative Sum (CUSUM) control charts are powerful statistical tools for early detection making of process changes. Unlike other industries, healthcare systems are of a wide range of variability and different levels of inputs. However, since variability in the output of healthcare process may result from different factors including environmental factors, doctor’s performance, or patient specifications; therefore, considering multiple outcomes facilitates and increases precision of the process control. Accordingly, in this paper, risk-adjusted CUSUM control chart with multiple outcomes is applied to monitor kidney transplantation surgery. It is assumed that transplantation surgery might result in full recovery of the patient, rejection of the organ, or after-surgery complications. Finally, the annual report of kidney transplant surgery in the U.K has been used to monitor 1779 surgeries between 2010 and 2011, and the associated CUSUM control charts have been presented.

Although statistical process monitoring methods were initially introduced for early detection of industrial and chemical process changes, soon Shewhart and Deming mentioned various applications of such methods including healthcare process monitoring. Cumulative sum (CUSUM) control charts are useful for rapid identification of tiny changes in process parameters (Montgomery, 2008; Altman & Royston, 1988). In this paper, the focus is on monitoring outputs of kidney transplantation surgery. Existing literature on monitoring surgery outputs indicates binary output as an assumption, i.e. failure or success for the process. However, there are possibly more than two outputs for a surgery. For example, kidney transplant surgery may lead to complete rejection of the kidney, infection or bleeding, deficiency of the organ, and acceptance of the kidney (Rossi et al., 2016). Furthermore, since each of the outputs may have a different origin, assuming multiple outcomes makes it possible to monitor the process more accurately. Therefore, in this paper a risk adjusted CUSUM chart is developed for monitoring kidney transplantation surgery assuming multiple outcomes for the process.

Three outputs are assumed for kidney transplantation surgery including: acceptance of the organ, complications, and full rejection. Then, a risk adjusted CUSUM chart is developed for monitoring surgery outputs based on the transplantation data of 1624 surgeries in U.K between 2008 and 2009 (Mumford & Brown, 2017). Then, the generated chart is used for monitoring 1779 transplant surgeries between 2010 and 2011 in the U.K.
Findings and

Monitoring the results indicated multiple out-of-control results. However, systems came back to the controlled mode. This implied an unstable performance. Overall, 57 signals were received by the chart out of which, 19 signals were due to complications and 38 signals were due to rejection. The 99.5 confidence interval for receiving signal from the process was [0.020, 0.44]. Also, chi square statistic was used to test independence of output levels from time and there was no evidence for the rejection of the null hypothesis at 0.005 significance level.

Monitoring processes with multiple outcomes helps better identification and categorization of the effective factors and better control of the process. In this paper, a risk adjusted CUSUM chart was developed for monitoring kidney transplant surgeries. The developed chart seems to be easily applicable in other healthcare processes.

Healthcare is one of the basic needs of all human beings and none of the people is needless from it. Personal and public health depends on providing appropriate, adequate and quality services. But a significant portion of the potency of the healthcare activists spent on providing health services and policy-making, monitoring and assessment is neglected. This weakness has led to the fact that the health care services is seriously flawed and unable to properly respond to public expectations. By considering the importance of assessment and supervision and aiming to fill this gap, this paper will architecture the healthcare assessment system in Iran. Therefore, after the design of conceptual model of assessment sector and definition of possible roles, we have distributed the roles between activists of this sector. Based on architecture results, it is suggested to set up organizations with public and non-governmental nature to collect and codify the healthcare indicators and also perform the assessment and accreditation of the healthcare production, services and activists.

Necessary of achieve to the objectives of national development is knowledge and advanced technology that only be achieved by doing fudamental, applied and development research. So evaluation and monitoring on the research situations is unavoidable. However, the evaluation and monitoring is done effectively when the proper indicators are developed for the formulation of the policy, judge and decide. This research aims to identify key indicators in health sector researches and compared them with researches in universities and institutions of science, research and technology ministry. This study was based on a survey using descriptive data has been collected.The research method of this paper is descriptive and analytical. Ishikawa Fuzzy Delphi Technique based on opinion of 8 experts is used for this study. Results show that experts have chosen 30 of 74 indicators as critical indicators that should be monitor continusly. Statistics also show differences in selected indicators between Ministry of Health and Medical Education and Ministry of Science and Technology.

Effective personal relationships, combined with knowledge and experience in the fields of health care, provide quality and appropriate services to patients. So this study aimed to analysis the relationship between personal relationships and knowledge storage and how these impacts on hospital service performance in selected hospitals of Tehran. Findings from research using structural equation modeling showed that personal relationships through individual and organizational memory have strong positive and significant effect on the performance of health care services in the hospital. The results also show that personal relationships have not a direct impact on service performance. Performance and quality of health care are important because it deals with human lives. Hospital managers should improve personal relationship of staff align with knowledge creation and sharing to achieve better health care performances.