Readmission Risk Factors in Patients of General Surgery Wards in Shiraz Hospitals: Applying LACE Index as a Predictive Indicator

Background: Today, the effective use of limited health care resources is increasingly regarded. Reduction of the readmission is one of the key tools can improve health outcomes and considered as one of the control levers that reduces health costs. Identifying the causes of readmission to the hospital helps to utilize hospital beds and facilities a more efficiently.Methods: This case-control study had been conducted in general surgery (GS) wards in 2011-2012. Using chisquare test, t-test, and multiple regressions, we studied risk factors associated with readmission in both groups of case and control. Finally, the predictive power of the Length of stay, Acuity of illness, Co morbidity of the patient, Emergency (LACE) index was evaluated using receiver operating characteristic (ROC) curve.Results: About 20% of patients in GS wards were admitted within 30 days. There is a significant difference between the two groups in the following variables: age, sex, length of hospital stay, marital status, discharge season, congestive heart failure, diabetes and renal failure. The rate of readmission with LACE index which is compared with the ROC curve shows that it is significant (P < 0.001 and Kappa = 0.22).Conclusions: Awareness of the prevalence and risk factors of readmission is effective in planning and decision making for using hospital facilities efficiently. Identifying patients at risk of readmission and erforming training plan, ischarging and following up medical programs can reduce the rate of readmission and costs of hospital. Predicting readmission can be very effective but identifying an effective index is very difficult

The Relationship Between Strategic Thinking and Hospital Managers’ Productivity in Teaching Hospitals of Shiraz

Background: Using different methods of strategic thinking is essential for organizations such as hospitals; without them, many organizations will not survive. The aim of the present study is to evaluate the relationship between strategic thinking and management productivity in teaching hospitals of Shiraz. Objectives: Because of the importance of strategic management in organizational productivity, the present study is conducted with the goal of assessing the relationship between strategic thinking and hospital managers’ productivity. Patients and Methods: This descriptive-correlational study was conducted in 2015. The statistical population included all managers in different levels in the teaching hospitals of Shiraz (170 persons). Among these, 119 participants were selected through Cochran’s formula and a simple random sampling method. Data were collected by a questionnaire addressing strategic thinking based on Liedtka’s model and Hersey and Blanchard’s theory. Its validity was verified by a panel of experts and its reliability was measured in previous studies. Data analysis was performed in SPSS version 20 using descriptive and analytic statistics (analysis of variance (ANOVA), Pearson’s correlation test and t-test). Results: The average and Standard Deviation of strategic thinking managers was (2.2 ± 0.04), and productivity of management (2.32 ± 0.37) was estimated on the average level. There was a direct meaningful relationship between strategically thinking managers and productivity (r = 0.387, P < 0.001). The results also showed that there is a meaningful correlation between strategic thinking and sustainability, organizational support and understanding of the job. Conclusions: Due to the correlation between strategic thinking and productivity, we recommend educating and training managers in the use of strategic thinking, and that they understand its importance to productivity. Managers should understand that increasing efficiency in a competitive environment today is a necessity for survival

The financial cost of preventive and curative programs for breast cancer: a case study of women in Shiraz-Iran

Background: This cross-sectional study was conducted to compare the average costs of breast cancer screening and treatment among women with the age of 25 and over in Shiraz-Iran. Methods: Three majors hospitals affiliated with Shiraz University of Medical Sciences (SUMS) were selected for data collection. Financial documents and interviews with the hospitals’ financial officers were used for data collection. Results: Finding shows that the total cost of screening would be 5,847,544.96 US dollars for age groups of 25–34 and 35 and above, demonstrating the huge expense of screening programs. On the other hand, the average cost of breast cancer treatment for each patient would be 3608.47, 996.89, and 311.47 US dollars for mastectomy, radiotherapy, and chemotherapy, respectively. In addition, the total average cost for treatment of 2217 patients would be 1,466,988.9 US dollars, which is much less than screening programs expenses. Conclusion: It is concluded that although screening can be effective for improving quality of life and treatment effectiveness, considering the high costs of screening, it is not economical in Iran. Screening methods within suitable intervals, and also considering patients’ medical history have been recommended by the present study

Factors affecting the technical efficiency of health systems: A case study of Economic Cooperation Organization (ECO) countries (2004–10)

Background: Improving efficiency of health sector is of particular importance in all countries. To reach this end, it is paramount to measure the efficiency. On the other hand, there are many factors that affect the efficiency of health systems. This study aimed to measure the Technical Efficiency (TE) of health systems in Economic Cooperation Organization (ECO) countries during 2004–10 and to determine the factors affecting their TE. Methods: This was a descriptive-analytical and panel study. The required data were gathered using library and field studies, available statistics and international websites through completing data collection forms. In this study, the TE of health systems in 10 ECO countries was measured using their available data and Data Envelopment Analysis (DEA) through two approaches. The first approach used GDP per capita, education and smoking as its inputs and life expectancy and infant mortality rates as the outputs. The second approach, also, used the health expenditures per capita, the number of physicians per thousand people, and the number of hospital beds per thousand people as its inputs and life expectancy and under-5 mortality rates as the outputs. Then, the factors affecting the TE of health systems were determined using the panel data logit model. Excel 2010, Win4Deap 1.1.2 and Stata 11.0 were used to analyze the collected data. Results: According to the first approach, the mean TE of health systems was 0.497 and based on the second one it was 0.563. Turkey and Turkmenistan had, respectively, the highest and lowest mean of efficiency. Also, the results of panel data logit model showed that only GDP per capita and health expenditures per capita had significant relationships with the TE of health systems. Conclusion: In order to maximize the TE of health systems, health policy-makers should pay special attention to the proper use of healthcare resources according to the people’s needs, the appropriate management of the health system resources, allocating adequate budgets to the health sector, establishing an appropriate referral system to provide better public access to health services according to their income and needs, among many others

Addressing Health Insurance Deductions through an Interventional Study: the Case of a Large Central Hospital

Objective: A large proportion of hospitals’ private income is provided by insurance organisations. Hospitals in Iran face various problems in terms of insurance deductions from insurance organisations resulting from inefficient performance by both the hospitals and the insurers. These problems necessitate more specific cost control in this area. This research assesses the causes of insurance deductions by using the Failure Mode Effects Analysis (FMEA) technique, and addresses the issues resulting in deductions by providing some interventions through the Pareto technique. Design: The 10-step pattern of FMEA was implemented for assessing the main causes of insurance deduction in this study. Setting: Data was collected from deduced amounts by three main/largest contracting party insurance organisations (e.g. the Social Security Insurance Organisation, Medical Services Insurance Organisation and Armed Forces Medical Services Insurance Organisation of Namazi Hospital, a large healthcare provider in the South of Iran, in 2014. Findings: Sixty-five potential failure causes were identified, of which 26 were related to the anaesthesia unit, 23 were related to the surgery room unit and 16 were related to the hospitalisation unit. Deductions in the anaesthesia and hospitalisation units and the surgery room were reduced after intervention programs by 14.42%, 57.76%, and 51.52%, respectively. Conclusions: Using the FMEA technique in a large healthcare provider in Iran resulted in identifying the main causes of insurance deductions and provided intervention programs in order to increase the efficiency and productivity of healthcare services. Abbreviations: FMEA – Failure Mode Effects Analysis; RPN – Risk Priority Number

Factors Affecting Resistance to Change among Hospital Staff using a Structural Equation Modeling Technique

Introduction: Hospitals are complex organizations faced with continuous fundamental changes complicated by expertise diversity. The aim of this study was to investigate the factors influencing hospital employees’ resistance to change. Methods: This cross-sectional study included 510 employees working in hospitals affiliated to Shiraz University of Medical Sciences; they were selected using stratified random sampling. Data were collected through a questionnaire. A structural equation modeling technique using LISREL Version 8.8 tested the hypotheses and conceptual model. Results: Results indicated that dispositional resistance to change and involvement with change directly affected the employees’ resistance to change. Perceived benefits of change to involvement in change were significant (T-values >1.96) and the hypotheses related to these paths were accepted. Perceived benefits of change indirectly affected the employees’ resistance to change by influencing involvement. Dispositional resistance to change and involvement in change (mediator variables) were estimated 0.89, 0.03, and 0.47, respectively. Conclusion: The study results indicated that hospital managers should encourage the employees to actively participate in their change program by strengthening perception of the benefits. This could help reduce the employees’ resistance

Localization of the Knowledge Workers’ Productivity Questionnaire and Evaluation of the Productivity of Knowledge Workers of the Central Field of Shiraz University of Medical Sciences

Introduction: Human resources impose a vast expense on health organizations. Therefore, improvement of the productivity of human resources is of considerable concern to executive managers of every country. Methods: In the present study, first, the knowledge workers’ productivity assessment questionnaire was localized. Then, the knowledge workers of the central field of Shiraz University of Medical Sciences were investigated regarding productivity and affecting factors thereof. Results: In this analytic and cross-sectional study, the questionnaire designed by Antikainen et al, was used as the pattern. 300 knowledge workers of the central field of this University were selected through the stratified random sampling in June 2011. Moreover, the data were analyzed through factor analysis, and etc. Conclusion: Factor analysis led to the identification of eight main components of the knowledge workers’ productivity. The reliability of the new version of the questionnaire was confirmed by the Cronbach’s alpha coefficient of 0.945. Additionally, in this sample, productivity level of 19.3% of employees was low and 80.7% was favorable. In this regard, attempts must be made in order to improve the productivity

The Financial Cost of Preventive and Curative Programs for Breast Cancer: A Case Study of Women in Shiraz-Iran

Background: This cross-sectional study was conducted to compare the average costs of breast cancer screening and treatment among women with the age of 25 and over in Shiraz-Iran. Methods:Three majors hospitals affiliated with Shiraz University of Medical Sciences (SUMS) were selected for data collection. Financial documents and interviews with the hospitals’ financial officers were used for data collection. Results:Finding shows that the total cost of screening would be 5,847,544.96 US dollars for age groups of 25–34 and 35 and above, demonstrating the huge expense of screening programs. On the other hand, the average cost of breast cancer treatment for each patient would be 3608.47, 996.89, and 311.47 US dollars for mastectomy, radiotherapy, and chemotherapy, respectively. In addition, the total average cost for treatment of 2217 patients would be 1,466,988.9 US dollars, which is much less than screening programs expenses. Conclusion:It is concluded that although screening can be effective for improving quality of life and treatment effectiveness, considering the high costs of screening, it is not economical in Iran. Screening methods within suitable intervals, and also considering patients’ medical history have been recommended by the present study

Factors Affecting the Technical Efficiency of Health Systems: A Case Study of Economic Cooperation Organization (ECO) Countries (2004–10)

Background: Improving efficiency of health sector is of particular importance in all countries. To reach this end, it is paramount to measure the efficiency. On the other hand, there are many factors that affect the efficiency of health systems. This study aimed to measure the Technical Efficiency (TE) of health systems in Economic Cooperation Organization (ECO) countries during 2004–10 and to determine the factors affecting their TE. Methods: This was a descriptive-analytical and panel study. The required data were gathered using library and field studies, available statistics and international websites through completing data collection forms. In this study, the TE of health systems in 10 ECO countries was measured using their available data and Data Envelopment Analysis (DEA) through two approaches. The first approach used GDP per capita, education and smoking as its inputs and life expectancy and infant mortality rates as the outputs. The second approach, also, used the health expenditures per capita, the number of physicians per thousand people, and the number of hospital beds per thousand people as its inputs and life expectancy and under-5 mortality rates as the outputs. Then, the factors affecting the TE of health systems were determined using the panel data logit model. Excel 2010, Win4Deap 1.1.2 and Stata 11.0 were used to analyze the collected data. Results: According to the first approach, the mean TE of health systems was 0.497 and based on the second one it was 0.563. Turkey and Turkmenistan had, respectively, the highest and lowest mean of efficiency. Also, the results of panel data logit model showed that only GDP per capita and health expenditures per capita had significant relationships with the TE of health systems. Conclusion:In order to maximize the TE of health systems, health policy-makers should pay special attention to the proper use of healthcare resources according to the people’s needs, the appropriate management of the health system resources, allocating adequate budgets to the health sector, establishing an appropriate referral system to provide better public access to health services according to their income and needs, among many others

Distribution of Health Resource Allocation in the Fars Province Using the Scalogram Analysis Technique in 2011

The importance of health indicators in the recent years has created challenges in resource allocation. Balanced and fair distribution of health resources is one of the main principles in achieving equity. The goal of this cross-sectional descriptive study, conducted in 2010, was to classify health structural indicators in the Fars province using the scalogram technique. Health structural indicators were selected and classified in three categories; namely institutional, human resources, and rural health. The data were obtained from the statistical yearbook of Iran and was analyzed according to the scalogram technique. The distribution map of the Fars province was drawn using ArcGIS (geographic information system). The results showed an interesting health structural indicator map across the province. Our findings revealed that the city of Mohr with 85 and Zarindasht with 36 had the highest and the lowest scores, respectively. This information is valuable to provincial health policymakers to plan appropriately based on factual data and minimize chaos in allocating health resources. Based on such data and reflecting on the local needs, one could develop equity based resource allocation policies and prevent inequality. It is concluded that, as top priority, the provincial policymakers should place dedicated deprivation programs for Farashband, Eghlid and Zaindasht regions