Are Doctors Equally Distributed Throughout the World?

Background: As the vital and scarce resource of the health system, physicians are responsible for treating patients and saving lives and the equitable distribution of physicians among the whole population is a prerequisite to achieving health for all. We aimed to investigate inequality in physician distribution in the world using the Gini coefficient. Methods: This descriptive-analytical study was conducted in 2021. The number of physicians and the population of countries were obtained from the WHO and United Nations (UN) databases. The Gini coefficient was calculated in three different modes and the distribution of physicians among countries in various Human Development Index (HDI) groups was determined using the physician ratio per 10,000 population. Results: There were generally more than 13 million doctors in the world. About 43% of the world's physicians were available to 20% of the world's population in very high HDI countries, and 12% of the population had access to about 1% of physicians in low HDI countries. An average of 19.5 physicians are distributed per 10,000 population worldwide. The Gini coefficient between the four groups of HDI countries was 0.55, and that of all countries in the world was 0.640. Conclusion: There was a shortage and inequality in the distribution of physicians worldwide. Governments should eliminate inequality in the distribution of the medical workforce, in particular physicians, by redoubling their efforts and accurate planning.

Factors disrupting the continuity of care for patients with chronic disease during the pandemics: A systematic review.

Background and Aims: Continuous routine care is necessary to prevent long-term complications of chronic diseases and improve patients' health conditions. This review study was conducted to determine the factors disrupting continuity of care for patients with chronic diseases during the pandemic. Methods: All original articles published on factors disrupting continuity of care for patients with chronic disease during a pandemic between December 2019 and June 28, 2023, in PubMed, Web of Science, Scopus, and ProQuest databases were searched. Selection of articles, data extraction, and qualitative evaluation of articles (through STROBE and COREQ checklist) were done by two researchers separately. Data graphing form was used to extract the data of each study and then the data were classified by thematic analysis method. Results: Out of 1708 articles reviewed from the databases, 22 were included. The factors disrupting the continuity of care for patients with chronic diseases during the epidemics were classified into two main categories: patient-side factors and health system-side factors. Patient-side factors including psychological, individual and social, disease-related, and health system-side factors including provider access, health system institutional, and infrastructural and financial problems were among the subcategories disrupting the continuity of care for patients with chronic diseases during the pandemic. Based on the studies, psychological factors and access to the provider were among the most frequent factors affecting the continuity of care for patients with chronic diseases in the pandemic. Conclusion: Considering the factors disrupting the continuity of care and applying appropriate interventions based on them, can guarantee the continuity of providing services to chronic patients in health crises.

Vaccination and its impact on healthcare utilization in two groups of vaccinated and unvaccinated patients with COVID-19: A cross-sectional study in Iran between 2021 and 2022.

Background and Aims: One of the main responsibilities of health systems impacted by the global Coronavirus disease 2019 (COVID-19) pandemic, where the first case was discovered in Wuhan, China, in December 2019, is the provision of medical services. The current study looked into the impact of vaccination on the utilization of services provided to COVID-19 patients. Methods: This study was conducted in Iran between 2021 and 2022, utilizing a cross-sectional research design. The research team collected data on the utilization of provided services and the number of COVID-19 vaccines administered to 1000 patients in Iran through a random sampling approach. The data were analyzed with statistical methods, including the mean difference test, and multiple linear regression. Results: Regression estimates show that after controlling for confounding variables like age, type of admission, and comorbidities, vaccination reduces the utilization of healthcare services in the general majority of services. The study's results reveal a fall in COVID-19 patients' utilization of services, specifically in patients administered two or three doses of the vaccine. However, the reduction is not statistically significant. Regression models are in contrast to univariate analysis findings that vaccination increases the mean utilization of healthcare services for COVID-19 patients in general. Comorbidities are a crucial factor in determining the utilization of diagnostic and treatment services for COVID-19 patients. Conclusion: Full COVID-19 vaccination and other implementations, including investing in public health, cooperating globally, and vaccinating high-risk groups for future pandemics, are essential as a critical response to this pandemic as they reduce healthcare service utilization to alleviate the burden on healthcare systems and allocate resources more efficiently.

Distribution of nursing workforce in the world using Gini coefficient.

INTRODUCTION: Unequal Access to human resources for health, reduces access to healthcare services, worsens the quality of services and reduces health outcomes. This study aims to investigate the distribution of the nursing workforce around the world. METHODS: This is a descriptive-analytical study, which was conducted in 2021. The number of nurses and world populations was gathered from World Health Organization (WHO) and The United Nations (UN) databases. The UN has divided world countries based on the Human Development Index (HDI) into four categories of very high, high, medium and low HDI. To investigate the distribution of the nurses around the world, we used the nurse population ratio (per 10,000 population), Gini coefficient, Lorenz curve and Pareto curve. FINDINGS: On average, there were 38.6 nurses for every 10,000 people in the world. Nations with the very high HDI, had the highest nurse/population ratio (95/10,000), while the low HDI nations had the lowest nurse/population ratio (7/10,000). Most nurses around the world were females (76.91%) who were in the age group of 35-44 (29.1%). The Gini coefficient of nations in the each four HDI categories varied from 0.217 to 0.283. The Gini coefficient of the nations between the four HDI categories was 0.467, and the Gini coefficient of the whole world was 0.667. CONCLUSION: There were inequalities between countries all over the world. Policymakers should focus on the equitable distribution of the nursing workforce across all local, national and regional levels.

The need to reorganize health research systems in pandemic crisis: A prospective study.

Background and Aims: A pandemic has posed a major challenge to health systems all over the world. All countries have realized that the only way to get real growth and development and solve their problems is to use what they have learned from research. Methods: A descriptive and analytic type of study was conducted with the help of experts in the field of health research. The components affecting the research system were obtained via process approach and content analysis methods, and then the position of each component was identified by the Mic Mac technique. Results: Seventeen influential structural components in the health research system were identified. The leadership and management components had the most direct and indirect influence among other components. The health promotion component had a greater dependency than the other components. Conclusion: All health systems need to provide adequate financial resources and manpower to provide a useful research system. Human resources are the most important inputs to such a system. Components such as the research process, research sustainability, quality, or innovation in research can play a balancing role. Having the right infrastructures for creating, transferring, developing, and getting access to knowledge makes it possible to do systematic science. It is hoped that this science will be used in other results of the health research system, like improving the effectiveness or promoting health.

An evaluation of the risk factors associated with implementing projects of health information technology by fuzzy combined ANP-DEMATEL.

BACKGROUND: Application of a Clinical Information System (CIS) like Electronic Patient Record (EPR), PACS system and CPOE has turned into one of the most important criteria of priorities of health care systems. The aims of the clinical information system include improving the physicians' efficiency level, integrating the caring process, and expanding the fuzzy quality of the services offered to patients. Achievement of these benefits in reality is not an easy task, and there are lots of plans in this field which are doomed to failure. About 50% of the implementation plans of clinical information systems in health care organizations have failed, and this trend is significantly affecting industrial countries. Proper implementation of hospital information systems lies in identifying and assessing the relationships among the most important risk factors of fuzzy. The present study aimed to provide an applicable model for identifying, ranking and evaluating the risk factors associated with projects of clinical information technology in hospitals of Shiraz University of Medical Sciences. METHOD: This is an applied study which evaluates the risk factors associated with implementation of clinical information technology projects in hospitals of Shiraz Medical Sciences University. The participants consisted of professionals and senior experts of clinical information technology. Fuzzy logic was used in this study. We also applied ANP-DEMATEL combined model with fuzzy procedure to provide the analytic model of the study. RESULTS: According to the study findings, lack of top-executive supports, and unstable organizational environment were the two most important risk factors, while the main organizational factors and technology were also highly important. In addition, the factors associated with technology had the highest influence on the other studied risk factors. CONCLUSION: Hospital authorities can benefit from this proposed model to reduce the risk of implementing the projects of clinical information technology and improve the success coefficient of the risk of such projects.

Development of a model for predicting hospital beds shortage and optimal policies using system dynamics approach.

BACKGROUND: Policymakers use simulation-based models to improve system feedback and model the reality of the problems in the system. This study uses the system dynamics approach to provide a model for predicting hospital bed shortages and determine the optimal policy in Shiraz, Southern Iran. METHODS: This study was designed based on Sterman's system dynamic modeling (SDM) process. Firstly, we determined the main variables affecting bed distribution using a mixed qualitative and quantitative study which includes scoping review, expert panel, Delphi, and DANP. Then, dynamic hypotheses were designed. Subsequently, we held several expert panels for designing the causal and stock-flow models, formulating and testing a simulation model, as well as developing various scenarios and policies. RESULTS: Dynamic modeling process resulted in four scenarios. All of the scenarios predicted a shortage of national hospital beds over a 20-year time horizon. Then, four policies were developed based on the changes in the number of beds and capacity of home care services; finally, the optimal policy was determined. CONCLUSIONS: Due to the high cost of setting up hospital beds, developing and supporting cost-effective home care services, strengthening the insurance coverage of these services, and improving the quantity and quality of community care, considering the real needs of the community could be considered as an optimal option for the future of the city.

The pattern of health insurance economic resilience in the Covid 19 pandemic shock.

OBJECTIVE: Health insurance is based on people's significant risks in receiving health services that they cannot afford alone. Since the outbreak of the corona epidemic, the health insurance system has suffered many economic problems. Designing a model of a health insurance system based on the requirements of a resilient economy can improve the functions of this system in the corona crisis. RESULTS: In this research 12, structural components were obtained in the form of 4 conceptual components. The 4 main conceptual components are Knowledge-based economy, Economic stability, Economic resilience, and justice. The knowledge-based economy is the basis for the formation of economic resilience in the health insurance systems. Health insurance systems will achieve two crucial intermediate results, namely economic resilience, and economic stability, by building the basic infrastructure of a knowledge-based economy. In the long run, maintaining such intermediate results is the foundation of justice in the health insurance system.

Presenting a Model to Evaluate Factors Affecting Outsourcing of Health Information Technology Services.

INTRODUCTION: Outsourcing of health information technology services (OHITS) is an important process for healthcare organizations due to the lack of expert staff to respond rapid advance in IT and the security of patient's information. This study aimed at presenting a model to evaluate factors affecting OHITS. METHOD: This is a descriptive-analytic study, conducted in 2017. Participants were experts of IT and accounting field. This research was performed in four general steps: identifying the factors affecting OHITS through literature review; determining suitable indicators by Delphi technique; prioritizing the factors using Analytical Hierarchical Process (AHP), measuring the accuracy of research hypotheses by Partial Least Square (PLS) and calculating the Goodness Of Fit (GOF) criteria for the model. FINDINGS: the most and the least important factors affecting OHITS were "motivation" and "selection of a provider" respectively. GOF criteria was 0.697, suggesting powerful model fitting. CONCLUSION: Using the model presented in this research, the healthcare managers and chief officers of IT will be able to decide consciously about outsourcing projects, and also manage the project better.

Factors influencing decision making for healthcare services outsourcing: A review and Delphi study.

Background: Outsourcing is considered as one of the tools for organizational development and promotion of productivity by managers. In recent years, outsourcing of healthcare services has become significant. The aim of this study was to identify the most important factors influencing the decision making of outsourcing healthcare services. Methods: This study is a combined study. First, the literature was examined to identify the factors influencing decision making for outsourcing. Then, with the aim of consensus on the most important factors affecting the decision making of outsourcing in health services, the panel of experts and Delphi technique were used. Sampling was purposeful. Results: In the selected articles, a total of 180 factors were extracted. The members of the panel of experts from these 180 factors selected 29 sub-factors in the form of six main factors: strategy, quality, management, technology, performance feature, and economy, as the most important factors affecting the outsourcing of services. Finally, the results of Delphi showed that 22 sub-factors were more important in outsourcing decision making at healthcare services. Conclusion: The study showed that the decision making to outsource health services is a complex and multi-criteria decision. Therefore, when deciding to outsource healthcare services, attention should be paid to various factors, such as strategy, quality, management, technology, and economics.

Relationship between Family-Work and Work-Family Conflict with Organizational Commitment and Desertion Intention among Nurses and Paramedical Staff at Hospitals.

BACKGROUND: High turnover intention rate is one of the most common problems in healthcare organizations throughout the world. There are several factors that can potentially affect the individuals' turnover intention; they include factors such as work-family conflict, family-work conflict, and organizational commitment. The aim of this research was to determine the relationship between family-work and work-family conflicts and organizational commitment and turnover intention among nurses and paramedical staff at hospitals affiliated to Shiraz University of Medical Sciences (SUMS) and present a model using SEM. METHODS: This is a questionnaire based cross-sectional study among 400 nurses and paramedical staff of hospitals affiliated to SUMS using a random-proportional (quota) sampling method. Data collection was performed using four standard questionnaires. SPSS software was used for data analysis and SmartPLS software for modeling variables. RESULTS: Mean scores of work-family conflict and desertion intention were 2.6 and 2.77, respectively. There was a significant relationship between gender and family-work conflict (P=0.02). Family-work conflict was significantly higher in married participants (P=0.001). Based on the findings of this study, there was a significant positive relationship between work-family and family-work conflict (P=0.001). Also, work-family conflict had a significant inverse relationship with organizational commitment (P=0.001). An inverse relationship was seen between organizational commitment and turnover intentions (P=0.001). CONCLUSION: Thus, regarding the prominent and preventative role of organizational commitment in employees' desertion intentions, in order to prevent negative effects of staff desertion in health sector, attempts to make policies to increase people's organizational commitment must be considered by health system managers more than ever.

Using Queuing Theory and Simulation Modelling to Reduce Waiting Times in An Iranian Emergency Department.

BACKGROUND: Hospital emergencies have an essential role in health care systems. In the last decade, developed countries have paid great attention to overcrowding crisis in emergency departments. Simulation analysis of complex models for which conditions will change over time is much more effective than analytical solutions and emergency department (ED) is one of the most complex models for analysis. This study aimed to determine the number of patients who are waiting and waiting time in emergency department services in an Iranian hospital ED and to propose scenarios to reduce its queue and waiting time. METHODS: This is a cross-sectional study in which simulation software (Arena, version 14) was used. The input information was extracted from the hospital database as well as through sampling. The objective was to evaluate the response variables of waiting time, number waiting and utilization of each server and test the three scenarios to improve them. RESULTS: Running the models for 30 days revealed that a total of 4088 patients left the ED after being served and 1238 patients waited in the queue for admission in the ED bed area at end of the run (actually these patients received services out of their defined capacity). The first scenario result in the number of beds had to be increased from 81 to179 in order that the number waiting of the "bed area" server become almost zero. The second scenario which attempted to limit hospitalization time in the ED bed area to the third quartile of the serving time distribution could decrease the number waiting to 586 patients. CONCLUSION: Doubling the bed capacity in the emergency department and consequently other resources and capacity appropriately can solve the problem. This includes bed capacity requirement for both critically ill and less critically ill patients. Classification of ED internal sections based on severity of illness instead of medical specialty is another solution.

Applying Quality Function Deployment Model in Burn Unit Service Improvement.

Quality function deployment (QFD) is one of the most effective quality design tools. This study applies QFD technique to improve the quality of the burn unit services in Ghotbedin Hospital in Shiraz, Iran. First, the patients' expectations of burn unit services and their priorities were determined through Delphi method. Thereafter, burn unit service specifications were determined through Delphi method. Further, the relationships between the patients' expectations and service specifications and also the relationships between service specifications were determined through an expert group's opinion. Last, the final importance scores of service specifications were calculated through simple additive weighting method. The findings show that burn unit patients have 40 expectations in six different areas. These expectations are in 16 priority levels. Burn units also have 45 service specifications in six different areas. There are four-level relationships between the patients' expectations and service specifications and four-level relationships between service specifications. The most important burn unit service specifications have been identified in this study. The QFD model developed in the study can be a general guideline for QFD planners and executives.

Assessment of Three "WHO" Patient Safety Solutions: Where Do We Stand and What Can We Do?

BACKGROUND: Most medical errors are preventable. The aim of this study was to compare the current execution of the 3 patient safety solutions with WHO suggested actions and standards. METHODS: Data collection forms and direct observation were used to determine the status of implementation of existing protocols, resources, and tools. RESULTS: In the field of patient hand-over, there was no standardized approach. In the field of the performance of correct procedure at the correct body site, there were no safety checklists, guideline, and educational content for informing the patients and their families about the procedure. In the field of hand hygiene (HH), although availability of necessary resources was acceptable, availability of promotional HH posters and reminders was substandard. CONCLUSIONS: There are some limitations of resources, protocols, and standard checklists in all three areas. We designed some tools that will help both wards to improve patient safety by the implementation of adapted WHO suggested actions.

Cost-of-illness analysis of type 2 diabetes mellitus in Iran.

INTRODUCTION: Diabetes is a worldwide high prevalence chronic progressive disease that poses a significant challenge to healthcare systems. The aim of this study is to provide a detailed economic burden of diagnosed type 2 diabetes mellitus (T2DM) and its complications in Iran in 2009 year. METHODS: This is a prevalence-based cost-of-illness study focusing on quantifying direct health care costs by bottom-up approach. Data on inpatient hospital services, outpatient clinic visits, physician services, drugs, laboratory test, education and non-medical cost were collected from two national registries. The human capital approach was used to calculate indirect costs separately in male and female and also among different age groups. RESULTS: The total national cost of diagnosed T2DM in 2009 is estimated at 3.78 billion USA dollars (USD) including 2.04±0.28 billion direct (medical and non-medical) costs and indirect costs of 1.73 million. Average direct and indirect cost per capita was 842.6±102 and 864.8 USD respectively. Complications (48.9%) and drugs (23.8%) were main components of direct cost. The largest components of medical expenditures attributed to diabetes's complications are cardiovascular disease (42.3% of total Complications cost), nephropathy (23%) and ophthalmic complications (14%). Indirect costs include temporarily disability (335.7 million), permanent disability (452.4 million) and reduced productivity due to premature mortality (950.3 million). CONCLUSIONS: T2DM is a costly disease in the Iran healthcare system and consume more than 8.69% of total health expenditure. In addition to these quantified costs, T2DM imposes high intangible costs on society in terms of reduced quality of life. Identification of effective new strategies for the control of diabetes and its complications is a public health priority.