Efficiency in COVID-19 inpatient care: findings from public hospitals in Iran.

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's <TEX>${\rho}_s$</TEX> and Kendall's <TEX>${\tau}_B$</TEX> are investigated in addition to Pearson's <TEX>${\gamma}$</TEX>. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

In this study, determinant input-output variables are identified for calculating Data Envelopment Analysis (DEA) efficiency scores relating to evaluating the efficiency of government-sponsored research and development (R&D) projects. In particular, this study proposes a systematic framework of design and analysis of experiments, called "all possible DEAs", for pinpointing DEA determinant input-output variables. In addition to correlation analyses, two modified measures of time series analysis are developed in order to check the similarities between a DEA complete data structure (CDS) versus the rest of incomplete data structures (IDSs). In this empirical analysis, a few DEA determinant input-output variables are found to be associated with a typical public R&D performance evaluation logic model, especially oriented to a mid- and long-term performance perspective. Among four variables, only two determinants are identified : "R&D manpower" (<TEX>$x_2$</TEX>) and "Sales revenue" (<TEX>$y_1$</TEX>). However, it should be pointed out that the input variable "R&D funds" (<TEX>$x_1$</TEX>) is insignificant for calculating DEA efficiency score even if it is a critical input for measuring efficiency of a government-sonsored R&D project from a practical point of view a priori. In this context, if practitioners' top priority is to see the efficiency between "R&D funds" (<TEX>$x_1$</TEX>) and "Sales revenue" (<TEX>$y_1$</TEX>), the DEA efficiency score cannot properly meet their expectations. Therefore, meticulous attention is required when using the DEA application for public R&D performance evaluation, considering that discrepancies can occur between practitioners' expectations and DEA efficiency scores.

BackgroundStrategic purchasing in healthcare services is a key component in improving health system performance, and it has been one of the most important issues in health system reform around the world, especially Europe in the last decade. Iran health system and insurance, although sometimes considered the issue of strategic purchasing goals, has not been made possible to achieve or even to implement, due to the associated problems.ObjectiveTo determine the associated problems of strategic purchasing in the Iran Health Insurance Organization (IHIO).MethodsThis study is a qualitative study, and framework analysis which was conducted in Iran in 2014–15. The participants in this study were 34 individuals from decision-makers and executives in the IHIO purchasing process, and university experts who have been chosen purposefully. This study conducted frame analysis, by using MAXQDA 10.ResultsThe findings included associated problems of IHIO strategic purchasing in 12 themes and 65 subthemes. The themes included: Laws and regulations for purchasing, Organization of purchasing, Qualified and authorized providers, Right type of services, Right type of contracts, Target groups for purchasing, Resources allocation, financing and pricing system, Purchasing as improving performance and quality, Purchasing as shaping the market and competition, Purchasing as health progress state of people and society, Guided purchasing and stewardship of government, Structure of decision-making process in the health and welfare ministries.ConclusionThe findings of this study showed associated problems in IHIO strategic purchasing. To achieve strategic purchasing goals in Iran, identification of all issues and factors of the total insurers and health system sets which affect strategic purchasing is essential.

Climate change is a long-term systematic climate variability caused by human activities that alters the composition of the global atmosphere. Health systems should be adaptive and resilient to climate change. Hence, this research aimed to strategically analyze the resilience of Iran's health system to climate change. This study utilized a multiple methods approach. First, in-depth semi-structured interviews were conducted with 32 key climate change and health experts to identify the strengths, weaknesses, opportunities and threats of the Iranian health system's resilience to climate change. Purposeful and snowball sampling techniques were used to ensure maximum diversity among the participants. Then, a questionnaire was developed based on the findings of the first stage and was completed by 33 climate change and health experts. Finally, the strategic position of Iran's health system's resilience to climate change was determined using the internal - external factors matrix. A total of 84 internal factors and 101 external factors were identified that affect the resilience of Iran's health system against climate change. The internal factors were categorized into seven dimensions (i.e., governance and leadership; health financing; health workforce; facilities, equipment and medicines; health information system; health services delivery, and key results). The external factors were categorized into six dimensions (i.e., political, economic, social, technological, environmental, and legal factors). The average score of internal and external factors were 2.47 and 2.12, out of 4 respectively. Iran's health system was found to be in the strategic position of V in terms of resilience to climate change. Therefore, precautionary strategies such as strengthening the climate resilience of healthcare facilities, promoting healthcare facilities' adaptation to climate change, public-private partnership, strengthening the health service delivery system, quality management and cost management, should be implemented to strengthen the resilience of Iran's health system to climate change. Iran's health system is facing significant weaknesses and challenges that have hindered its resilience to climate change. Iran's health system can better prepare and respond to the health impacts of climate change, and safeguarding the health and well-being of its population by addressing these challenges and implementing adaptive and resilience strategies.

BACKGROUND: The public hospital preparedness is essential for epidemic disaster like COVID-19 pandemic. This study was conducted to present a hospital management preparedness model of Iran's public hospitals for the epidemic. MATERIALS AND METHODS: The method of this study was an exploratory sequential mix method study (qualitative–quantitative). In this study, qualitative and quantitative methods were used in four stages. (1) Interviews with hospital managers to identify hospital management experiences during the COVID-19 epidemic and categorize the results in themes and subthemes, (2) assessing the performance of public hospitals in managing the coronavirus epidemic in a quantitative method, (3) present the initial hospital management model for a public hospital in epidemic conditions using an expert panel, and (4) validation of the model using the Delphi method. RESULTS: Experiences of hospital managers and specialists were categorized into eight themes: information gathering and environmental analysis, general and operational planning, provision of equipment and physical and financial resources, training and empowerment of human resources, a compilation of instructions and job descriptions, review and ensuring maximum readiness, monitoring and follow-up of service provision and existing problems, evaluation and feedback of performance problems and level of preparation and 51 sub-themes. The quantitative study indicated that all the investigated indicators had a significant decrease in the first month and an increase in the epidemic's continuation. The results were categorized in nine themes and 59 sub-themes, and finally, the model was validated in one round by the Delphi method. CONCLUSION: In Iran, managers have valuable experiences in COVID-19 epidemy management, but these experiences are scattered and not organized. In this study, by a qualitative–quantitative, a model was presented that contains essential points obtained from the experience of hospital managers and experts in actual disaster conditions and is appropriate and fits hospital structure and infrastructure of the health system in Iran.

Operation cancelations are a serious problem with undesirable consequences. The Health Transformation Plan was launched in the health system of Iran on May 5, 2014, to enhance the efficiency and quality of services in public hospitals. Comprehensive coverage of patients’ basic treatment needs and reduction of patients’ out-of-pocket expenditures through insurance for all are other objectives of Health Transformation Plan as well. Then, the present study aimed to determine the impact of the Health Transformation Plan on the number of surgical operations and the cancelation of elective surgeries within public hospitals of Iran. This retrospective comparative study was conducted in 2017 within 2 tertiary public hospitals in the South-East of Iran. Using systematic random sampling method and census, 8138 scheduled surgical files and all canceled operations files were reviewed from April 2012 to March 2017, respectively. A standard checklist was used for data collection. The data were analyzed using χ2 test and a logistic regression model in SPSS, version 21. The study population was 8138 patients with mean age of 33 ± 19 years. Female patients comprised about 51% of the study population (n = 4115), and nearly two-third of them were married (n = 5192 [63.79%]). Coverage by Iranian health insurance was reported in more than half of patients (n = 4415 [54.79%]). The common reason for surgeries was injury and poisoning (n = 2814 [34.52%]) followed by delivery (n = 1747 [21.46%]). The number of operations increased from 26 677 before Health Transformation Plan (cancelation rate = 1.5%) to 33 190 after Health Transformation Plan (cancelation rate = 2.0%). The cancelation rate had a significant relationship with age (odds ratio = 1.009; confidence interval: 1.00-1.01), health insurance status (odds ratio = 2.12; confidence interval: 1.33-3.38), outpatient service referrals (odds ratio = 0.5; confidence interval: 0.43-0.62), inpatient service referrals (odds ratio = 1.5; confidence interval: 1.36-1.77), and surgical types (P < .05). In general, the Health Transformation Plan was markedly associated with a rise in the number of surgeries and cancelation rate in the public hospitals. The information obtained in the present study concerning the causes of operation cancelations can be used to decrease the number of future cancelations.

BackgroundsBreast cancer is the most prevalent cancer among women. Breast cancer imposes a considerable economic burden on the health system. This study aimed to compare the cost of breast cancer among patients who referred to private and public hospitals in Iran (2017).MethodsThis was a prevalence-based cost of illness study. A total of 179 patients were selected from private and public hospitals using the census method. The researcher-constructed checklist was used for data collection. Data were analyzed using SPSS software version 22.ResultsThe estimated total mean (SD) direct cost of patients who referred to the private hospital and the public hospital was $10,050 (19,480) and $3960 (6780), respectively. Further, the total mean indirect cost of patients who referred to the private hospital was lower than those referring to the public hospital at $1870 (15 % of total costs) and $22,350 (85 % of total costs), respectively. These differences were statistically significant (P < 0.05).ConclusionsBreast cancer imposes a substantial cost on patients, health insurance organizations and the whole society in Iran. Therefore, the adoption of effective measures for the prevention and early diagnosis of breast cancer is urgently needed.

This study attempts to exploit information from environmental variables together with data envelopment analysis (DEA) efficiency scores for efficiency predictions of groups with more limited information. Based on DEA efficiency scores, decision-making units (DMUs) are sorted into two sets containing efficient and inefficient units, respectively. Then they are reshuffled into homogeneous groups with respect to environmental factors. We assume that the efficiency of DMUs in such a homogeneous group would be correlated. However, efficiency of different groups would vary. A beta binomial logistic model is proposed to fit such phenomena and is applied to predict the performance of a new group of commercialization projects for given environmental characteristics.

Purpose Studies show that economic sanctions have had major negative impacts on health systems during the past years. The aim of this study is to identify the impacts of US sanctions on the performance of public hospitals in Iran. Design/methodology/approach A qualitative research study was conducted between October 2019 and September 2020 in Kermanshah Province, Iran. Semi-structured, face-to-face interviews, lasting between 25 and 90 min, were carried out with 20 participants in seven public hospitals affiliated to the authors’ institution in Kermanshah Province. Inductive thematic analysis was used to identify themes in the data. Findings Five main themes emerged from the analysis: resource management challenges; financial restrictions; interruptions in planning; reductions in the quality of service delivery; and changes in organizational relationships. Originality/value The results of the present study demonstrate that US economic sanctions have considerably reduced access to necessary medical equipment and medicines for public hospitals in Iran. Policymakers should monitor the distribution of equipment and pharmaceutical products within public hospitals in Iran and take actions to ameliorate shortages during times of economic sanctions.

BackgroundThe objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019.MethodsA nonparametric approach—that is, multistage data envelopment analysis (DEA)—was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied.ResultsOn average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974).ConclusionsThe study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels.

Background and Objectives: Public-Private Partnership (PPP) is a well-established model to alleviate the risk of investment in health domain. While the model is widely applied in the developed countries, the adoption of the model in many developing countries is hampered partly by the lack of knowledge on dimensions and requirements of its local implementation. The present study, thus, aimed to identify the key aspects of PPP for hospital building in an Iranian context. Methods: A comparative study of PPP implementation in seven pioneer countries revealed 53 elements potentially influencing development of PPP. Using rigorous expert opinion seeking, these elements were refined and adapted with respect to the Iranian context. Based on this information a 38-item questionnaire was designed. The questionnaire was distributed among 220 experts from different health domains, including clinicians of public and private hospitals and policy makers, executives, and authorized advisors from MOHME and various medical universities. The collected data were analyzed using exploratory factors analysis in order to identify factors influencing PPP development. The robustness of the identified factors was further explored by confirmatory factor analysis. Findings: Legislation, policy making, finance, capacity building, and social orientation were identified as the five key dimensions of hospital-building PPP implementation in the Iranian context. Conclusions: Identification of the major dimensions of hospital PPP implementation may help policy-makers to develop effective strategies for promotion of PPP in the Iranian health system.

Background Identifying a population at risk of risks is imperative for primary disease prevention and allows the promotion of health maintenance in a healthy population. Previous studies on hypertension and dyslipidemia using data envelopment analysis (DEA) showed that populations at risk of risks could be identified using this method. In this study, we extended DEA to include pre-diabetes. Methods A retrospective cohort study was conducted using specific health check-up data from 2008 to 2013. DEA efficiency scores were calculated for healthy subjects with baseline glycated hemoglobin (HbA1c) &amp;lt;5.7%. Odds ratios (ORs) for pre-diabetes onset within 3 years were analyzed. Results Among 1,501 subjects, with 373 cases of disease onset (24.9%), the OR for the incidence of pre-diabetes (on the basis of a 0.1-point increase in the efficiency score) was 0.77 (90% confidence interval [CI] 0.68–0.86, p &amp;lt; 0.0002). After adjusting for age and sex, the OR was 0.66 (90% CI 0.58–0.75, p &amp;lt; 0.0001). Furthermore, for the subgroup with no conventional diabetes risk factors, the adjusted OR was 0.50 (90% CI 0.38–0.67, p = 0.0001). Conclusions We showed that the DEA efficiency score can help identify a pre-diabetes population at risk of risks. Further studies to validate these findings would be worthwhile for optimizing primary preventative measures. Key messages DEA was assessed for its ability to evaluate the risk of pre-diabetes. Results showed that an efficiency score could predict pre-diabetes onset and demonstrated the feasibility of applying this analysis in primary preventive healthcare.

Iranian public hospitals have been excessively changing during the healthcare reform since 2014. This study aimed to examine the technical efficiency of public hospitals during before and after the implementation of Health Sector Evolution Plan (HSEP) and to determine whether, and how, efficiency is affected by various factors. Forty-two public hospitals were selected in Tehran, Iran, from 2012 to 2016. Data envelopment analysis was employed to estimate the technical and scale efficiency sample hospitals. Tobit regression was used to relate the technical efficiency scores to seven explanatory variables in 2016, the last year. Overall, 24 (57.1%), 26 (61.9%), 26 (61.9%), 24 (57.1%) and 21 (50%) of the 42 sample hospitals ran inefficiently in 2012 to 2016, with average technical efficiency of 0.859, 0.836, 0.845, 0.905 and 0.934, respectively. The average pure technical efficiency in sample hospitals increased from 0.860 in 2010 (before the HSEP) to 0.944 in 2012 (after the HSEP). Tobit regression showed that average length of stay had a negative impact on technical efficiency of hospitals. In addition, bed occupancy rate, ratio of beds to nurses and ratio of nurses to physicians assumed a positive sign with technical efficiency. Despite government support, public hospitals operated relatively inefficien. Managers can enhance technical efficiency by increasing bed occupancy rate through shortening the average length of stay, proportioning the number of doctors, nurses, and beds along with service quality assurance.

The pandemic of COVID-19 is the second one in the 21st century after H1N1 Swine Flu in 2009-2010, which infected more than 4.9 million and caused more than 327000 death as of 23 May 2020 worldwide.¹ This pandemic has overwhelmed the health systems, specially hospitals, and the need for ICU beds and ventilators increased while many of patients with mild symptom of COVID-19 could be recovered at home.²<br /> <span lang="EN-GB">In addition, early discharge of hospitalized patient and referring for Home Health Care (HHC) would be a suitable strategy for decreasing the overload of patient in hospitals and its consequences such as nosocomial infections. On the other side, many patients who receive HHC for other conditions (usually old people with chronic disease) need special attention during the pandemic for ensuring continuation of care and prevention of COVID-19 threat. </span><br /> <span lang="EN-GB">The first patient in Iran was officially reported on February 19, 2020 in Qom city. According to World Health Organization about 129 341 Iranians were infected by Novel Corona Virus and 7249 died till 23 May 2020.¹ As the nurses are frontline health worker who provide services in hospitals as well as in home settings, Deputy for Nursing of MOHME published the guideline for Home care for COVID-19 patient and about 405 institute for Home Care services were active to care of patient in their homes.³ Regardless of the availability of detailed information about hospitalized COVID-19 patients by means of integrated Hospital Information Systems (HIS), there is no information about the number, characteristics and health outcomes of people who receive professional HHC in Iran during this pandemic. It is not only the problem of Iran’s Health system, but European countries have also encounter with lack of home care data.⁴</span><br /> <span lang="EN-GB">The history of HHC, as an industry in Iran, dates back to 1999 when the first bylaw for HHC was ratified by Health Minister. In recent years, Act on the Sixth Five-Year Economic, Cultural and Social Development Plan of Iran for 2017-2022 enforced the MOHME to expand the HHC in community and insurance coverage for HHC is on the High Council of Health Insurance’s agenda. Thus, nowadays home health care is becoming integrated in the health system of Iran more than ever.</span><br /> <span lang="EN-GB">One of the problems of HHC during the COVID-19 in Iran (at least in the beginning of epidemic) was lack of appropriate and adequate Personal Protective Equipment (PPE) for the staff who worked in HHC settings directly with patients and families and raised fear of the risk of cross-infections by the staff and patients. </span><br /> <span lang="EN-GB">The lack of information and data about home care in Iran’s healthcare system, lack of adequate and accurate monitoring, and inability of supervising have been among the challenges of HHC in Iran,⁵ which during COVID-19 epidemic became more challenging. The lack of data has weakened the ability of policymakers for evidence-based and timely decisions to combat the disease. </span><br /> <span lang="EN-GB">Using Information Technology (IT) in HHC has many advantages such as gathering and sharing information, supervising and providing telenursing. The HHC teams and patients as well as policymakers can benefit from IT implementation in HHC. This issue is especially a priority in the disasters like COVID-19 pandemic when the health system needs integrated and real-time data. On the other hand, to minimize the contacts between nurses and patients aiming to decrease the cross-contamination, Telenursing can be used for frequent contact between the nurses and patients to manage the condition by telephone or video call without direct contact.</span><br /> <span lang="EN-GB">According to lessons learned from COVID-19 pandemic, using IT in Home Health Care, especially implementation of Home Health Care Information System and its integration into national Electronic Health Record (EHR) and using Telenursing are among the important factors for developing the role of HHC in the health system of Iran; this could help to better manage the outbreaks. It is not a simple policy to implement and needs a national determination and plan with multi-sectoral cooperation.</span><br /> <strong><span lang="EN-GB"> </span></strong>

BackgroundUnderstanding the Spatio-temporal distribution and interpersonal comparisons are important tools in etiological studies. This study was conducted to investigate the temporal and geographical distribution of COVID-19 hospitalized patients in the Iran Health Insurance Organization (IHIO) insured population (the second largest social health insurance organization) and the factors affecting their case fatality rate (CFR).MethodsIn this descriptive-analytical cross-sectional study, the demographic and clinical data of all insured of the IHIO who were hospitalized with COVID-19 in hospitals across the country until March 2021 was extracted from the comprehensive system of handling the inpatient documents of this organization. The Excel 2019 and GeoDA software were used for descriptive reporting and geographical distribution of variables. A multiple logistic regression model was used to estimate the Odds Ratio (OR) of death in patients with COVID-19 using STATA 14 software.ResultsDuring the first 14 months of the COVID-19 outbreak in Iran, 0.72% of the IHIO insured (303,887 individuals) were hospitalized with COVID-19. Hospitalization per 100,000 people varied from 192.51 in East Azerbaijan to 1,277.49 in Yazd province. The overall CFR in hospitalized patients was 14%. Tehran and Kohgiluyeh & BoyerAhmad provinces had the highest and lowest CFR with 19.39% and 5.19%, respectively. The highest odds of death were in those over 80 years old people (OR = 9.65), ICU-admitted (OR = 7.49), Hospitalized in governmental hospitals (OR = 2.08), Being a foreign national (OR = 1.45), hospitalized in November (OR = 1.47) and Residence in provinces such as Sistan & Baluchestan (OR = 1.47) and Razavi Khorasan (OR = 1.66) respectively. Furthermore, the odds of death were lower in females (OR = 0.81) than in males.ConclusionsA sound understanding of the primary causes of COVID-19 death and severity in different groups can be the basis for developing programs focused on more vulnerable groups in order to manage the crisis more effectively and benefit from resources more efficiently.