Iran Health Insurance Organization Research Articles

Patterns of case fatality and hospitalization duration among nearly 1 million hospitalized COVID-19 patients covered by Iran Health Insurance Organization (IHIO) over two years of pandemic: An analysis of associated factors.

Different populations and areas of the world experienced diverse COVID-19 hospitalization and mortality rates. Claims data is a systematically recorded source of hospitalized patients' information that could be used to evaluate the disease management course and outcomes. We aimed to investigate the hospitalization and mortality patterns and associated factors in a huge sample of hospitalized patients. In this retrospective registry-based study, we utilized claim data from the Iran Health Insurance Organization (IHIO) consisting of approximately one million hospitalized patients across various hospitals in Iran over a 26-month period. All records in the hospitalization dataset with ICD-10 codes U07.1/U07.2 for clinically/laboratory confirmed COVID-19 were included. In this study, a case referred to one instance of a patient being hospitalized. If a patient experienced multiple hospitalizations within 30 days, those were aggregated into a single case. However, if hospitalizations had longer intervals, they were considered independent cases. The primary outcomes of study were general and intensive care unit (ICU) hospitalization periods and case fatality rate (CFR) at the hospital. Besides, various demographic and hospitalization-associated factors were analyzed to derive the associations with study outcomes using accelerated failure time (AFT) and logistic regression models. A total number of 1 113 678 admissions with COVID-19 diagnosis were recorded by IHIO during the study period, defined as 917 198 cases, including 51.9% females and 48.1% males. The 61-70 age group had the highest number of cases for both sexes. Among defined cases, CFR was 10.36% (95% CI: 10.29-10.42). The >80 age group had the highest CFR (26.01% [95% CI: 25.75-26.27]). The median of overall hospitalization and ICU days were 4 (IQR: 3-7) and 5 (IQR: 2-8), respectively. Male patients had a significantly higher risk for mortality both generally (odds ratio (OR) = 1.36 [1.34-1.37]) and among ICU admitted patients (1.12 [1.09-1.12]). Among various insurance funds, Foreign Citizens had the highest risk of death both generally (adjusted OR = 2.06 [1.91-2.22]) and in ICU (aOR = 1.71 [1.51-1.92]). Increasing age groups was a risk of longer hospitalization, and the >80 age group had the highest risk for overall hospitalization period (median ratio = 1.52 [1.51-1.54]) and at ICU (median ratio = 1.17 [1.16-1.18]). Considering Tehran as the reference province, Sistan and Balcuchestan (aOR = 1.4 [1.32-1.48]), Alborz (aOR = 1.28 [1.22-1.35]), and Khorasan Razavi (aOR = 1.24 [1.20-1.28]) were the provinces with the highest risk of mortality in hospitalized patients. Hospitalization data unveiled mortality and duration associations with variables, highlighting provincial outcome disparities in Iran. Using enhanced registry systems in conjunction with other studies, empowers policymakers with evidence for optimizing resource allocation and fortifying healthcare system resilience against future health challenges.

Non-COVID-19 hospitalization and mortality during the COVID-19 pandemic in Iran: a longitudinal assessment of 41 million people in 2019-2022.

During a COVID-19 pandemic, it is imperative to investigate the outcomes of all non-COVID-19 diseases. This study determines hospital admissions and mortality rates related to non-COVID-19 diseases during the COVID-19 pandemic among 41 million Iranians. This nationwide retrospective study used data from the Iran Health Insurance Organization. From September 23, 2019, to Feb 19, 2022, there were four study periods: pre-pandemic (Sept 23-Feb 19, 2020), first peak (Mar 20-Apr 19, 2020), first year (Feb 20, 2020-Feb 18, 2021), and the second year (Feb 19, 2021-Feb 19, 2022) following the pandemic. Cause-specific hospital admission and in-hospital mortality are the main outcomes analyzed based on age and sex. Negative binomial regression was used to estimate the monthly adjusted Incidence Rate Ratio (IRR) to compare hospital admission rates in aggregated data. A logistic regression was used to estimate the monthly adjusted in-hospital mortality Odds Ratio (OR) for different pandemic periods. During the study there were 6,522,114 non-COVID-19 hospital admissions and 139,679 deaths. Prior to the COVID-19 outbreak, the standardized hospital admission rate per million person-month was 7115.19, which decreased to 2856.35 during the first peak (IRR 0.40, [0.25-0.64]). In-hospital mortality also increased from 20.20 to 31.99 (OR 2.05, [1.97-2.13]). All age and sex groups had decreased admission rates, except for females at productive ages. Two years after the COVID-19 outbreak, the non-COVID-19 hospital admission rate (IRR 1.25, [1.13-1.40]) and mortality rate (OR 1.05, [1.04-1.07]) increased compared to the rates before the pandemic. The respiratory disease admission rate decreased in the first (IRR 0.23, [0.17-0.31]) and second years (IRR 0.35, [0.26-0.47] compared to the rate before the pandemic. There was a significant reduction in hospitalizations for pneumonia (IRR 0.30, [0.21-0.42]), influenza (IRR 0.04, [0.03-0.06]) and COPD (IRR 0.39, [0.23-0.65]) during the second year. There was a significant and continuous rise in the hematological admission rate during the study, reaching 186.99 per million person-month in the second year, reflecting an IRR of 2.84 [2.42-3.33]compared to the pre-pandemic period. The mortality rates of mental disorders (OR 2.15, [1.65-2.78]) and musculoskeletal (OR 1.48, [1.20-1.82), nervous system (OR 1.42, [1.26-1.60]), metabolic (OR 1.99, [1.80-2.19]) and circulatory diseases (OR 1.35, [1.31-1.39]) increased in the second year compare to pre-pandemic. Myocardial infarction (OR 1.33, [1.19-1.49]), heart failure (OR 1.59, [1.35-1.87]) and stroke (OR 1.35, [1.24-1.47]) showed an increase in mortality rates without changes in hospitalization. In the era of COVID-19, the changes seem to have had a long-term effect on non-COVID-19 diseases. Countries should prepare for similar crises in the future to ensure medical services are not suspended.

Changes in emergency department visits and mortality during the COVID-19 pandemic: a retrospective analysis of 956 hospitals

BackgroundDuring the COVID-19 pandemic, many non-COVID-19 emergency department (ED) visits were indirectly affected. ED visits and mortality were assessed during different pandemic time periods compared with pre-pandemic.MethodsThe study used data from 41 million Iran Health Insurance Organization members. The outcomes were non-COVID-19 ED visits and associated mortality in 956 hospitals. An analysis of ED visits was conducted both for all-cause and cause-specific conditions: cardiovascular diseases (CVD), mental and substance use disorders, unintentional injuries, and self-harm. In addition, total in-hospital ED mortality was analyzed. A negative binomial regression and a Poisson regression with a log link were used to estimate the incidence rate ratio (IRR) of visits and mortality relative risk (RR).Results1,789,831 ED visits and 12,377 deaths were reported during the study. Pre-pandemic (Sep 2019 to Feb 2020), there were 2,767 non-COVID-19 visits rate per million person-month, which decreased to 1,884 during the first COVID-19 wave with a national lockdown from Feb 20 to Apr 19, 2020 (IRR 0.68, [0.56–0.84]). The non-COVID-19 ED mortality risk was 8.17 per 1,000 visit-month during the pre-pandemic period, rising to 12.80 during the first wave of COVID-19 (RR 1.57, [1.49–165]). Non-COVID-19 ED visit rates decreased during the first pandemic year from Sep 2020 to Feb 2021 (IRR 0.73, [0.63–0.86]), but increased after COVID-19 vaccination two years later from Sep 2021 to Feb 2022 (IRR 1.11, [0.96–0.17]). The total ED mortality risk for non-COVID-19 was significantly higher after the COVID-19 outbreak in the first (RR 1.66, [1.59–1.72]) and second years (RR 1.27, [1.22–1.32]) of the pandemic. The visit incidence rate for mental health and substance use disorders declined from 8.18 per million person-month to 4.57 (IRR 0.53, [0.32 to 0.90]) in the first wave. In the second year, unintentional injury visits increased significantly compared with pre-pandemic (IRR 1.63, [1.30–2.03]). As compared to before the pandemic, there was no significant change in CVD and self-harm visit rates during the pandemic. Cardiac arrest was the leading cause of death in Iran hospitals’ EDs.ConclusionIn the first year of the COVID-19 pandemic, non-COVID-19 hospital ED visits declined and mortality risk increased. Despite two years since the COVID-19 outbreak, non-COVID-19 ED mortality risk remains high.

Age-related and Gender-related Differences in Hospital Admission Rate and Hospital Costs of People Covered by the Iran Health Insurance Organization: A Retrospective Study

Objectives The impact of population aging on health expenditure is inevitable. It affects health expenditure by causing changes in people’s health status and the demand for health care services. In this study, we aim to investigate the age-related and gender-related differences in hospital admission rate, length of stay, and hospital costs of people in Iran. Methods & Materials This is a quantitative, descriptive-analytical study with a cross-sectional design conducted on data of 41 million Iranian people covered by the Iran Health Insurance Organization in 2020. Hospital admission rate, length of stay, and hospital costs were dependent variables. Hospital costs included insurance payments, patients’ out-of-pocket spending, and government subsidies. Age and sex of the patients, ownership of the hospital, type of patients’ medical files were descriptive variables. The Mann-Whitney U test was used to compare hospital costs between elderly (>60 years of age) and non-elderly (<60 years of age) groups and between females and males. Spearman’s correlation test was used to find the correlation between age and dependent variables. Results During the study period, there were about 3,800,000 hospital admissions. The rate of hospital admission in the elderly was 3.7 times higher than that of non-elderly groups. The average length of stay was 1.3 days for the elderly, and 2.2 days for the non-elderly. In the elderly group, men had a higher hospital admission rate than women, while in non-elderly groups, women had a higher admission rate. The average hospital cost was 28 million IRR for the non-elderly and 45 million IRR for the elderly. The average cost of surgery, hospitalization, medicine and medical consumables for the elderly was 1.5 times more than that of the non-elderly. There was a positive and significant relationship between the hospital admission rate and age of the patients (r=0.879, P<0.001). As the age of the patients increased, the length of stay in the hospital increased significantly (r=0.582, P<0.001). The relationship between patients’ age and the average hospital cost was also positive and significant (r=0.582, P=0.006). Conclusion Hospital admission rate, length of stay, and average hospital costs are significantly higher for the elderly in Iran.

Drug prescription patterns and their association with mortality and hospitalization duration in COVID-19 patients: insights from big data.

Different medication prescription patterns have been associated with varying course of disease and outcomes in COVID-19. Health claims data is a rich source of information on disease treatment and outcomes. We aimed to investigate drug prescription patterns and their association with mortality and hospitalization via insurance data for a relatively long period of the pandemic in Iran. We retrieved hospitalized patients' data from Iran Health Insurance Organization (IHIO) spanning 26 months (2020-2022) nationwide. Included were patients with ICD-10 codes U07.1/U07.2 for confirmed/suspected COVID-19. A case was defined as a single hospitalization event for an individual patient. Multiple hospitalizations of a patient within a 30-day interval were aggregated into a single case, while hospitalizations with intervals exceeding 30 days were treated as independent cases. The Anatomical Therapeutic Chemical (ATC) was used for medications classification. The two main study outcomes were general and intensive care unit (ICU) hospitalization periods and mortality. Besides, various demographic and clinical associate factors were analyzed to derive the associations with medication prescription patterns and study outcomes using accelerated failure time (AFT) and logistic regression models. During the 26 months of the study period, 1,113,678 admissions with COVID-19 diagnosis at hospitals working in company with IHIO were recorded. 917,198 cases were detected from the database, among which 51.91% were females and 48.09% were males. Among the main groups of medications, antithrombotics (55.84% [95% CI: 55.74-55.94]), corticosteroids (54.14% [54.04-54.24]), and antibiotics (42.22% [42.12-42.32]) were the top used medications among cases with COVID-19. Investigation of the duration of hospitalization based on main medication groups showed antithrombotics (adjusted median ratio = 0.94 [0.94-0.95]) were significantly associated with shorter periods of overall hospitalization. Also, antithrombotics (adjusted odds ratio = 0.74 [95%CI, 0.73-0.76]), corticosteroids (0.97 [0.95-0.99]), antivirals (0.82 [0.80-0.83]), and ACE inhibitor/ARB (0.79 [0.77-0.80]) were significantly associated with lower mortality. Over 2 years of investigation, antithrombotics, corticosteroids, and antibiotics were the top medications for hospitalized patients with COVID-19. Trends in medication prescription varied based on various factors across the country. Medication prescriptions could potentially significantly impact the trends of mortality and hospitalization during epidemics, thereby affecting both health and economic burdens.

Prescription pattern analysis of Type 2 Diabetes Mellitus: a cross-sectional study in Isfahan, Iran

BackgroundPatients with Type 2 Diabetes Mellitus (T2DM) are at a higher risk of polypharmacy and more susceptible to irrational prescriptions; therefore, pharmacological therapy patterns are important to be monitored. The primary objective of this study was to highlight current prescription patterns in T2DM patients and compare them with existing Standards of Medical Care in Diabetes. The second objective was to analyze whether age and gender affect prescription patterns.MethodThis cross-sectional study was conducted using the Iran Health Insurance Organization (IHIO) prescription database. It was mined by an Association Rule Mining (ARM) technique, FP-Growth, in order to find co-prescribed drugs with anti-diabetic medications. The algorithm was implemented at different levels of the Anatomical Therapeutic Chemical (ATC) classification system, which assigns different codes to drugs based on their anatomy, pharmacological, therapeutic, and chemical properties to provide an in-depth analysis of co-prescription patterns.ResultsAltogether, the prescriptions of 914,652 patients were analyzed, of whom 91,505 were found to have diabetes. According to our results, prescribing Lipid Modifying Agents (C10) (56.3%), Agents Acting on The Renin-Angiotensin System (C09) (48.9%), Antithrombotic Agents (B01) (35.7%), and Beta Blocking Agents (C07) (30.1%) were meaningfully associated with the prescription of Drugs Used in Diabetes. Our study also revealed that female diabetic patients have a higher lift for taking Thyroid Preparations, and the older the patients were, the more they were prone to take neuropathy-related medications. Additionally, the results suggest that there are gender differences in the association between aspirin and diabetes drugs, with the differences becoming less pronounced in old age.ConclusionsAlmost all of the association rules found in this research were clinically meaningful, proving the potential of ARM for co-prescription pattern discovery. Moreover, implementing level-based ARM was effective in detecting difficult-to-spot rules. Additionally, the majority of drugs prescribed by physicians were consistent with the Standards of Medical Care in Diabetes.

The effect of Covid-19 pandemic on healthcare utilization in public vs private centers in Iran: a multiple group interrupted time-series analysis

BackgroundThe outbreak of Coronavirus in late 2019 and its continuation in the following years has affected all human societies, government organizations, and health systems. Access to health services is an important issue during crises. The present study aimed to investigate the effect of the Covid-19 pandemic on the consumption of health services in the public sector compared to the private sector in Iran.MethodsThe research population consisted of all insured individuals covered by Iran Health Insurance Organization in Fars province, which amounts to approximately 2,700,000 people. The required information including the utilization of laboratory, radiology, medicine, and hospitalization services was extracted on a monthly basis from February 2019 to February 2021. The Multiple Group Interrupted Time Series Analysis (MGITSA) was used for data analysis along with STATA.15 software.ResultsAccording to the findings of MGITSA, in the short-term, the utilization of private laboratory, radiology, medication, and hospital admissions had decreased by approximately 18,066, 8210, 135,445, and 1086 times, respectively (P < 0.05). In the long-run, the use of laboratory and radiology services had increased by about 2312 and 514 times (P < 0.05), respectively. The comparison between the public and private sectors showed that in the short-term, the use of radiology services decreased by about 12,525, while the use of medication increased by about 91,471 times (P < 0.05). In the long-run, the use of laboratory services decreased by about 1514 times (P = 0.076) and no change was observed in the other services utilization (in public relative to private centers).ConclusionsUtilization of health services in the public versus private centers, except for medication and hospitalization, significantly decreased in the short-term. However the utilization of most services returned to the usual trend in the long-term. The reduction in access to health services could impose a significant burden of various diseases, at least in the short-term, and increase health costs in the coming years.

Utilization Trend of Parenteral Antidiabetic Drugs in Type 2 Diabetic Patients Covered by Iran Health Insurance Organization from 2011 to 2030.

Exploring and analyzing the cost of medicines is an important tool for their management and planning. This study aims to analyze the utilization and costs of parenteral anti-diabetic medications during the past decade and predict the future trend of these medications from 2021 to 2031 in people that are covered by Iran Health Insurance Organization (IHIO). This study was based on secondary analysis of data routinely reported to IHIO from 2011 to 2019. For each drug, the Defined Daily Dose (DDDs) and DDDs per 1000 inhabitants per day were calculated for the last 9 years according to the WHO protocol. Then a regression analysis was used to predict the utilization trend of each drug for the following 10 years. The overall utilization of injectable antidiabetic drugs has constantly increased during the last nine years. This increasing trend is estimated to continue during the next decade. In Iran, the increase in the diabetic population and better access in the future will be the main reasons for the increase in the utilization of various insulins. The increasing trend of utilizing injectable anti-diabetic drugs in Iran might be partly due to new patients and partly because of improvement in patient access to new treatments. This also suggests that, compared to the average in the commonwealth countries, Iranian diabetic patients has faced lack of drug utilization in the past decade that is gradually reducing.

Network analysis of Iranian's health insurance ecosystem before and after the introduction of Universal Health Insurance law

IntroductionThe policy-making process in health reform is challenging due to the complexity of organizations, overlapping roles, and diversity of responsibilities. The present study aims to investigate and analyze the network of actors in the Iran health insurance ecosystem regarding the laws before and after the adoption of the Universal Health Insurance (UHI).MethodsThe present study was done by sequential exploratory mixed method research, consisting of two distinct phases. During the qualitative phase, the actors and issues pertaining to the laws of the Iranian health insurance ecosystem from 1971 to 2021 were identified through a systematic search of the laws and regulations section of the Research Center of the Islamic Legislative Assembly website. Qualitative data was analyzed in three steps using directed content analysis. During the quantitative phase, in order to draw the communication network of the actors in Iran's health insurance ecosystem, the data related to the nodes and links of the networks was collected. The communication networks were drawn using Gephi software and the micro- and macro-indicators of network were calculated and analyzed.ResultsThere were 245 laws and 510 articles identified in the field of health insurance in Iran from 1971 to 2021. Most of the legal comments were on financial matters and credit allocation, and the payment of premiums. The number of actors before and after the enactment of the UHI Law was 33 and 137, respectively. The Ministry of Health and Medical Education and the Iran Health Insurance Organization were found the two main actors in the network before and after the approval of this law.ConclusionsAdopting a UHI Law and delegating various legal missions and tasks, often with support to the health insurance organization, have facilitated the achievement of the law objectives. However, it has created a poor governance system and a network of actors with low coherence. Based on the results of the study, it is suggested to reduce actor roles and separate them for better governance and to prevent corruption in health insurance ecosystem. Introducing knowledge and technology brokers can be effective in strengthening governance and filling the structural gaps between actors.

Utilization and cost of outpatient services: A cross‐sectional study on the Iran Health Insurance Organization insurees in Fars province

Analyzing the utilization of health services is necessary for allocating the resources and planning the provision of health services. The present study aimed at investigating the utilization and cost of outpatient services and the factors affecting it among the insurees of the Iran Health Insurance Organization in Fars province in 2019. The study population consisted of all Iran Health Insurance Organization insurees in Fars province in 2019 (n = 2,618,973). The data on the utilization and cost of the services were extracted from the information systems of Fars Health Insurance Organization. The descriptive statistics of the utilization and cost of outpatient services were provided by gender, age, and type of insurance fund. The effects of different factors on the utilization and cost of various services were also investigated using univariate analysis as well as cross-sectional regression. The data analysis was done using EXCEL and STATA 15 software as well. The average utilization rates of laboratory, drug, and radiology services were 0.940, 0.945, and 0.108 prescriptions per year, respectively. In addition, the mean costs of laboratory, drug, and radiology services were $1.13, $7.44, and $2.26 per year, respectively. The univariate and multivariate analyses showed that gender, type of insurance fund, and age had significant effects on the utilization and costs of laboratory, drug, and radiology services (p < 0.05). The utilization and expenditure of outpatient services were higher among the elderly and women. To control the costs of insurance organizations, it is helpful to identify the effective factors. In addition, due to the increasing trend of aging in Iran, it seems necessary to periodically monitor the pattern of the elderly people's utilization of health services and to plan to increase sustainable resources for insurance financing in the coming years.

Effect of the chronic medication use on outcome measures of hospitalized COVID-19 patients: Evidence from big data.

Concerns about the role of chronically used medications in the clinical outcomes of the coronavirus disease 2019 (COVID-19) have remarkable potential for the breakdown of non-communicable diseases (NCDs) management by imposing ambivalence toward medication continuation. This study aimed to investigate the association of single or combinations of chronically used medications in NCDs with clinical outcomes of COVID-19. This retrospective study was conducted on the intersection of two databases, the Iranian COVID-19 registry and Iran Health Insurance Organization. The primary outcome was death due to COVID-19 hospitalization, and secondary outcomes included length of hospital stay, Intensive Care Unit (ICU) admission, and ventilation therapy. The Anatomical Therapeutic Chemical (ATC) classification system was used for medication grouping. The frequent pattern growth algorithm was utilized to investigate the effect of medication combinations on COVID-19 outcomes. Aspirin with chronic use in 10.8% of hospitalized COVID-19 patients was the most frequently used medication, followed by Atorvastatin (9.2%) and Losartan (8.0%). Adrenergics in combination with corticosteroids inhalants (ACIs) with an odds ratio (OR) of 0.79 (95% confidence interval: 0.68-0.92) were the most associated medications with less chance of ventilation therapy. Oxicams had the least OR of 0.80 (0.73-0.87) for COVID-19 death, followed by ACIs [0.85 (0.77-0.95)] and Biguanides [0.86 (0.82-0.91)]. The chronic use of most frequently used medications for NCDs management was not associated with poor COVID-19 outcomes. Thus, when indicated, physicians need to discourage patients with NCDs from discontinuing their medications for fear of possible adverse effects on COVID-19 prognosis.

Estimation and predictors of direct hospitalisation expenses and in-hospital mortality for patients who had a stroke in a low-middle income country: evidence from a nationwide cross-sectional study in Iranian hospitals

ObjectiveStroke is the second most prevalent cardiovascular disease in Iran. This study investigates the estimation and predictors of hospitalisation expenses and in-hospital mortality for patients who had a stroke in...

Prevalence of Hypothyroidism in Children and Adolescents of Fars Province (Southern Iran): A Nationwide Prescription Study, 2018-2019.

Hypothyroidism is the most common hormonal deficiency worldwide; however, there is limited data about its prevalence in the children and adolescents of the Middle East. The prevalence of hypothyroidism were calculated by dividing the number of patients purchasing levothyroxine in 1397 Solar-Hijri year (Correlate with March 2018-February 2019) by the population at risk (per 10000 persons). Data were collected from the Iran health insurance organization registration records and family physician databases of health vice-chancellor of Shiraz University of Medical Sciences. The present study shows that the prevalence of levothyroxine treated population aged under 18 years is 13 in 10000 in the Fars province and it is more common in females (17 in 10000 in females versus 9 in 10000 in males). This study also revealed that the prevalence of hypothyroidism was different in various age groups and increased in older children and adolescents after pubertal ages. Also, an increase in the female: male ratio of prevalence was more obvious during and after puberty. Our study showed that the prevalence of congenital hypothyroidism was 3/10000 in southern Iran. Also, the prevalence of hypothyroidism in children and adolescents was totally 13/10000 population, and this prevalence increased in older age and female gender. This prevalence was close to the data from iodine sufficient areas in Europe and the United States.

National geographical pattern of COVID-19 hospitalization, case fatalities, and associated factors in patients covered by Iran Health Insurance Organization

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.

Hospitalization Expenses and Influencing Factors for Inpatients with Ischemic Heart Disease in Iran: A Retrospective Study

Background: Ischemic heart disease (IHD) is the leading cause of death and disability worldwide and in Iran, which imposes a heavy financial burden both on patient’s family and society. Objectives: This study aimed to analyze the direct medical costs of inpatients with IHD and its influencing factors in Iran in 2020. Methods: The sample of this cross-sectional study included 41,357 patients with IHD selected from the hospital information system (HIS) of the Iran Health Insurance Organization from August 23, 2019, to June 20, 2020. The study used the claims data of these patients, which included their demographics, length of stay (LOS), intensive care unit (ICU) admission, hospital accreditation grade, hospital ownership type, and patient discharge status. The multiple linear regression model was employed to evaluate the relationship between hospitalization costs and the associated factors. All statistical tests were conducted at the significance level of P &lt; 0.05 using the R 3.6.3 software. Results: The mean age of patients was 63.95 ± 12.63 years old, and most of them were male (54.4%). The mean hospitalization cost per patient and per day was 586.42 ± 472.51 USD and 103.64 ± 100.29 USD, respectively. Moreover, the mean LOS was 4.92 days. Drugs and consumable medical supplies, as well as nursing and hoteling services, had the highest shares of hospitalization costs (29.54% and 29.4%, respectively). The hospitalization costs of patients with IHD were higher among men (β = 1.24), age 61 - 70 years (β = 1.38), LOS ≥ 5 (β = 2.92), ICU admission (β = 1.62), Iranian health fund (β = 1.21), and private hospitals (β = 1.91). Top-grade and first-grade hospitals had higher costs compared to grade 2 (β = 0.67), grade 3 (β = 0.35), and grade 4 (β = 0.72) hospitals. Deceased patients had also higher costs than patients with complete recovery (β = 0.63), relative recovery (β = 0.59), follow-up (β = 0.51), transfer to other medical centers (β = 0.44), and discharge against medical advice (DAMA) (β = 0.62). Conclusions: According to the results, shortening the LOS and controlling the high costs of drugs and consumable medical supplies are among the main strategies to reduce high hospitalization costs.

Preferences of people in choosing a family physician in rural areas: a qualitative inquiry from Iran.

Creating a stable and long-term relationship called 'longitudinality' between the population and general practitioners is crucial for the family physician program. The constant change of family physicians (FPs) can deteriorate longitudinality. This study aims to reveal what factors people usually consider when choosing a new FP or changing their current FP. A qualitative study with a thematic analysis approach was carried out in Ilam province, Iran, in 2019. Purposeful sampling with a maximum variation strategy was followed to select the key informants. We did 34 interviews with following groups: patients (rural residents); FPs; and experts from Iran Health Insurance Organization, Ilam University of Medical Sciences, and Health Network Development Center. Data were analyzed using a thematic analysis to identify and contextualize the preferences of people in choosing a FP in rural areas. All the processes related to data coding and emerging themes were carried out using MAXQDA 2012 software. The content of the interviews was categorized into 2 main themes, 6 sub-themes, and 39 codes. The first theme was 'family physician characteristics' including four sub-themes: general behaviors, social and physical characteristics, professional expertise, and pharmaceutical prescriptions. The second theme was 'health center' consisting of two sub-themes including location and physical features and properties of the health center. Some of the factors extracted from the interviews may have a different effect on the choice of people with different demographics. For instance, patients may have different ideas about the age, gender, years of medical practice, and finally, language and origin of the birthplace of FPs. Quantitative studies are needed to rank the factors identified in this study according to their significance for choosing FP and reveal patients' preferences for each factor.

Incremental Healthcare Resource Utilization and Expenditures Associated with Cardiovascular Diseases in Patients with Diabetes: A Cross-Sectional Study.

Background: Cardiovascular disease (CVD) is the most prevalent comorbid condition among patients with diabetes. The objective of this study is to determine the incremental healthcare resource utilization and expenditures (HRUE) associated with CVD comorbidity in diabetic patients.Methods: In a cross-sectional study, patients receiving antidiabetic drugs were identified using the 2014 database of the Iran Health Insurance Organization of East Azerbaijan province (Iran). The frequency of HRUE was the main outcome. Outcome measures were compared between diabetic patients with and without CVD comorbidity during 2014-2016. The generalized regression model was used to adjust for cofounders because of a highly skewed distribution of data. Negative binomial regression and gamma distribution model were applied for the count and expenditure data, respectively.Results: A total of 34,716 diabetic patients were identified, of which 21,659 (63%) had CVD comorbidity. The incremental healthcare resource utilization associated with CVD compared to non-CVD diabetic patients for physician services, prescription drugs, laboratory tests, and medical imaging was 5.9±0.34 (28% increase), 46±1.9 (46%), 12.9±0.66 (27%), and 0.16±0.40 (7%), respectively (all P<0.001). Similarly, extra health care costs associated with CVD comorbidity for physician services, prescription drugs, laboratory tests, and medical imaging were 10.6±0.67 million IRR (294.4±18.6 USD) (50% increase), 1.44±0.06 million IRR (40±1.6 USD) (32%), 8.36±0.57 million IRR (232.2±15.8 USD) (58%), 0.51±0.02 million IRR (14.1±0.5 USD) (24%), and 0.29±0.02 million IRR (8±0.5 USD) (22%), respectively (all P<0.001).Conclusion: CVD comorbidity substantially increases HRUE in patients with diabetes. Our findings draw the attention of healthcare decision-makers to proactively prevent CVD comorbidity in diabetic patients.

Mapping Drug Prescription, Polypharmacy, and Pharmaceutical Spending in Older Adults in Iran: A Multilevel Analysis Based on Claims Data.

Background: To date, comprehensive data on drug utilization in Iranian people are lacking. The purpose of this study was to graphically describe drug prescription, polypharmacy, and pharmaceutical spending in > 3 million Iranian elderly people. Methods: In this multilevel cross-sectional study, using administrative claims data provided by the Iran Health Insurance Organization (IHIO), we assessed drug claims and drug costs in 2018 in >3 million individuals living in Iran and who have been insured with health insurance (Bimeh Salamat). In particular, we analyzed the prevalence of polypharmacy and pharmaceutical spending use according to the annual Report of Iranian Health Insurance Organization. Multilevel ordinal logistic and multilevel beta regression models were used to analyze the data. Significance level was set as P ≤ .05 and CI at 95%. Results: Nationally, the mean number of drug prescriptions per patient was 1.46 (SD, 0.81). The mean number of prescribed drugs per patient was 4.32 (SD, = 3.04). The drug cost for each elderly patient was $6.86 (interquartile range (IQR), 12.26), with $4.96 and $1.76 for the insurance and the insured shares, respectively. For elderly women, the odds of polypharmacy (excessive and nonexcessive vs no polypharmacy) were 1.164 (95% CI, 1.142 to 1.186) times that of elderly men. In addition, in the spring season, the odds of polypharmacy were 1.274 (95% CI, 1.241 to 1.309) times that of the winter. Similarly, polypharmacy was strongly higher among patients who had noncommunicable diseases (OR, 2.174; 95% CI, 2.069 to 2.275 (P < 0.001)). Conclusion: The high prevalence of hyper prescription in Iran elderly people may indicate a need for interventions aiming at deprescribing drugs with an unfavorable benefit-risk profile. The best practice guidelines should be developed for improved medical practice in the prescription of medications for such a vulnerable population.

Change in health spending after implementation of a health transformation plan in Iran: an interrupted time series analysis

BackgroundHealth transformation plan (HTP) implemented in Iran since 2014 to improve accessibility and financial protection of patients. This study aimed to assess the impact of HTP on health spending in Iran.MethodsThis was a quasi-experimental design using Interrupted Time Series. All registered impatient records in Iran health insurance organization (IHIO) for the population of Mazandaran province (1,628,919 population in 2011), north of Iran from March 2010 to February 2019 were included. Data for three depended variables: hospitalization rate, average inpatient cost and inpatient expenditure per capita was extracted in 96 monthly observations. Segmented regression analysis was done in R version 3.6.1.ResultsHospitalization rate in 2010 was 6.6 in 1000 people and its level change was 0/799 immediately after HTP (P < 001). Post-reform level and trend changes for monthly average inpatient cost of registered admissions in IHIO were also significant (P < 001). IHIO inpatient expenditure per capita for 1,628,919 population in Mazandaran province was 24,436 Rials in 2011 and increased significantly immediately following HTP as 34,459 Rials (P < 001).ConclusionsThree important components of health spending including hospitalization rate, average inpatient cost and inpatient expenditure per capita were increased dramatically after HTP. Cost containment strategies and strengthening the preventive care initiatives is required to control the escalating trends of inpatient expenditure in Iran.

Consulting Services of Iran Health Insurance Organization During the COVID-19 Era

Consulting Services of Iran Health Insurance Organization During the COVID-19 Era