Prediction of COVID-19 patients' participation in financing informal care using machine learning methods: willingness to pay and willingness to accept approaches.

Background: Informal care plays an essential role in managing the COVID-19 pandemic. Expanding health insurance packages that reimburse caregivers' services through cost-sharing policies could increase financial resources. Predicting payers' willingness to contribute financially accurately is essential for implementing such a policy.

Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study.

Background: There is limited evidence on the prevalence and socioeconomic inequality in informal payments (IP) of households in the Iranian health system. This study was conducted to investigate the prevalence of IP and related socioeconomic inequalities among Iranian households in all provinces.

Method: Data on Household Income and Expenditure Surveys (HIES) for 91,360 households were used to examine the prevalence and inequality in informal health sector payments in the years 2016 to 2018.

Which patients bring the most costs for hospital? A study on the cost determinants among COVID-19 patients in Iran.

Background: Accurate information on the cost determinants in the COVID-19 patients could provide policymakers a valuable planning tool for dealing with the future COVID-19 crises especially in the health systems with limited resources.

Objectives: This study aimed to determine the factors affecting direct medical cost of COVID-19 patients in Hamadan, the west of Iran.

Methods: This study considered 909 confirmed COVID-19 patients with positive real-time reverse-transcriptase polymerase-chain-reaction test which were hospitalized from 1 March to 31 January 2021 in Farshchian (Sina) hospital in Hamadan, Iran.

Socio-economic inequality in reported dental self-care behaviour among Iranian households: A national pooled study.

Background: Setting out effective prevention strategies in dental diseases needs recognition related factors of the prevention behaviours and targeting the most disadvantaged groups in the term of dental hygiene. This study aimed to investigate socio-economic inequality in the dental self-care status (DSS) of Iranian households and decompose the measured inequality into its contributors.

Method: In this cross-sectional study, pooled data were extracted from Households Income and Expenditure Surveys (HIESs) conducted in Iran from 2012 to 2017.

Construction data mining methods in the prediction of death in hemodialysis patients using support vector machine, neural network, logistic regression and decision tree.

Objectives: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldwide. Detecting survival modifiable factors could help in prioritizing the clinical care and offers a treatment decision-making for hemodialysis patients. The aim of this study was to develop the best predictive model to explain the predictors of death in Hemodialysis patients by data mining techniques.

Decomposition of Health Inequality Determinants in Shiraz, South-west Iran.

Background: Despite the enhancement in health outcomes worldwide, health inequity and inequality is one of the most relevant topics both for health policy and public health. This research was designed to decompose the health inequality of people living in Shiraz, south-west Iran.

Methods: Data were obtained from a multistage-sample survey conducted in Shiraz from April to May 2012, to find determinants of health related quality of life (HRQoL).

Horizontal inequity in access to outpatient services among Shiraz City residents, Iran.

Background: lack of access to health services has been mentioned as one of the main causes of health inequity in health system. The aim of this study was to measure horizontal inequity in access to outpatient services in Shiraz.

Methods: This household survey was conducted among 1608 participants above 18 years in Shiraz in 2012.