This is a cross-sectional study. We conducted a secondary analysis of the data obtained from the Iranian Healthcare Utilization Survey (IrUHS) of 2016. The IrUHS included all individuals in both ordinary and group households living in urban and rural areas of Iran. The planned sample size in this survey was 22 470 households comprising 76674 individuals. IrUHS consisted of two questionnaires entitled Household Questionnaire (to collect household socio-demographic and healthcare needs information) and Individual Questionnaire (to gather detailed information of healthcare utilization). The data collection was based on face-to-face interviews with the surveyed individuals .
The participants were asked about their outpatient and inpatient healthcare needs in the household questionnaire. Respectively, 2 weeks and 12 months preceding the interviews were considered as the recall period for outpatient and inpatient healthcare needs. The participants with a history of healthcare needs were asked about the utilization of healthcare services in the individual questionnaire. The respondents older than 15 years who had outpatient healthcare needs (13005 individuals) were included in this research.
Measuring Subjective Unmet Need And Its Reasons
Subjective unmet need (SUN) in this research was indirectly defined by the following question: "Was there any time during the past 2 weeks that you utilized outpatient healthcare services?” Two groups of respondents were formed; those who used healthcare services and those who did not. In the latter group, those who had self-medication were considered as the individuals with met healthcare needs and were added to the former. Hence, the individuals with unmet healthcare needs were considered those who did not use formal healthcare services and did not have a history of self-medication in the last two weeks.
Those who did not utilize healthcare services were asked about the reasons for not using the services. This was performed through ten questions in the individual questionnaires. According to the previous literature on the reasons for unmet healthcare, the answers to these questions were categorized into three main reasons for unmet healthcare needs. The first group of responses decreased the accessibility of health care services through lower affordability (Accessibility). The second group of responses dealt with the waiting list and availability of healthcare services (Availability). Similar to previous studies [6, 18], the unmet need due to accessibility and availability accounted for the responsibility of the health system. The third group was about the personal circumstances of the responders such as the postponement of healthcare needs due to lack of free time or other circumstances (Acceptability).
Andersen's Behavioral Model of Health Services Use was used to explore potential determinants of subjective unmet need. This model assumes that utilization of healthcare services is a function of predisposing, enabling and need factors [19, 20]. According to the model, predisposing factors include demographic characteristics such as age, sex, marital status and family size, plus social structure such as employment, education and ethnicity. Moreover, material resources such as income, health insurance and distance from healthcare services were considered as enabling factors. Severity of illness, self-rated health and multiple chronic conditions were also considered as the need factors in this model .
Considering Anderson’s model, predisposing factors included in this study were sex (male/female), age (< 30, 30–59, and ≥ 60 years), marital status (married/unmarried), educational status (illiterate, primary, secondary, and diploma or higher), and employment status (employed/unemployed). On the other hand, area of residence (urban/rural), economic status (poorest, poor, middle, rich and richest), and health insurance (basic and complementary) were included as enabling factors. Furthermore, the number of outpatient healthcare needs (one/two or more) was used as a need factor.
The principal component analysis was used to create economic status by using asset data such as having a separate kitchen, central heating, telephone usage, computer, Internet access at home, owning a motorcycle or a car, and whether the person owned a house or not. This statistical scheme has been widely used in previous studies [19, 21, 22]. The Pearson's chisquare test was also used to analyze the differences between the respondents with unmet and met healthcare needs. A logistic regression analysis with maximum likelihood was used to analyze the determinants of unmet healthcare needs and their major reasons. We also calculated the odds ratios (OR) and 95% confidence intervals (CIs). The results were considered statistically significant when the p-value was ≤ 0.05. The analysis was performed by using the Stata/SE version 12.0.