Utilization of primary and secondary medical care among disadvantaged populations: a log-linear model analysis.

AIM: We examined how, where an overall population is covered by universal health insurance, characteristics of disadvantaged populations interact to influence inequality in primary and secondary medical care utilization. SUBJECTS & METHODS: Disadvantaged populations, the focus of the study, were defined as populations who have lower socio-economic status (SES), who are elderly and/or reside in a peripheral area. Data from the 2009 Israeli National Health Survey were analysed using log-linear models to estimate utilization of medical care. RESULTS: The main findings were: a) pro-poor utilization of primary medical care among elderly populations, with higher odds ratios for low SES populations in the periphery; (b) lack of interaction between SES and primary medical care utilization among younger populations, between SES and secondary medical care utilization among the elderly and pro-rich utilization of secondary medical care among younger populations who did not regularly visit general practitioners (GP); (c) the odds ratios of secondary medical care utilization increased as SES decreased for both elderly and younger populations who also regularly visited a GP. CONCLUSION: Potential policy implications for disadvantaged populations, regarding possible inequality in primary and secondary medical care utilization, can be drawn using log-linear model analysis of interactions among characteristics (SES, age, location) of disadvantaged populations.

The impact of preventive health behaviour and social factors on visits to the doctor.

BACKGROUND: The aim of this study is to examine the joint impact of preventive health behavior (PHB) and social and demographic factors on the utilization of primary and secondary medical care under a universal health care system, as measured by visits to the doctor, who were categorized as either a General Practitioner (GP) or Specialist Doctor (SD). METHODS: An ordered probit model was utilized to analyze data obtained from the 2009 Israeli National Health Survey. The problem of endogeneity between PHB factors and visits to GP was approached using the two-stage residuals inclusion and instrumental variables method. RESULTS: We found a positive effect of PHB on visits to the doctor while the addition of the PHB factors to the independent variables resulted in important changes in explaining visits to GP (in values of the estimates, in their sign, and in their statistical significance), and only in slight changes for visits to SD. A 1% increase in PHB factors results in increasing the probability to visit General Practitioner in the last year in 0.6%. The following variables were identified as significant in explaining frequency of visits to the doctor: PHB, socio-economic status (pro-poor for visits to GP, pro-rich for visits to SD), location (for visits to SD), gender, age (age 60 or greater being a negative factor for visits to GP and a positive factor for visits to SD), chronic diseases, and marital status (being married was a negative factor for visits to GP and a positive factor for visits to SD). CONCLUSIONS: There is a need for allowing for endogeneity in examining the impact of PHB, social and demographic factors on visits to GP in a population under universal health insurance. For disadvantaged populations with low SES and those living in peripheral districts, the value of IndPrev is lower than for populations with high SES and living in the center of the country. Examining the impact of these factors, significant differences in the importance and sometimes even in the sign of their influence on visits to different categories of doctors - GP and SD, are found.