Our results partially confirmed the hypotheses investigated in this study. We found that increases in geographic variation for all-cause mortality and cancer death following cancer diagnosis, mainly during the last years of the study. In addition, only a minority of districts in the center of Israel and the metropolitan areas (1/4 and 1/3, respectively) were associated with increased risk of all-cause mortality, in contrast to the majorities of districts in the north (4/5) and south (1/1). Nevertheless, the risk of mortality was attenuated in various districts between the 1998–2000 and 2001–2003 periods.
The mitigated geographic variation for all-cause mortality following cancer diagnosis among districts up to 2003 may be explained by the introduction of National Health Insurance [11, 16]. Since 1995, Israel has a National Health Insurance Law, which results in improved health system beyond universal health coverage [11]. Citizens choose from a few competing non-profit health plans, which provide a broad package of benefits stipulated by the government [11]. Indeed, the Israeli health care system has become quite efficient; despite spending a relatively low proportion of the gross domestic product on health care (less than 8%), the country’s health variables are comparable to those of other developed countries [11].
The increased geographic variation of mortality risk observed since 2004 may be explained by several factors. Improvement in survival following cancer diagnosis, together with the introduction of novel therapies [7], have challenged the health system. These advances require repeated visits to cancer centers and efficient integration of hospital, community, and professional primary care services. In addition, the remarkable strides in cancer treatment, which have yielded improvements in patient outcomes, have generated increasing costs [17]. Despite health basket in Israel regarding cancer treatments is one of the richest and best globally, the financial burden of cancer treatment is beyond the price of specific medication. Indeed, it includes advanced molecular analyses, imaging technique, consultation with multi-disciplinary teams and delaying in approval of novel medications of a numerous months by the health basket’s committee. These expenditures may not be covered by the health basket. Consequently, the financial burden has been shifted to patients, which has resulted in higher out-of-pocket expenses [17]. Actually, higher residential socioeconomic score was associated with decreased risk for death following cancer diagnosis in the current study (Additional file 1: Table S3). Indeed, developing financial difficulties during cancer illness has been associated with an increased risk of death in Italy [18]. This dismal outcome was reported although that most of the clinical pathway of cancer patients is covered by the Italian public health system, including inpatient and outpatient services and drugs [18]. In parallel, over the study period, reliance on private financing has grown, with potentially deleterious effects; the proportion of private financing that contributes to total health expenditure has sharply increased from 32% in 1995 to 39% in 2012 [11, 19, 20]; this change may have played a dominant role in the growing geographic variation among the study population.
Our current results may also be explained by increased geographic variation of mortality risk unrelated to cancer diagnosis during the lasts years of the study. However, this hypothesis is not supported by the similar trend which was seen in cancer mortality (Table 3). In addition, a disproportionally high incidence of highly aggressive malignancies during the last years of the study, in some districts may explained the study’s results. Indeed, heterogeneity in several variables among districts may result in changes in the incidence of lung cancer and other aggressive, smoking-related malignancies over the study period. Smoking cessation was associated with multiple variables, include age, marital status [21], ethnicity, and education levels [21, 22]. Consequently, taking into account the long delay between smoking and a lung cancer diagnosis, the changes we observed may have reflected changes that took place during the twentieth century.
Increased risk of mortality following a cancer diagnosis was mainly observed among non- metropolitan districts and districts located outside the center of Israel. Israel is a small country; it is approximately 470 km long, and 135 km at its widest point. The districts located in the central region extend approximately 80 km in length. The current results were consistent with previous publications [23, 24], which highlighted the worst health outcomes among cancer patients that lived in non-metropolitan regions. For example, among patients diagnosed with glioblastoma multiforme, those living in rural zones had larger tumor sizes at diagnosis, lower rates of radiotherapy, and worse survival, compared to patients living in urban zones, even after controlling for potential confounders [22]. Similarly, the present study emphasized the poor outcomes of patients in peripheral districts. Furthermore, these poor outcomes were seen not only among non-metropolitan districts but also in the peripheral metropolitan (BeerSheva district). Consequently, these dismal outcomes which were reported in previous studies were validated in a relatively small country with highly appreciated health services [11, 16], including National Health Insurance coverage [11, 16].
The current study had several strengths. The high-quality dataset and linkage to highly validated databases (Israel Cancer Registry and the Cause of Death File) supported the internal validity of the study. The population-based inception cohort supported the study’s external validity. Furthermore, our exclusion of malignancies associated with screening program (breast, colorectal, prostate, and cervical cancers) reduced the risks of a lead-time bias and a length-time bias. Similar results were seen also in the analyses which assessed cancer mortality, as opposed to analyses which include also malignancies associated with screening program. These findings suggest that the present study assesses the impact of geographic variations on the care of cancer patients rather than the geographic variation of cancer incidence and the implantation of screening programs.
Our study also had some limitations. Because information on staging was only partially available, it was not included in the current analyses. Consequently, we could not assess whether the distribution of late diagnoses among the districts might have explained the current results. In addition, we lacked information on suggested treatments and compliance. Thus, some uncertainty in our results might be due to disparities in treatment options and compliance among the districts. In addition, residual confounding may also have influenced our findings. For example, data on competing comorbidities and functional status were lacking. However, these limitations did not impair the validity of the study results. Lastly, the current study emphasizes geographic variation in mortality following cancer diagnosis, rather than cancer risk and compliance to screening programs which may have greatest impact on cancer morbidity and mortality. Taking into account the high prevalence of cancer, our results may provide important information for those caring for cancer patients and planning health services.
