Background
Many countries have responded to the rising costs of healthcare by implementing some form of cost-sharing in which insured individuals pay part of the costs involved as an out-of-pocket (OOP) expense [
1,
2]. Cost-sharing payments (also referred to as users’ fees or patient contributions) aim to increase the awareness of healthcare costs among those insured, but may also have counter-effects. Cost-sharing payments discourage insured individuals from seeking care. In turn, not seeking care can have adverse health effects [
3]. Payments may consist of copayments (i.e., a fixed amount or a percentage of the costs per unit healthcare), deductibles (i.e., a predetermined amount paid by the individual after which the insurer covers all other costs) or a combination of both [
2]. Rice et al. [
4] have shown that OOP spending has risen or remained relatively high in many countries in the two last decades. In their analysis of high-income countries from the years 2000 onwards, they have observed that relatively high growth rates have been observed for those with historically low OOP spending (e.g., the Netherlands, France and the United Kingdom). Although smaller in relative growth rate, OOP spending has also increased among countries with historically high levels (e.g., the United States (US) and Switzerland) [
4]. These trends have shifted a larger share of the costs to the insured individuals which forces them to devote an increasing portion of their annual income to these expenses [
5,
6]. This shift should make those insured more aware of the costs involved which may, in turn, contribute to slowing down the rise of healthcare expenditures. However, this shift may also have "offset effects” as argued by Chandra et al. [
7]. The authors have found that, while the rise of cost-sharing payments for outpatient physician visits and prescription drugs had resulted in a decline in the use of these services among older individuals, the number of hospitalizations increased. The authors have observed substantial offsets for the sickest populations with chronic conditions [
7]. Hence, the policy shift towards more OOP spending may cancel out any costs initially saved due to cost-sharing if those insured forgo relatively cheap health services such as outpatient physician visits, but require additional and more expensive health services such as a hospitalization in the long run.
The rationale for implementing cost-sharing programs is underpinned by a large body of literature of which the RAND Health Insurance Experiment (RAND-HIE) has generated the methodological strongest evidence [
1,
2]. The RAND-HIE has shown that cost-sharing payments reduce the demand for healthcare. The RAND-HIE has also revealed that this reduction occurs both in services with relatively little or no medical benefit for a patient’s health as judged by physicians (hereafter referred to as
non-recommended healthcare), and in those with significant medical benefits (hereafter referred to as
recommended healthcare) [
8]. Hence, cost-sharing has often been described in literature as an effective yet blunt policy instrument [
9‐
11]: for instance, Baicker and Goldman have argued that such payments create effective incentives that influence the demand for healthcare, but do so in indiscriminate manner with respect to recommended and non-recommended healthcare [
11].
Besides studying OOP spending, Rice et al. [
4] have also investigated perceived cost-related problems affecting access to healthcare using country-specific consumer survey data of Commonwealth Fund. In these surveys, respondents have been asked if they have forgone healthcare such as hospital visits and medication due to costs. The US and Switzerland (i.e., countries with high OOP spending) rank as the top two, while France ranks third despite its relatively low OOP spending: in 2016, 33%, 22% and 17% of the respondents respectively, had forgone healthcare due to costs [
4,
12].
As certain individuals are more likely to struggle to afford rising cost-sharing payments, they are more prone to forgo healthcare because of these expenses [
4,
5]. For instance, previous research suggests that low-income groups are more price sensitive than those with a high income [
11]. The RAND-HIE have shown that the reduction of healthcare utilization due to cost-sharing have led to adverse health effects for those with the lowest income and in poor initial health [
8]. Not using recommended healthcare in particular may result in the "offset effects” as described above [
7].
Besides income, other patient characteristics might also play role and may even interplay with income, i.e., reinforcing or neutralizing each other’s effects. For example, on average and relative to high-income groups, low-income groups may be
more likely to forgo healthcare due to costs [
3]. However, among those with a low income, the amount of money available for discretionary spending may vary. Those with the smallest amount may be more likely to cut back healthcare due to costs than those with a larger amount of money available for discretionary spending. Hence, having more financial leeway may compensate for the effect of having a low income on the access to healthcare.
This study aims at gaining insights into the extent to which income explains individuals having forgone healthcare due to cost-sharing payments. Following a mixed methods sequential explanatory study design [
13], we first use quantitative data to assess the relative importance of income and other patient characteristics with respect to having forgone healthcare due to cost-sharing payments. We then employ qualitative methods while applying an interpretative approach to understand better and enrich the quantitative findings. Our insights may be used to inform policy makers who must carefully design cost-sharing programs in such a way that they reduce the use of non-recommended healthcare and stimulate that of recommended healthcare, while providing adequate financial protection to prevent impoverishment of vulnerable groups.
Dutch context
In this study, we have focused on the Dutch health system that similar to, for example, the US, is characterized by a relatively high healthcare expenditure: in 2018, as share of Gross Domestic Product: 10.0% (NL) and 16.9% (US) [
14]. In addition, the Dutch government has implemented provider competition [
15‐
17]. The reform of 2006 aims to stimulate effective competition between providers on price and quality, and to encourage patient choice. An important characteristic of the Dutch health system is universal access; it allows insured individuals to use healthcare—covered by the compulsory basic health insurance package—across
all hospitals. Health insurers are allowed to offer various health plans that cover the same basic package but with different conditions. Health insurers are obligated to accept all applications, are not allowed to differentiate the premium of a plan across individuals and are compensated by a risk equalization fund for differences in the risk profiles of their insured population. Insured individuals older than 18 years pay an income-dependent contribution—capped at a specific income and paid through the employer—to this fund and a flat-rate premium directly to their insurer, while all costs of those aged under 18 are paid by the government. Those with a low-income are compensated by a healthcare allowance. In 2015, approximately one-third of the Dutch population (36%) has received some allowance [
15]. According to Vermeend and Van Boxtel, the overall Dutch healthcare financing remains considered to be regressive after the 2006 reform [
18].
The content of the basic package is determined by the Ministry of Health. According to its guidelines, only services that are deemed necessary, effective, efficient and otherwise unaffordable for most citizens are covered. For most such services, the General Practitioner (GP) serves as gatekeeper, while a mandatory front-end deductible is applicable to all covered services with the exception of a specific few such as GP care [
15‐
17].
Rice et al. [
4] have described the share of individuals that have forgone healthcare due to costs in the Netherlands as relatively low compared to that of, for example, the US. However, the authors have observed a ‘
dramatic fluctuation’ in this measure for the Netherlands over time [
4]. In 2010, 6% of the Dutch respondents indicated they had forgone healthcare due to cost-sharing payments. In 2013, this number peaked at 22%, but then declined to 8% by 2016. Rice and coauthors ascribe this pattern to the introduction of the deductible in 2008 and its relatively fast year-to-year increases thereafter. While initially capped at 155 euros when implemented, the deductible amount gradually increased to 170 euros in 2011 (+ 9.7% in three years), then rapidly expanded to 220 euros in 2012 (+ 29.4%) and 350 euros in 2013 (+ 59.1%). In part due to political pressure, the deductible’s threshold increased with relatively small increments to 385 euros (+ 2.6% to + 4.2% per year) between 2014 to 2016 and has remained fixed since then [
4,
15,
19‐
21].
Discussion
Principal findings
In the quantitative phase, we assessed the relative importance of patient characteristics with regard to individuals having forgone recommended healthcare due to cost-sharing payments. The regression model indicated that having a higher income reduced the odds of having forgone recommended healthcare due to the deductible (ORs of higher income categories relative to the lowest income category (reference): 0.29–0.49). The model also revealed several significant relationships across various determinants. Being older, the presence of one or more chronic conditions, having a higher level of mastery and more financial leeway were all shown to be protective factors (i.e., decreased the odds of having forgone recommended healthcare due to the deductible), while having a moderate or good self-reported health showed to be a risk factor (i.e., increased the odds). Dominance analyses revealed that financial leeway was the most important patient characteristic: this determinant contributed the most (34.8%) to the model’s overall R2mf (i.e., 0.123), followed by income (25.6%), age (19.6%) and sense of mastery (8.9%). Relative to the main model, the results of additional models stratified by type of healthcare service and of the population weighted models (i.e., IPW models) revealed no meaningful differences.
In the qualitative phase, we conducted interviews to understand and enrich the quantitative findings. Four main themes were distinguished that affected the patient’s decision whether to use healthcare: (1) financial barriers, (2) structural barriers related to the complex design of cost-sharing programs, (3) individual considerations of the patient, and (4) perceived lack of control regarding treatment choices within a given treatment trajectory. Furthermore, “having forgone healthcare” seemed to have some negative connotation as the topic of the interview had to be reframed using more neutral terms.
Possible explanations and comparison with the literature
Our quantitative findings indicating the importance of financial leeway and income, correspond with previous studies that have linked factors such as the price of a given healthcare service, available household resources and income to the response in demand for healthcare [
3,
36,
37]. Our quantitative findings also correspond with our qualitative findings as analyses distinguished financial factors as a relevant theme. In addition, and in line with literature [
3,
8,
11,
38], we found a stronger response to cost-sharing among low-income interviewees relative to those with higher incomes.
Moreover, dominance analyses revealed that financial leeway was more important than income. On the one hand, this implies that an individual who is able to save some money for future health expenses despite having a low income, is less likely to forgo healthcare due to these expenses, and vice versa. On the other hand, this finding reflects the impact that unexpected expenses (e.g., due to multiple cost-sharing payments) or a sudden drop in income (e.g., being self-employed with no clients) may have on an individual’s financial situation and, in turn, they forgo healthcare due to the costs involved. These findings correspond with our qualitative findings. As regular users of healthcare, interviewees often had to pay the full deductible. To minimize the impact of paying such deductibles on their financial leeway, most interviewees had arranged to pay by monthly installments. Having to pay the deductible in itself therefore played a minor role.
In line with literature [
37,
39], our qualitative analyses distinguished the complexity of cost-sharing programs as a relevant theme, and also indicated that its relevance differed across educational level. Interviewees with a low to moderate educational levels had more difficulty in determining in advance whether, and if so, how much they had to pay for a given healthcare service. Unsure or unable to determine whether they could afford these costs, interviewees decided not to use the given healthcare service or stopped any future use. In contrast, the interviewee with a higher educational level was able to navigate effectively within the insurance plan.
Among the remaining determinants, being older, having one or more chronic conditions and having a higher level of mastery were protective factors, while having a better self-reported health level was a risk factor. It is reasonable to assume that, given their age and previous experience with the use of healthcare, older individuals and those with chronic condition are more likely to be aware of the potential adverse effects -that having forgone recommended healthcare may result in- compared to those who are younger or who have no chronic condition. Hence, they may be keener on maintaining their current level of health and thus be more incentivized to use the healthcare as recommended.
Regarding sense of mastery, our findings are in line with the literature: previous research has linked higher levels of mastery to better health levels, and suggests that those with such high levels are more capable (1) of effectively managing their health-related problems and (2) of using coping strategies to deal with these problems [
40]. This mechanism also supports our qualitative findings as some interviewees had forgone healthcare because they had difficulties accepting their chronic conditions and the resultant problems.
Regarding self-reported health, our qualitative findings may provide an explanation. If the perceived medical benefits were too small considering their health level, interviewees would not use the given healthcare service despite their physician’s judgement. More specifically, having a better state of health may reduce the perceived medical benefits of the given healthcare service that, in turn, leads individuals to forgo healthcare. This post-referral consideration may also explain why many eligible individuals have declined to participate in our interviews as they would not classify themselves as individuals who forgo healthcare. Previous research has indicated that the term “
having forgone healthcare” is often perceived as stigmatizing as it suggests that the individual acted irresponsibly and thus should be blamed for not using healthcare [
41]. Hence, the seemingly rational consideration that individuals give to the matter after being referred, contradicts the common opinion that those who forgo healthcare are irresponsible.
Furthermore, as treatment trajectories are generally comprised of multiple health services, interviewees often perceived the use of health services as part of this trajectory as compulsory. Consequently, they may reconsider to follow up on a referral if they believed this could lead to a full treatment trajectory. Our findings are in line with literature. Lippiett et al. have shown in their review that treatment trajectories for lung cancer have been described as demanding in terms impact on everyday life (e.g., frequent hospital visits) [
42]. According to Sav et al., when patients perceive the burden of treatment as high, non-adherence to treatment is the most likely consequence to occur [
43].
Implications
Our findings have several implications. First, the observed importance of financial leeway indicates that solely adapting cost-sharing programs to income levels to prevent certain individuals from seeking recommended healthcare due to the costs involved (e.g., lower payments for low-income groups) will only get one so far. Individuals who are faced with multiple expenses due to frequent use of healthcare find that they are left with little financial leeway. To prevent such accumulation of expenses, policy makers need to adopt a broader perspective in which they consider
all healthcare expenses that an individual may have at a given time and design their cost-sharing programs accordingly. Moreover, as cost-sharing payments reduce the demand for both recommended and non-recommended healthcare [
8,
11], policy makers should follow the design principles of value-based health insurance that directly link these payments to the ‘
value’ of the given healthcare service [
44,
45]. More specifically, healthcare services that yield high value (i.e., substantial medical benefits for a patient’s health relative to their costs) should be subject to lower or no cost-sharing payments, while those with little value should be levied with higher payments. Policy makers should also consider the administrative costs
3 involved [
46]. An all-payer claims processing data infrastructure, as implemented in the Netherlands, may help to limit administrative costs. In the Netherlands, all invoices between hospitals and payers are sent to and processed by a nation-wide system (i.e., VeCoZo). Processing individually adapted cost-sharing payments through the same nation-wide system should help to reduce the administrative burden.
Second, the relevance of the complexity of cost-sharing programs warrants additional efforts aimed at improving the transparency of these programs. For example, relative to a front-end deductible, flat-fee copayments paid at point of care offer individuals clear and immediate information on the required payments in advance; in a hypothetical decision context, Salampessy et al. [
22] have demonstrated that such payments stimulate adherence to recommended healthcare.
Third, policy makers and physicians should be aware that various personal considerations and the perceived compulsory use of healthcare play a role in whether an individual uses healthcare. It underlines the importance of shared-decision making; a process that Elwyn et al. [
47] have defined as “
an approach where clinicians and patients make decisions together using the best available evidence” (p971). Policy measures that improve patient-centered care in clinical practice may help physicians to address these issues during consultations.
Strengths and limitations
A strength of our study is the use of an explanatory sequential study design. The mix of quantitative and qualitative methods enhances the quality of our inferences and leads to a deeper understanding of our findings [
48]. In addition, we followed principles of good practice in qualitative research [
34]. For example, we sought feedback on the summary of the interview (member check) to improve the credibility of our findings. Also, we collected and analyzed data iteratively, and discussed the findings with multiple researchers; all of which improved the dependability and confirmability of our findings.
Certain limitations to our study should however be noted. With regard to the quantitative phase, our sample was not representative of the whole Dutch population. Although IPW models based on weighted representative sample in terms of age, gender and educational level produced similar results, we did not have population data for other relevant characteristics such as health and sense of mastery. However, as our sample consisted of regular users of healthcare who have faced cost-sharing payments, their observed responses may resemble their decision behavior in real-life settings more closely, which improves the internal validity of our findings.
With respect to the qualitative phase, we did not achieve data saturation due to the small number of interviews. Also, due to this small number we may have missed other relevant perspectives such as those of young people. Both aspects reduce the transferability and dependability of our findings [
34]. While more interviews conducted among a wider sample is required to capture all relevant themes (i.e., a full-scale qualitative study) and achieve data saturation, we believe that our qualitative data is rich enough considering its explanatory purpose: most quantitative findings have been supported by one or more subthemes.
Furthermore, recent studies have demonstrated that factors related to the COVID-19 pandemic affect a patient’s decision to use health care: for example, Karacin et al. have shown that fear for COVID-19 has reduced the adherence to chemotherapy among patients with cancer [
49]. However, as our data was collected prior to the COVID-19 pandemic, we could not consider the effects of this pandemic. It remains unclear to which extent a factor such as fear for COVID-19 would have affected our quantitative findings. Regarding our qualitative findings, we expect that fear for COVID-19 will be distinguished as an additional (sub)theme.
Conclusions
Our findings show that financial leeway is more important than income with respect to having forgone recommended healthcare due to cost-sharing payments. Besides (1) financial barriers related to the health insurance plan, other factors such as (2) structural barriers related to the complex design of cost-sharing programs, (3) individual considerations of the patient and (4) the perceived lack of control regarding treatment choices within a given treatment trajectory, also play an important role. Our findings imply that, if cost-sharing programs focus solely on lowering these payments, they will only partly succeed in their goal of preventing certain individuals from seeking healthcare due to costs involved. Our study furthermore underlines the need for a broader perspective in the design of cost-sharing programs, the need to improve the transparency of these programs and the importance of shared-decision making.
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