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Impact of NHI copayment adjustments on healthcare seeking behavior: the mediating role of health facility identification

BMC Health Services Research volume 24, Article number: 1148 (2024) Cite this article

Abstract

Objective

This study investigates the impact of healthcare consumers’ involvement, price perception, and attitude toward National Health Insurance (NHI) copayment adjustments on their healthcare-seeking behavior, focusing on the mediating role of health facility identification.

Methods

A questionnaire survey was conducted among outpatient customers in Taiwan from October 2023 to March 2024, resulting in 746 valid responses. The survey included demographic variables, involvement, price perception, attitude, health facility identification, and healthcare-seeking behavior. Data were analyzed using descriptive statistics, correlation analysis, and multiple regression analysis with SPSS 20.0.

Results

The study found that involvement, price perception, and attitude significantly influence healthcare-seeking behavior. Health facility identification was identified as a significant mediator in the relationship between copayment perception and healthcare-seeking behavior. The regression analysis also highlighted the impact of demographic factors such as age, education level, marital status, and annual income on healthcare-seeking behavior. The path model illustrated the complex interplay between perceptual factors and their influence on healthcare-seeking behavior.

Conclusion

This study emphasizes the importance of consumer involvement, price perception, and attitude in shaping healthcare utilization patterns. Health facility identification plays a crucial mediating role, suggesting that stronger patient-provider relationships can mitigate potential negative impacts of copayment adjustments. Policymakers and healthcare providers should enhance patient engagement, foster strong patient-facility identification, and provide targeted support for vulnerable groups to ensure equitable access to healthcare services despite copayment changes.

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Introduction

Since the implementation of National Health Insurance (NHI) in Taiwan in 1995, the public has enjoyed high accessibility to healthcare services. However, the system has faced challenges such as a lack of an effective referral system. To address these challenges and promote a tiered healthcare system, the Taiwanese government began in 2017 to limit the outpatient volume and growth of minor illness services in medical centers and regional hospitals. The policy stipulated that outpatient visits in these hospitals should not exceed 90% of the 2016 level, with excesses not covered by NHI [1]. Consequently, some hospitals resorted to upcoding minor illness diagnoses to avoid these restrictions [2].

In 2018, the Ministry of Health and Welfare further announced the NHI reimbursement cap for hospital departments, aiming to implement a tiered healthcare and referral system by reducing outpatient services in regional and higher-level hospitals by 2% in 2018, with a goal of a 10% reduction over five years [3]. However, the outbreak of COVID-19 and flu in 2019 overwhelmed emergency departments in major hospitals, leading to long waiting times for COVID-19 PCR testing. Thus, on January 28, 2019, the NHI Administration relaxed the outpatient reduction policy for regional and higher-level hospitals [4].

Currently, the NHI copayment design employs a fixed amount system. With an aging population and increasingly complex disease patterns, the proportion of copayments to total medical expenses has been decreasing annually, currently accounting for only about 6.5% [5]. In response, the NHI Administration proposed a copayment adjustment scheme based on user charges, announced on March 16, 2022, and initially scheduled for implementation on May 15, 2022. However, due to the peak of the COVID-19 pandemic and significant social pressures, the implementation of this copayment adjustment was postponed [6, 7].

In addition to factors directly related to healthcare, price perception plays a critical role in shaping healthcare-seeking behavior. Price perception refers to how consumers perceive the cost associated with services, which can significantly impact their decision-making processes and satisfaction with the services received. In the context of healthcare, price perception influences patients’ willingness to seek care, particularly when out-of-pocket expenses are involved. Studies have shown that higher perceived costs can deter patients from seeking necessary medical treatment, even in systems with comprehensive insurance coverage. For instance, cost-sharing mechanisms, such as copayments, can significantly reduce the utilization of healthcare services [8]. Increased copayments for prescription drugs have also led to reduced use of essential hypertension or diabetes services [9]. Similarly, increased patient cost-sharing can exacerbate socioeconomic disparities in healthcare access [10]. Changes in payment structures, such as copayment adjustments, could significantly alter patient behavior, leading to a reduction in healthcare service utilization [11]. This evidence underscores the importance of understanding price perception in the context of healthcare policy and its impact on patient behavior.

Consumer behavior theories provide a framework for understanding these dynamics. For instance, the Theory of Planned Behavior suggests that an individual’s intentions and behaviors are influenced by their attitudes towards the behavior, perceived norms, and perceived control over the behavior [12]. In healthcare, this translates to how patients view the importance and affordability of medical care, as well as their perceived ability to pay for services. Studies have shown that patients’ attitudes towards the cost and perceived necessity of treatment can significantly influence their healthcare-seeking behavior. Behavioral economics principles, including price framing and perceived affordability, affect decision-making in healthcare settings [13]. Emotional factors and cognitive biases also play a crucial role in how patients perceive healthcare costs and make treatment decisions [14]. By understanding these factors, healthcare providers and policymakers can better anticipate patient responses to copayment adjustments and design interventions that minimize barriers to accessing care.

After the COVID-19 pandemic subsided, the NHI Administration resumed the copayment adjustment policy in 2023, announcing the implementation of the revised copayment scheme for outpatient drugs and emergency services starting July 1 [15]. This scheme included adjustments to emergency copayments based on hospital levels: NTD750 for medical centers, NTD400 for regional hospitals, and NTD150 for local hospitals and clinics. For low-income households and individuals with disabilities, the copayments were adjusted to NTD550 for medical centers, NTD300 for regional hospitals, and NTD150 for local hospitals and clinics [15]. These increased copayments are expected to significantly impact the operation of major hospitals.

Healthcare-seeking behavior (HSB) involves patients’ decisions on where to seek medical care [16,17,18,19]. HSB is influenced by a variety of factors including patients’ health conditions, socio-economic and demographic characteristics, healthcare quality, availability, accessibility, and the pathways chosen for seeking medical care [20]. Globally, tiered healthcare systems aim to provide treatment for common illnesses with mild to moderate severity at lower-level institutions, while higher-level institutions focus on specialized care, ensuring equitable access to medical services [12]. However, despite the presence of such systems in many countries, a significant number of patients often bypass lower-level institutions and directly seek treatment at higher-level institutions [21, 22].

Key determinants of HSB include socio-economic factors, cultural background, gender differences, involvement, attitudes, and health facility identification [23]. Previous research has shown that consumer behavior, including involvement and price perception, significantly influences decision-making processes [24, 25]. The perceived relevance of an issue to oneself [26] or the ability to evoke personal engagement [19] also plays a crucial role. In the context of healthcare, price perception influences patient satisfaction and the decision to seek medical care [27,28,29]. While empirical measures of copayment adjustments are essential, public attitudes toward these adjustments should not be overlooked. The “Knowledge-Attitude-Practice” (KAP) model in behavioral theory suggests that individuals form expected responses after acquiring information related to behavior, which eventually manifests in behavior consistent with their attitudes [30].

Despite the extensive research on copayments, few studies have explored the impact of health facility identification on copayment policy adjustments and healthcare-seeking behavior. For instance, it has been highlighted that hospital brand image significantly influences patient loyalty and satisfaction, particularly in the context of quality healthcare delivery [31]. Additionally, studies have suggested that the way hospitals are perceived can play a critical role in patient decision-making, including responses to financial aspects like copayment adjustments. Understanding how these factors interact in the context of Taiwan’s healthcare system is crucial, given the potential implications for patient access to care and hospital operations. Therefore, this study aims to thoroughly investigate the effects of new copayment policies on public healthcare-seeking behavior, evaluate the actual impacts of these policies, and provide valuable insights for government departments and hospital management.

Materials and methods

Theoretical background and hypotheses development

The theoretical foundation for this study is grounded in several well-established theories and models in consumer behavior and healthcare research. The Theory of Planned Behavior (TPB), proposed by Ajzen, posits that an individual’s behavior is determined by their intention to perform the behavior, which is influenced by attitudes, subjective norms, and perceived behavioral control [12]. In the context of this study, TPB provides a framework for understanding how patients’ attitudes towards copayment adjustments, their perceived control over healthcare costs, and societal norms may influence their healthcare-seeking behavior.

Involvement refers to the level of personal relevance or interest that a consumer perceives in a particular issue. In healthcare, higher involvement levels may lead to more informed and deliberate decision-making processes [24].

Price Perception relates to how consumers perceive the cost associated with healthcare services, which can significantly affect their satisfaction and willingness to seek care. Previous studies have shown that perceived high costs can deter patients from seeking necessary medical treatment [8, 32,33,34]. In the context of healthcare-seeking behavior, price perception is crucial as it directly influences patients’ decisions on whether to pursue medical care. For instance, when patients perceive healthcare costs as too high relative to the expected benefit, they may delay or avoid seeking necessary treatment, which can negatively impact their health outcomes. Conversely, when healthcare costs are perceived as reasonable or offering good value, patients are more likely to seek timely care, leading to better health outcomes. By understanding how price perception affects consumer behavior in healthcare, we can better comprehend patient responses to copayment adjustments and tailor policies to encourage more proactive healthcare-seeking behaviors.

Health Facility Identification reflects the degree to which patients identify with and prefer certain healthcare facilities, which can be influenced by factors such as facility reputation, perceived quality of care, and personal experiences. The identification with a healthcare facility can moderate the relationship between copayment adjustments and healthcare-seeking behavior, as patients may be more willing to continue using preferred facilities despite increased costs [31].

Based on these theoretical considerations, we propose the following hypotheses:

  • H1: There is a positive relationship between patient involvement in copayment adjustments and healthcare-seeking behavior.

  • H2: Price perception negatively influences healthcare-seeking behavior.

  • H3: Positive attitudes towards copayment adjustments are positively associated with healthcare-seeking behavior.

  • H4: Health facility identification positively moderates the relationship between copayment adjustments and healthcare-seeking behavior.

Research model

To visually represent the relationships among the variables in this study, a research model is constructed. The model depicts the hypothesized relationships between the independent variables (Involvement, Price Perception, Attitude, Health Facility Identification) and the dependent variable (Healthcare-Seeking Behavior), as well as the moderating role of Health Facility Identification.

Study subjects

This study targeted outpatient customers in Taiwan using a questionnaire survey method for data collection. The subjects were recruited through hospital outpatient departments and community clinics across various regions in Taiwan. They needed to meet the following criteria: (1) clear consciousness and ability to communicate in Mandarin or Taiwanese; (2) consent to participate in the survey after being informed about the study. The survey was conducted from October 2023 to March 2024. After eliminating questionnaires with regular response patterns and incomplete answers, a total of 746 valid questionnaires were collected. The inclusion criteria ensured that participants had experienced copayment adjustments or were aware of the changes. The elimination criteria included: (1) identical answers across all items, (2) incomplete demographic information, and (3) inconsistent responses indicating a lack of understanding. The participants were informed about the purpose of the study, their rights, and the confidentiality of their responses. The survey was conducted anonymously to protect privacy, and all collected data were securely stored with password protection.

Research design and sampling strategy

The study employed a random sampling method to ensure a representative sample of outpatient customers across various regions in Taiwan. The participants were selected randomly from outpatient departments of hospitals and community clinics. To determine the appropriate sample size, we calculated the number of participants based on the outpatient volume of each hospital, adhering to statistical principles to ensure adequate representation. This approach allowed us to capture a diverse range of patient experiences and perceptions related to copayment adjustments.

To safeguard the rights and privacy of participants, all respondents were fully informed about the study’s purpose, their rights, and the confidentiality of their responses. Participation was entirely voluntary, and respondents had the right to refuse participation without any consequences. The survey was conducted anonymously, and all collected data were securely stored with password protection to ensure privacy.

Given the logistical requirements of collecting data from multiple hospitals across different regions, the survey period extended over six months. We acknowledge that this time span could potentially introduce variations in participants’ perceptions. However, we have carefully monitored and controlled for any significant events or policy changes during this period that could affect the study’s findings. The extended survey period was necessary to gather a sufficiently large and representative sample, ensuring the robustness of our results.

Questionnaire structure and variables

The questionnaire used in this study was developed based on a thorough review of existing literature, both domestic and international. It consisted of several sections, including respondents’ demographic information, involvement in copayment adjustments (Involvement), price perception (Price Perception), attitude towards copayment adjustments (Attitude), health facility identification (Health Facility Identification), and healthcare-seeking behavior (Healthcare-Seeking Behavior). An English version of the questionnaire is provided as a supplementary file (see Supplementary File 1).

To clarify the operationalization of the variables, Table 1 presents the definitions and measurement items for each construct, adapted from relevant studies. The questionnaire used a five-point Likert scale ranging from “strongly agree” to “strongly disagree,” with scores from 5 to 1. The content validity and face validity of the questionnaire were ensured through expert reviews and pilot testing. Two healthcare management scholars and two hospital practitioners reviewed the questionnaire, achieving an average Content Validity Index (CVI) of 0.868. Cronbach’s alpha values for each construct indicated acceptable internal consistency, with the overall reliability analysis yielding a Cronbach’s alpha of 0.864.

Table 1 Variable definitions and measurement items
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For empirical analysis, the average variance extracted (AVE) for each construct exceeded 0.5, confirming convergent validity [35, 37]. The AVE values ranged from 0.455 to 0.565, and the composite reliability (CR) values ranged from 0.741 to 0.921, demonstrating the reliability and validity of the measurement model.

Ethical considerations

The study protocol was reviewed and approved by the Institutional Review Board of Show Chwan Memorial Hospital (IRB No: 1120901, September 15, 2023). Participants provided informed consent, and their rights and privacy were protected throughout the study.

Data analysis

Data analysis was conducted using SPSS for Windows version 20.0. The analysis included descriptive statistics, correlation analysis, mean values, standard deviations, frequency distributions, percentages, Pearson’s product-moment correlation coefficient, and multiple regression analysis. These methods were employed to examine the relationships between the independent variables (Involvement, Price Perception, Attitude, Health Facility Identification) and the dependent variable (Healthcare-Seeking Behavior). Demographic variables such as age, gender, education level, and income were included as control variables to account for their potential influence on perceptions and behavior.

Results

Respondent profile

The demographic characteristics of the 746 respondents are summarized in Table 2. The mean age was 46.2 years, with a standard deviation of 14.5 years. The majority were male (62.5%), with the largest age group being 40–49 years (22.9%). Most respondents held a Bachelor’s degree (37.5%) or higher (31.9%), and the majority were married (69.4%). Regarding income, 15.3% reported no income, 9.8% reported an income less than 20,000 NTD, and 9.3% reported over 60,000 NTD. Nearly half (48.5%) of the respondents frequented medical centers, reflecting the characteristics of the study participants and providing a foundation for analyzing their healthcare-seeking behavior (Table 3).

Table 2 Respondent profile (N=746)
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Table 3 Composite reliability and convergent validity of constructs
Full size table

Mediating effect of health facility identification

Table 4 presents the results of the analysis examining the mediating effect of health facility identification on the relationship between copayment perception and healthcare-seeking behavior. Four models are presented in the table. In Model 1, involvement, price perception, attitude, and health facility identification are regressed on healthcare-seeking behavior. Model 2 adds copayment perception to Model 1 to examine its direct effect on healthcare-seeking behavior. Model 3 introduces health facility identification as a mediator between copayment perception and healthcare-seeking behavior. Finally, Model 4 includes all variables to assess the mediating effect of health facility identification.

Table 4 Analysis of the mediating effect of organizational identification on the relationship between copayment perception and healthcare-seeking behavior
Full size table

The results indicate that in Model 3 and Model 4, the coefficient for health facility identification is statistically significant (p < 0.001), suggesting a mediating effect. Specifically, the inclusion of health facility identification in the model reduces the direct effect of copayment perception on healthcare-seeking behavior, indicating a partial mediation.

These findings support the hypothesis that health facility identification plays a significant role in mediating the relationship between copayment perception and healthcare-seeking behavior, highlighting the importance of health facility factors in shaping individuals’ decisions regarding healthcare utilization.

Regression analysis of healthcare-seeking behavior

Table 5 presents the results of the regression analysis examining the factors influencing healthcare-seeking behavior among the respondents. The table includes two models. In Model 1, demographic variables such as gender, age group, education level, marital status, and annual income are regressed on healthcare-seeking behavior. Model 2 adds perceptual variables (involvement, price perception, attitude, and health facility identification) to Model 1 to examine their additional effects on healthcare-seeking behavior.

Table 5 Regression analysis of healthcare-seeking behavior
Full size table

The results indicate several significant predictors of healthcare-seeking behavior. In Model 1, demographic variables such as age, education level, marital status, and annual income show significant coefficients, suggesting their influence on healthcare-seeking behavior. In Model 2, perceptual variables, including involvement, price perception, attitude, and health facility identification, also demonstrate significant coefficients, indicating their additional effects on healthcare-seeking behavior beyond demographic factors.

Overall, the regression analysis highlights the importance of both demographic and perceptual factors in shaping individuals’ decisions regarding healthcare utilization.

Path model

Figure 1 illustrates the path model depicting the relationships between perceptual factors (involvement, price perception, attitude, and health facility identification) and healthcare-seeking behavior. In the model, perceptual factors are hypothesized to influence healthcare-seeking behavior directly and indirectly through their effects on each other. For example, involvement may directly impact healthcare-seeking behavior, while also influencing price perception, attitude, and health facility identification, which in turn affect healthcare-seeking behavior.

Fig. 1
figure 1

Path model of this study

Full size image

This path model provides a visual representation of the complex interplay between perceptual factors and healthcare-seeking behavior, highlighting the various pathways through which individuals’ perceptions may influence their decisions regarding healthcare utilization.

Discussion

This study aimed to investigate the impact of healthcare consumers’ involvement, price perception, and attitude towards NHI copayment adjustment on their healthcare-seeking behavior, with a particular focus on the mediating role of health facility identification. The results provide valuable insights into how these factors interplay to influence patient behavior in the context of Taiwan’s healthcare system.

Influence of involvement, price perception, and attitude

Our findings indicate that involvement, price perception, and attitude significantly affect healthcare-seeking behavior. Consistent with previous studies [24, 30, 38], the results supported previous findings that higher levels of consumer involvement and positive attitudes towards copayment adjustments lead to more proactive healthcare-seeking behavior. This suggests that when patients are more engaged and perceive copayment adjustments positively, they are more likely to seek necessary healthcare services.

Mediating role of health facility identification

The analysis supported previous findings that health facility identification mediates the relationship between copayment perception and healthcare-seeking behavior. This finding aligns with the theoretical framework that health facility identification can influence patients’ decisions by providing a sense of trust and familiarity with the healthcare provider [23]. Patients who identify strongly with a particular health facility are likely to be less deterred by copayment increases and more inclined to maintain their usual healthcare-seeking patterns.

Demographic factors and their impact

Our regression analysis reveals significant effects of demographic factors such as age, education level, marital status, and income on healthcare-seeking behavior. These variables influence perceptions in several ways. For instance, older individuals often have more defined patterns of healthcare utilization and different perceptions of healthcare costs due to increased health needs and experiences with the healthcare system. Similarly, those with higher education levels tend to have greater health literacy, leading to more informed attitudes towards copayment policies.

By controlling for these demographic variables in our analysis, we ensured that the effects of involvement, price perception, and health facility identification on healthcare-seeking behavior were accurately captured, free from confounding influences. This approach allows us to better understand the direct and indirect effects of these factors on patient behavior.

The results indicated that certain demographic factors, such as education level and income, significantly influence perceptions of copayment adjustments. For example, respondents with higher education levels were more likely to perceive copayment adjustments positively, likely due to a better understanding of the healthcare system and the rationale behind such policies. Conversely, lower-income individuals were more sensitive to price changes, leading to more negative perceptions of copayment adjustments.

These findings highlight the necessity of tailoring healthcare policies to account for the diverse needs and perceptions of different demographic groups. Policymakers should consider these demographic influences when designing and implementing copayment adjustments to minimize potential negative impacts on specific population segments, particularly those who may be more vulnerable to changes in healthcare costs.

Policy implications

The results of this study show that the perception of copayment adjustments and their impact on healthcare-seeking behavior is particularly significant for vulnerable groups. For low-income households and individuals with disabilities, while the current scheme of reduced copayments within Taiwan’s NHI system helps maintain equitable access to healthcare services, further strengthening of these policies is necessary. Policymakers should ensure that these measures effectively prevent financial barriers from limiting access to essential services. Specifically, policy recommendations should be more tailored, such as providing differentiated financial support based on income levels and health conditions to address the varied sensitivities to price perception. These measures can alleviate the pressure from increased copayments and encourage vulnerable groups to seek necessary healthcare services, thereby enhancing the overall accessibility and equity of healthcare services.

Conclusions and policy implications

This study sheds light on the critical factors influencing healthcare-seeking behavior in the context of NHI copayment adjustments. The findings highlight the importance of consumer involvement, price perception, and attitude in shaping healthcare utilization patterns. Moreover, the mediating role of health facility identification emphasizes the need for healthcare providers to foster strong connections with patients to mitigate potential negative impacts of copayment adjustments.

Policy implications

Enhanced Patient Engagement: Policies should aim to increase patient involvement by providing clear information about copayment adjustments and their benefits. Engaging patients through educational programs can help foster positive attitudes and reduce apprehensions about copayment changes.

Health Facility Identification: Healthcare providers should focus on building strong relationships with patients to enhance their identification with the facility. This could involve personalized care, improved communication, and initiatives that create a sense of community within the healthcare facility.

Targeted Support for Vulnerable Groups: The results of this study highlight the significant influence of demographic factors, and tailored interventions should be developed to support older adults, individuals with lower education levels, and low-income populations. These interventions should include designing a more flexible copayment system that allows vulnerable groups to benefit from varying levels of copayment reductions based on their financial capacity and health needs. This approach will prevent reductions in healthcare-seeking behavior due to differences in price perception. Ensuring that these groups continue to access necessary healthcare services despite copayment adjustments is crucial for maintaining healthcare equity.

Future research

Future studies should explore the long-term effects of copayment adjustments on healthcare-seeking behavior, considering potential changes in patient attitudes and facility identification over time. Additionally, research could examine the specific mechanisms through which health facility identification mediates the relationship between copayment perception and healthcare-seeking behavior, providing deeper insights into how healthcare providers can effectively manage patient responses to policy changes.

By comprehensively understanding these dynamics, policymakers and healthcare providers can better design and implement strategies that promote optimal healthcare utilization, ensuring that copayment adjustments do not adversely affect access to necessary medical services.

Limitations

This study has several limitations. First, the cross-sectional design limits the ability to establish causality. Future research could use longitudinal designs to better understand causal relationships between variables.

Second, the sample consists of outpatient customers in Taiwan, which may limit the generalizability of the findings to other regions or countries. Future studies should consider including diverse populations to examine the broader applicability of the results.

Third, the use of self-administered questionnaires may introduce social desirability bias and recall bias. Although measures were taken to ensure anonymity, these biases may still affect the accuracy of the findings.

Despite these limitations, the study provides valuable insights into the impact of copayment adjustments on healthcare-seeking behavior, offering useful information for policymakers and healthcare managers.

Availability of data and materials

No datasets were generated or analysed during the current study.

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Acknowledgements

We would like to thank all the participants who participated in this study.

Funding

Tainan Municipal Hospital (Managed by Show Chwan Medical Care Corporation), Grant/Award: RA23013.

Author information

Author notes

  1. Liang-Hsi Kung, Chih-Ming Kung and Chien Chih Chen contributed equally to this work.

Authors and Affiliations

  1. Tainan Municipal Hospital (Managed by Show Chwan Medical Care Corporation), Tainan, Taiwan

    Liang-Hsi Kung

  2. Department of Information Technology and Communication, Shih Chien University Kaohsiung, Kaohsiung, Taiwan

    Chih-Ming Kung

  3. Department of Future Studies and LOHAS Industry, Fo Guang University, Yilan, Taiwan

    Chien Chih Chen

  4. Tainan Municipal Hospital (Managed by Show Chwan Medical Care Corporation), No. 670, Chung Te Road, Tainan, 701, Taiwan

    Yu-Hua Yan

Authors
  1. Liang-Hsi Kung
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  2. Chih-Ming Kung
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  3. Chien Chih Chen
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  4. Yu-Hua Yan
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Contributions

The authors confirm contribution to the paper as follows: Y conceived and designed the study, performed the statistical analyses, was in charge of recruiting study participants, helped design the study, collected information, and interpreted the data. K, K and C monitored the research and assist in editing and correcting the paper. All authors have read and approved the final paper.

Corresponding author

Correspondence to Yu-Hua Yan.

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Ethics approval and consent to participate

This study adheres to the guidelines of the Declaration of Helsinki. This study was granted an ethics waiver by the Institutional Review Board at Show Chwan Memorial Hospital (IRB1120901). According to the same committee, formal written informed consent was not required. Similarly, the study was deemed as “not involving human subjects research” by the Institutional Review Board at Show Chwan Memorial Hospital Human Subjects Committee and exempted from human subjects’ oversight. The first author invited all participants by email or telephone, emphasizing that participation was voluntary and anonymous. All participants provided oral consent.”

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Competing interests

The authors declare no competing interests.

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Kung, LH., Kung, CM., Chen, C.C. et al. Impact of NHI copayment adjustments on healthcare seeking behavior: the mediating role of health facility identification. BMC Health Serv Res 24, 1148 (2024). https://doi.org/10.1186/s12913-024-11640-6

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  • DOI: https://doi.org/10.1186/s12913-024-11640-6

Keywords

BMC Health Services Research

ISSN: 1472-6963

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