Introduction

Effective patient contact is a critical component of public health service delivery, particularly for the prevention and early management of chronic diseases1,2. Patient contact, akin to customer contact in service industries, refers to the direct encounter between a patient and a healthcare provider, whether through face-to-face interactions or digital channels such as telephone calls, instant messaging, or video consultations3,4. This initial interaction provides healthcare providers with valuable opportunities both to identify patient needs and encourage proactive health-seeking behavior5,6. Within the context of public health, patient contact plays a pivotal role in disease prevention, patient education, and behavioral change, reinforcing its importance as a strategic touchpoint for healthcare engagement7,8.

In recent years, predictive analytics has enabled the identification of individuals at high risk of developing chronic diseases, such as hypertension, through the analysis of accumulated health records9,10. However, a fundamental challenge remains: high-risk individuals often do not recognize the need for preventive healthcare interventions, as chronic diseases tend to be asymptomatic in their early stages11,12. Without a sense of urgency or perceived necessity, these individuals are less likely to engage in preventive health behaviors, making initial patient contact a crucial mechanism for encouraging participation in health programs13,14.

Despite the importance of initial contact, achieving positive behavioral responses remains a challenge. Patients may perceive outreach efforts as intrusive, irrelevant, or inconvenient, leading to low engagement rates15,16. Studies suggest that high-quality interactions, personalized communication, and a sense of being well-received can significantly enhance patient receptivity and compliance17,18. Moreover, effective initial contact facilitates self-management education, equipping patients with the necessary skills and confidence to manage their health conditions, ultimately improving their quality of life19,20.

This study investigates the initial patient contact process at a public health center in South Korea, which provides hypertension prevention services. The center follows a four-stage healthcare process: (1) patient identification, (2) patient attraction, (3) patient education, and (4) patient monitoring. The initial patient contact process encompasses the first two stages—patient identification and attraction—where individuals at high risk of developing hypertension are identified and encouraged to attend educational programs. However, despite these efforts, the health center visit rate among contacted individuals remains at a critically low 2%, underscoring the need for a more effective engagement strategy.

To address this issue, this study evaluates alternative patient contact strategies through a field experiment involving 480 individuals at high risk of hypertension. Specifically, the study examines the impact of two communication interventions:

  1. 1.

    SMS notifications preceding telephone calls to improve patient responsiveness.

  2. 2.

    Customized health discussions tailored to patients’ medical records to enhance the perceived relevance of the contact.

While SMS reminders and customized communication have been shown to improve patient engagement in prior studies8,17,18the present research extends this literature in several important ways. First, the study adopts a parameter-based experimental design that separately evaluates the effects of communication timing (via SMS) and content customization (via customized scripts), allowing for a clearer understanding of their independent and additive contributions. Second, by embedding the intervention within a government-run public health center, the study offers practical evidence on the operational scalability and contextual effectiveness of targeted outreach strategies in a real-world public sector setting. By systematically analyzing the effects of these interventions, the study aims to generate evidence-based insights that can optimize patient engagement strategies and inform the design of more effective public health delivery systems.

The remainder of this paper is structured as follows. The “Research background” section presents a comprehensive background on the initial patient contact process for individuals at high risk of hypertension at the public health center. The “Research design and experimentation” section outlines the research objectives, key design parameters (DPs), experimental treatments, and the methodology employed in the field experiment. The “Analysis and results” section presents the results of the experiment, analyzing the effects of the design parameters and determining the optimal intervention strategies. The “Discussion” section addresses practical implications and challenges associated with implementing effective patient contact strategies in public health services. Finally, the “Concluding remarks” section summarizes key findings and suggests directions for future research.

Research background

The public health center is a key public healthcare institution in Gimhae City, South Korea, serving a population of approximately 520,000 residents. Established in 1965, the center has played a pivotal role in community health promotion and disease prevention, ensuring the accessibility and quality of public health services. The center operates with approximately 130 employees across two primary departments: Public Health Management and Home Visiting Health Services.

A core component of the center’s chronic disease prevention program is the early identification and engagement of individuals at high risk of developing hypertension. This process is structured into four stages of health service delivery (Fig. 1): (1) Patient Identification – Identifying high-risk individuals based on public health examination records. (2) Patient Attraction – Conducting outreach to encourage participation in educational programs. (3) Patient Education – Providing preventive healthcare education to those who visit the center. (4) Patient Monitoring – Conducting follow-ups on individuals who have attended the programs. The effectiveness of these stages relies heavily on the initial patient contact process, which comprises the patient identification and attraction stages. However, the current approach has exhibited low effectiveness, particularly in encouraging patient visits to the center.

Fig. 1
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Health service delivery process of the public health center.

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Initial patient contact is a critical step in preventive healthcare services, as it serves as a bridge between risk identification and behavioral intervention. It provides an opportunity for healthcare providers to engage with high-risk individuals, educate them on potential health risks, and encourage proactive healthcare behaviors21,22,23. Effective patient contact has been shown to significantly impact patient adherence to preventive care measures and improve health outcomes24,25. At the public health center, patient contact occurs through both online and offline channels: (1) Online (Remote) Contact: Telephone-based outreach conducted during the patient attraction and monitoring stages. (2) Face-to-Face (In-Person) Contact: conducted during the patient education stage when patients visit the center for hypertension prevention programs. Since high-risk individuals often do not perceive an immediate need for preventive healthcare, strategic communication during the patient attraction stage is essential to encourage health center visits26,27. The center’s outreach efforts aim to overcome patient inertia by providing information on health risks and the benefits of preventive care.

Patient identification is the first step in the health service delivery process. In South Korea, over 50.1 million citizens (out of a total population of 51.2 million) are covered under the National Health Insurance Service (NHIS), which mandates a biennial health examination for individuals aged 40 and older. The NHIS stores these health examination records in a public health information system, from which public health centers identify high-risk patients using predictive analytics.

Once high-risk patients are identified, the patient attraction stage involves direct outreach via telephone calls. Healthcare providers use a standardized script to discuss the patient’s health status and encourage them to visit the health center for hypertension prevention programs. The primary goal of this stage is to convert outreach into physical visits, ensuring that at-risk individuals receive necessary education and preventive care. Despite these efforts, the current patient attraction strategy has yielded suboptimal results. Approximately 2,900 contact attempts were made via telephone over a six-month period. The overall call reception rate was approximately 32%, indicating that nearly two-thirds of the contacted individuals did not respond to the calls. More critically, only 2% of the contacted patients subsequently visited the health center, underscoring the limited effectiveness of the current patient engagement strategy in encouraging participation in hypertension prevention programs.

The findings indicate that the current telephone-based outreach strategy has limited effectiveness in engaging high-risk individuals and motivating health center visits. Given the increasing availability of digital health communication tools, incorporating multi-channel engagement strategies may improve outreach effectiveness. This study aims to address these challenges by evaluating alternative patient contact methods through a field experiment at the public health center. The study will specifically test:

  1. 1.

    The effect of SMS notifications preceding telephone calls on patient responsiveness.

  2. 2.

    The effect of customized health discussions in encouraging patient visits.

By systematically analyzing the impact of these interventions, this research seeks to provide evidence-based recommendations for enhancing patient contact efficiency, improving public health engagement, and optimizing preventive care strategies.

Research design and experimentation

Experimental design

This study aims to enhance the initial patient contact process for individuals at high risk of developing hypertension at the public health center through a field experiment. The experiment evaluates two design parameters (DPs) to improve the effectiveness and efficiency of patient engagement strategies.

The first design parameter (DP1) involves the use of SMS notifications prior to phone contact. This intervention is hypothesized to increase phone call reception rates by reducing hesitation and improving patient preparedness for the scheduled conversation. The second design parameter (DP2) focuses on the customization of phone conversations, wherein contact employees personalize discussions based on the patient’s problematic health behaviors identified through health examination records. This approach is expected to enhance patient engagement by making the conversation more relevant and increasing the likelihood of health center visits.

The selection of DP levels was guided by expected effectiveness and feasibility, based on consultations with the public health center staff. For DP1, two levels were established: (1) no SMS notification and (2) SMS notification prior to the phone call. Similarly, DP2 consisted of two levels: (1) standardized conversation, in which the patient’s risk level for hypertension is communicated without reference to individual health behaviors, and (2) customized conversation, where the patient’s specific health behaviors, such as smoking, heavy drinking, lack of exercise, and excessive sodium intake, are discussed. The original patient contact process was designated as Level 1 for both parameters, while Level 2 represented alternative interventions aimed at improving patient engagement.

A between-subjects experimental design was employed, wherein each patient experienced only one treatment condition. A total of three treatment groups were established by combining the levels of DP1 and DP2. The combination of Level 1 in DP1 (no SMS) and Level 2 in DP2 (customized conversation) was excluded due to concerns regarding its low cost-effectiveness, as determined through discussions with health center managers. Table 1 presents the treatment conditions used in the experiment, and Fig. 2 shows examples of each level for the treatments. This design allows for the evaluation of the main effects of both DPs while maintaining practical feasibility in the implementation of patient outreach strategies.

Table 1 Treatment description.
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Fig. 2
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SMS and standardized and customized conversation scripts.

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To assess the effectiveness of the experimental treatments, three response variables (RVs) were established. The first response variable (RV1) measures the effectiveness of SMS notifications in improving patient responsiveness. It is defined as the number of phone calls received divided by the total number of phone contact attempts:

$$\:RV1=\frac{Number\:of\:phone\:calls\:received}{Total\:phone\:contact\:attempts}$$

The second response variable (RV2) evaluates the impact of both SMS notifications and customized conversations on patient engagement. It is defined as the number of health center visits within two weeks divided by the total number of phone calls received:

$$\:RV2=\frac{Number\:of\:health\:center\:visits\:within\:two\:weeks}{Total\:phone\:calls\:received}$$

The third response variable (RV3) measures patient satisfaction with the phone contact experience. This variable is assessed using a five-point Likert scale, whereby patients who visit the health center after the phone conversation evaluate the quality and usefulness of the interaction.

By systematically analyzing the effects of SMS notifications and customized phone conversations, this study seeks to identify evidence-based strategies for improving the effectiveness of initial patient contact. The findings will contribute to the optimization of public health intervention strategies and enhance the efficiency of hypertension prevention programs.

Experimental method and procedure

To evaluate the effectiveness of different initial patient contact strategies, a field experiment was conducted with a total of 480 subjects. These subjects were identified as high-risk individuals for developing hypertension based on the risk prediction model described in the “Research background” section. The selection criteria included individuals flagged by the model with an elevated probability of developing hypertension within the next two years, as determined from their health examination records. Individuals with preexisting hypertension who were under active treatment were excluded to ensure that the intervention targeted those most in need of preventive care.

The 480 subjects were randomly assigned to one of three treatment groups in equal proportions to ensure comparability across experimental conditions. Demographic characteristics such as gender and age distribution were balanced among the groups, as presented in Table 2. The gender ratio was approximately 2:1, with males comprising the majority of participants. Furthermore, approximately 80% of the subjects were between the ages of 30 and 50, reflecting the population most at risk of developing hypertension and most likely to benefit from early preventive interventions. Informed consent was obtained from all participants, and all methods were carried out in accordance with relevant guidelines and regulations. Additionally, this field experiment was conducted under the supervision and management of the public health center. This study did not involve any direct intervention with human participants and was based solely on observational data. According to Article 36, Paragraph 2, Clause 3 of the Bioethics and Safety Act of the Republic of Korea, research that involves only observation without any intervention to the subjects is exempt from IRB review. Therefore, ethical approval was not required for this study. Approval was waived by the POSTECH (Pohang University of Science and Technology) IRB.

Table 2 Gender and age distribution of the subjects in the three treatments.
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The experiment was conducted by six employees of the public health center. Five employees were responsible for contacting high-risk individuals under the assigned treatment conditions, while one employee managed the scheduling of phone calls and monitored the overall outcomes of the intervention. To ensure consistency in the implementation of the treatments, standardized phone contact guidelines were developed in collaboration with the public health center staff. These guidelines specified the structure of the phone conversations for both the standardized and customized treatments. Additionally, the content of the SMS notification used for advance phone contact announcements was formulated to ensure uniformity in messaging.

Phone contact attempts were conducted daily between 1 p.m. and 6 p.m., with an average of twenty subjects contacted per day. For treatment groups involving an SMS notification, the message was sent at least three hours before the scheduled phone call. If a subject did not answer the initial phone call, the contact employee attempted up to two additional calls on the same day. A subject was classified as a respondent if they answered any of the three attempted calls.

All contact attempts and responses were systematically documented. The recorded data included whether the call was answered, the duration of the conversation, the patient’s engagement level, and whether they agreed to visit the health center. For subjects in the customized conversation treatment, the contact employees also noted whether the patient responded to the personalized health behavior information and whether they expressed any concerns or interest in further preventive care.

Analysis and results

The experiment was conducted over a two-month period to evaluate the effects of different initial contact strategies on patient engagement. A total of 480 high-risk individuals were randomly assigned to three treatment groups, as outlined in the “Experimental design” section. The primary response variables were the phone call reception rate (RV1), health center visit rate (RV2), and patient satisfaction with the phone conversation (RV3).

Table 3 presents the summary statistics from the experiment. Among the 480 targeted individuals, 306 successfully received a phone call, resulting in an overall reception rate of 63.75%. Among those who received the call, only 22 patients (7.19%) subsequently visited the public health center within two weeks.

Table 3 Summary of the collected data from the experiment.
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The data indicate that the use of SMS notifications prior to phone calls (Treatment 2 and Treatment 3) increased the likelihood of patients answering phone calls. This effect is shown by the highest phone call reception rate in Treatment 2. Meanwhile, Treatment 3, which combined SMS notification with a customized phone conversation, resulted in the highest health center visit rate and the highest patient satisfaction score.

To evaluate the statistical significance of each design parameter (DP), appropriate hypothesis tests were conducted based on the experimental structure (Table 4). The analysis was organized around two binary design parameters: DP1 (use of SMS) and DP2 (customization of phone conversation).

Table 4 Comparison structure and statistical analysis by response variable.
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The response variable RV1 (phone call reception) is a binary variable indicating whether a participant answered the incoming phone call. The SMS message was sent prior to the phone call, and participants could only decide whether to answer based on the presence or absence of the SMS. They had no prior knowledge of the content or customization of the phone conversation, which was only revealed after the call was answered. Given this temporal sequence, the appropriate comparison for evaluating the effect of DP1 was between Treatment 1 (no SMS) and the combined group of Treatment 2 and 3 (received SMS) (Table 4). A chi-squared test was used to assess differences in reception rates. With a total sample size of 480 and all cell counts exceeding 5, the test assumptions were fully met.

RV2 (health center visit) is a binary variable that indicates a participant visited a health center following the phone contact. Two separate comparisons were conducted to assess the isolated effects of each design parameter. To evaluate DP1, Treatment 1 was compared with Treatment 2 (Table 4), since both groups received standardized phone calls, thereby isolating the effect of the SMS alone. Due to the small number of visits (n = 22), which resulted in some cell frequencies falling below 5, Fisher’s exact test was used to ensure valid statistical inference. To assess DP2, Treatment 2 was compared with Treatment 3 (Table 4), as both groups had received the SMS, thereby controlling for DP1. The sample size for this comparison was sufficient, and a chi-squared test was applied.

RV3 (patient satisfaction score) measured participant satisfaction with the phone call using a five-point Likert scale and was treated as a continuous variable. Importantly, this measure captured perceptions exclusively regarding the phone conversation itself, not the SMS or other elements. Furthermore, both Treatment 1 and 2 received standardized phone calls, identical in structure and delivery format. As such, the grouping of T1 and T2 into a single comparison group is methodologically sound for evaluating DP2, isolating the effect of the customized phone experience in Treatment 3. Given the approximately symmetric distribution of scores and a sufficiently large sample of respondents, a two-sample t-test was used to compare mean satisfaction scores between groups.

The results indicate that DP1 (SMS notification) had a significant effect on phone call reception rates (RV1), confirming that patients who received advance SMS notifications were more likely to answer phone calls from the health center (Table 5). Additionally, DP2 (customized conversation) significantly improved health center visit rates (RV2), suggesting that personalized health risk discussions were effective in motivating patients to seek medical attention. However, neither DP1 nor DP2 had a statistically significant effect on patient satisfaction (RV3). Although mean satisfaction scores were slightly higher for Treatment 3, which included both SMS notification and customized conversation, the observed differences were not statistically meaningful.

Table 5 Statistical test results.
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The results demonstrate that DP1 (use of SMS) had a statistically significant effect on RV1 (phone reception rate). Patients who received an SMS prior to the phone call (Treatment 2 and 3) were significantly more likely to answer the call from the health center than those who did not receive any SMS (Treatment 1), with a reception rate of 72.2% versus 46.9% (p = 0.0106). This finding highlights the importance of pre-call SMS messaging as a mechanism for enhancing patient responsiveness and facilitating communication.

For RV2 (health center visit rate), two separate comparisons were conducted to isolate the effects of DP1 and DP2. The comparison between Treatment 1 and Treatment 2, isolating the effect of DP1 (SMS), revealed no statistically significant difference in visit rates (5.6% vs. 4.9%, p = 1.0000), suggesting that SMS notifications alone did not increase the likelihood of a health center visit. However, the comparison between Treatment 2 and Treatment 3, targeting DP2 (customization of phone conversation), showed a higher visit rate in the customized group (13.2% vs. 4.9%, p = 0.0862). Although this difference did not meet the conventional threshold for statistical significance (p < 0.05), it represents a meaningful behavioral impact, with the visit rate nearly tripled. The effect size, calculated as the risk difference (13.2% – 4.9% = 8.3% points), and an odds ratio of 2.97, indicates that patients who received customized risk communication were nearly three times as likely to visit the health center compared to those who received standardized messaging. This suggests that even in the absence of statistical significance, the intervention had a practically important effect in terms of public health behavior change.

With respect to RV3 (satisfaction with phone conversation), the results indicate no statistically significant difference in satisfaction scores between Treatment 3 (customized conversation) and the combined group of Treatment 1 and 2 (standardized conversation). Mean satisfaction scores were 4.83 and 4.60, respectively (p = 0.3644). Although the scores trended higher in the customized group, this difference was not large enough to reach statistical significance.

The statistically significant increase in phone call reception among patients who received an advance SMS suggests that prior notification can play a critical role in reducing hesitation and increasing receptiveness to public health outreach. By informing patients in advance about the purpose and timing of the call, the SMS may help reduce psychological resistance and elevate the perceived legitimacy of the health center’s outreach efforts. This simple intervention thus enhances communication effectiveness at minimal operational cost.

Although the effect of SMS on subsequent health center visits was not statistically significant, the customization of phone conversations showed meaningful potential in encouraging patient follow-up. Patients who received tailored conversations that highlighted specific health risks such as high sodium intake or insufficient physical activity demonstrated substantially higher visit rates. This result, despite a p-value above 0.05, reflects a clinically and behaviorally important difference, with a nearly threefold increase in health center attendance. Such a targeted behavioral approach likely enhances the personal relevance of the message and may activate risk perception and self-efficacy, both known predictors of health-related decision-making.

As for satisfaction with the phone call experience, the absence of statistically significant differences should be interpreted in light of the study design. All participants received calls of consistent structure and tone, with only the content varying by treatment. The lack of difference suggests that structural elements such as clarity, tone, and duration may outweigh message personalization in shaping overall satisfaction. However, the modest upward trend in satisfaction scores for customized conversations still points to the potential for enhanced engagement and information retention.

Taken together, these findings support the integration of behaviorally informed, low-cost communication strategies into patient outreach programs. The combination of advance SMS notifications and tailored conversation content appears not only feasible but also functionally impactful, particularly in increasing initial engagement and motivating health-seeking behaviors. As such, they may serve as scalable levers to enhance public health intervention outcomes, especially in resource-constrained healthcare environments.

Discussion

This study examined the effectiveness of improvements to the initial patient contact process for hypertension prevention at the public health center. The findings of the field experiment suggest that incorporating SMS notifications for phone contact announcements and customizing phone conversations can significantly enhance patient engagement. As a result, the original process of initial patient contact requires modification to integrate these strategies systematically. Specifically, two primary changes should be considered: first, integrating SMS notifications into the patient attraction stage to increase call reception rates by preparing patients for upcoming conversations, and second, incorporating data-driven identification of problematic health behaviors into the patient identification stage to enhance the relevance and personalization of outreach efforts. The expected improvements in the patient contact process following these modifications are illustrated in Fig. 3.

Fig. 3
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Changes in the initial patient contact process based on the experimental results.

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Moreover, by evaluating the interventions as separate design parameters, specifically the use of SMS notifications and the customization of message content, the study provides a clear understanding of which components of the outreach process influence different stages of patient engagement. The findings indicate that SMS notifications were particularly effective in improving initial responsiveness to phone calls, whereas customized conversations had a stronger impact on motivating health center visits. These results offer practical insights that can inform the design of patient contact strategies depending on the specific goals of public health programs, such as increasing contact rates or encouraging follow-up behaviors.

Despite the demonstrated benefits of these enhancements, several practical considerations must be addressed to ensure the successful implementation of these process changes. One of the key challenges is the accuracy of health behavior identification. Patients may react skeptically to personalized health advice if the information provided appears incorrect or lacks credibility28,29. During the experiment, some contacted individuals expressed doubt about the validity of their health assessments, particularly those sensitive to discussions about their lifestyle habits. Ensuring that data-driven patient profiling is both precise and clearly communicated is critical to building trust and increasing the likelihood of positive patient responses30,31.

Beyond improving the initial contact process, this study underscores the need for a broader patient retention strategy to sustain engagement beyond the first interaction. While this research primarily focused on initial contact, its long-term impact depends on the ability to maintain patient participation in hypertension prevention programs. A multi-stage patient retention strategy could include alternative interventions for different patient response scenarios. For instance, if a patient does not answer the phone call, sending an informational guidebook or a follow-up SMS could serve as a secondary engagement method32,33. If a contacted patient does not visit the center after the call, additional follow-up calls or incentives, such as free initial consultations, could be considered to encourage participation. For patients who do visit the center, structured educational programs and continuous health monitoring should be reinforced to ensure sustained behavioral changes.

In addition to operational considerations, this study highlights the broader implications of leveraging digital communication strategies in public health outreach. The findings contribute to the growing body of research on patient engagement, demonstrating that simple technological interventions, such as SMS reminders and personalized health counseling, can substantially enhance the effectiveness of preventive healthcare initiatives. Future research should explore the scalability of such interventions in different public health contexts, particularly in low-resource settings where automated and low-cost communication methods may provide a cost-effective means of improving health outcomes.

Concluding remarks

This study investigated strategies to improve the initial patient contact process for hypertension prevention through a real-world field experiment conducted at a public health center. Unlike many prior studies that rely on online surveys or hypothetical scenarios, this research was conducted on-site with actual patients, addressing practical constraints and reflecting real engagement behaviors. The empirical setting significantly enhances the ecological validity of the findings and demonstrates the feasibility of applying structured communication strategies in resource-limited public health contexts.

The key innovation of this study lies in its parameter-based experimental design that independently identifies the effects of two of the most widely used communication modalities in public health: SMS notifications and phone call customization. Rather than simply testing a bundled outreach intervention, this study separates the individual contributions of these components, both of which are commonly used but rarely evaluated systematically in combination. This disaggregation provides actionable insights for policymakers and practitioners by showing not only whether these interventions work, but also how they work in isolation and in interaction.

In terms of contribution, this research provides empirical evidence for the separate and joint effects of low-cost digital engagement strategies in a public health setting. It also offers a practical experimental framework that can be extended to other chronic disease interventions. In addition, it provides behavioral insights into how small communication adjustments can meaningfully affect preventive health behaviors. While the interventions enhanced initial engagement, the study also highlights persistent motivational barriers that limit downstream behaviors, suggesting future research directions for long-term behavior change and patient retention.

Despite the improvements achieved in patient engagement, the health center visit rate remained relatively low, reaching only 11.7% at best. While some patients may be willing to visit the health center, logistical barriers, such as limited operating hours and accessibility constraints, continue to hinder participation. More critically, a fundamental challenge lies in patients’ low self-motivation to seek preventive care, particularly in the absence of immediate symptoms. Therefore, future research should explore more effective strategies to enhance self-motivation through phone communication, behavioral nudges, and other remote interventions. Investigating psychological, social, and environmental factors influencing patients’ willingness to seek preventive care could provide valuable insights for designing more effective engagement strategies.

This study is not without limitations. First, the findings are based on a single public health center, which may limit their generalizability to different healthcare settings. However, the site selected for this study is a well-established institution that has been in operation since 1965 and is located in Gimhae, a city with a population of over 500,000. This setting reflects the characteristics of a typical urban public health center in Korea rather than those of a small or highly specialized facility. In addition, the study sample was constructed with attention to demographic balance in order to improve the potential for generalization. Nevertheless, the effectiveness of the intervention strategies may vary depending on regional and population-specific conditions. For instance, in rural areas, limited access to mobile technology or a higher proportion of elderly individuals may hinder the effectiveness of SMS notifications and phone-based communication. These contextual differences could influence how patients respond to outreach efforts. To better understand such variability, future research should compare the outcomes of similar interventions across multiple sites, including both urban and rural public health centers. This approach would support the development of regionally tailored strategies for patient engagement.

Second, while this study primarily focused on short-term patient responses, the long-term impact of improved patient contact methods on sustained health behaviors and chronic disease prevention remains unknown. In particular, it is unclear whether increased visit rates translate into continued engagement, adherence to lifestyle modifications, or long-term reductions in hypertension risk. To address this gap, future longitudinal studies could follow up with patients over several months or years after the initial contact to assess behavioral adherence (e.g., exercise, diet), participation in follow-up health services, and clinical indicators such as blood pressure levels. Such studies would help determine whether early improvements in patient contact ultimately lead to measurable and sustained improvements in health outcomes, thereby strengthening the case for scalable adoption of these outreach strategies.

Third, although participants were randomly assigned to treatment groups and demographic characteristics were balanced across groups, the analysis did not explicitly adjust for individual-level covariates such as socioeconomic status, baseline health literacy, or comorbidities. While randomization helps mitigate the influence of such confounders, future research may benefit from covariate-adjusted models, such as logistic regression or ANCOVA, to further strengthen causal inference. Lastly, while the study assessed patient satisfaction with phone interactions, a more comprehensive evaluation of patient experiences that includes both qualitative feedback and behavioral outcomes could provide deeper insights and help enhance the effectiveness of patient engagement strategies.

In conclusion, this study provides evidence-based recommendations for improving patient engagement in preventive healthcare. By systematically integrating SMS notifications and personalized phone conversations, public health centers can overcome communication barriers and increase participation in disease prevention programs. However, successful implementation requires a holistic approach that considers patient trust, data accuracy, logistical barriers, and long-term engagement strategies. Future research should focus on refining predictive analytics, exploring behavioral motivators, and expanding digital health interventions to enhance public health outreach and chronic disease prevention efforts.