Analysis of Factors Affecting Service Quality, Marketing Mix and Patient Satisfaction on the Decision to Choose a Place of Delivery at Hermina Serpong Hospital

 

Prima Sesari Saraswati1*, Rokiah Kusumapradja2, Erry Yudhya Mulyani3

Esa Unggul University, Jakarta, Indonesia1,2,3

Email: prisesa1404@student.esaunggul.ac.id

 

KEYWORDS

ABSTRACT

service quality, marketing mix, patient satisfaction, patient decisions

The patient's choice of a service provider is critical to the hospital's business success. A decline in patient visits, a gap between the hospital's target market, and suboptimal service quality and marketing strategies present significant risks. Consequently, delivering high-quality services to meet patient expectations and ensure their satisfaction is paramount. Satisfied patients are more likely to return for future health services, reinforcing the hospital's reputation and market position. This study investigates how service quality, the marketing mix, and patient satisfaction collectively impact the decision to choose a place of delivery at Hermina Serpong General Hospital. Research Implications: The findings highlight the importance of service quality and a well-structured marketing mix in enhancing patient satisfaction, which in turn significantly influences the patient's decision-making process when selecting a healthcare provider. These insights underscore the need for hospitals to invest in improving service delivery and refining marketing strategies to better align with patient needs and expectations. By doing so, hospitals can not only increase patient satisfaction but also strengthen their competitive advantage in the healthcare market. Research Methods: This study employs a quantitative cross-sectional approach, utilizing a questionnaire for data collection from 190 patients selected through purposive sampling. The results demonstrate that service quality and the marketing mix have a significant and positive impact on patient satisfaction. Additionally, these factors, alongside patient satisfaction, significantly and positively influence the patient's decision to choose a hospital. Suggestions: To further enhance patient satisfaction and attract more patients, the hospital has initiated several programs, including classes for pregnant women, door-to-door services, online consultations, and services for obtaining birth certificates and Child Identity Cards.

DOI: 10.58860/ijsh.v3i9.233

 

Corresponding Author: Prima Sesari Saraswati*

Email: prisesa1404@student.esaunggul.ac.id

 

INTRODUCTION

The competition among hospitals to attract patients is intense, requiring them to develop specific strategies to stay competitive in the healthcare industry (van den Broek et al., 2018). To thrive, hospitals must deliver excellent services that meet patient expectations, ensuring patient satisfaction. Satisfied patients are more likely to choose the same healthcare services again in the future.

Based on the performance achievement data of Hermina Serpong Hospital, it can be seen that the quality of health services provided is not in accordance with the standards or is below the target, especially in the BOR (Bed Occupancy Rate) which reached 69.03% in 2020, then increased to 73.51% in 2021, but experienced a drastic decrease in 2022 to 51.44%. Data from the Obstetrics and Gynecology Polyclinic of Hermina Serpong Hospital shows that the number of patients continues to decrease, from 1,767 patients in 2019, to 1,536 patients in 2021, and in 2022 from January to March there were 363 patients with an estimate until December that only reached 1,300 patients. This shows a significant decrease in the number of patients every year. The difference between the potential target of pregnant women patients and the number of patients achieved is still quite large (Ilekis et al., 2016). Based on this data, it can be assumed that the potential number of patients in hospitals compared to the number of type C hospitals in South Tangerang City is around 1,928 pregnant women and 1,892 mothers giving birth. Therefore, hospitals must compete to attract public interest in conducting pregnancy checks for 1,982 pregnant women and 1,892 mothers giving birth at the hospital.

To initially identify the factors contributing to the decline in patient visits, the researcher conducted a preliminary survey or direct interviews with several patients. The findings from these interviews revealed various factors that influenced patients' decisions to continue using the hospital's services (revisit) (Waters et al., 2016). The pre-survey results indicated that patients' willingness to return to the hospital was influenced by the hospital's acceptance of BPJS guarantees, its proximity to the patient's residence, the availability of specific medical services, other specialist services, and lower prices compared to nearby hospitals. However, some issues led to patient dissatisfaction, such as inconsistent responsiveness from the hospital, uncomfortable waiting and treatment areas, long service wait times, and an outdated queuing system (Al Hammadi, 2019).

The perceived quality of a product or service can influence a user's intention to make repeat purchases. When the service or product provided surpasses consumer expectations, it is viewed as ideal quality. Conversely, if the service or product falls short of expectations, it is perceived as poor quality. A study by Park et al. (2021) involving 540 clinic patients in South Korea found that service quality significantly impacts patient satisfaction and their intention to revisit. Similarly, Siripipatthanakul (2021) conducted a study on 352 clinic patients in Thailand, revealing that aspects of service quality, including Tangibles, Reliability, and Empathy, positively and significantly affect patients' decisions to return for health services.

The marketing mix is a collection of tools that companies can use to achieve their marketing objectives in a target market. Jerome McCarthy's traditional marketing mix, as described by Kotler & Keller (2018), includes four key elements: product, price, place, and promotion. Zeithaml & Bitner (2023) argue that service marketing requires an expanded mix, adding three additional elements: people, process, and physical evidence. Before choosing a healthcare service, consumers typically go through the stages of the purchasing decision process, including problem recognition, information search, and alternative evaluation (Kotler & Amstrong, 2018). If a hospital can provide healthcare services that meet the needs and expectations of consumers, it can influence patients' decisions to use the hospital's services. According to a study by Tarihoran et al. (2021) involving 300 patients in public hospitals in Iran, the marketing mix was found to have a 70.65% impact on the increase in patient visits. This indicates that the 7P marketing mix is highly effective in helping hospitals increase the number of patient visits.

According to Kotler and Keller (2018), consumer satisfaction is the level of a person's feelings that results from the comparison between expectations and the reality received from a product or service. Patient satisfaction is very important in the healthcare industry, where satisfied consumers tend to become loyal customers (Homburg et al., 2011). Satisfied consumers will return to using the product or service, as researched by Spiridon et al. (2018). Pighin et al. (2022) in their research in Argentina found that patient satisfaction has a significant influence on patients' decisions to reuse health services. A study conducted by Park et al. (2021) on 540 clinic patients in South Korea showed that patient satisfaction significantly contributed to increasing the intention of repeat visits in clinic patients. Therefore, a more in-depth analysis of the patient's decision to choose the place of delivery as a means of service is needed, because similar research has never been conducted. In addition, it is necessary to conduct an in-depth analysis of the influence of service quality and marketing mix on the decision to choose a delivery place at Hermina Serpong Hospital, with satisfaction as an intervening variable.

Despite extensive research on these factors, there has been no in-depth analysis of how service quality, marketing mix, and patient satisfaction specifically influence the decision to choose a place of delivery, particularly in the context of Hermina Serpong Hospital. This research fills that gap, offering a novel perspective by examining these variables with patient satisfaction as an intervening variable, thereby providing insights that have not been explored in previous studies (Uzir et al., 2021).

The primary objective of this study is to analyze the influence of service quality, marketing mix, and patient satisfaction on the decision to choose a place of delivery at Hermina Serpong General Hospital. By identifying the key factors that contribute to patient satisfaction and decision-making, this research aims to provide valuable insights for hospital management in improving service quality and marketing strategies. The expected benefits of this study include enhancing patient satisfaction, increasing patient loyalty, and ultimately boosting the hospital's competitiveness in the healthcare industry (Hossain et al., 2020).

 

METHOD

This study was conducted to determine the influence of service quality and marketing mix on the decision to choose a place of delivery at Hermina Serpong Hospital, with satisfaction as an intervening variable. The research design is quantitative with a cross-sectional approach. The sampling method was carried out using the non-probability sampling method in a purposive way. Data collection was carried out using a questionnaire instrument consisting of Service Quality Variables with the Dimensions of Tangibles, Reliability, Responsiveness, Assurance, and Empathy. by using the Likert scale (1-4), Variable Marketing Mix with the Dimensions of Product, Price, Promotion, Place, People, Process, and Physical Evidence) by using the Likert scale (1-4), Variable of Patient Satisfaction with the Dimension of the outcome, continuity of care and availability with using the Likert scale (1-4) and the Place Selection Decision Variable with the dimension of problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior with Using Likert Scale (1-4)

Inferential Stadot data analysis was carried out to assess the significance of the relationship between variables (Norris & Walker, 2020). Test the hypothesis with a path coefficient to find out the direction of influence between variables in the research model.

 

 

 

 

 

 

 

 

 

 


Figure 1. Research Model

Sample

The number of samples determined was 190 patients. The sampling technique was carried out by purposive sampling with the criteria that the respondent was an ANC patient at Hermina Serpong Hospital

Research Hypothesis

a)    There is a relationship between service quality and patient satisfaction at Hermina Serpong Hospital

b)   There is a relationship between marketing mix and patient satisfaction at Hermina Serpong Hospital

c)    There is a relationship between patient satisfaction and consideration of the decision to choose a place of delivery at Hermina Serpong Hospital

d)   There is a relationship between the quality of service and the consideration of the decision to choose a place of delivery at Hermina Serpong Hospital

e)    There is a marketing mix relationship and consideration of the decision to choose a place of delivery at Hermina Serpong Hospital.

f)    There is a relationship between service quality, marketing mix, patient satisfaction and consideration of the decision to choose a delivery place at Hermina Serpong Hospital.

 

RESULT AND DISCUSSION

Respondent profiles

In this study, as many as 190 patients of Hermina Serpong Hospital. Based on gender, 100% of respondents are Women. Based on age groups, 16 people, or 8.42%, are 18-22 years old, 98 people, or 51.58%, are 23-30 years old, 36 people, or 40%, are 31-60 years old, and age > 60 years is non-existent. Based on the type of work, it is dominated by private employees, namely 97 people or 51.05%, in the 2nd position of patients with the profession of housewives, which is as many as 45 people or 23.6%, in the 3rd position of Civil Servants 26 people or 13.68%, self-employed as many as 21 people or 11.05%, others less than 10%.  Based on your monthly income, less than Rp. 3,000,000 7 people or 3.68%, the group of patients with an income of Rp. 3,000,100 – 5,000,000 as many as 39 people 20.53%, Rp. 5,000,100 – 7,000,000 as many as 54 people or 28.42% and Rp. 7,000,100 – 9,000,000 as many as 76 people or 40%, > 9 million as many as 14 people or 7.37%.

Analysis of Partial Least Square - structural equation modeling (SEM-PLS)

1)   Determinant Coefficient (R-Squared)

The R-squared tilapia or determination coefficient explains how much the dependent variable can be affected by the independent variable. The R-squared value ranges from 0 to 1 (0 ≤ R2 ≤ 1); the higher the R-squared value, the greater the influence of the independent variable on the dependent variable. As a rule of thumb, the R2 value > 0.75 (strong), R2 >0.50 (moderate), and R2 >0.25 (weak), but if the R-square value is found above 0.9, the model can be considered overfit. (Sarstedt et al., 2017; (Hair et al., 2019).

Table 1.

R-Squared Values

Dependent

R Square Adjusted

Classification

Patient Satisfaction

                      0.501

Moderate

Patient Decision

                      0.648

Strong

Source: Research Data Processing (2022)

 

Based on the data presented in the table above, it can be seen that the R-squared value for the patient satisfaction variable of 0.501 was obtained. This value explains that the percentage of patient satisfaction can be explained by the quality of service and marketing mix of 50.1%; the remaining (100%-50.1%) 49.9% is influenced by other variables that are not in the model. The R-squared value for the patient decision variable of 0.648 obtained the value explained that the percentage of patient decision size can be explained by the variables of patient satisfaction, service quality, and marketing mix of 64.8%, the remaining (100%-64.8%) 35.2% is influenced by other variables that are not in the model.

2)   Hypothesis Testing

The main part of the analysis of the inner model or structural model in this study is to look at the value of the path coefficient to find out the direction of influence between the variables in the research model. It is said that there is a positive and significant influence if the T-statistic value > T-table (1.645) is at a significance level of 5% (alpha = 0.05); on the other hand, if the T-statistic < T-table (1.645) then there is no significant influence between the two variables (Ringle et al., 2015; Sarstedt et al., 2017). Table 5 below shows the results of PLS-SEM data processing for the determination of hypothesis test results.

Figure 2. Hypothesis Test Results

 

Table 2.

 Results of Hypothesis Test

Standardized Coefficient

T-Statistics

P-Value

Result

H1

0.470

4.076

0.000

Supported

H2

0.271

2.518

0.006

Supported

H3

0.322

2.415

0.008

Supported

H4

0.354

3.217

0.001

Supported

H5

0.216

1.894

0.029

Supported

H6.a

0.151

1.852

0.032

Supported

H6.b

0.138

2.865

0.002

Supported

 

The Effect of Service Quality on Patient Satisfaction

From the table above, it is known that the t calculation for the service quality variable is 4.076 at a significance level of 0.000 with a regression coefficient value (Path Coefficient) of +0.470. Because the path coefficient value is marked positively, the t-value statistic is >1.645, and the p-value is 0.000<0.05, it can be concluded that the service quality variable has a positive and significant effect on patient satisfaction. Thus, the H1 hypothesis "There is a relationship between service quality and patient satisfaction at Hermina Serpong Hospital" is accepted.

The Effect of Marketing Mix on Patient Satisfaction

From the table above, it is known that the t calculation for the marketing mix variable is 2.518 at a significance level of 0.006 with a regression coefficient value (Path Coefficient) of +0.271. Because the path coefficient value is marked positively, the t-value statistic is >1.645, and the p-value is 0.006<0.05, it can be concluded that the marketing mix variable has a positive and significant effect on patient satisfaction. Thus, the H2 hypothesis "There is a relationship between marketing mix and patient satisfaction at Hermina Serpong Hospital" is accepted.

The Effect of Patient Satisfaction on Patients' Decision to Choose a Hospital

From the table above, it is known that the t calculation for the Patient Satisfaction variable is 2.415 at a significance level of 0.008 with a regression coefficient value (Path Coefficient) of +0.322. Because the path coefficient value is marked positively, the t-value statistically >1.645, and the p-value is 0.008<0.05, it can be concluded that the Patient Satisfaction variable has a positive and significant effect on the patient's decision to choose a hospital. Thus, the H3 hypothesis "There is a relationship between patient satisfaction and patient decision in choosing a hospital" is accepted.

The Influence of Service Quality on Patients' Decision to Choose a Hospital

From the table above, it is known that the t calculation for the service quality variable is 3.217 at a significance level of 0.001 with a regression coefficient value (Path Coefficient) of +0.354. Because the path coefficient value is marked positively, the t-value statistically >1.645, and the p-value 0.001<0.05, it can be concluded that the service quality variable has a positive and significant effect on the patient's decision to choose a hospital. Thus, the H4 hypothesis "There is a relationship between service quality and patient decision in choosing a hospital" is accepted.

The Influence of Marketing Mix on Patients' Decision to Choose a Hospital

From the table above, it is known that the t calculation for the marketing mix variable is 1.894 at a significance level of 0.029 with a regression coefficient value (Path Coefficient) of +0.216. Because the path coefficient value is marked positively, the t-value statistic is >1.645, and the p-value is 0.029 <0.05, it can be concluded that the marketing mix variable has a positive and significant effect on the patient's decision to choose a hospital. Thus, the H5 hypothesis "There is a relationship between marketing mix and patient decision in choosing a hospital" is accepted.

The Effect of Patient Satisfaction as an Intervening Variable on the Relationship between Service Quality and Patient Decision in Choosing a Hospital

Figure 3. Path Analysis Hypothesis 6

 

a)    Direct effect  = 0.354

b)   Indirect Effect = 0.151

c)    Total effect = Direct effect + Indirect effect = 0.354 + 0.151 = 0.505

d)   Variance accounted for (VAF) value = Direct effect / Total Effect = (0.354/ 0.505) = 0.701 or 70.1%

From the figure above, it is known that the p-value for the influence of the patient satisfaction variable on the relationship between service quality and patient welfare (indirect effect) is 0.032 with a regression coefficient value (Path Coefficient) of +0.151. Because the path coefficient value is positive and the p-value is 0.032<0.05, it can be concluded that the patient satisfaction variable has a significant effect on the relationship between service quality and patient well-being. The VAF value is 0.701 or 70.1% because the VAF value is> 20%, so it can be concluded that patient satisfaction is a mediating variable. Thus, the H6a hypothesis "There is a relationship between service quality and patient decision in choosing a hospital through patient health" is accepted.

The Effect of Patient Satisfaction as an Intervening Variable on the Relationship between Marketing Mix and Patient Decision in Choosing a Hospital

Figure 4 Path Analysis Hypothesis 6b

a)    Direct effect = 0.216

b)   Indirect Effect = 0.087

c)    Total effect = Direct effect + Indirect Effect = 0.216 + 0.087 = 0.303

d)   Variance accounted for (VAF) value = Direct effect / Total Effect = (0.216 / 0.303) = 0.713 or 71.3%

From the figure above, it is known that the p-value for the influence of the patient satisfaction variable on the relationship between the marketing mix and patient retention (indirect effect) is 0.038 with a regression coefficient value (Path Coefficient) of +0.087. Because the path coefficient value is marked positively and the p-value is 0.038<0.05, it can be concluded that the patient satisfaction variable has a significant effect on the relationship between marketing mix and patient well-being. The VAF value is 0.729 or 72.9% because the VAF value is> 20%, so it can be concluded that patient satisfaction is a mediating variable. Thus, the H6b hypothesis, "the relationship between the marketing mix and the patient's decision to choose a hospital through patient intelligence," is accepted.

The effect of service quality on patient satisfaction

The results of the research show that the t-value for the service quality variable is 4.476 at a significance level of 0.000 with a regression coefficient value (Path Coefficient) of +0.470. Because the path coefficient value is marked positively, the t-value statistic is >1.645, and the p-value is 0.000<0.05, it can be concluded that the service quality variable has a positive and significant effect on patient satisfaction. Thus, the H1 hypothesis "There is a relationship between service quality and patient satisfaction at Hermina Serpong Hospital" is supported. This means that the better the service quality that patients get, the more significant the impact on increasing patient satisfaction (Karsana & Murhadi, 2021).

The results of this study were showed that to increase patient satisfaction, it is necessary to improve the quality of service by increasing Tangibles, Reliability, Responsiveness, Assurance, and Empathy (Agustina & Handayani, 2023). Efforts made to improve the quality of service are that the hospital improves services by increasing the class of pregnant and maternity women so that patients know the benefits and advantages, especially from the aspects of safety, convenience, and comfort during the delivery process, the hospital improves communication and services to patients such as making 24-hour online consultations, contacting patients to re-control according to schedule,  asking for opinions and patient input to get service feedback after pregnancy control, the hospital carries out a "pick up the ball" service strategy for mothers who are close to the estimated delivery so as to increase access to services at health facilities. The hospital creates programs and packages of childbirth services that are attractive to patients, such as providing services for making birth certificates, Family Cards, and Child Identity Cards in collaboration with the Population and Civil Registration Office.

The results of this study corroborate the theory of Parasuraman et al. (2016) about service quality is greatly influenced by how the quality of the service dimension is felt by service users with the SERVQUAL dimensions, namely Tangibles, Reliability, Responsiveness, Assurance, and Empathy. Service quality is an assessment given on the perfection of a product or service from the value of benefits perceived by consumers on the basis of a comparison between what consumers expect and what consumers receive. This is supported by a study conducted by Kondasani & Panda (2018), a study on patients in 5 private hospitals in Rourkela, India. The results of the study show that the aspects of service quality consisting of the physical environment, reliability, customer-friendly staff, communication, responsiveness, privacy & safety have a positive effect on patient satisfaction (Singh & Dixit, 2020).

The effect of marketing mix on patient satisfaction

Based on the results of the research, it is known that the t calculation for the marketing mix variable is 2.518 at a significance level of 0.006 with a regression coefficient value (Path Coefficient) of +0.217. Because the path coefficient value is marked positively, the t-value statistic is >1.645, and the p-value is 0.006<0.05, it can be concluded that the marketing mix variable has a positive and significant effect on patient satisfaction. Thus, the H2 hypothesis "There is a positive and significant influence between marketing mix on patient satisfaction at Hermina Serpong Hospital" is supported. This means that the better the marketing mix will have an impact on high patient satisfaction (Nasution et al., 2020).

The results of this study showed that to increase patient satisfaction, it is necessary to increase the marketing mix by increasing the 7P (Product, Price, Promotion, Place, People, Process, and Physical Evidence). Efforts are made to increase the marketing mix; namely, the Hospital complies with the use of the hospital management information system (SIMRS) and reviews the Standard Operating Procedures (SOP) for outpatient services in which quality indicators related to outpatient waiting times are set.  Making the indicator of response time and service waiting time as indicators of service quality. Re-socialize service procedures with quality indicators of outpatient waiting time to all officers so that health workers can provide maximum service to patients (Oosterhuis, 2014). Improving services on time and according to the schedule that the hospital has determined. Increase the competitiveness of hospitals by creating online consultation services for patients. The Management of the Board of Directors reminds and motivates all doctors in the Hospital to start services in the Outpatient Unit on time and, if necessary, implement the "punishment and reward concept." The hospital reviews the SPO of patient service procedures starting from the registration process, outpatient polyclinic and inpatient. Optimizing all activities carried out with the Hospital Management Information System and online registration system to make it easier for patients (Wager et al., 2021). Periodic evaluation of the implementation of the Hospital Management Information System and the online registration system. There are rewards and penalties for members who implement the Hospital Management Information System and the online registration system. Mobilizing internal commitments to have the same mission for improving patient services.

According to Zeithaml and Bitner (2023) about the marketing mix where classifying the elements of the marketing mix into seven variables (7P) by adding 4P (Product, Price, Promotion, and Place) and 3P (People, Process, and Physical Evidence) that can be used well in the service business. The overall marketing mix is a series of marketing variables that can be controlled and used by hospital marketing implementers to market the health services produced. The results of this study are supported by research conducted by Mene Paradill (2022).

The effect of patient satisfaction on the decision to choose a place of delivery

The results of the study showed that the t calculation for the Patient Satisfaction variable was 2.415 at a significance level of 0.008 with a regression coefficient value (Path Coefficient) of +0.322. Because the path coefficient value is marked positively, the t-value statistically >1.645, and the p-value is 0.008<0.05, it can be concluded that the Patient Satisfaction variable has a positive and significant effect on the patient's decision to choose a hospital. Thus, the H3 hypothesis "There is a positive and significant influence between patient satisfaction and the patient's decision to choose a hospital" is supported.

From the results of this study, it was found that to improve the decision to choose a place of delivery, it is necessary to increase satisfaction. In an effort to increase patient satisfaction, it is necessary to increase the ease of information and appointments for patients with 24-hour online services and excellent service.

The results of this study confirm the theory of Ware et al. (2021) that Patient satisfaction is built based on 8 dimensions, namely: interpersonal manner (patient understanding of politeness, friendliness, and attention), technical quality of care (competence or skills), accessibility (ease and waiting time), finances, efficacy (reducing diseases suffered), continuity of care (similarity of doctors and nurses in serving), physical environment (physical condition of health service facilities), and availability (the presence of officers and the availability of medical equipment).

The results of this study are supported by the research of Siti Lubis (2017), stating that purchasing decisions have a positive influence on consumer satisfaction. Pighin et al (2022) results of the study show that there is a significant influence between patient satisfaction and patient decisions in reusing health services. Results of the study show that patient satisfaction contributes significantly to increasing revisit intention

The effect of service quality on the decision to choose a place of delivery

The results showed that the t calculation for the service quality variable was 3.217 at a significance level of 0.001 with a regression coefficient value (Path Coefficient) of +0.354. Because the path coefficient value is marked positively the t-value statistically >1.645 and p-value 0.001<0.05, it can be concluded that the service quality variable has a positive and significant effect on the patient's decision to choose a hospital. Thus, the H4 hypothesis "There is a positive and significant influence between service quality and patients' decisions in choosing hospitals" is supported. This means that the better the patient's assessment of the quality of the service received, the more positive it will have on the patient's decision to choose a hospital (Meesala & Paul, 2018).

The results of this study were obtained that to improve the decision to choose a place of delivery, it is necessary to improve the quality of plea services by increasing the class of pregnant and maternity women so that patients know the benefits and advantages, especially from the aspects of safety, convenience, and comfort during the delivery process, the hospital improves communication and services to patients such as making 24-hour online consultations, contacting patients to re-control according to schedule, asking for opinions and patient input to get service feedback after pregnancy control, the hospital carries out a "pick up the ball" service strategy for mothers who are close to the estimated delivery so as to increase access to services at health facilities. The hospital creates programs and packages of childbirth services that are attractive to patients, such as providing services for making birth certificates, Family Cards, and Child Identity Cards in collaboration with the Population and Civil Registration Office.

The results of this study are supported by research conducted by Park et al (2021), a study conducted on 540 clinic patients in South Korea. The results of the study show that service quality has a significant effect on patient satisfaction and revisit intention. Siripipatthanakul (2021), a study on 352 clinic patients in Thailand, the results of the study showed that service quality (Tangibles, Reliability, and Empathy) had a positive and significant effect on patients' decisions to reuse health services. Siti Araini Lubis (2017) shows that the existence of quality service will encourage consumer purchase decisions. In addition, quality service can also encourage consumers to establish a strong bond with the company (Wangsa et al., 2023).

The influence of marketing mix on the decision to choose a place of delivery

The results of the study show that the t calculation for the marketing mix variable is 1.894 at a significance level of 0.029 with a regression coefficient value (Path Coefficient) of +0.216. Because the path coefficient value is marked positively, the t-value statistic is >1.645, and the p-value is 0.029 <0.05, it can be concluded that the marketing mix variable has a positive and significant effect on the patient's decision to choose a hospital. Thus, the H5 hypothesis "There is a positive and significant influence between marketing mix on patients' decisions in choosing hospitals" is supported.

The results of this study were obtained that to improve the decision to choose a place of delivery, it is necessary to increase the marketing mix by increasing compliance with the use of the hospital management information system (SIMRS), review Standard Operating Procedures (SOP) for outpatient services in which quality indicators related to outpatient waiting times are set.  This is in accordance with the theory of consumer behavior of (Kotler & Amstrong, 2018). When making a choice, there are five stages that are passed, starting from when the buyer recognizes a need or problem, the buyer feels a difference between reality and the desired situation. Then, consumers who are aroused by their needs will be encouraged to look for more information. The next stage is that consumers try to meet their needs; consumers seek certain benefits from product solutions, and consumers view each product as a set of attributes with different abilities in providing benefits that are used to satisfy these needs. The stages that form preferences among product brands in the selection group. Consumers form the intention of purchase to buy the most preferred brand and after the purchase, the consumer may experience a discrepancy due to noticing certain features that are annoying or with pleasant things about other brands and will always be alert to information that supports his decision. This is supported by research conducted by Tarihoran et al. (2021); these results show that mix marketing (7P) has proven to be very helpful for hospitals in increasing the number of patient visits.

The influence between service quality, marketing mix and patient satisfaction has a positive effect on the decision to choose a delivery place at Hermina Serpong Hospital

Based on the results of the analysis of the role of patient satisfaction as a mediation or intervening variable, it is known that the patient satisfaction variable has a significant effect on the relationship between service quality and patient literacy. The VAF value is 0.701 or 70.1% because the VAF value is> 20%, so it can be concluded that patient satisfaction is a mediating variable. Thus, the H6a hypothesis, "There is a positive and significant influence between service quality and the patient's decision to choose a hospital through patient intelligence," is supported.  Patient satisfaction has a significant effect on the relationship between marketing mix and patient literacy. The VAF value is 0.729 or 72.9% because the VAF value is> 20%, so it can be concluded that patient satisfaction is a mediating variable. Thus, the H6b hypothesis "There is a positive and significant influence between marketing mix on patient decisions in choosing hospitals through patient satisfaction" is supported.

The results of this study are supported by several previous studies, namely Pighin et al (2022); Park et al (2021) and Siripipatthanakul (2021), the results of the study show that service quality has a positive and significant effect on patients' decisions in choosing a clinic through patient satisfaction.

 

CONCLUSION

Based on an analysis conducted on 190 samples of patients at Hermina Serpong Hospital. The study was conducted with the aim of analyzing the influence of service quality and marketing mix on the decision to choose a place of delivery at Hermina Serpong Hospital, with satisfaction as an intervening variable. the conclusions that can be stated in this study are as follows: The quality of service affects patient satisfaction at Hermina Serpong Hospital is supported. To increase patient satisfaction, it is necessary to improve the quality of service by improving timely services, providing accurate information, and providing fast and responsive services. The marketing mix affects patient satisfaction at Hermina Serpong Hospital, and it is supported. To increase patient satisfaction, it is necessary to increase the marketing mix by increasing compliance with the use of the hospital management information system (SIMRS), improving services on time and according to schedule, and creating online consultation services for patients. Patient satisfaction affects the patient's decision to choose a hospital at Hermina Serpong Hospital. To improve patient decisions in choosing a hospital, it is necessary to increase patient satisfaction with easy access to information and appointments for patients. The quality of service affects the patient's decision to choose a hospital at Hermina Serpong Hospital. To improve patients' decisions in choosing a hospital, it is necessary to improve the quality of service with a pick-up service and a program to make baby identity cards. Marketing mix affects patients' decisions when choosing a hospital at Hermina Serpong Hospital. To improve patients' decisions in choosing hospitals, it is necessary to increase the marketing mix by increasing the classes of pregnant and maternity women and expanding information on service flows and hospital facilities for the community. Service quality, marketing mix, and patient satisfaction affect the patient's decision to choose a hospital at Hermina Serpong Hospital. To improve patient decisions when choosing a hospital, it is necessary to improve the quality of service, marketing mix, and patient satisfaction.

 

REFERENCE

Agustina, R., & Handayani, S. (2023). HHC RSPP patient satisfaction and the impact of reliability, assurance, tangible, empathy, and responsiveness. East Asian Journal of Multidisciplinary Research, 2(2), 799–810.

Al Hammadi, H. M. H. M. (2019). Waiting Time And Patients’satisfaction.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.

Hossain, M. S., Yahya, S. B., & Khan, M. J. (2020). The effect of corporate social responsibility (CSR) health-care services on patients’ satisfaction and loyalty–a case of Bangladesh. Social Responsibility Journal, 16(2), 145–158.

Ilekis, J. V., Tsilou, E., Fisher, S., Abrahams, V. M., Soares, M. J., Cross, J. C., Zamudio, S., Illsley, N. P., Myatt, L., Colvis, C., Costantine, M. M., Haas, D. M., Sadovsky, Y., Weiner, C., Rytting, E., & Bidwell, G. (2016). Placental origins of adverse pregnancy outcomes: potential molecular targets: an Executive Workshop Summary of the Eunice Kennedy Shriver National Institute of Child Health and Human Development. American Journal of Obstetrics and Gynecology, 215(1), S1–S46. https://doi.org/10.1016/j.ajog.2016.03.001

Ismail, A., & Yunan, Y. M. (2016). Service quality as a predictor of customer satisfaction and customer loyalty. LogForum, 12(4), 269–283.

Karsana, W., & Murhadi, W. R. (2021). Effect of service quality and patient satisfaction on behavioral intention. Journal of Entrepreneurship and Business, 2(1), 25–36.

Kijima, T., Matsushita, A., Akai, K., Hamano, T., Takahashi, S., Fujiwara, K., Fujiwara, Y., Sato, M., Nabika, T., & Sundquist, K. (2021). Patient satisfaction and loyalty in Japanese primary care: a cross-sectional study. BMC Health Services Research, 21, 1–12.

Kotler, P., & Amstrong, G. (2018). Principles of Marketing. Edisi 15 Global Edition. Pearson.

Meesala, A., & Paul, J. (2018). Service quality, consumer satisfaction and loyalty in hospitals: Thinking for the future. Journal of Retailing and Consumer Services, 40, 261–269. https://doi.org/10.1016/j.jretconser.2016.10.011

Nasution, N. R., Girsang, E., Ginting, R., & Silean, M. (2020). The effect of marketing mix on patient satisfaction in Prima Vision Medan Special Hospital in 2019. International Journal of Research and Review, 7(8), 241–249.

Norris, J. R., & Walker, J. J. (2020). Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States. Remote Sensing of Environment, 249, 112013. https://doi.org/10.1016/j.rse.2020.112013

Nurfitriani, N., Paradilla, M., & Jariyah, A. (2022). Patient Satisfaction Service Experience Influence at Pertiwi Special Hospital for Mothers and Children, South Sulawesi. Journal of Asian Multicultural Research for Medical and Health Science Study, 3(1), 76–82.

Oosterhuis, H. (2014). Treatment as punishment: Forensic psychiatry in The Netherlands (1870–2005). International Journal of Law and Psychiatry, 37(1), 37–49. https://doi.org/10.1016/j.ijlp.2013.10.004

Park, S.-J., Yi, Y., & Lee, Y.-R. (2023). Assessment of six alternative models of service quality. Total Quality Management & Business Excellence, 34(3–4), 364–396.

Pighin, M., Alvarez-Risco, A., Del-Aguila-Arcentales, S., Rojas-Osorio, M., & Yáñez, J. A. (2022). Factors of the Revisit Intention of Patients in the Primary Health Care System in Argentina. Sustainability, 14(20), 13021. https://doi.org/10.3390/su142013021

Singh, D., & Dixit, K. (2020). Measuring perceived service quality in healthcare setting in developing countries: A review for enhancing managerial decision-making. Journal of Health Management, 22(3), 472–489.

Tarihoran, U., Girsang, E., Nasution, S. L. R., & Ginting, C. (2021). Marketing mix 7P application to increase patient re-visits. Science and Technology Publications, 73–79.

Uzir, M. U. H., Al Halbusi, H., Lim, R., Jerin, I., Abdul Hamid, A. B., Ramayah, T., & Haque, A. (2021). Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19. Technology in Society, 67, 101780. https://doi.org/10.1016/j.techsoc.2021.101780

van den Broek, J., Boselie, P., & Paauwe, J. (2018). Cooperative innovation through a talent management pool: A qualitative study on coopetition in healthcare. European Management Journal, 36(1), 135–144. https://doi.org/10.1016/j.emj.2017.03.012

Wager, K. A., Lee, F. W., & Glaser, J. P. (2021). Health care information systems: a practical approach for health care management. John Wiley & Sons.

Wangsa, I. H. S., Sulastri, S., & Arini, D. P. (2023). It Goes Beyond Product-Business Innovativeness and Consumer’s New Values Adoption.

Ware, J. E. (2021). Measuring functioning, well-being, and other generic health concepts. In Effect of cancer on quality of life (pp. 7–23). CRC Press.

Waters, S., Edmondston, S. J., Yates, P. J., & Gucciardi, D. F. (2016). Identification of factors influencing patient satisfaction with orthopaedic outpatient clinic consultation: A qualitative study. Manual Therapy, 25, 48–55. https://doi.org/10.1016/j.math.2016.05.334

 

 

https://jurnal.syntax-idea.co.id/public/site/images/idea/88x31.png

© 2024 by the authors. It was submitted for possible open-access publication under the terms and conditions of the Creative Commons Attribution (CC BY SA) license (https://creativecommons.org/licenses/by-sa/4.0/).