Factors Affecting Patient Assessment Based On Hospital Medical Care Services With Discriminant Analysis Methods (Case Study At Mother Thamrin Hospital)

Feb 27, 2025 by ADMIN 152 views

Introduction

In the healthcare industry, patient assessment of hospital services plays a crucial role in improving service quality. One method that can be used to analyze the factors that influence patient assessment is discriminant analysis. This analysis serves to determine the relationship between variables, namely the respondent variable and the explanatory variable, assuming the data is normally multivariate.

Background

Research conducted at the Mother Thamrin Medan General Hospital aims to identify variables that affect patient assessment. The results of discriminant analysis show that there are five significant variables, namely: physical evidence (X1), empathy (X2), reliability (X3), responsiveness (X4), and certainty (X5). Of the five variables, physical evidence (X1) and reliability (X3) have proven to be the dominant factor that affects patient assessment.

Physical Evidence (X1)

Physical evidence includes all aspects that can be seen and felt by patients, such as hospital cleanliness, available facilities, and medical appearance. In this case, hospitals that have good facilities and a clean environment tend to get a higher assessment than patients. Physical evidence is a critical factor in patient assessment, as it reflects the hospital's ability to provide a safe and comfortable environment for patients.

Reliability (X3)

Reliability, which refers to the ability of hospitals in providing promised services, is also very influential. Patients want to feel confident that they will get treatment that suits their needs. Reliability is a key factor in patient assessment, as it reflects the hospital's ability to deliver on its promises and provide high-quality care.

Empathy (X2), Responsiveness (X4), and Certainty (X5)

The other three variables, namely empathy, responsiveness, and certainty, also contribute to the assessment, although not as strong as the two main variables. Empathy includes the attention and understanding of medical personnel to patients, while responsiveness is related to how fast the hospital staff responds to the patient's request or complaint. Certainty regarding guarantees and safety felt by patients when getting services.

Classification Accuracy

With a classification accuracy level of 58.5%, the results of discriminant analysis show that this model can be used to understand and analyze the factors that affect patient assessment. This knowledge can be the basis for hospital management in designing service improvement strategies. Improving the quality of physical evidence and reliability, along with strengthening aspects of empathy, responsiveness, and certainty, can be a strategic step to increase patient satisfaction.

Conclusion

In this context, it is essential to understand that patient assessment is not only a reflection of service quality but also has a direct impact on the reputation and sustainability of hospital operations. Therefore, by using discriminant analysis methods, hospitals such as Mother Thamrin General Hospital can be more effective in identifying areas that need to be improved for better patient satisfaction and more optimal service results.

Recommendations

Based on the results of this study, the following recommendations can be made:

Improve physical evidence: Hospitals should focus on improving their physical evidence, including hospital cleanliness, available facilities, and medical appearance.
Enhance reliability: Hospitals should prioritize enhancing their reliability, including providing promised services and delivering high-quality care.
Strengthen empathy: Hospitals should focus on strengthening their empathy, including providing attention and understanding to patients.
Improve responsiveness: Hospitals should prioritize improving their responsiveness, including responding quickly to patient requests or complaints.
Increase certainty: Hospitals should focus on increasing certainty, including providing guarantees and safety to patients.

By implementing these recommendations, hospitals can improve patient satisfaction and achieve more optimal service results.

Limitations

This study has several limitations, including:

Sample size: The sample size of this study is relatively small, which may limit the generalizability of the results.
Data collection: The data used in this study was collected through a survey, which may be subject to biases and limitations.
Analysis: The analysis used in this study is based on discriminant analysis, which may not capture all the complexities of patient assessment.

Future Research Directions

Future research should focus on:

Increasing sample size: Future studies should aim to increase the sample size to improve the generalizability of the results.
Using multiple data sources: Future studies should use multiple data sources, including administrative data and patient feedback, to provide a more comprehensive understanding of patient assessment.
Analyzing complex relationships: Future studies should analyze complex relationships between variables, including interactions and non-linear relationships.

Q1: What is discriminant analysis, and how is it used in patient assessment?

A1: Discriminant analysis is a statistical method used to analyze the relationship between variables, including the respondent variable and the explanatory variable. In patient assessment, discriminant analysis is used to identify the factors that influence patient satisfaction and to develop strategies to improve service quality.

Q2: What are the five significant variables that affect patient assessment?

A2: The five significant variables that affect patient assessment are:

Physical evidence (X1): This includes all aspects that can be seen and felt by patients, such as hospital cleanliness, available facilities, and medical appearance.
Empathy (X2): This includes the attention and understanding of medical personnel to patients.
Reliability (X3): This refers to the ability of hospitals in providing promised services.
Responsiveness (X4): This is related to how fast the hospital staff responds to the patient's request or complaint.
Certainty (X5): This refers to the guarantees and safety felt by patients when getting services.

Q3: Why are physical evidence and reliability the dominant factors that affect patient assessment?

A3: Physical evidence and reliability are the dominant factors that affect patient assessment because they reflect the hospital's ability to provide a safe and comfortable environment for patients and to deliver on its promises.

Q4: How can hospitals improve patient satisfaction based on the results of this study?

A4: Hospitals can improve patient satisfaction by:

Improving physical evidence: Focus on improving hospital cleanliness, available facilities, and medical appearance.
Enhancing reliability: Prioritize providing promised services and delivering high-quality care.
Strengthening empathy: Focus on providing attention and understanding to patients.
Improving responsiveness: Prioritize responding quickly to patient requests or complaints.
Increasing certainty: Focus on providing guarantees and safety to patients.

Q5: What are the limitations of this study, and how can they be addressed in future research?

A5: The limitations of this study include:

Sample size: The sample size of this study is relatively small, which may limit the generalizability of the results.
Data collection: The data used in this study was collected through a survey, which may be subject to biases and limitations.
Analysis: The analysis used in this study is based on discriminant analysis, which may not capture all the complexities of patient assessment.

Future research should aim to increase the sample size, use multiple data sources, and analyze complex relationships between variables.

Q6: What are the implications of this study for hospital management and policy-making?

A6: The implications of this study for hospital management and policy-making are:

Prioritize patient satisfaction: Hospital management should prioritize patient satisfaction and develop strategies to improve service quality.
Use discriminant analysis: Hospital management can use discriminant analysis to identify the factors that influence patient satisfaction and to develop targeted interventions.
Monitor and evaluate: Hospital management should regularly monitor and evaluate patient satisfaction and service quality to ensure that improvements are sustained over time.

By addressing these implications, hospital management can improve patient satisfaction and achieve more optimal service results.