2.5. Population-Based Value Pre-Configuration

This correlated general medical knowledge plays a vital role in the formulation of personalized treatment plans that are aligned with patients’ needs and values, leading to improved satisfaction, enhanced recovery, and overall health benefits (refer to Figure 8). The values of individuals are closely associated with their specific characteristics. For example, individuals in the public eye may prioritize appearance and charisma, while writers may highly value their creative abilities, and assembly line workers may prioritize rest. In our research, we specifically focus on exploring the relationship between occupation-related characteristics and values within the population. We selected five evenly distributed community service centers in the local city area and conducted a one-week survey activity in each community. We conducted a uniform survey of individuals aged 18 and above but below 65 to understand their occupations and explored their valued beliefs using interviews and questionnaires. During the interviews, we guided them to express the values related to their professions and asked them to rate the importance on a scale from 0 to 1. After completing the surveys in the five community service centers, we grouped data from individuals with the same occupations and calculated the average values. Ultimately, these values are used as the predefined weight values for the value system of different occupational groups. We employ statistical mapping techniques to identify the correlations between occupations and values, considering the impact of side effects on these values. Moreover, we provide preset values that represent the significance of such impact, contributing to a more comprehensive understanding of the values influencing decision-making processes.

Structure that takes breast cancer as an example to show the mapping of general medical knowledge and values.

The statistical preset values initially determined are further fine-tuned based on individualized values for each patient, thereby providing a more precise assessment of the influence of side effects on patients’ demographic characteristics. This personalized adjustment enables a better alignment of the preset values with the specific circumstances of each patient. For instance, personalized modifications can be made to accommodate patients in particular occupations, ensuring that the preset values are more tailored to their unique needs. Table 5 exemplifies preset values for three distinct occupations, serving as a valuable reference for healthcare professionals to consider patients’ demographic characteristics and values during the formulation of personalized treatment plans. By incorporating these considerations, doctors can provide more targeted and effective care that accounts for the diverse needs and values of their patients.

Population-based value pre-configuration.

Based on these works, our approach of correlating population and values enables a comprehensive understanding of patients’ unique requirements, allowing us to effectively address their individualized needs. By incorporating this knowledge, we can develop treatment plans that are closely aligned with their values, resulting in more personalized and patient-centered care. This approach provides robust support for enhancing the quality of medical interventions and promoting patient satisfaction and well-being.