The impact of perceived value on patient satisfaction and behavioral intention in private teaching hospitals of Nepal

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To meet the growing expectations of patients, it has become inevitable for healthcare institutions to improve their quality. This study investigates how perceived value influences patient satisfaction and behavioral intentions in four private teaching hospitals in Nepal. This study employed a mixed-methods approach. In the first phase, the qualitative study extracted value dimensions using thematic analysis following an in-depth interview with nine patients. The five themes were functional value of emotion, personnel, price, establishment and service quality. These findings guided the development of a structured questionnaire used in the quantitative study phase. 399 patients of Outpatient Department across four private teaching hospitals of Kathmandu participated in this phase. The study used convenience sampling for respondent selection and data analysis was conducted using structural equation modelling with the SMART PLS approach.
The findings showed that patient satisfaction was significantly affected by the functional values related to emotion (β = 0.160, p < 0.001), personnel (β = 0.238, p < 0.001), price (β = 0.239, p < 0.001) and service quality (β = 0.376, p < 0.001), while establishment (β = -0.207, p < 0.001) was found to have no impact on satisfaction. The result also showed a significant impact of patient satisfaction on behavioral intention (β = 0.229, p < 0.001). The insights from the findings highlight the main factors that patients link to value, which enables the healthcare providers to strategize and offer services accordingly. Understanding these factors helps develop the value aspects that focus on optimizing patient satisfaction, trust and build loyalty towards healthcare services over time.

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    • Figure 1. Conceptual model
    • Figure 2. Measurement model with factor loading path coefficient and Average Variance Extracted (AVE)
    • Table 1. Demographic characteristics
    • Table 2. Result of normality test
    • Table 3. Reliability and convergent validity
    • Table 4. Fornell-Larcker criterion
    • Table 5. HTMT ratios
    • Table 6. Model fit
    • Table 7. Test of multicollinearity
    • Table 8. Structural model assessment and hypotheses testing
    • Conceptualization
      Ashtha Karki, Priti Ranjan Sahoo
    • Data curation
      Ashtha Karki, Kharabela Rout
    • Formal Analysis
      Ashtha Karki
    • Funding acquisition
      Ashtha Karki
    • Investigation
      Ashtha Karki
    • Methodology
      Ashtha Karki, Priti Ranjan Sahoo
    • Project administration
      Ashtha Karki
    • Resources
      Ashtha Karki
    • Software
      Ashtha Karki, Kharabela Rout
    • Writing – original draft
      Ashtha Karki
    • Supervision
      Priti Ranjan Sahoo
    • Validation
      Priti Ranjan Sahoo, Kharabela Rout
    • Writing – review & editing
      Priti Ranjan Sahoo, Kharabela Rout