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Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling.

Khondker Mohammad Zobair1, Louis Sanzogni1, Luke Houghton2

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Patient satisfaction with telemedicine in rural Bangladesh is driven by expectations, performance, and enjoyment. Understanding these factors is key for improving healthcare access and telemedicine adoption.

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Area of Science:

  • Health Informatics
  • Digital Health
  • Rural Health

Background:

  • Rural populations increasingly utilize telemedicine for health needs.
  • Understanding patient satisfaction is crucial for successful telemedicine adoption.
  • Existing theories need extension to explain telemedicine satisfaction in rural settings.

Purpose of the Study:

  • To investigate the factors influencing patient satisfaction with telemedicine in rural Bangladesh.
  • To develop and validate a predictive model for telemedicine adoption.
  • To provide insights for enhancing telemedicine services in public hospitals.

Main Methods:

  • Adaptation of Expectation Disconfirmation Theory and Social Cognitive Theory.
  • Development of a predictive model with four antecedents: expectations, performance, disconfirmation, and enjoyment.
  • Validation using two-staged structural equation modeling and artificial neural network approaches.

Main Results:

  • Identified key determinants of patient satisfaction with telemedicine.
  • Demonstrated the significant contribution of expectations, performance, disconfirmation, and enjoyment.
  • Validated the predictive model for telemedicine adoption in the study context.

Conclusions:

  • The study provides a robust model for predicting patient satisfaction with telemedicine.
  • Findings offer practical guidance for healthcare providers and policymakers to improve telemedicine services.
  • Recommendations support the long-term sustainability and effectiveness of telemedicine in rural areas.