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Unlocking the Black Box of E-Health Adoption: A Peek into the Minds of Healthcare Professionals

원문정보

초록

영어

Introduction: E-health technologies promise enhanced quality of care through greater access to patient data and improved provider-patient interactions. However, adoption rates remain suboptimal. This study investigates factors influencing healthcare professionals’ intentions to adopt e-health solutions. Methods: A survey was administered to a diverse sample of 414 healthcare providers across inpatient and outpatient settings. The questionnaire comprised validated scales measuring TAM constructs of perceived usefulness and perceived ease of use along with other adoption factors identified in literature. Data analysis included EFA, SEM, and ANN predictive modelling. Results: Findings highlight the significance of accessibility to records, availability of patient information, and provider-patient relationships facilitated through e-health in driving adoption intentions beyond perceived usefulness and ease of use. Significant predictors are expected to inform targeted interventions promoting seamless e-health integration. Conclusions: By scrutinizing technological contexts alongside cognitive beliefs within a healthcare-specific framework, the study will enrich understanding of e-health adoption from providers’ perspective. Results can guide training programs and change management strategies for enabling greater utilization of impactful e-health tools in practice. This research is poised to provide actionable insights on the multifaceted factors influencing healthcare professionals’ acceptance versus resistance of promising e-health solutions for enhancing quality and performance.

목차

A B S T R A C T
Ⅰ. Introduction
1.1. Theoretical Framework
1.2. Hypothesis and Research ModelDevelopment
Ⅱ. Methods
2.1. Study Design and Settings
2.2. Study Population and Sample
2.3. Data Collection Tool
2.4. Statistical Analysis
2.5. Demographics Profile
Ⅲ. Results
3.1. Multivariate Assumptions
3.2. Normality Test
3.3. Common Method Bias
3.4. Internal Reliability
3.5. Discriminant Validity
3.6. Path Analysis
3.7. Artificial Neural Network (ANN)
Ⅳ. Discussion
4.1. Limitations and Future Research
4.2. Practical Implications
Ⅴ. Conclusions

저자정보

  • Abhishek Dondapati Assistant Professor, Centre for Healthcare Management, AdministrativeSstaff College of India, Hyderabad, India
  • Vaneeta Aggarwal Assistant Professor, Department of Management Studies, University of Madras, Chennai, India
  • Ranjit Kumar Dehury Assistant Professor, School of Management Studies, University of Hyderabad, Hyderabad, India

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