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Implementing the information system for older adult patients post-discharge self-management: a qualitative study
Dorothy Yingxuan Wang1, Eliza Lai-Yi Wong1,2, Annie Wai-Ling Cheung1,2
1JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.
Background:
Discharging older adult patients from the hospital poses risks due to their vulnerable conditions, complex instructions and limited health literacy. Insufficient information about medication side effects adds to patient concerns. To address this, a post-discharge information summary system was developed. While it has shown positive impacts, concerns exist regarding implementation fidelity.
Objective:
This study employed a theory-driven approach to understand health providers' perspectives on effective implementation.
Method:
Individual semi-structured interviews were conducted via telephone with nurses, doctors and pharmacists from local public hospitals. All interviews were audio-recorded and transcribed verbatim. Theoretical Domains Framework (TDF) was applied for direct content analysis. Belief statements were generated by thematic synthesis under each of the TDF domains.
Results:
A total of 98 participants were interviewed. Out of the 49 belief statements covering eight TDF domains, 19 were determined to be highly relevant to the implementation of the post-discharge information summary system. These TDF domains include knowledge, skills, social/professional role and identity, beliefs about consequences, intentions, memory, attention and decision processes, environmental context and resources and social influences.
Conclusion:
Our study contributes to the understanding of determinants in implementing discharge interventions for older adult patients' self-care. Our findings can inform tailored strategies for frontline staff, including aligning programme rationale with stakeholders, promoting staff engagement through co-creation, reinforcing positive programme outcomes and creating default settings. Future research should employ rigorous quantitative designs to examine the actual impact and relationships among these determinants.
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