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Bridging the gap and developing a home-based palliative care model for cancer patients
Zahra Alizadeh1, Camelia Rohani2,3, Maryam Rassouli4
1Department of Medical-Surgical Nursing, School of Nursing & Midwifery, Iran University of Medical Sciences, Tehran, Iran.
This study developed a home-based palliative care model for cancer patients in Iran to enhance quality of life and reduce costs. The model, comprising 92 indicators across eight pillars, guides practical implementation and innovative programs.
Area of Science:
- Health Policy and Systems Research
- Palliative Care
- Oncology
Background:
- Early integration of palliative care in home health services is crucial for cancer patients.
- Palliative care improves quality of life and reduces healthcare costs for cancer patients.
- A structured home-based model is needed for Iranian cancer patients.
Purpose of the Study:
- To develop a comprehensive home-based palliative care model for adult cancer patients in Iran.
- To address barriers and enhance the delivery of palliative care at home.
- To provide a framework for improving patient outcomes and healthcare efficiency.
Main Methods:
- Health policy and systems research following WHO guidelines.
- Four phases: integrative review, qualitative study (interviews, focus groups), result integration, and Delphi rounds for validation.
- Utilized 37 individual interviews and 1 focus group (8 participants), followed by 4 Delphi rounds with 118 integrated indicators.
Main Results:
- Identified barriers and developed 22 categories within eight pillars from qualitative data.
- Integrated findings into a conceptual model with 118 indicators.
- Validated a final conceptual model for home-based palliative care in cancer patients, featuring 92 indicators across eight pillars.
Conclusions:
- The developed model serves as a guide for similar societies to design practical home-based palliative care programs.
- The model can inform innovative strategies for cancer patient care at home.
- Future research should investigate the model's application in predicting patient outcomes.
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