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Indicators for palliative care integration in primary health care: how expert profile shapes consensus in a modified
Carolina Muñoz Olivar1,2,3, Juan Sebastián Gómez Quintero4, Fernando Pastrana Rendon5
1Health Sciences, Faculty of Medicine, Antonio Nariño University, Bogotá, Colombia. camunoz97@uan.edu.co.
Background:
Integrating palliative care into primary health care requires clear, feasible, and valid indicators. Consensus-based methods such as Delphi are commonly used for this purpose, but they may overlook differences in how heterogeneous expert panels prioritize indicators. This study aimed to strengthen the methodological approach used to select indicators for assessing the integration of palliative care into primary health care. This study aimed to strengthen the methodological approach used to select indicators for assessing the integration of palliative care into primary health care.
Methods:
A two-round modified Delphi was conducted with 23 experts from different regions of Colombia. Each indicator was rated for relevance, feasibility, and validity. A priori consensus was defined as ≥70% of ratings ≥7/10 and IQR ≤2. Global content validity indices (S-CVI) and Lawshe's content validity ratio (CVR) were calculated as supportive evidence. Expert profile was quantified using the Metric for Assessing Knowledge and Understanding (MAKU) and used to stratify analyses, To explore data patterns, separate 2×2 SOMs were trained for Strategic and Operational profiles using normalized medians and robust coefficients of variation. Neurons with higher median scores and lower dispersion were interpreted as favorable.
Results:
Global S-CVI increased from 0.86 in Round 1 to 0.88 in Round 2. By dimension, relevance rose from 0.82 to 0.85, feasibility remained stable at 0.72, and validity increased from 0.62 to 0.71. Stratification by expert profile revealed meaningful differences in consensus patterns. SOM analysis showed both shared and differing prioritization patterns across profiles. After removing overlaps, a final set of eighteen indicators was retained from the dominant neurons of the profile-specific SOMs.
Conclusion:
Combining a modified Delphi with MAKU-based stratification and self-organizing maps provided a transparent and profile-sensitive approach to strengthen consensus-based indicator selection in a heterogeneous expert panel. Differences in expert profile influenced how indicators were prioritized. This approach supports more rigorous and context-aware selection of indicators for monitoring palliative care integration in primary health care.
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