安宁疗护的家庭决策机制OACHSSCD

"Expanding the supply of hospice care services"is one of the key tasks for advancing the Healthy China initiative during the 15th Five-Year Plan period.Using the Grounded Theory approach,this paper explores in depth the influencing factors and their mechanisms in the family decision-making process regarding hospice care.The results reveal that within this family decision-making process,decision initiation serves as the triggering condition,family characteristics constitute the internal foundation,environmental empowerment provides the external context,and the decision outcome is the ultimate manifestation of the combined effects of these categories.This study constructs a model of the family decision-making mechanism in hospice care,to explain that the family decision-making mechanism of hospice care is based on the logic of"ineffective treatment"and"no access to medical care",with family traits and environmental empowerment deeply embedded in a networked manner.Multiple factors are characterized by concurrency,mutual causality,and dynamic interaction,jointly shaping the decision outcome.At the same time,the study clarifies the relative weight and applicable boundaries of each factor in family decision-making,which reveals a dynamic evolutionary process characterized by a sequence of"hesitation-conflict-consensus-execution",and elucidates that family decision-making is the differentiation mechanism distributed along a continuum from"active choice"to"passive acceptance".This research can provide practical guidance for families facing hospice care decisions,advocating a shift from"passively dealing with problems only when they arise"to"proactively planning ahead before issues arise"and suggesting that families make optimal decisions through a four-step approach:clarifying family needs,identifying family resources,finding suitable services,and evaluating decision options.At the same time,it provides a theoretical basis for improving the policy guarantee system for hospice care and a practical reference for optimizing service resources allocation.