<![CDATA[This study investigates how human and organizational factors shape Patient Safety Culture in healthcare settings. Specifically, we evaluate the direct and indirect structural relationships between intrinsic motivation, preventive discipline, and evidence-based risk management, while identifying the minimum necessary baseline levels (bottlenecks) required to sustain a resilient safety culture. We conducted a quantitative, descriptive-verificative study surveying 86 hospital employees at a facility in Bandung City, Indonesia. We collected primary data using validated questionnaires covering Intrinsic Motivation, Preventive Discipline, Risk Management, and Patient Safety Culture. To analyze the data, we integrated Path Analysis—to evaluate structural direct and indirect effects—with Necessary Condition Analysis (NCA) to uncover non-linear necessity logic and operational bottlenecks. Path analysis reveals that intrinsic motivation exerts a 41.2% total effect on evidence-based risk management (23.0% direct effect and 17.7% indirect effect mediated by preventive discipline), while risk management subsequently drives 83.4% of patient safety culture (epsilon = 0.194). Furthermore, NCA results establish that Preventive Discipline (d = 0.499, p < 0.001), Risk Management (d = 0.447, p < 0.001), and Intrinsic Motivation (d = 0.420, p < 0.001) all function as strong necessary conditions. Without satisfying the baseline thresholds of each variable, high patient safety culture cannot exist. Hospital administrators must pursue a dual managerial approach: utilize motivation and risk management as proactive levers to elevate safety culture while rigorously enforcing baseline preventive discipline. Relying on advanced risk systems alone is insufficient if individual motivation or discipline drops below critical necessity thresholds. This research bridges a critical methodological gap by combining traditional sufficiency-based structural modeling (Path Analysis) with necessity-based evaluation (NCA) in healthcare safety literature, offering explicit quantitative thresholds for patient safety conditions rather than relying solely on average linear relationships.]]>
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