ObjectiveMedical Psychiatry Units (MPUs), also known as Complexity Intervention Units (CIUs), provide care for complex patients suffering from both psychiatric and physical disorders. Because there is no consensus on the indications for admission to an MPU, daily practice and effectiveness research are hampered. This study therefore used a concept mapping approach to investigate which organizational and medical factors determine the decision to admit a patient to an MPU.MethodsThe first step of the concept mapping approach was to create a list of factors determining MPU admission from literature. Secondly, clinical experts sorted and ranked these factors. The sorted and ranked data were then analyzed, and a draft conceptual framework was created. A final conceptual MPU admission framework was then drawn during an expert consensus meeting and recommendations for implementation were suggested.ResultsThirteen clinical experts defined 90 factors from literature, which were sorted and ranked by 40 experts from 21 Dutch hospitals. This concept mapping approach resulted in a five-cluster solution for an MPU admission framework based on: 1. Staff competencies and organizational pre-requisites; 2. Patient context; 3. Patient characteristics; 4. Medical needs and capabilities; and 5. Psychiatric symptoms and behavioral problems. Furthermore, three inclusion and two exclusion criteria were formulated to help the clinicians decide whether or not to admit patients to an MPU. These criteria can be implemented in daily practice.ConclusionImplementing the five criteria derived from this conceptual framework will help make the admission decision for complex patients with psychiatric and physical disorders to an MPU more correct, consistent, and transparent.

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a) demographic data (e.g. age) and (b) non-sensitive data related to general health (e.g. sleep). HCPs were less comfortable sharing sensitive information about HIV status, sexual health, behaviour and identity. Service user consent and relevance of data to sharing context were key determinants of data-sharing comfort. Conclusion Understanding the context of data-sharing in HIV care is increasingly important given the shift to remote consultations and expectations for self-management. We demonstrate the complex interplay of data types, relationship dynamics, and contexts of care provision that shape the data-sharing ecosystem in HIV care. Developing guidance on the sharing of service user and clinic-generated data in HIV care must account for these complexities.

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