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PLoS One ; 14(9): e0221807, 2019.
Article in English | MEDLINE | ID: mdl-31527872

ABSTRACT

OBJECTIVE: Medical 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. METHODS: The 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. RESULTS: Thirteen 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. CONCLUSION: Implementing 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.


Subject(s)
Patient Admission , Psychiatric Department, Hospital , Decision Making, Organizational , Expert Testimony , Hospitalization , Humans , Medicine , Netherlands , Psychiatry , Systems Analysis
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