[Developing a decision tool: indicating care for mild intellectual disability]. / Ontwikkeling decision tool voor een lichte verstandelijke beperking: zorg aan de juiste doelgroep.

BACKGROUND: Children and youth with an intellectual disability and psychiatric problems are a complex group. By identifying clients who require highly specialized mental health care at an early stage, it is expected that the provided care can be utilized more effectively, there will be less non-response and clients will more efficiently receive the most appropriate care. AIM: To develop a decision tool which can identify clients who need highly specialized care at an early stage. METHOD: A review of the literature and qualitative research methods were used, including a Delphi study to get consensus on criteria that could be used as indicators for highly specialized care. These criteria were included in a decision tool, followed by validation of these criteria by testing them on the population of the Banjaard, a mental health care setting for young people with intellectual disability and psychiatric problems. RESULTS: Ten criteria emerged from the Delphi method that were seen to be predictive of the need for highly specialized care. After applying these criteria to the Banjaard population, it appeared that three or more criteria reliably identified clients needing highly specialized care (sensitivity 76.5% and specificity 75.6%). CONCLUSION: The decision tool developed in the current study is a reasonable instrument for identifying clients who could benefit from highly specialized mental health care.

[Linking mental healthcare- and Statistics Netherlands microdata to assess the effectiveness of care]. / Koppelen van ggz- en CBS-microdata om zorgeffectiviteit te meten.

BACKGROUND: The effectiveness of mental health care is currently monitored through routine quantitative symptom-driven measurements in most clinical settings. These measurements seem inadequate, especially for target groups with complex, multi-faceted problems. There is as yet no alternative method. AIM: 1. To describe why quantitative symptom-driven measurements are inadequate for measuring healthcare effectiveness; and 2. to introduce a new data platform that adjusts for socioeconomic and environmental factors to monitor the effectiveness of healthcare. METHOD: Overview of developments based on literature and introduction of a unique data platform. RESULTS: In the case of complex, multi-faced problems, such as in children with mild intellectual disability and comorbid psychopathology, mental health problems cannot be quantified, isolated, and individualized, i.e., decontextualized. To evaluate care for external benchmarking and scientific research, a shift is advised from measuring clinical symptoms within the treatment period to measuring longer-term group-level social functioning across multiple life domains, with a focus on socio-demographic differences. The Extramuraal LUMC Academisch Netwerk Gezond & Gelukkig Den Haag (ELAN-GGDH ; in English: Extramural LUMC Academic Network Healthy & Happy The Hague) data platform accomplishes this by combining mental health data with Statistics Netherlands microdata. CONCLUSION: The data platform could add value to external benchmarking and scientific research at group level.