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Identifying High-Cost, High-Risk Patients Using Administrative Databases in Tuscany, Italy
OBJECTIVE: (1) Assessing the performance of the algorithm in terms of sensitivity and positive predictive value, considering General Practitioners' (GPs) judgement as benchmark, and (2) describing adverse events (hospitalisation, death, and health services' consumption) of complex patients...
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Publicado en: | Biomed Res Int |
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Autores principales: | , , , , , , , |
Formato: | Artigo |
Lenguaje: | Inglês |
Publicado: |
Hindawi
2017
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Materias: | |
Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5523251/ https://ncbi.nlm.nih.gov/pubmed/28770229 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/9569348 |
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