You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Medication Reconciliation During Hospitalization and in Hospital-Home Interface: An Observational Retrospective Study Medication errors are one of the leading causes of patient harms. Medication reconciliation is a fundamental process that to be effective, it should be embraced during each single care transition. Our objectives were to investigate current medication reconciliation practices in the 2 Fondazione Toscana Gabriele Monasterio hospitals and comprehensively assess the quality of medication reconciliation practices between inpatient and outpatient care by analyzing the medication patterns 6 months before admission, during hospitalization, and 9 months after discharge for a selected group of patients with cardiovascular diseases. A retrospective observational study was conducted in the Cardiothoracic Department of the Fondazione Toscana Gabriele Monasterio hospitals. Medication history was reviewed for all the patients admitted from and discharged to the community, from January to March 2013. Patients were excluded if they had less than 4 drugs or less than 2 drugs for cardiovascular system in their prescription list at admission or if they died during follow-up. We selected 714 patients, and we obtained the clinical charts and all drug prescriptions collected during patients ' hospitalization by the electronic clinical recording system. We also analyzed the list of prescriptions of this sample of patients, from 6 months before admission to 9 months after discharge, extracted from the regional prescription registry. In the resulting sample, prescriptions were analyzed to assess unintentional discrepancies. The study included 298 patients (mean age, 71.2 years), according to the inclusion and exclusion criteria. Among 14,573 prescriptions analyzed, we found 4363 discrepancies (14.6 discrepancies per patient). Among these discrepancies, 1310 were classified as unintentional (4.4 discrepancies per patient). Among unintentional discrepancies, only 63 (4.8%) took place during hospitalization. Although at the hospital-home interface, 33.1% of unintentional discrepancies were detected through the comparison between the patients ' declared therapy and the previous medication consumption and 62.1% were identified in the comparison between the prescription at the discharge and the following medication pattern at home. Medication errors have important implications for patient safety, and their identification is a main target for improving clinical practice. The comparison between the medication patterns acquired through the regional prescription registry before and after hospitalization outlined critical touchpoint in the current medication reconciliation process, calling for the definition of shared medication reconciliation standards between hospitals and primary care services to minimize medication discrepancies and enhance patient safety.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["cardiovascular diseases"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": ["cardiovascular system"], "Chemical": [], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["discrepancies"], "Food": [], "HealthCareActivity": ["discharged", "patient safety", "Medication Reconciliation", "admission", "discharge", "care transition", "Hospitalization", "medication reconciliation", "primary care services", "hospitalization", "admitted", "drugs", "follow-up", "Medication reconciliation"], "InjuryOrPoisoning": [], "IntellectualProduct": ["prescriptions", "drug prescriptions", "regional prescription registry", "list of prescriptions", "prescription list", "clinical charts", "Medication history", "prescription"], "MedicalDevice": [], "Organization": ["Fondazione Toscana Gabriele Monasterio hospitals", "Cardiothoracic Department", "hospitals"], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study", "analyzing", "retrospective observational study", "analyzed", "Observational Retrospective Study"], "SpatialConcept": ["home"], "Virus": []}