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:

Visual Analytics for Pattern Discovery in Home Care. Clinical Relevance for Quality Improvement Visualization can reduce the cognitive load of information, allowing users to easily interpret and assess large amounts of data. The purpose of our study was to examine home health data using visual analysis techniques to discover clinically salient associations between patient characteristics with problem-oriented health outcomes of older adult home health patients during the home health service period. Knowledge, Behavior and Status ratings at discharge as well as change from admission to discharge that was coded using the Omaha System was collected from a dataset on 988 de-identified patient data from 15 home health agencies. SPSS Visualization Designer v1.0 was used to visually analyze patterns between independent and outcome variables using heat maps and histograms. Visualizations suggesting clinical salience were tested for significance using correlation analysis. The mean age of the patients was 80 years, with the majority female (66%). Of the 150 visualizations, 69 potentially meaningful patterns were statistically evaluated through bivariate associations, revealing 21 significant associations. Further, 14 associations between episode length and Charlson co-morbidity index mainly with urinary related diagnoses and problems remained significant after adjustment analyses. Through visual analysis, the adverse association of the longer home health episode length and higher Charlson co-morbidity index with behavior or status outcomes for patients with impaired urinary function was revealed. We have demonstrated the use of visual analysis to discover novel patterns that described high-needs subgroups among the older home health patient population. The effective presentation of these data patterns can allow clinicians to identify areas of patient improvement, and time periods that are most effective for implementing home health interventions to improve patient outcomes.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["Visualization", "Visualizations", "visualizations", "Pattern Discovery"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["behavior or status outcomes", "clinical salience"], "Food": [], "HealthCareActivity": ["Visual Analytics", "home health interventions", "visual analysis techniques", "admission", "discharge", "visually analyze patterns", "patient outcomes", "home health service", "Home Care", "older adult home health patients", "home health episode", "visual analysis"], "InjuryOrPoisoning": [], "IntellectualProduct": ["home health data", "Omaha System", "Charlson co-morbidity index", "Knowledge", "SPSS Visualization Designer v1.0", "dataset", "subgroups"], "MedicalDevice": [], "Organization": ["home health agencies"], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": ["clinicians"], "ResearchActivity": ["correlation analysis"], "SpatialConcept": [], "Virus": []}