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33 lines
3.0 KiB
33 lines
3.0 KiB
1. Objective:
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We want to identify unusual inpatient records based on factors like the number of lab procedures performed and the number of diagnoses.
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2. License: Free to use with citation: Beata Strack, Jonathan P. DeShazo, Chris Gennings, Juan L. Olmo, Sebastian Ventura, Krzysztof J. Cios, and John N. Clore, “Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records,” BioMed Research International, vol. 2014, Article ID 781670, 11 pages, 2014.
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3. Data Source:
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https://archive.ics.uci.edu/ml/datasets/Diabetes+130-US+hospitals+for+years+1999-2008
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"The data are submitted on behalf of the Center for Clinical and Translational Research, Virginia Commonwealth University, a recipient of NIH CTSA grant UL1 TR00058 and a recipient of the CERNER data. John Clore (jclore '@' vcu.edu), Krzysztof J. Cios (kcios '@' vcu.edu), Jon DeShazo (jpdeshazo '@' vcu.edu), and Beata Strack (strackb '@' vcu.edu). This data is a de-identified abstract of the Health Facts database (Cerner Corporation, Kansas City, MO)."
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4. Data Set Information:
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"The dataset represents 10 years (1999-2008) of clinical care at 130 US hospitals and integrated delivery networks. It includes over 50 features representing patient and hospital outcomes. Information was extracted from the database for encounters that satisfied the following criteria:
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(1) It is an inpatient encounter (a hospital admission).
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(2) It is a diabetic encounter, that is, one during which any kind of diabetes was entered to the system as a diagnosis.
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(3) The length of stay was at least 1 day and at most 14 days.
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(4) Laboratory tests were performed during the encounter.
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(5) Medications were administered during the encounter.
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The data contains such attributes as patient number, race, gender, age, admission type, time in hospital, medical specialty of admitting physician, number of lab test performed, HbA1c test result, diagnosis, number of medication, diabetic medications, number of outpatient, inpatient, and emergency visits in the year before the hospitalization, etc."
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5. Field Meanings:
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1. num_lab_procedures: Number of lab procedures performed
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2. num_medications: Number of medications administered
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3. num_procedures: Number of procedures performed
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4. number_diagnoses: Number of diagnoses made
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5. number_inpatient: Number of inpatient visits made in the year before the hospitalization
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6. number_outpatient: Number of outpatient visits made in the year before the hospitalization
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7. number_emergency: Number of emergency room visits made in the year before the hospitalization
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6. Parameter Selection:
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A. Dashboard: Detect Categorical Outliers
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Settings:
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1) Search: | inputlookup diabetic.csv | fields num_lab_procedures num_medications num_procedures number_diagnoses number_inpatient number_outpatient number_emergency
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2) Fields to analyze: num_lab_procedures num_medications num_procedures number_diagnoses number_inpatient number_outpatient number_emergency
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