{ "format": "dataset-manifest/1", "slug": "remote-patient-data-collection-app", "version": 3, "seed": "remote-patient-data-collection-app:1", "engine": 1, "engineVersion": "1.0.0", "spec": { "format": "dataset/1", "slug": "remote-patient-data-collection-app", "name": "Patient Monitoring Insights", "tagline": "Patient records including vital signs, medications, adherence logs, device usage, and alerts for critical health events.", "description": "Clinicians utilize continuous patient monitoring to ensure timely interventions and effective treatments for individuals in their care. This business thrives on gathering and analyzing critical health data, including patients' vital signs, medication adherence, and device usage. Through diligent tracking, healthcare professionals can identify patterns, respond to abnormalities, and make informed decisions that enhance patient outcomes. Metrics such as blood pressure readings, heart rates, and device activity logs play a pivotal role in the daily operations of this healthcare model. Alerts generated from abnormal readings serve to notify clinicians of urgent health events, ensuring immediate attention is given where necessary. \n\nThe data is organized into several related tables. The 'patients' table provides a fundamental overview of individuals under monitoring, while the 'vital_signs' table records the various health metrics collected from these patients. The 'medications' table details the treatment plans, outlining what medications each patient is prescribed. 'Adherence_logs' track whether patients follow their medication schedules, offering insight into compliance. 'Device_usage' records how often and effectively patients utilize their monitoring devices, while 'alerts' flag any critical deviations in health metrics that require swift clinician response. Each row in these tables connects, allowing for comprehensive analysis across patient profiles and health data. \n\nThis dataset is ideal for practitioners looking to answer questions around medication adherence, the impact of device usage on vital signs, and the effectiveness of timely interventions based on alert data. With its synthetic nature, it provides a safe and controlled environment for developers to hone their skills in data analysis, visualizations, and healthcare analytics without risking real patient information.", "domain": "healthcare", "shape": "time-series", "useCases": [ "analytics-demo", "bi-dashboards" ], "keywords": [ "patient monitoring", "healthcare analytics", "vital signs", "medication adherence", "device usage", "alerts" ], "locale": "en", "license": "CC0-1.0", "version": 1, "tables": { "patients": { "description": "This table contains information about each patient being monitored, linking to their vital signs and medication data.", "rows": 200, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each patient." }, "full_name": { "kind": "fullName", "description": "The full name of the patient." }, "date_of_birth": { "kind": "date", "from": "1940-01-01", "to": "2005-12-31", "description": "The patient's date of birth.", "trend": "growing" }, "gender": { "kind": "enum", "values": [ "male", "female", "other" ], "description": "Gender of the patient.", "nullable": true, "weights": [ 6, 4, 1 ] } } }, "vital_signs": { "description": "Captures the vital signs readings for each patient over time, linked to the patients table.", "rows": { "per": "patients", "via": "patient_id", "min": 1, "max": 5, "skew": "long-tail" }, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each vital sign record." }, "patient_id": { "kind": "fk", "ref": "patients.id", "description": "Links to the patient this record belongs to." }, "timestamp": { "kind": "datetime", "from": "2020-01-01", "to": "2023-12-31", "description": "The date and time when the vital sign was recorded." }, "blood_pressure": { "kind": "decimal", "min": 70, "max": 180, "scale": 1, "description": "Blood pressure reading in mmHg.", "distribution": "normal" }, "heart_rate": { "kind": "int", "min": 40, "max": 180, "description": "Heart rate in beats per minute.", "distribution": "normal" } } }, "medications": { "description": "Details the medications prescribed to each patient, linked to the patients table.", "rows": 300, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each medication record." }, "patient_id": { "kind": "fk", "ref": "patients.id", "description": "Links to the patient this medication is prescribed for." }, "medication_name": { "kind": "words", "max": 3, "description": "Name of the medication.", "pool": [ "aspirin", "ibuprofen", "acetaminophen", "metformin", "lisinopril", "simvastatin", "amoxicillin", "prednisone", "levothyroxine", "omeprazole", "losartan", "gabapentin", "albuterol", "clopidogrel", "sertraline", "fluoxetine", "dexamethasone", "hydrochlorothiazide", "furosemide", "atorvastatin", "citalopram", "venlafaxine", "tramadol", "warfarin", "naproxen", "tamsulosin", "digoxin", "insulin", "sildenafil", "metoprolol", "carvedilol", "amlodipine", "diltiazem", "verapamil", "pravastatin", "rosuvastatin", "bupropion", "mirtazapine", "topiramate", "lamotrigine", "levetiracetam", "quetiapine", "aripiprazole", "buspirone", "tizanidine", "cyclobenzaprine", "nitroglycerin", "clonazepam", "loratadine", "cetirizine", "diphenhydramine", "phenylephrine", "dextromethorphan", "guaifenesin" ], "min": 1 }, "dosage": { "kind": "decimal", "min": 1, "max": 1000, "scale": 0, "description": "Dosage of the medication in mg.", "nullable": true, "when": { "column": "frequency", "in": [ "once daily", "twice daily", "three times daily" ] }, "distribution": "normal" }, "frequency": { "kind": "enum", "values": [ "once daily", "twice daily", "three times daily" ], "description": "Frequency of medication intake.", "weights": [ 7, 2, 1 ] } } }, "adherence_logs": { "description": "Records the adherence of patients to their medication schedules, linked to the medications table.", "rows": { "per": "medications", "via": "medication_id", "min": 1, "max": 3, "skew": "long-tail" }, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each adherence log." }, "medication_id": { "kind": "fk", "ref": "medications.id", "description": "Links to the medication this log is associated with." }, "timestamp": { "kind": "datetime", "from": "2020-01-01", "to": "2023-12-31", "description": "The date and time of the adherence check.", "dayProfile": "waking" }, "adhered": { "kind": "bool", "trueRate": 0.8, "description": "Indicates whether the patient adhered to the medication schedule." }, "adherence_reason": { "kind": "enum", "values": [ "forgot", "side effects", "understanding", "schedule change", "travel", "other commitments", "doctor's advice", "feeling better", "medication change", "lack of supplies", "no symptoms", "personal issues" ], "weights": [ 12, 6, 4, 3, 2, 2, 2, 2, 1, 1, 1, 1 ], "description": "Reason for adherence or non-adherence to medication." } } }, "device_usage": { "description": "Logs the usage of monitoring devices by patients, linking to the patients table.", "rows": { "per": "patients", "via": "patient_id", "min": 1, "max": 4, "skew": "long-tail" }, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each device usage record." }, "patient_id": { "kind": "fk", "ref": "patients.id", "description": "Links to the patient using the device." }, "device_type": { "kind": "enum", "values": [ "blood pressure monitor", "heart rate monitor", "smartwatch" ], "description": "Type of device used for monitoring." }, "timestamp": { "kind": "datetime", "from": "2020-01-01", "to": "2023-12-31", "description": "The date and time when the device was used.", "dayProfile": "business" }, "duration_minutes": { "kind": "int", "min": 1, "max": 180, "distribution": "normal", "description": "Duration of device usage in minutes." } } }, "alerts": { "description": "Contains alerts generated from abnormal vital sign readings, linked to the vital signs table.", "rows": { "per": "vital_signs", "via": "vital_sign_id", "min": 0, "max": 2, "skew": "long-tail" }, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each alert." }, "vital_sign_id": { "kind": "fk", "ref": "vital_signs.id", "description": "Links to the vital sign record that triggered the alert." }, "alert_type": { "kind": "enum", "values": [ "high blood pressure", "low heart rate", "abnormal reading" ], "description": "Type of alert generated.", "weights": [ 5, 3, 2 ] }, "timestamp": { "kind": "datetime", "from": "2020-01-01", "to": "2023-12-31", "description": "The date and time when the alert was generated.", "dayProfile": "waking", "trend": "seasonal" }, "resolved": { "kind": "bool", "trueRate": 0.5, "description": "Indicates whether the alert has been resolved." } } } }, "structure": "multi-table", "traits": [ "timestamped", "nullable", "self-referencing" ], "analysisQuestions": [ "What is the average blood pressure of patients over the last year?", "How many patients are adhering to their medication schedules?", "Which devices are most commonly used by patients?", "What alerts have been triggered the most frequently and why?", "Is there a correlation between medication adherence and vital sign stability?" ], "suggestedQueries": [ { "title": "Join Patients and Vital Signs", "sql": "SELECT p.full_name, v.blood_pressure FROM patients p JOIN vital_signs v ON p.id = v.patient_id;", "dialect": "postgres" }, { "title": "Aggregate Average Heart Rate", "sql": "SELECT AVG(v.heart_rate) as avg_heart_rate FROM vital_signs v GROUP BY v.patient_id;", "dialect": "postgres" }, { "title": "Count Medication Adherence", "sql": "SELECT m.medication_name, COUNT(a.id) as adherence_count FROM medications m LEFT JOIN adherence_logs a ON m.id = a.medication_id WHERE a.adhered = TRUE GROUP BY m.medication_name;", "dialect": "postgres" }, { "title": "Find Most Common Alerts", "sql": "SELECT a.alert_type, COUNT(a.id) as alert_count FROM alerts a GROUP BY a.alert_type ORDER BY alert_count DESC;", "dialect": "postgres" }, { "title": "Device Usage Trends Over Time", "sql": "SELECT d.device_type, COUNT(d.id) as usage_count, DATE(d.timestamp) as usage_date FROM device_usage d GROUP BY d.device_type, usage_date ORDER BY usage_date;", "dialect": "postgres" } ], "usageScenarios": [ { "title": "Healthcare Data Analysts", "body": "Healthcare data analysts would utilize this dataset to explore trends in patient vital signs over time. By analyzing the data, they can identify patterns and deviations that may indicate health risks, allowing them to recommend interventions to healthcare providers." }, { "title": "Clinical Researchers", "body": "Clinical researchers could leverage this dataset to investigate the effectiveness of various medications and adherence rates among patients. This analysis can help enhance patient care strategies and optimize treatment protocols based on real-world data." }, { "title": "BI Dashboard Developers", "body": "Business Intelligence dashboard developers can use this dataset to create visual representations of patient health metrics. By integrating this data into dashboards, they can provide healthcare professionals with user-friendly insights into patient conditions, improving clinical decision-making." }, { "title": "Healthcare Providers", "body": "Healthcare providers can reference this dataset to monitor their patients' adherence to treatment plans and device usage. Understanding these patterns helps providers engage with patients more effectively and tailor care plans based on individual needs." } ] }, "counts": { "patients": 200, "device_usage": 391, "medications": 300, "adherence_logs": 504, "vital_signs": 446, "alerts": 253 }, "stats": { "patients": { "rows": 200, "columns": { "id": { "nulls": 0, "distinct": 200, "min": 1, "max": 200 }, "full_name": { "nulls": 0, "distinct": 196, "min": "Alice Khan", "max": "Zoe Cruz" }, "date_of_birth": { "nulls": 0, "distinct": 199, "min": "1940-07-03", "max": "2005-11-29" }, "gender": { "nulls": 19, "distinct": 3, "min": "female", "max": "other" } } }, "vital_signs": { "rows": 446, "columns": { "id": { "nulls": 0, "distinct": 446, "min": 1, "max": 446 }, "patient_id": { "nulls": 0, "distinct": 200, "min": 1, "max": 200 }, "timestamp": { "nulls": 0, "distinct": 446, "min": "2020-01-03 23:05:30", "max": "2023-12-31 23:38:31" }, "blood_pressure": { "nulls": 0, "distinct": 314, "min": 87.7, "max": 164.2 }, "heart_rate": { "nulls": 0, "distinct": 94, "min": 58, "max": 161 } } }, "medications": { "rows": 300, "columns": { "id": { "nulls": 0, "distinct": 300, "min": 1, "max": 300 }, "patient_id": { "nulls": 0, "distinct": 148, "min": 2, "max": 200 }, "medication_name": { "nulls": 0, "distinct": 236 }, "dosage": { "nulls": 0, "distinct": 233, "min": 98, "max": 856 }, "frequency": { "nulls": 0, "distinct": 3, "min": "once daily", "max": "twice daily" } } }, "adherence_logs": { "rows": 504, "columns": { "id": { "nulls": 0, "distinct": 504, "min": 1, "max": 504 }, "medication_id": { "nulls": 0, "distinct": 300, "min": 1, "max": 300 }, "timestamp": { "nulls": 0, "distinct": 504, "min": "2020-01-01 20:31:51", "max": "2023-12-30 19:54:23" }, "adhered": { "nulls": 0, "distinct": 2, "min": "false", "max": "true" }, "adherence_reason": { "nulls": 0, "distinct": 12, "min": "doctor's advice", "max": "understanding" } } }, "device_usage": { "rows": 391, "columns": { "id": { "nulls": 0, "distinct": 391, "min": 1, "max": 391 }, "patient_id": { "nulls": 0, "distinct": 200, "min": 1, "max": 200 }, "device_type": { "nulls": 0, "distinct": 3, "min": "blood pressure monitor", "max": "smartwatch" }, "timestamp": { "nulls": 0, "distinct": 391, "min": "2020-01-03 09:54:20", "max": "2023-12-30 17:54:09" }, "duration_minutes": { "nulls": 0, "distinct": 106, "min": 31, "max": 160 } } }, "alerts": { "rows": 253, "columns": { "id": { "nulls": 0, "distinct": 253, "min": 1, "max": 253 }, "vital_sign_id": { "nulls": 0, "distinct": 175, "min": 1, "max": 446 }, "alert_type": { "nulls": 0, "distinct": 3, "min": "abnormal reading", "max": "low heart rate" }, "timestamp": { "nulls": 0, "distinct": 253, "min": "2020-01-01 15:36:56", "max": "2023-12-30 14:20:57" }, "resolved": { "nulls": 0, "distinct": 2, "min": "false", "max": "true" } } } }, "artifacts": [ { "file": "csv/patients.csv", "format": "csv", "table": "patients", "key": "datasets/remote-patient-data-collection-app/v3/csv/patients.csv", "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/remote-patient-data-collection-app/v3/csv/patients.csv", "bytes": 6613, "sha256": "12c976b5a307c9bc1e8a47fd8866a52231c1fa3aed14c12c6f8c5c9de54427cc", "rows": 200, "contentType": "text/csv; 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