{
  "format": "dataset-manifest/1",
  "slug": "patient-health-timeline",
  "version": 2,
  "seed": "patient-health-timeline:1",
  "spec": {
    "format": "dataset/1",
    "slug": "patient-health-timeline",
    "name": "Patient Health Timeline",
    "tagline": "Timeline of patient health events, including vaccinations, appointments, vital signs, and family medical histories.",
    "description": "Users track their health journeys over time, documenting key events and interactions with healthcare services through a personal medical history app. From vaccinations to routine check-ups, patients log their vital signs, record allergies, and note family medical histories that can impact their health. This creates a dynamic timeline that highlights everyday health maintenance alongside critical medical events, allowing users to visualize their overall health experience more effectively.\n\nThe central table, patient_health_events, contains rows that represent individual health occurrences, with each entry detailing specific events such as appointments, vaccinations, and significant medical interventions. This table serves as the nexus of the data, showing how various health events relate to each patient over time. Users can join this table with other potential identifiers, such as patient demographics or service providers, to gain a broader context of the healthcare interactions that shape their health narratives.\n\nThis data answers key questions related to patient health journeys: How frequently do patients receive preventive care? What types of vaccinations are most common within specific demographics? Are there noticeable patterns in health events that correlate with family medical histories? Practicing with this dataset allows developers to build applications that analyze health trends, generate reminders for vaccinations or check-ups, and potentially identify gaps in preventative care.\n\nIt's important to note that the data within this dataset is synthetic, designed to mimic real-world scenarios while maintaining privacy and security for actual patient information.",
    "domain": "healthcare",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "patient health",
      "medical history",
      "health events",
      "vaccinations",
      "appointments",
      "vital signs",
      "allergies",
      "family history"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "patient_health_events": {
        "description": "Each row represents a health event recorded by a user, detailing various aspects of their healthcare journey. This includes vaccinations, appointments, and vital signs, with timestamps indicating when these events occurred.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each health event."
          },
          "event_type": {
            "kind": "enum",
            "values": [
              "vaccination",
              "appointment",
              "vital_sign",
              "allergy",
              "family_history"
            ],
            "description": "Type of health event recorded.",
            "weights": [
              6,
              3,
              2,
              1,
              1
            ]
          },
          "event_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the health event occurred.",
            "trend": "seasonal"
          },
          "description": {
            "kind": "sentence",
            "min": 10,
            "max": 200,
            "description": "Detailed description of the health event."
          },
          "clinic_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "nullable": true,
            "description": "Name of the clinic or healthcare provider where the event took place.",
            "pool": [
              "wellness",
              "care",
              "health",
              "family",
              "medical",
              "community",
              "urgent",
              "specialty",
              "primary",
              "pediatric",
              "women's",
              "men's",
              "internal",
              "orthopedic",
              "cardiology",
              "dermatology",
              "oncology",
              "rehabilitation",
              "surgery",
              "diagnostic"
            ]
          },
          "vital_sign_type": {
            "kind": "enum",
            "values": [
              "blood_pressure",
              "heart_rate",
              "temperature"
            ],
            "nullable": true,
            "description": "Type of vital sign recorded, if applicable."
          },
          "vital_sign_value": {
            "kind": "decimal",
            "min": 0,
            "max": 300,
            "scale": 2,
            "nullable": true,
            "description": "Value of the recorded vital sign, if applicable.",
            "distribution": "normal"
          },
          "allergy_type": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "nullable": true,
            "description": "Type of allergy documented, if applicable.",
            "pool": [
              "pollen",
              "dust",
              "mold",
              "pet",
              "food",
              "latex",
              "medication",
              "insect",
              "chemical",
              "seasonal",
              "bee",
              "shellfish",
              "peanut",
              "soy",
              "wheat",
              "milk",
              "egg",
              "tree",
              "grass",
              "fish"
            ]
          },
          "family_medical_history": {
            "kind": "sentence",
            "min": 10,
            "max": 200,
            "nullable": true,
            "description": "Details about relevant family medical history."
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "timestamped",
      "free-text",
      "categorical"
    ],
    "analysisQuestions": [
      "What types of health events are most frequently recorded?",
      "How do vaccination dates correlate with appointments?",
      "What vital signs show the most variation over time?",
      "Are there common allergies reported among patients?",
      "How does family medical history influence recorded health events?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all health events for a specific patient",
        "sql": "SELECT * FROM patient_health_events WHERE patient_id = :patient_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count of health events by type",
        "sql": "SELECT event_type, COUNT(*) FROM patient_health_events GROUP BY event_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average vital sign values by type",
        "sql": "SELECT vital_sign_type, AVG(vital_sign_value) FROM patient_health_events WHERE vital_sign_value IS NOT NULL GROUP BY vital_sign_type;",
        "dialect": "postgres"
      },
      {
        "title": "List all events in the last year",
        "sql": "SELECT * FROM patient_health_events WHERE event_date >= NOW() - INTERVAL '1 year';",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Healthcare Professionals Tracking Patient Health",
        "body": "Healthcare professionals can utilize this dataset to gain insights into patient health trends over time. By analyzing the recorded events, they can identify patterns in vaccinations and appointments, helping them to provide tailored care and timely interventions."
      },
      {
        "title": "Data Analysts Creating Visual Dashboards",
        "body": "Data analysts can leverage this dataset to create dynamic BI dashboards that visualize the health event timeline. By aggregating data on event types and dates, they can present a comprehensive overview of a patient's health journey, which can inform decision-making processes."
      },
      {
        "title": "Researchers Studying Health Patterns",
        "body": "Researchers can use this dataset to study the relationships between different health events, such as the impact of vaccinations on appointment frequency. This analysis could lead to insights that enhance public health initiatives and improve healthcare outcomes."
      }
    ]
  },
  "counts": {
    "patient_health_events": 500
  },
  "stats": {
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      "columns": {
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          "nulls": 0,
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        "event_type": {
          "nulls": 0,
          "distinct": 5,
          "min": "allergy",
          "max": "vital_sign"
        },
        "event_date": {
          "nulls": 0,
          "distinct": 425,
          "min": "2020-01-01",
          "max": "2023-12-28"
        },
        "description": {
          "nulls": 0,
          "distinct": 490
        },
        "clinic_name": {
          "nulls": 64,
          "distinct": 284
        },
        "vital_sign_type": {
          "nulls": 45,
          "distinct": 3,
          "min": "blood_pressure",
          "max": "temperature"
        },
        "vital_sign_value": {
          "nulls": 52,
          "distinct": 444,
          "min": 25.46,
          "max": 262.99
        },
        "allergy_type": {
          "nulls": 49,
          "distinct": 301
        },
        "family_medical_history": {
          "nulls": 72,
          "distinct": 426
        }
      }
    }
  },
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