{
  "format": "dataset-manifest/1",
  "slug": "telehealth-transactions",
  "version": 1,
  "seed": "telehealth-transactions:1",
  "spec": {
    "format": "dataset/1",
    "slug": "telehealth-transactions",
    "name": "Telehealth Transactions",
    "tagline": "Telehealth transactions detailing patient interactions and prescription activities in remote healthcare consultations.",
    "description": "Healthcare providers offer remote consultations and prescription services through telemedicine, allowing patients to receive medical advice without needing to visit a clinic. This dataset models the transactions involved in such telehealth services, capturing essential details about patient interactions, prescription transactions, and medical support requests. By analyzing this data, users can gain insights into common conditions treated via telehealth and the frequency of various prescription types. The dataset includes routine consultations, standard prescriptions, and unique cases, providing a comprehensive view of modern healthcare delivery. Practicing on this synthetic dataset will enhance understanding of healthcare data management, improve SQL skills, and facilitate ORM seeding for application development.",
    "domain": "pharmacy",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "telehealth",
      "transactions",
      "prescriptions",
      "healthcare",
      "consultations",
      "medical advice"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "telehealth_transactions": {
        "description": "Each row represents a telehealth transaction involving a patient, detailing the interaction type, prescription, and associated medical information.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each transaction."
          },
          "patient_id": {
            "kind": "uuid",
            "description": "Unique identifier for the patient involved in the transaction."
          },
          "provider_id": {
            "kind": "uuid",
            "description": "Unique identifier for the healthcare provider."
          },
          "transaction_date": {
            "kind": "datetime",
            "description": "Date and time when the telehealth transaction occurred.",
            "from": "2022-01-01",
            "to": "2023-12-31",
            "dayProfile": "waking"
          },
          "interaction_type": {
            "kind": "enum",
            "values": [
              "consultation",
              "prescription",
              "support_request"
            ],
            "description": "Type of interaction that took place in the transaction."
          },
          "condition": {
            "kind": "words",
            "min": 3,
            "max": 15,
            "description": "The medical condition addressed during the transaction.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "cancelled"
              ]
            }
          },
          "prescription": {
            "kind": "words",
            "min": 3,
            "max": 10,
            "description": "Details of any prescription provided during the transaction.",
            "nullable": true,
            "when": {
              "column": "interaction_type",
              "in": [
                "prescription"
              ]
            }
          },
          "notes": {
            "kind": "paragraph",
            "min": 5,
            "max": 100,
            "description": "Additional notes or comments related to the transaction.",
            "nullable": true
          },
          "status": {
            "kind": "enum",
            "values": [
              "completed",
              "pending",
              "cancelled"
            ],
            "description": "Status of the transaction."
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "categorical",
      "nullable",
      "timestamped"
    ],
    "analysisQuestions": [
      "What are the most common conditions treated through telehealth?",
      "How many prescriptions are issued per consultation?",
      "What percentage of transactions are cancelled, and why might that be?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all completed transactions",
        "sql": "SELECT * FROM telehealth_transactions WHERE status = 'completed';",
        "dialect": "postgres"
      },
      {
        "title": "Count prescriptions per interaction type",
        "sql": "SELECT interaction_type, COUNT(*) AS prescription_count FROM telehealth_transactions WHERE interaction_type = 'prescription' GROUP BY interaction_type;",
        "dialect": "postgres"
      },
      {
        "title": "Find average transactions per day",
        "sql": "SELECT DATE(transaction_date) AS transaction_day, COUNT(*) AS transaction_count FROM telehealth_transactions GROUP BY transaction_day ORDER BY transaction_day;",
        "dialect": "postgres"
      },
      {
        "title": "List unique conditions treated",
        "sql": "SELECT DISTINCT condition FROM telehealth_transactions;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Healthcare Data Analysts",
        "body": "Healthcare data analysts can leverage this dataset to identify trends in telehealth consultations, such as the most frequently treated conditions and the effectiveness of remote prescriptions. This can inform strategic decisions and improve service offerings."
      },
      {
        "title": "Developers Building Telehealth Applications",
        "body": "Developers can use this dataset to seed their databases when building telehealth applications. It provides realistic data for testing functionalities related to patient management, consultation tracking, and prescription handling."
      },
      {
        "title": "Medical Researchers",
        "body": "Medical researchers examining the efficacy of telehealth can analyze this dataset to study the types of conditions commonly addressed remotely and assess patient outcomes based on transaction data."
      }
    ]
  },
  "counts": {
    "telehealth_transactions": 500
  },
  "stats": {
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        "provider_id": {
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        "transaction_date": {
          "nulls": 0,
          "distinct": 500,
          "min": "2022-01-01 17:54:06",
          "max": "2023-12-31 00:53:06"
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        "interaction_type": {
          "nulls": 0,
          "distinct": 3,
          "min": "consultation",
          "max": "support_request"
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        "condition": {
          "nulls": 338,
          "distinct": 162
        },
        "prescription": {
          "nulls": 321,
          "distinct": 179
        },
        "notes": {
          "nulls": 51,
          "distinct": 449
        },
        "status": {
          "nulls": 0,
          "distinct": 3,
          "min": "cancelled",
          "max": "pending"
        }
      }
    }
  },
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