{
  "format": "dataset-manifest/1",
  "slug": "medication-reminder-app",
  "version": 2,
  "seed": "medication-reminder-app:1",
  "spec": {
    "format": "dataset/1",
    "slug": "medication-reminder-app",
    "name": "Medication Adherence Insights",
    "tagline": "Patient engagement data on medication reminders, adherence rates, and reported side effects.",
    "description": "Pharmacists and healthcare providers work diligently to ensure that patients adhere to their medication regimens, thereby enhancing health outcomes and reducing the risk of complications. By sending reminders to patients, they aim to engage them in their treatment plans, ensuring timely consumption of prescribed medications. This operational flow revolves around understanding how and when patients interact with their medication schedules, as well as monitoring any reported side effects that may occur during their treatment journey.\n\nThe primary table in this dataset, medication_reminders, includes detailed records of each reminder sent to patients, the timing of those reminders, and the response from patients regarding their medication adherence. Each row in this table captures a unique reminder event associated with a specific patient, detailing not only the reminder content but also the outcomes, such as whether the patient took their medication as prescribed or reported any side effects. This allows for meaningful analysis of adherence patterns over time and helps identify periods when patients may struggle with their medication routines.\n\nDevelopers and analysts can utilize this dataset to explore various questions related to medication adherence, such as identifying peak times for missed doses, evaluating the effectiveness of reminder strategies, and understanding the correlation between side effects and adherence rates. The insights derived from this data can help shape better reminder systems, enhance patient communication, and ultimately improve healthcare delivery.\n\nAll data within this dataset is synthetic, offering a safe environment for practice and experimentation without the risks associated with using real patient data. Engaging with this dataset can strengthen your analytical skills while providing valuable insights into the critical role of medication adherence in healthcare.",
    "domain": "pharmacy",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "medication adherence",
      "patient engagement",
      "healthcare analytics",
      "pharmacy",
      "reminders",
      "side effects",
      "synthetic data"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "medication_reminders": {
        "description": "Each row represents a unique instance of medication reminders sent to patients, including details about adherence and reported side effects.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the reminder record."
          },
          "patient_id": {
            "kind": "uuid",
            "description": "Unique identifier for the patient, linking to a hypothetical patient database."
          },
          "medication_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the medication prescribed to the patient.",
            "pool": [
              "aspirin",
              "metformin",
              "lisinopril",
              "atorvastatin",
              "simvastatin",
              "omeprazole",
              "sertraline",
              "levothyroxine",
              "amoxicillin",
              "gabapentin",
              "prednisone",
              "fluoxetine",
              "clonazepam",
              "hydrochlorothiazide",
              "furosemide",
              "losartan",
              "venlafaxine",
              "carvedilol",
              "duloxetine",
              "tamsulosin"
            ]
          },
          "reminder_sent_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-12-31",
            "description": "Timestamp when the reminder was sent.",
            "nullable": true,
            "when": {
              "column": "adherence_status",
              "in": [
                "missed"
              ]
            },
            "dayProfile": "waking"
          },
          "adherence_status": {
            "kind": "enum",
            "values": [
              "adhered",
              "missed"
            ],
            "weights": [
              80,
              20
            ],
            "description": "Whether the patient adhered to the medication schedule."
          },
          "side_effects_reported": {
            "kind": "bool",
            "trueRate": 0.1,
            "description": "Indicates if the patient reported experiencing any side effects.",
            "nullable": true
          },
          "condition_managed": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Medical condition being managed with the medication.",
            "nullable": true,
            "pool": [
              "hypertension",
              "diabetes",
              "anxiety",
              "depression",
              "asthma",
              "cholesterol",
              "arthritis",
              "insomnia",
              "pain",
              "allergy",
              "infection",
              "thyroid",
              "bipolar",
              "migraine",
              "seizure",
              "heartburn",
              "osteoporosis",
              "ADHD",
              "cancer",
              "GERD",
              "COPD"
            ]
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable"
    ],
    "analysisQuestions": [
      "What percentage of reminders resulted in adherence?",
      "Are there specific medications that have higher missed doses?",
      "How frequently are side effects reported across different conditions?",
      "Is there a time of day when reminders are more effective for adherence?",
      "What trends can be observed in adherence rates over the months?"
    ],
    "suggestedQueries": [
      {
        "title": "Fetch all reminders and adherence status",
        "sql": "SELECT * FROM medication_reminders;",
        "dialect": "postgres"
      },
      {
        "title": "Count total reminders sent with adherence status",
        "sql": "SELECT adherence_status, COUNT(*) FROM medication_reminders GROUP BY adherence_status;",
        "dialect": "postgres"
      },
      {
        "title": "Find the most common medication with missed doses",
        "sql": "SELECT medication_name, COUNT(*) AS missed_count FROM medication_reminders WHERE adherence_status = 'missed' GROUP BY medication_name ORDER BY missed_count DESC LIMIT 1;",
        "dialect": "postgres"
      },
      {
        "title": "Daily adherence trend over the last month",
        "sql": "SELECT DATE(reminder_sent_at) AS date, AVG(adherence_status = 'adhered') AS adherence_rate FROM medication_reminders WHERE reminder_sent_at >= CURRENT_DATE - INTERVAL '1 month' GROUP BY date ORDER BY date;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Healthcare Provider Analysis",
        "body": "Healthcare providers can use this dataset to analyze patient adherence patterns over time. By identifying trends in missed doses, they can adjust their communication strategies to improve patient engagement and adherence rates. This analysis can help providers understand the effectiveness of their reminder systems and identify patients who may need additional support."
      },
      {
        "title": "Pharmacy Performance Monitoring",
        "body": "Pharmacists can leverage this dataset to monitor the performance of various medications in terms of patient adherence. By analyzing the adherence rates associated with different medications, pharmacists can make informed recommendations to patients and healthcare providers, ultimately enhancing patient care and medication management."
      },
      {
        "title": "Research and Development Insights",
        "body": "Researchers in the healthcare domain can utilize this dataset to study the relationship between medication adherence and reported side effects. By analyzing these factors, they can gain insights into patient experiences and the effectiveness of different medications, which can inform future research and development efforts."
      }
    ]
  },
  "counts": {
    "medication_reminders": 500
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  "stats": {
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        "medication_name": {
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          "distinct": 312
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        "reminder_sent_at": {
          "nulls": 400,
          "distinct": 100,
          "min": "2022-01-06 18:23:51",
          "max": "2023-12-28 22:08:37"
        },
        "adherence_status": {
          "nulls": 0,
          "distinct": 2,
          "min": "adhered",
          "max": "missed"
        },
        "side_effects_reported": {
          "nulls": 55,
          "distinct": 2,
          "min": "false",
          "max": "true"
        },
        "condition_managed": {
          "nulls": 44,
          "distinct": 300
        }
      }
    }
  },
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