aiacademy-kg/kg_health_dataset

🏥 KG Health 2023 — Synthetic Healthcare Dataset

🇬🇧 SYNTHETIC DATA — FOR EDUCATIONAL PURPOSES ONLY This dataset is entirely synthetic and was generated programmatically. It does not represent real patients, real medical records, or real statistics of any kind. Any resemblance to actual persons, institutions, or events is coincidental. Do not use for medical, policy, or research decisions.

🇷🇺 СИНТЕТИЧЕСКИЕ ДАННЫЕ — ТОЛЬКО ДЛЯ ОБУЧЕНИЯ Этот датасет является полностью синтетическим и был сгенерирован программно. Он не отражает реальных пациентов, медицинских записей или статистики. Любое сходство с реальными людьми, учреждениями или событиями случайно. Не использовать для медицинских, политических или исследовательских решений.

🇰🇬 СИНТЕТИКАЛЫК МААЛЫМАТТАР — ТЕК ОКУУ МАКСАТЫНДА Бул датасет толугу менен синтетикалык болуп саналат жана программалык жол менен түзүлгөн. Ал реалдуу бейтаптарды, медициналык жазууларды же эч кандай статистиканы чагылдырбайт. Реалдуу адамдарга, мекемелерге же окуяларга окшоштук кокустан болуп саналат.

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Dataset Summary

A synthetic dataset of 400,000 patient records simulating a healthcare registry in Kyrgyzstan. It was created for teaching statistics and exploratory data analysis — specifically to practice concepts such as sampling, central tendency, categorical encoding, and data cleaning on a realistic, messy dataset with intentional anomalies.

The dataset contains dirty data, outliers, encoding errors, and hidden group patterns, which students are expected to discover and interpret.

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Dataset Structure

Column	Description	Type
patient_id	Unique patient identifier (KG-XXXXXX)	string
region	Administrative region of Kyrgyzstan (9 regions)	nominal categorical
district	District within the region (36 districts)	nominal categorical
gender	Patient gender — contains intentional dirty values (~2%)	nominal categorical
age	Patient age in years — contains intentional outliers (~0.5%)	integer
income_monthly	Monthly income in Kyrgyzstani som — heavy right skew	integer
hospital_type	Type of medical facility: государственная, частная, НКО/миссия	nominal categorical
wait_time_days	Days waited before receiving medical care	integer
treatment_cost_usd	Cost of treatment in USD	integer
doctor_visits_year	Number of doctor visits in the past year	integer
diagnosis	Diagnosis category: профилактика, острое, хроническое, травма, неотложное	ordinal categorical
has_insurance	Whether the patient has health insurance	boolean
satisfaction	Patient satisfaction score, 1–5	ordinal integer

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Regions Included

Бишкек · Чуй · Ош (город) · Ошская обл. · Джалал-Абад · Иссык-Куль · Нарын · Талас · Баткен

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Key Properties

• 400,000 rows, 13 columns
• Realistic skewed income distribution (lognormal with heavy right tail)
• Gender pay gap embedded in income generation (~24%)
• Regional disparity in wait times (up to 13× difference between regions)
• Intentional dirty data in gender (10 variants of the same value) and age (impossible values: 999, 150, -1)
• Hidden anomalies for students to discover through analysis
• Diagnosis probabilities vary by age group and gender

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License

CC0 1.0 — Public Domain. Free to use for any educational purpose.