We extract doctor schedules, hospital directories, medical articles, and drug catalogues from Alodokter. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Doctor Profiles objects from alodokter.com. All fields typed and schema-versioned.
"doctor_id": "DR-84921", "name": "Dr. Budi Santoso, Sp.PD", "specialty": "Penyakit Dalam", "experience_years": 12, "consultation_fee": 250000, "rating": 4.8, "review_count": 142, "str_number": "3111100220199283"
| # | doctor_id | name | specialty | experience_years | hospital_affiliations | consultation_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hospital Directory objects from alodokter.com. All fields typed and schema-versioned.
"hospital_id": "HOSP-1029", "name": "RS Siloam Kebon Jeruk", "type": "Rumah Sakit Umum", "city": "Jakarta Barat", "province": "DKI Jakarta", "bed_capacity": 250, "rating": 4.6, "facilities": "['IGD 24 Jam', 'ICU', 'Apotek', 'Laboratorium']"
| # | hospital_id | name | type | address | city | province |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Drug Information objects from alodokter.com. All fields typed and schema-versioned.
"drug_id": "MED-4920", "name": "Paracetamol 500mg", "generic_name": "Paracetamol", "drug_class": "Analgesik", "category": "Obat Bebas", "pregnancy_category": "Kategori B", "price_estimate": "Rp 2.000 - Rp 5.000", "indication": "Meredakan nyeri ringan hingga sedang dan menurunkan demam."
| # | drug_id | name | generic_name | drug_class | category | indication |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Disease Database objects from alodokter.com. All fields typed and schema-versioned.
"disease_id": "DIS-883", "name": "Demam Berdarah Dengue", "category": "Infeksi", "symptoms": "['Demam tinggi', 'Nyeri sendi', 'Ruam kulit']", "causes": "Virus Dengue melalui gigitan nyamuk Aedes aegypti", "icd_10_code": "A91", "author_doctor": "Dr. Kevin Adrian", "prevention": "Pemberantasan sarang nyamuk (3M Plus)"
| # | disease_id | name | category | symptoms | causes | diagnosis |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Medical Articles objects from alodokter.com. All fields typed and schema-versioned.
"article_id": "ART-9921", "title": "Cara Mengatasi Asam Lambung Naik", "category": "Kesehatan Pencernaan", "publish_date": "2025-11-12", "author": "Tim Medis Alodokter", "reviewer_doctor": "Dr. Sienny Agustin", "tags": "['GERD', 'Asam Lambung', 'Pencernaan']", "url": "https://www.alodokter.com/cara-mengatasi-asam-lambung"
| # | article_id | title | category | publish_date | author | reviewer_doctor |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Alodokter scraper extracts the entire directory structure: doctors, hospitals, drugs, and medical content, bypassing rate limits and geographic blocks with Indonesian residential proxies.
Capture profiles, specialties, experience metrics, STR numbers, and patient reviews across all listed medical professionals.
Extract facility lists, available specialties, bed capacities, and precise geographic locations for healthcare centres.
Monitor out-of-pocket consultation costs across different doctors, hospitals, and geographic regions.
Parse dynamic booking calendars to determine doctor availability and typical wait times per facility.
Extract medication details including generic names, dosages, contraindications, and estimated retail prices.
Scrape the entire disease and article database, including symptoms, treatments, and author credentials.
Standardise city and province data to enable accurate regional density analysis of healthcare providers.
Route requests through local Indonesian residential IPs to bypass region blocks and ensure accurate localisation.
Identify changes in doctor schedules, hospital affiliations, or consultation fees without downloading the entire dataset again.
Normalise inconsistent formatting in addresses, qualifications, and facility lists into strict JSON schemas.
Brief in. Clean data out.
Specify target categories: doctor specialties, specific cities, or drug classifications. We map the extraction requirements.
We configure Scrapy crawlers, Indonesian proxy rotation, and DOM parsers specifically for Alodokter's layout.
Schema validation, null-rate checks, and location standardisation before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on your defined schedule.
Healthcare directories deploy strict rate limiting to prevent scraping. We manage the infrastructure so you receive clean data without operational overhead.
Alodokter serves content tailored to Indonesian users and employs geographic filtering. We route all traffic through Indonesian ISP residential proxies to maintain access and ensure accurate regional data.
Directory search results often cap at a specific page depth. We bypass this by programmatically intersecting search parameters like city, specialty, and hospital to extract the entire underlying dataset.
Doctor schedules and booking availability rely on client-side JavaScript. We deploy Playwright to execute DOM scripts and capture the hydrated calendar data accurately.
Medical articles and drug descriptions frequently change formatting. Our extraction logic uses fallback selectors and NLP-based field identification to maintain strict output schemas.
We monitor extraction yields continuously. If a layout update causes null values in consultation fees or hospital addresses, our alerting stack flags the pipeline for immediate developer intervention.
Telemedicine platforms and clinic aggregators use directory data to map competitor networks and identify unserved geographic areas.
Pharma companies analyse the drug directory and disease database to understand local indications and consumer-facing medical content.
Health insurers validate doctor affiliations, track consultation fees, and map hospital facilities to optimise their provider networks.
Machine learning teams use the structured disease symptom and treatment database to train Indonesian-language diagnostic models.
Investors and analysts track the growth of hospital chains and specialist availability across different Indonesian provinces.
Private hospital groups monitor competitor consultation fees, patient review volumes, and doctor recruitment trends.
"Alodokter holds the most comprehensive map of Indonesia's healthcare providers, but extracting that relational data requires dedicated infrastructure."
Building scrapers for healthcare directories often fails at scale due to IP bans, structural changes, and complex pagination. DataFlirt handles proxy rotation, DOM parsing, and schema validation, delivering structured records directly to your warehouse so your team can focus on analysis.
Everything supported by our alodokter.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy manages directory traversal and deduplication, while Playwright handles JavaScript execution for dynamic doctor schedules and booking widgets.
We utilise Indonesian residential proxies to prevent rate limiting and ensure that geographic-specific pricing and availability data is accurate.
Airflow schedules periodic directory sweeps on AWS ECS, ensuring your data warehouse receives fresh updates exactly when required.
Data delivered to where your team already works — no new tooling required.
About alodokter.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly accessible directory information, such as doctor profiles, hospital addresses, and medical articles, is generally permissible. We do not bypass authentication walls to access private patient records, teleconsultation chats, or prescription data. Clients should consult legal counsel regarding their specific use cases.
Alodokter limits the number of pages visible for a broad search. We bypass this by intersecting multiple search parameters, such as combining specific cities with individual medical specialties, ensuring we extract the complete dataset rather than a truncated list.
Yes. Our change detection system records historical data. We can provide time-series datasets showing how consultation fees for specific doctors or specialties fluctuate over months or years.
Yes, we extract aggregated rating scores and individual review text where publicly available on doctor and hospital profiles, standardising the output for sentiment analysis.
We can configure pipelines to refresh critical data, such as doctor schedules, on a daily basis. Full directory sweeps of all hospitals and medical articles typically run weekly or monthly depending on your requirements.
We deliver data in JSON, CSV, or Parquet formats. Files can be pushed directly to your AWS S3 bucket, Google Cloud Storage, or ingested directly into data warehouses like BigQuery and Snowflake.
Yes. We offer a sample extraction of up to 500 doctor profiles or hospital records during the scoping phase, allowing your engineering team to validate the schema and data quality before committing to a production pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full dump of the doctor directory or continuous tracking of hospital facilities, we scope, build, and operate the pipeline. Tell us what you need.
