Our NHS doctors database holds current medical and clinical specialists, and has valid doctors email addresses, for responsive clinical marketing and medical research.

Source: http://data.gov.bd/dataset/doctor-directory Doctor Directory

Health Knowledge about this information will help citizens be aware of the location and service facilities of various doctors across Bangladesh. This data will also help the government to stay updated and accordingly allocate resources where there’s deficiencies.

This dataset contains information on medical professionals across Bangladesh, with details such as their posts, providers, district, upazila, facility, professional designation, contact information, and more. It is intended to be a comprehensive directory of healthcare providers in the country. The data is sourced from the official data.gov.bd named Doctor Directory maintained by the Government of Bangladesh.

Source: The data is sourced from the official http://data.gov.bd/doctor-directory . 🌐

Features: Post: The designation of the doctor, including categories like Medical Officer, Medical Officer (IMO), and others. 🏥 Provider: The type of healthcare facility or organization the doctor is affiliated with. 🏨 Division: The division within Bangladesh where the doctor is located (e.g., Rajshahi). 📍 District: The district where the healthcare provider works. 🏘️ Upazila: The specific upazila or sub-district of the doctor’s location. 🗺️ Facility: The name of the medical facility or hospital. 🏥 Professional Designation: The professional status or title of the healthcare provider (e.g., Medical Officer, Specialist). 🩺 Contact No: The contact number of the healthcare provider for inquiries. 📞 Address: The physical address of the medical facility or healthcare provider. 🏠

Purpose: This dataset serves as a doctor directory for Bangladesh, offering detailed contact information and professional data for healthcare providers across the country. It can be used for a variety of purposes, including:

Research and Analysis: To study the distribution of medical professionals across Bangladesh, identify healthcare accessibility in different regions, and examine trends in medical professional designations. Public Health Studies: To support research on the healthcare infrastructure in Bangladesh and facilitate access to medical professionals for health initiatives. Healthcare Provider Lookup: To find specific doctors or facilities in different regions of Bangladesh for patients or researchers. How Researchers Can Use the Dataset: Healthcare Accessibility Studies: Researchers can study the distribution of medical professionals in various divisions and districts, comparing regions with higher and lower densities of healthcare providers. Trend Analysis: The dataset can be used to track trends in medical staffing and identify areas that may be underserved in terms of medical professionals. Public Health Research: Useful for projects focused on the availability of healthcare in different regions, especially for public health planning and policy development. Provider Lookup: Researchers or health professionals looking to collaborate or find specific doctors can use the dataset to locate them by name, location, and specialty.

ONC uses the SK&A Office-based Provider Database to calculate the counts of medical doctors, doctors of osteopathy, nurse practitioners, and physician assistants at the state and count level from 2011 through 2013. These counts are grouped as a total, as well as segmented by each provider type and separately as counts of primary care providers.

🩺 Overview This dataset is a simulated directory of doctors in Bangladesh, crafted for data analysis, machine learning projects, and educational purposes. It mimics a real-world healthcare directory, containing structured information about doctors, their qualifications, specializations, locations, and affiliations.

📌 Key Features Name of the doctor

Specialization (e.g., cardiology, dermatology, internal medicine)

Degrees/Qualifications (e.g., MBBS, FCPS, MD)

Hospital/Clinic Affiliation

Location (City/Division)

Contact/Phone (dummy format)

Note: All names, contacts, and institutions in this dataset are fictional or anonymized. This dataset is not intended for real-life use or medical reference.

🎯 Use Cases NLP tasks such as named entity recognition (NER) or text classification

Training models for appointment scheduling or doctor recommendation systems

Practicing data cleaning, visualization, and preprocessing

Geolocation-based analysis and healthcare access mapping

Development of dummy apps or dashboards for health tech projects

📂 File Format Format: CSV

Rows: (based on your file — please confirm the number)

Columns: Includes doctor name, specialization, qualification, hospital, chamber location, etc.

🛡️ Disclaimer This dataset is synthetic and solely for research and academic use. It does not represent any real individual or organization.

We offer a doctor database in India that is designed to help you generate highly qualified sales leads. With our Doctors Database, you can easily connect with the appropriate healthcare professionals in India and abroad. These doctor data are invaluable for promoting and selling products, services, and solutions within the healthcare industry, as well as for medical publications, travel-related services, insurance, banking, charity/donations, and memberships, among other areas. All India Doctors Database list consists of approximately 11 lakh doctors in India who are specialists in various fields of medicine. This database of doctors in India includes Doctors across various specialties/fields of medicine such as General Practitioners, Family Physicians, Obstetrics and Gynecology Cardiology, Gastroenterology, Endocrinology and Diabetes, Anesthesia, Pediatrics, Oncology, Emergency Medicine, Neurology, Nephrology, Haematology, Internal Medicine, Dermatology etc.

Description: The Doctors in Pakistan Dataset offers a detailed overview of healthcare professionals across the country, featuring a range of medical specialists in various locations. This dataset includes key information such as the doctor’s name, designation, specialty, location, and consultation fees. It serves as a vital resource for patients seeking medical services, helping them identify qualified professionals based on their specific needs and budget.

Data Structure: The dataset contains the following information:

• Name: The name of the doctor.
• Designation: The professional title or position held by the doctor.
• Specialty: The area of medical expertise, such as psychiatry, cardiology, or dentistry.
• Location: The clinic or hospital address where the doctor practices.
• Fee: The consultation fee charged by the doctor.

Usage: This dataset can be utilized by/for: - Patients: To find specialized medical professionals that meet their healthcare needs. - Researchers: To study healthcare accessibility and specialization trends within Pakistan. - Healthcare Providers: To analyze competition and market dynamics in the medical field.

• This dataset is not preprocessed to any degree, so if you are practicing data preprocessing then this dataset will prove to be useful for you.

The Physician and Physician Practice Research Database (3P-RD) captures characteristics of physicians and physician practices in 13 states. The database describes the supply of physician services available across selected states for data year 2019-2020.

Contains details of doctors that are appointed in writing by HSE to conduct statutory medical surveillance under a range of HSE regulations relating to asbestos, chemicals, lead and working in compressed air. Basic contact data for appointed doctors are made publically available to dutyholders via HSE’s website. Records include: name, address, email, telephone number, which regulations the doctor is appointed under, General Medical Council registration number, companies that the doctor provides services to (name and address), date of appointment, date of next review and date of revocation. There are approximately 800 records in the database and none of them are sensitive except the names of the companies to whom the doctors provide services, which is commercially sensitive.

Medical Doctors in the United States increased to 2.77 per 1000 people in 2019 from 2.74 per 1000 people in 2018. This dataset includes a chart with historical data for the United States Medical Doctors.

The Medicare Physician & Other Practitioners by Provider dataset provides information on use, payments, submitted charges and beneficiary demographic and health characteristics organized by National Provider Identifier (NPI).

This dataset contains comprehensive information about 3,644 doctors practicing in Bangalore, India. The data was ethically scraped from Practo.com using a robots.txt compliant web scraping implementation with Playwright and Scrapy.

Dataset Features: - Doctor names and specialties - Educational qualifications - Years of experience - Consultation fees (INR) - Patient ratings - Geographic locations (with lat/long coordinates) - Google Maps links to clinics - Multiple practice locations per doctor

Perfect for: - Healthcare analytics - Machine learning (fee prediction) - Chatbot development (used in Medibot project: https://github.com/PurpleRadish42/medibot) - Geographic distribution analysis - Market research - Data visualization projects

Collection Method: Ethical web scraping with proper rate limiting and robots.txt compliance.

Real-World Application: This dataset powers the Medibot project, a medical chatbot that helps users find doctors in Bangalore based on specialty, location, and consultation fees.

For the complete web scraping implementation and source code, visit the GitHub repository: https://github.com/KevinG45/bangalore-doctors-scraper

The repository includes: - Complete scraper implementation (Playwright + Scrapy) - Configuration files and setup instructions - Ethical scraping practices documentation - Installation and usage guide

Pakistan ranked 154th among 195 countries in terms of the Healthcare Access and Quality index, according to a Lancet study.

The Dataset provides comprehensive information about Pakistani doctors, encompassing various key aspects to aid in understanding and evaluating healthcare professionals. This dataset aims to provide valuable insights into the profiles of Pakistani doctors, facilitating informed decision-making for both healthcare professionals and patients.

Data Source: The data is collected using Web-Scraping and Crawling Techniques from a leading Pakistani healthcare consultation platform Marham.pk

Columns Description: The dataset includes the following essential columns:

Doctor Name: The full name of the healthcare professional.

City: The city in which the doctor's clinic is based, providing geographical context.

Specialization: The specific area of medical expertise or specialization of the doctor.

Doctor Qualification: The highest educational qualification attained by the doctor.

Experience(Years): The total number of years of professional experience the doctor has accumulated.

Total_Reviews: The cumulative number of reviews given by patients, reflecting the overall feedback received.

Patient Satisfaction Rate(%age): The percentage indicating the level of satisfaction reported by patients who have received medical care from the doctor.

Avg Time to Patients(mins): The average amount of time the doctor spends with each patient during consultations.

Wait Time(mins): The average waiting time experienced by patients at the clinic before their consultation.

Hospital Address: The name and location of the hospital or clinic where the doctor practices.

Doctors Link: An online access link or platform where patients can connect with the doctor, reflecting the growing trend of digital healthcare.

Doctor Fee(PKR): The fee charged by the doctor for their services, measured in Pakistani Rupees (PKR).

               **General Use Cases:**

Fee Prediction: Predicting the fees of doctors based on factors such as experience, qualification, and patient satisfaction rate. Wait Time Estimation: Forecasting the average wait time at a clinic, helping patients plan their appointments more efficiently. Patient Satisfaction Analysis: Understanding the factors influencing patient satisfaction and identifying areas for improvement.

              **Advanced Use Cases:**

Optimizing Appointment Scheduling: Developing algorithms to optimize the scheduling of appointments, considering factors like doctor availability and patient preferences. Healthcare Resource Allocation: Predicting future demand for specific specializations in different cities, assisting in the allocation of healthcare resources effectively. Personalized Patient Recommendations: Utilizing patient reviews and satisfaction rates to recommend doctors to new patients based on their preferences and requirements.

      **3. Where the Regression model can be used:**

Healthcare Platforms: Integrate the model into online healthcare platforms and directories to assist patients in finding suitable doctors. Hospital Management: Support hospital management in resource allocation, appointment scheduling, and fee structure decisions. Telemedicine Services: Enhance telemedicine services by providing personalized doctor recommendations and predicting patient needs. Health Insurance: Assist health insurance companies in assessing risk factors and setting appropriate premium rates based on the predicted healthcare demand in different regions. Government Health Planning: Aid government health agencies in strategic planning, ensuring optimal distribution of healthcare resources across regions.

The Medicare Physician & Other Practitioners by Provider and Service dataset provides information on use, payments, and submitted charges organized by National Provider Identifier (NPI), Healthcare Common Procedure Coding System (HCPCS) code, and place of service.

According to Ahram online Egyptian doctors among top five foreign physicians who joined UK medical system in 2021: British report. Check: https://english.ahram.org.eg/News/478143.aspx In this dataset, we collected over 1000 doctor data from the appointment booking website.

You can use this data to practice:

1. Data cleaning
2. Data Analysis
3. Data visualization

Inspiration for the analysis:

1. Think about it as a patient and what is important for you to be a doctor like locations, fees, doctor rating, and so on.
2. think about it as a doctor if you want to buy a new clinic, about the fees, about waiting time, and so on.

Questions:

1. What are the most common specialties among Egyptian doctors in this dataset?
2. How many doctors are located in each governorate (province) of Egypt?
3. What is the average age of the doctors in this dataset?
4. How many male and female doctors are included in this dataset?
5. Which governorate has the highest number of doctors per capita?
6. What is the distribution of doctors across different specialties in each governorate?
7. Who are the top 10 doctors with the highest number of patients?
8. What is the average number of years of experience for doctors in each specialty?
9. How many doctors have international certifications or degrees?
10. What is the average consultation fee for doctors in each specialty?

This dataset provides values for MEDICAL DOCTORS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Doctor email list is a list of emails of doctors. It helps people reach doctors fast. Companies use it for many reasons. They can send health news, medical tools, or event invites. However, a doctor, also known as a physician, is a licensed professional who practices medicine to maintain or restore human health. Their primary role is to diagnose and treat injuries, illnesses, and other medical conditions. People can know about names, job titles, and where doctors work. It may also show what kind of doctor they are. For example, heart doctors or eye doctors. Moreover, a good email list brings good results. It can also help in sales, jobs, and learning. It builds links between people. Even, it helps doctors stay up to date.

Doctor email list helps medicine companies a lot. They use it to share new medicine. Hospitals use it to find doctors for work. Moreover, that saves time, it is better than calling one by one. You can buy or rent a doctor email list. Some lists are free, but many are not. Wrong emails waste time. Good lists are always updated, our dataset must be correct. Privacy is key, our list must follow laws. People on the list should agree to get emails. We collect all datasets from trustworthy sources. We sell very big lists and other side make small lists for local needs. In short, this package is very useful. It is fast, easy, and smart. Hence, buy this lead. Doctor email database can give you more potential clients for your online marketing. As well as building numerous advantages for the company’s benefit. Any seller can promote their brand through this package. Hence, our professionals update these contact numbers monthly. Similarly, we provide a CSV and an Excel file that can run in any CRM software. Most importantly, it brings a great return on investment (ROI). So, if anyone needs any contacts for digital marketing, they can buy these from List to Data.

Number of Doctors: Registered: Medical Council of India data was reported at 1,169.000 Person in 2014. This records a decrease from the previous number of 5,603.000 Person for 2013. Number of Doctors: Registered: Medical Council of India data is updated yearly, averaging 1,989.000 Person from Dec 2002 (Median) to 2014, with 13 observations. The data reached an all-time high of 5,603.000 Person in 2013 and a record low of 921.000 Person in 2004. Number of Doctors: Registered: Medical Council of India data remains active status in CEIC and is reported by Central Bureau of Health Intelligence. The data is categorized under India Premium Database’s Health Sector – Table IN.HLB001: Health Human Resources: Number of Doctors: Registered.

The average for 2020 based on 27 countries was 3.56 doctors per 1,000 people. The highest value was in Austria: 5.35 doctors per 1,000 people and the lowest value was in Brazil: 2.05 doctors per 1,000 people. The indicator is available from 1960 to 2021. Below is a chart for all countries where data are available.

This dataset contains comprehensive information about Pakistani doctors, extracted from oladoc.com. It includes doctor profiles with specializations, locations, ratings, and other key attributes, making it ideal for building healthcare recommendation systems. Whether you're developing a recommendation engine, analyzing healthcare trends, or exploring medical data in Pakistan, this dataset offers valuable insights. The data is structured for easy integration into machine learning models and recommendation algorithms.

The CMS Program Statistics - Medicare Physician, Non-Physician Practitioner and Supplier tables provide use and payment data for physicians, other practitioners, limited-licensed practitioners, and durable medical equipment, prosthetic, and orthotic (DMEPOS) suppliers. For additional information on enrollment, providers, and Medicare use and payment, visit the CMS Program Statistics page. Below is the list of tables: MDCR PHYSSUPP 1. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Type of Entitlement, Yearly Trend MDCR PHYSSUPP 2. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Demographic Characteristics and Medicare-Medicaid Enrollment Status MDCR PHYSSUPP 3. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Area of Residence MDCR PHYSSUPP 4. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Type of Service MDCR PHYSSUPP 5. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Place of Service MDCR PHYSSUPP 6. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Physician Specialty MDCR PHYSSUPP 7. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization and Program Payments for Original Medicare Beneficiaries, by Berenson-Eggers Type of Service (BETOS) Classification