Global Number of Medical Doctors by Country, 2023 Discover more data with ReportLinker!

🩺 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.

In 2023 the countries with the most doctors per capita was Cuba, the country with the highest physician density. There were 84 physicians per every 10,000 of Cuba's population, however, the most recent data was from 2021. Other countries with high physician density were mostly found in Europe, including Monaco, Greece, Belgium, and Lithuania.

Afghanistan Physicians: per 1000 People data was reported at 0.254 Ratio in 2020. This records an increase from the previous number of 0.212 Ratio for 2019. Afghanistan Physicians: per 1000 People data is updated yearly, averaging 0.186 Ratio from Dec 1960 (Median) to 2020, with 26 observations. The data reached an all-time high of 0.298 Ratio in 2014 and a record low of 0.035 Ratio in 1960. Afghanistan Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Social: Health Statistics. Physicians include generalist and specialist medical practitioners.;World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.;Weighted average;This is the Sustainable Development Goal indicator 3.c.1 [https://unstats.un.org/sdgs/metadata/].

The average for 2020 based on 2 countries was 2.23 doctors per 1,000 people. The highest value was in Mexico: 2.41 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.

Dataset Description

This dataset is designed for fine-tuning large language models in the medical domain. It consists of a series of conversations between users (patients) and assistants (doctors). Each conversation centers around a specific medical topic, such as gynecology, male dysfunction, erectile dysfunction, endocrinology, internal medicine, hepatology, etc.

Dataset Background

• Source and Inspiration:Although the real doctor-patient communication data collected from the Internet and hospitals conforms to the doctor's style, it is too noisy and difficult to clean. The data obtained through large model distillation is easy to understand, but may cause ‘model collapse’.The dataset comes from the consultation and communication between patients and doctors in the real world and the data generated from the dialogue with LLM. By mixing the two in a certain proportion and cleaning them, the fine-tuning effect can be better.
• Data Type: The dataset includes dialogue data where users present health issues and doctors provide advice, covering multiple medical specialties.

Dataset Examples

Each conversation typically includes the following components: 1. System Prompt: Provides the doctor's specialization, e.g., "You are a doctor specializing in gynecology." 2. User Query: The patient describes symptoms or asks health-related questions. 3. Doctor's Response: The doctor offers advice and a diagnostic plan based on the user's query.

By using such dialogue datasets, language models can better understand and generate medical-related text, providing more accurate and useful advice.

Health professionals, especially primary care physicians, are in high demand in many parts of the U.S. Some areas are experiencing health professional shortages. This map shows the ratio of population to primary care physicians in the U.S. Areas in dark red show where there are less primary care physicians per person.The data comes from County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. The layer used in the map comes from ArcGIS Living Atlas of the World, and the full documentation for the layer can be found here.County data are suppressed if, for both years of available data, the population reported by agencies is less than 50% of the population reported in Census or less than 80% of agencies measuring crimes reported data.

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Hyper target within and outside your desired markets with GDPR and CAN-SPAM compliant healthcare email lists that get integrated into your CRM and ESPs. Balance out the sales and marketing efforts by aligning goals using email lists from the healthcare industry. Build strong business relationships with potential clients through personalized campaigns. Call Infotanks Media for a free consultation. Explore new geographies and target markets with a focused approach using healthcare email lists. Align your sales teams and marketing teams through personalized email marketing campaigns to ensure they accomplish business goals together. Add value and grow revenue to take your business to the next level of success. Double up your business and revenue growth with email lists of healthcare professionals. Send segmented campaigns to monitor behaviors and understand the purchasing habits of your potential clients. Send follow up nurturing email marketing campaigns to attract your potential clients to become converted customers. Close deals sooner with detailed information of your prospects using the healthcare email list from Infotanks Media. Reach healthcare professionals on their preferred platform of communication with the email list of healthcare professionals. Identify, capture, explore, and grow in your target markets anywhere in the world with a fully verified, validated, and compliant email database of healthcare professionals. Move beyond the traditional approach and automate sales cycles with buying triggers sent through email marketing campaigns. Use the healthcare email list from Infotanks Media to engage with your targeted potential clients and get them to respond. Increase email marketing campaign response rate to convert better! Reach out to Infotanks Media to customize your healthcare email lists. Call today!"

Yemen YE: Physicians: per 1000 People data was reported at 0.311 Ratio in 2014. This records an increase from the previous number of 0.310 Ratio for 2009. Yemen YE: Physicians: per 1000 People data is updated yearly, averaging 0.219 Ratio from Dec 1960 (Median) to 2014, with 15 observations. The data reached an all-time high of 0.338 Ratio in 2004 and a record low of 0.007 Ratio in 1990. Yemen YE: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Yemen – Table YE.World Bank: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;

Physicians (per 1,000 people) in Costa Rica was reported at 2.636 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Costa Rica - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Patient Reviews & Ratings of Doctor's (For Text Classification)

Natural Language Processing for Text Classification

By Michael [source]

About this dataset

Explore the world of German patient reviews of doctors from 2021 with this dataset!

It's time to dive deep into the fascinating realm of German doctor reviews from 2021, held within this rich data set. Containing 439280 rows, each row stands for a review submitted by a patient and includes a numerical rating as well as text comment about their experience with the doctor. The ratings range from 1 (the best) to 6, and the comments are raw texts that have not been preprocessed or cleaned.

This original dataset has been collected at the end of 2019 but new data has since been added at the beginning of 2021. It covers reviews over multiple years which makes it perfect for Natural Language Processing projects for those interested in exploring text classifiers which can predict rating using text comments alone. As an example, Data-Dive provides several tutorials that use Python to look further into this [link to part 1 etc].

From building neural networks on neural networks on LSTM and FastText embeddingsto introducing transformer models with BERT and tuning GPT-2s with Tensorflow transformer on TPUs while generating new text – if you’re interested in getting your hands dirty in machine learning then this is just right project for you! Don’t wait before diving right in – let’s see what insights we can uncover today!

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How to use the dataset

This dataset contains reviews of German doctors from patients who consulted them in 2021. The data provides a numerical rating and a comment associated with each review, gathered from an online platform. This resource can prove useful for both medical professionals to listen and understand patient sentiment, as well as for data scientists who want to build Natural Language Processing (NLP) applications that use text comments to predict ratings.

Research Ideas

• Using the data set to build a Machine Learning model that can accurately predict ratings of upcoming doctors based on previous comments.
• Utilizing Natural Language Processing (NLP) techniques to automatically categorize or classify reviews into groups by sentiment or context which can provide valuable insights into areas where a doctor may need improvement with their service.
• Building a predictive model that will use machine learning and NLP techniques to estimate patient satisfaction rates for upcoming doctors reviews, allowing healthcare services to make better decisions about the quality of care they are providing

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: 2021_german_doctor_reviews.csv | Column name | Description | |:--------------|:-------------------------------------------------------------------------| | rating | Numerical rating from 1-6, with 1 being the best. (Numerical) | | comment | Text comments from patients about their experience with a doctor. (Text) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Michael.

Actual value and historical data chart for Nigeria Physicians Per 1 000 People

The average for 2020 based on 18 countries was 3.93 doctors per 1,000 people. The highest value was in Austria: 5.35 doctors per 1,000 people and the lowest value was in the United Kingdom: 3.03 doctors per 1,000 people. The indicator is available from 1960 to 2021. Below is a chart for all countries where data are available.

📝 Dataset Overview: This dataset provides a comprehensive view into patient care and hospital operations at Eko Hospital, Lagos. It captures both clinical and financial details — including patient demographics, diagnoses, treatment procedures, and billing data.

It is a powerful tool for health data analysts, students, and researchers to explore real-world healthcare delivery in a Nigerian context.

🔍 Dataset Features: Column Name Description Patient_ID Unique patient identifier (anonymized) Name Patient's name (consider anonymizing further before public use) Age Age of the patient Gender Gender identity Department Medical department visited (e.g., Pediatrics, Cardiology) Doctor Name of the attending physician Diagnosis Medical condition diagnosed Admission_Date Date of hospital admission Discharge_Date Date the patient was discharged Bill_Amount (₦) Total cost incurred (in Nigerian Naira) Lab_Tests_Conducted Number or type of lab tests carried out Medications_Administered Types or count of drugs administered Nurses_Assigned Number of nurses responsible during care Surgery_Cost (₦) Cost of any surgical procedures performed

🎯 Ideal Use Cases: Create interactive Power BI dashboards for patient flow or billing breakdowns

Analyze treatment cost per diagnosis

Predict length of stay or discharge patterns using machine learning

Monitor resource allocation (nurses, doctors)

Understand clinical performance across departments

🧰 Tools to Use: Python (Pandas, Scikit-learn, Seaborn)

Power BI / Tableau for dashboarding

R (Shiny, ggplot2)

Excel pivot tables and charts

📌 Important Notes: Please ensure patient names are anonymized before full public sharing.

Excellent for portfolio projects, capstone work, or public health exploration.

👤 Created By: Fatolu Peter (Emperor Analytics) Healthcare analytics specialist working on real Nigerian datasets to bridge the gap between clinical care and data intelligence. This marks Project 10 in my growing analytics journey 🚀

✅ LinkedIn Post: 🩺 New Healthcare Dataset Alert 📊 Eko Hospital Patient Care Analytics – Now Live on Kaggle 🔗 Check it out here

Looking to sharpen your healthcare analytics or build a project with real-world medical data?

This dataset features:

Admissions & discharges

Diagnosis, medications, surgeries

Billing info (₦), lab tests, and staffing

You can use it to: ✅ Build Power BI dashboards ✅ Train ML models to predict outcomes or costs ✅ Analyze treatment patterns by age, gender, or department

Let’s use data to improve healthcare outcomes. If you build anything with it, tag me — I’d love to share and learn from you.

KaggleDataset #HealthcareAnalytics #PowerBI #PublicHealth #NigerianData #DataScience #FatoluPeter #EmperorAnalytics #Project10 #RealWorldData #PatientCare #HospitalAnalytics

Haiti: Doctors per 1,000 people: The latest value from is doctors per 1,000 people, unavailable from doctors per 1,000 people in . In comparison, the world average is 0.00 doctors per 1,000 people, based on data from countries. Historically, the average for Haiti from to is doctors per 1,000 people. The minimum value, doctors per 1,000 people, was reached in while the maximum of doctors per 1,000 people was recorded in .

Ukraine UA: Physicians: per 1000 People data was reported at 3.000 Ratio in 2014. This records a decrease from the previous number of 3.506 Ratio for 2013. Ukraine UA: Physicians: per 1000 People data is updated yearly, averaging 3.686 Ratio from Dec 1980 (Median) to 2014, with 28 observations. The data reached an all-time high of 4.407 Ratio in 1995 and a record low of 2.951 Ratio in 2003. Ukraine UA: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;

Long-term quantitative series for 20 Latin American countries, spanning from 1960 to 2020, on the number of hospital beds, physicians, nurses and healthcare expenditure.

Matus-Lopez, M. and Fernández Pérez, P. 2023. "Transformations in Latin American Healthcare: A Retrospective Analysis of Hospital Beds, Medical Doctors, and Nurses from 1960 to 2022". Journal of Evolutionary Studies in Business.

The information was extracted from official reports and cross-country databases. Official reports were available in digital format in the Institutional Repository for Information Sharing (IRIS) of Pan American Health Organization (PAHO). They were summary of four-year reports on Health Conditions in the Americas (PAHO 1962, 1966, 1970, 1974, 1978, 1982, 1986, 1990, 1994, 1998, 2002a), annual reports of Basic Indicators (PAHO 2002b, 2007, 2008, 2010, 2013), Health in South America (PAHO 2012) and Core Indicators (PAHO 2016). Databases were Open Data Portal of the Pan American Health Organization (PLISA) (PAHO 2023), Core Indicator Database provided directly by PAHO (PAHO 2022), Data Portal of National Health Workforce Accounts of the World Health Organization (NHWA) (WHO 2022), and the Global Health Expenditure Database of the World Health Organization (GHED) (WHO 2023).

Serie 1. Hospital Beds per 1,000 inhabitants

Serie 2. Physicians per 10,000 inhabitants

Serie 3. Nurses per 10,000 inhabitants

Serie 4. Government spending on health, per capita. Constant US dollars of 2020

Cite as:

Physicians (per 1,000 people) in Chile was reported at 3.17 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Chile - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Physicians (per 1,000 people) in Netherlands was reported at 3.906 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Netherlands - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Physicians (per 1,000 people) in Iran was reported at 1.514 in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Iran - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.