According to a ranking by Statista and Newsweek, the best hospital in the United States is the *********** in Rochester, Minnesota. Moreover, the *********** was also ranked as the best hospital in the world, among over 50,000 hospitals in 30 countries. **************** in Ohio and the ************* Hospital in Maryland were ranked as second and third best respectively in the U.S., while they were second and forth best respectively in the World.

According to a ranking by Statista and Newsweek, the world's best hospital is the *********** in Rochester, Minnesota. A total of **** U.S. hospitals made it to the top ten list, while one hospital in each of the following countries was also ranked among the top ten best hospitals in the world: Canada, Sweden, Germany, Israel, Singapore, and Switzerland.

About Dataset:

The Global Hospital Dataset is a comprehensive collection of information on 20,000 hospitals located across the world. This dataset has been curated to provide a wide range of valuable information about these healthcare institutions, making it a valuable resource for various stakeholders in the healthcare industry, researchers, analysts, and policymakers.

Key Features:

Hospital Name: The names of the hospitals in the dataset. Country: The countries in which each hospital is located, providing a global perspective. World Rank: Ranking of hospitals on a global scale based on various criteria, showcasing the healthcare landscape. Size: Information about the physical size and capacity of each hospital. Visibility: A measure of the hospitals' visibility, which could include factors such as media coverage and online presence. Rich Files: Data related to any rich files associated with the hospitals, which could be valuable resources for analysis. Scholarship: Scholarly or academic scores for hospitals, reflecting their contributions to research and education.

The dataset provides performance ratings for coronary artery bypass graft (CABG) surgery, inpatient mortality indicators (IMIs), and elective percutaneous coronary intervention (PCI). The outcome measures include: operative mortality for isolated CABG; inpatient mortality for acute stroke, acute myocardial infarction, heart failure, gastrointestinal hemorrhage, hip fracture, pneumonia, abdominal aortic aneurysm repair, carotid endarterectomy, esophageal resection, pancreatic resection, percutaneous coronary intervention; three outcome measures for elective PCI without on-site cardiac surgery: mortality, post-PCI stroke, and post-PCI emergency coronary artery bypass graft surgery; postoperative sepsis following elective surgeries. It includes risk-adjusted rates, number of adverse events and cases.

According to a ranking of the best hospitals in the U.S., the best hospital for adult cancer is the University of *******************************, which had a score of *** out of 100, as of 2025. This statistic shows the top 10 hospitals for adult cancer in the United States based on the score given by U.S. News and World Report's annual hospital ranking.

Ranking of the 100 highest-rated Hospitals And Health Care companies with 3,000+ employees. Includes cyber resilience score, security band rating, NAICS classification, and recorded cyber incident count. Updated regularly.

The average for 2020 based on 36 countries was 4.44 hospital beds. The highest value was in South Korea: 12.65 hospital beds and the lowest value was in Mexico: 0.99 hospital beds. The indicator is available from 1960 to 2021. Below is a chart for all countries where data are available.

HCAHPS Hospital Ratings Survey

Patient Experience Ratings 2018-2020

By Health [source]

About this dataset

This dataset contains ratings of hospitals, based on the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). This survey collects data from hospital patients on their experiences during an inpatient stay. The list includes several indicators to help gauge a hospital's quality, such as star ratings based on patient opinions and percentage of positive answers to HCAHPS questions. Additionally, there are measures such as the number of completed surveys, survey response rate percent and linear mean value which assist in evaluating patient experience at each medical institution. With this comprehensive dataset you can easily draw comparisons between hospitals and make informed decisions about healthcare services provided in your area

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How to use the dataset

This dataset provides useful information on the quality of care that hospitals provide. This dataset provides ratings and reviews of several hospitals, making it easy to compare hospitals in order to find out which hospital may best meet your needs.

The following guide will walk you through how to use this dataset effectively:

• Navigate the different columns available in this dataset by scrolling through the table. These include Hospital Name, Address, City, State, ZIP Code, County Name, Phone Number and HCAHPS Question among others.
• Examine important information such as the patient survey star rating and HCAHPS linear mean value for each hospital included in the dataset in order to evaluate it's performance against other hospitals based on standards set out by HCAHPS .
• Read any footnotes associated with each column carefully in order to fully understand what exactly is being measured. These may directly affect your evaluation of a particular hospital’s performance compared to others included in this dataset or even more so when compared against external sources of data outside this dataset such as other surveys or studies related to health care quality measurement metrics within that state or region where applicable & relevant (i..e Measure Start Date and Measure End Date).

• Pay careful attention also when evaluating factors related to survey response rates (e..g Survey Response Rate Percent Footnote) & what percentages are being reported here within each category; these figures may selectively bias results so ensure full transparency is achieved by reviewing all potential influencing factors/variables prior commencing investigations/data analysis/interpretation based upon this data-set alone(or any subset thereof).

  By following these steps you should be able set up your own criteria for measuring various aspects of health care quality across different states & cities - ensuring optimal access & safety measures for both patients & healthcare providers alike over time - thus ultimately aiding decision making processes towards improved patient outcomes worldwide!

Research Ideas

• Tracking patient experience trends over time: This dataset can be used to analyze trends in patient experience over time by identifying changes in survey responses, star ratings, and response rates across hospitals.
• Establishing a benchmark for high-quality hospital care: By studying the scores of the top-performing hospitals within each category, healthcare administrators can set standards and benchmarks for quality of care in their own hospitals.
• Comparing hospital ratings to inform decision making: Patients and family members looking to book an appointment at a hospital or doctors office can use this dataset to compare different facilities’ HCAHPS scores and make an informed decision about where they would like to go for their medical treatment

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 int...

As of 2025, New York-Presbyterian hospital is the largest hospital in the United States with its eight campuses based in New York City. This was followed by AdventHealth Orlando in Florida stands as the second largest hospital in the United States, boasting an impressive 2,787 beds. Evolving landscape of U.S. hospitals Despite the decline in the total number of hospitals since 1980, the healthcare sector continues to grow in other ways. U.S. hospitals now employ about 7.5 million workers and generate a gross output of around 1,263 billion U.S. dollars. The Hospital Corporation of America, based in Nashville, Tennessee, leads the pack as the largest health system in the country, operating 222 hospitals as of February 2025. This reflects a trend towards consolidation and the rise of for-profit hospital chains, which gained prominence in the 1990s. Specialization and emergency care While bed count is one measure of hospital size, institutions also distinguish themselves through specialization and emergency care capabilities. For instance, the University of California at Los Angeles Medical Center performed 22,287 organ transplants between January 1988 and March 2025, making it the leading transplant center in the nation. In terms of emergency care, Parkland Health and Hospital System in Dallas recorded the highest number of emergency department visits in 2024, with 235,893 patients seeking urgent care.

Public reporting of measures of hospital performance is an important component of quality improvement efforts in many countries. However, it can be challenging to provide an overall characterization of hospital performance because there are many measures of quality. In the United States, the Centers for Medicare and Medicaid Services reports over 100 measures that describe various domains of hospital quality, such as outcomes, the patient experience and whether established processes of care are followed. Although individual quality measures provide important insight, it is challenging to understand hospital performance as characterized by multiple quality measures. Accordingly, we developed a novel approach for characterizing hospital performance that highlights the similarities and differences between hospitals and identifies common patterns of hospital performance. Specifically, we built a semi-supervised machine learning algorithm and applied it to the publicly-available quality measures for 1,614 U.S. hospitals to graphically and quantitatively characterize hospital performance. In the resulting visualization, the varying density of hospitals demonstrates that there are key clusters of hospitals that share specific performance profiles, while there are other performance profiles that are rare. Several popular hospital rating systems aggregate some of the quality measures included in our study to produce a composite score; however, hospitals that were top-ranked by such systems were scattered across our visualization, indicating that these top-ranked hospitals actually excel in many different ways. Our application of a novel graph analytics method to data describing U.S. hospitals revealed nuanced differences in performance that are obscured in existing hospital rating systems.

*Standardized units.Characteristics of the top 50 Cancer Hospitals, as ranked by the US News and World Report.

BackgroundThe conceptualization of hospital quality indicators usually includes some form of risk adjustment to account for hospital differences in case mix. For binary outcome variables like in-hospital mortality, frequently utilized risk adjusted measures include the standardized mortality ratio (SMR), the risk standardized mortality rate (RSMR), and excess risk (ER). All of these measures require the estimation of expected hospital mortality, which is often based on logistic regression models. In this context, an issue that is often neglected is correlation between hospital performance (e.g. care quality) and patient-specific risk factors. The objective of this study was to investigate the impact of such correlation on the adequacy of hospital rankings based on different measures and methods.MethodsUsing Monte Carlo simulation, the impact of correlation between hospital care quality and patient-specific risk factors on the adequacy of hospital rankings was assessed for SMR/RSMR, and ER based on logistic regression and random effects logistic regression. As an alternative method, fixed effects logistic regression with Firth correction was considered. The adequacies of the resulting hospital rankings were assessed by the shares of hospitals correctly classified into quintiles according to their true (unobserved) care qualities.ResultsThe performance of risk adjustment approaches based on logistic regression and random effects logistic regression declined when correlation between care quality and a risk factor was induced. In contrast, fixed-effects-based estimations proved to be more robust. This was particularly true for fixed-effects-logistic-regression-based ER. In the absence of correlation between risk factors and care quality, all approaches showed similar performance.ConclusionsCorrelation between risk factors and hospital performance may severely bias hospital rankings based on logistic regression and random effects logistic regression. ER based on fixed effects logistic regression with Firth correction should be considered as an alternative approach to assess hospital performance.

The dataset contains counts for the Top Five inpatient diagnosis groups based on Major Diagnostic Categories (MDCs) from the Patient Discharge Data (PDD) for each California hospital. Each MDC corresponds to a major organ system (e.g., Respiratory System, Circulatory System, Digestive System) rather than a specific disease (e.g., cancer, sepsis). The MDCs are also generally associated with a particular medical specialty. Therefore, the MDCs can be used to help identify what types of health care specialists are needed at each facility. For instance, a facility with “Circulatory System, Disease and Disorders” as one of their Top Five MDC diagnosis groups is more likely to have a greater need for cardiac specialists. The data will be updated on an annual basis.

The Hospital Compare dataset is part of a data repository maintained by the Centers for Medicare & Medicaid Services (CMS), focusing on the quality of care at over 4,500 Medicare-certified hospitals (including acute care hospitals, critical access hospitals (CAHs), children’s hospitals, and hospital outpatient departments) across the country. The dataset was created in collaboration with organizations representing consumers, doctors, hospitals, employers, accrediting organizations, and other federal agencies, as part of an overall effort to improve patient safety and care.

The Hospital Compare dataset on PolicyMap includes data on:

General information (Overall Rating, Mortality, Safety of Care, Readmission, Patient Experience, Effectiveness of Care, Timeliness of Care, Effective use of Medical Imaging): The overall hospital rating is given in stars from 1 to 5, while all other measures are designated as either being below, same, or above the national average. Data for these measures is compiled through the Inpatient/Outpatient Quality Reports and other programs mandatory for Medicare-certified hospitals. All comparisons on national average were standardized to ensure a common scale and direction for each measure. This implies that hospitals that perform above average on mortality or readmission comparison have a higher standardized z-score on these measures, based on lower mortality and readmission rates than the national average. The overall star rating in this section is intended primarily for acute care hospitals, due to which CMS may have omitted the measure for specialty hospitals. More details on the methodology for calculating overall ratings can be found here. Survey of patients’ experiences – (Ratings on Care transition, Cleanliness, Communication, Pain Management, Staff Responsiveness, Quietness, Discharge Information, and overall hospital ratings): All of these measures are assigned a star rating from 1 to 5. Data for these measures is compiled using the Hospital Consumer Assessment of Healthcare Providers and Systems survey [HCAHPS], which is administered to a random sample of adult inpatients after discharge. In order to receive HCAHPS Star Ratings, hospitals must have at least 100 completed HCAHPS surveys over a given four-quarter period. While all of the star ratings are based on direct patient responses, the summary star rating is calculated as a weighted measure using all categories of patient responses, including overall patient rating. More details on the methodology for calculating HCAHPS star ratings can be found here. Healthcare Associated Infections (HAI): HAI measures show how often patients in a particular hospital contract certain infections during the course of their medical treatment, when compared to like hospitals. These infections can often be prevented when healthcare facilities follow guidelines for safe care. Hospitals currently submit information on central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), colon and abdominal hysterectomy surgical site infections (SSIs), MRSA Bacteremia, and C.difficile laboratory-identified events. More details on the methodology for calculating HCAHPS star ratings can be found here.

Reasons for exclusion of certain measures for a hospital may include when number of cases/patients is too few to report, results are based on a shorter time period than required, data suppressed by CMS for one or more quarters, results are not available for this reporting period, there were discrepancies in the data collection process, this result is not based on performance data; the hospital did not submit data and did not submit a waiver, data are shown only for hospitals that participate in the Inpatient Quality Reporting (IQR) and Outpatient Quality Reporting (OQR) programs.

More details on data collection and computation methodology for each dataset can be found here. This dataset is available on PolicyMap as point data based on hospital location, and can be viewed upon clicking each respective point. The CMS Hospital Compare data was joined by PolicyMap to hospital locations using data from HRSA. HRSA hospital location data can be found here.

Summary characteristics of hospitals comprising each neighborhood, demographics of their Hospital Service Areas, and their U.S. News and World Report, Leapfrog, Consumer Reports, and Health Grades ratings.

Context

This are the official datasets used on the Medicare.gov Hospital Compare Website provided by the Centers for Medicare & Medicaid Services. These data allow you to compare the quality of care at over 4,000 Medicare-certified hospitals across the country.

Content

Dataset fields:

• Provider ID
• Hospital Name
• Address
• City
• State
• ZIP Code
• County Name
• Phone Number
• Hospital Type
• Hospital Ownership
• Emergency Services
• Meets criteria for meaningful use of EHRs
• Hospital overall rating
• Hospital overall rating footnote
• Mortality national comparison
• Mortality national comparison footnote
• Safety of care national comparison
• Safety of care national comparison footnote
• Readmission national comparison
• Readmission national comparison footnote
• Patient experience national comparison
• Patient experience national comparison footnote
• Effectiveness of care national comparison
• Effectiveness of care national comparison footnote
• Timeliness of care national comparison
• Timeliness of care national comparison footnote
• Efficient use of medical imaging national comparison
• Efficient use of medical imaging national comparison

Acknowledgements

Dataset was downloaded from [https://data.medicare.gov/data/hospital-compare]

Inspiration

If you just broke your leg, you might need to use this dataset to find the best Hospital to get that fixed!

According to a ranking by Statista and Newsweek, the best hospital in Norway is Oslo Universitetssykehus in Oslo. Moreover, Oslo Universitetssykehus was also ranked as the **** best hospital in the world, among over ****** hospitals in ** countries. St. Olavs Hospital in Trondheim and Haukeland Universitetssykehus in Bergen were ranked as second and third best respectively in the Norway, while they were ***** and ***** best respectively in the World.

South Korea Number of Hospital was up 3.5% in 2019, compared to the previous year.

This dataset lists the Structural Performance Category or “SPC rating” and Nonstructural Performance Category or “NPC rating” of all General Acute Care Hospitals in California, including a building’s probability of collapse in a significant earthquake as assessed by Multi-Hazard Loss Estimation Technology (HAZUS). To link the HCAI IDs with those from other Departments, like CDPH, please reference the "Licensed Facility Cross-Walk" Open Data table at https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk.

Annual Excel pivot tables display the top 25 MS-DRGs (Medicare Severity-Diagnosis Related Groups) per hospital. The ranking can be sorted by the number of discharges, average charge per stay, or average length of stay.