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.

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

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

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...

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 by Statista and Newsweek, the best hospital in Denmark is the Rigshospitalet - København in Copenhagen. Moreover, the Rigshospitalet - København was also ranked as the **** best hospital in the world, among over ****** hospitals in ** countries. Aarhus Universitetshospital in Aarhus and Odense Universitetshospital in Odense were ranked as second and third best respectively in the Denmark, while they were **** and **** best respectively in the World.

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.

Hospital Compare Downloadable Database Data Dictionary, Centers for Medicare & Medicaid Services

This analysis was a part of my PG Diploma Data Science Course

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.

Context

There are all sorts of reasons why you'd want to know a hospital's quality rating.

• Your mom is having her second hip replacement. Her first one went terribly and you're nervous about how she'll do. Which hospital would you suggest she have her surgery?
• You're selecting a health plan on your state's Exchange, but your top two choices partner with different hospitals. How will you decide which plan to pick?
• Your brother has Cystic Fibrosis and has to go to the ER frequently. He hates waiting. Which hospitals/states provide care in the timeliest manner?
• Your in-laws moved to Florida recently to retire, and have been trying to convince you to move there too. You're looking for any way possible to show them that your state is better. Does your state have better hospitals?

Every hospital in the United States of America that accepts publicly insured patients (Medicaid or MediCare) is required to submit quality data, quarterly, to the Centers for Medicare & Medicaid Services (CMS). There are very few hospitals that do not accept publicly insured patients, so this is quite a comprehensive list.

Content

This file contains general information about all hospitals that have been registered with Medicare, including their addresses, type of hospital, and ownership structure. It also contains information about the quality of each hospital, in the form of an overall rating (1-5, where 5 is the best possible rating & 1 is the worst), and whether the hospital scored above, same as, or below the national average for a variety of measures.

This data was updated by CMS on July 25, 2017. CMS' overall rating includes 60 of the 100 measures for which data is collected & reported on Hospital Compare website (https://www.medicare.gov/hospitalcompare/search.html). Each of the measures have different collection/reporting dates, so it is impossible to specify exactly which time period this dataset covers. For more information about the timeframes for each measure, see: https://www.medicare.gov/hospitalcompare/Data/Data-Updated.html# For more information about the data itself, APIs and a variety of formats, see: https://data.medicare.gov/Hospital-Compare

Acknowledgements

Attention: Works of the U.S. Government are in the public domain and permission is not required to reuse them. An attribution to the agency as the source is appreciated. Your materials, however, should not give the false impression of government endorsement of your commercial products or services. See 42 U.S.C. 1320b-10.

Inspiration

Which hospital types & hospital ownerships are most common?

Which hospital types & ownerships are associated with better than average ratings/mortality/readmission/etc?

What is the average hospital rating, by state?

Which hospital types & hospital ownerships are more likely to have not submitted proper data ("Not Available" & "Results are not available for this reporting period")?

Which parts of the country have the highest & lowest density of religious hospitals?

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.

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

Every year, all U.S. hospitals that accept payments from Medicare and Medicaid must submit quality data to The Centers for Medicare and Medicaid Services (CMS). CMS' Hospital Compare program is a consumer-oriented website that provides information on "the quality of care hospitals are providing to their patients." CMS releases this quality data publicly in order to encourage hospitals to improve their quality and to help consumer make better decisions about which providers they visit.

"Hospital Compare provides data on over 4,000 Medicare-certified hospitals, including acute care hospitals, critical access hospitals (CAHs), children’s hospitals, Veterans Health Administration (VHA) Medical Centers, and hospital outpatient departments"

The Centers for Medicare & Medicaid Services (CMS) uses a five-star quality rating system to measure the experiences Medicare beneficiaries have with their health plan and health care system — the Star Rating Program. Health plans are rated on a scale of 1 to 5 stars, with 5 being the highest.

Content

• Includes the most recent Hospital General Information.csv data for each archive year found on CMS' archive site. Years: 2016-2020

| Column Name | Data Type | Description | | --- | --- | -- | | Facility ID | Char(6) | Facility Medicare ID | | Facility Name | Char(72) | Name of the facility | | Address | Char(51) | Facility street address | | City | Char(20) | Facility City | | State | Char(2) | Facility State | | ZIP Code | Num(8) | Facility ZIP Code | | County Name | Char(25) | Facility County | | Phone Number | Char(14) | Facility Phone Number | | Hospital Type | Char(34) | What type of facility is it? | | Hospital Ownership | Char(43) | What type of ownership does the facility have? | | Emergency Services | Char(3)) | Does the facility have emergency services Yes/No? | | Meets criteria for promoting interoperability of EHRs | Char(1) | Does facility meet government EHR standard Yes/No? | | Hospital overall rating | Char(13) | Hospital Overall Star Rating 1=Worst; 5=Best. Aggregate measure of all other measures | | Hospital overall rating footnote | Num(8) | | | Mortality national comparison | Char(28) | Facility overall performance on mortality measures compared to other facilities | | Mortality national comparison footnote | Num(8) | | | Safety of care national comparison | Char(28) | Facility overall performance on safety measures compared to other facilities | | Safety of care national comparison footnote | Num(8) | | | Readmission national comparison | Char(28) | Facility overall performance on readmission measures compared to other facilities | | Readmission national comparison footnote | Num(8) | | | Patient experience national comparison | Char(28) | Facility overall performance on pat. exp. measures compared to other facilities | | Patient experience national comparison footnote | Char(8) | | | Effectiveness of care national comparison | Char(28) | Facility overall performance on effect. of care measures compared to other facilities | | Effectiveness of care national comparison footnote | Char(8) | | | Timeliness of care national comparison | Char(28) | Facility overall performance on timeliness of care measures compared to other facilities | | Timeliness of care national comparison footnote| Char(8) | | | Efficient use of medical imaging national comparison | Char(28) | Facility overall performance on efficient use measures compared to other facilities | | Efficient use of medical imaging national comparison footnote | Char(8) | | | Year | Char(4) | cms data release year |

Acknowledgements

A similar dataset called Hospital General Information was previously uploaded to Kaggle. However, that dataset only includes data from one year (2017). I was inspired by this dataset to go a little further and try to add a time dimension. This dataset includes a union of Hospital General Information for the years 2016-2020. The python script used to collect and union all the datasets can be found on my [github[(https://github.com/abrambeyer/cms_hospital_general_info_file_downloader). Thanks to this dataset owner for the inspiration.

Thanks to CMS for releasing this dataset publicly to help consumers find better hospitals and make better-informed decisions.

***All Hospital Compare websites are publically accessible. As works of the U.S. government, Hospital Compare data are in the public domain and permission is not required to reuse them. An attribution to the agency as the source is appreciated. Your ...

The dataset contains risk-adjusted mortality rates, quality ratings, and number of deaths and cases for 6 medical conditions treated (Acute Stroke, Acute Myocardial Infarction, Heart Failure, Gastrointestinal Hemorrhage, Hip Fracture and Pneumonia) and 3 procedures performed (Carotid Endarterectomy, Pancreatic Resection, and Percutaneous Coronary Intervention) in California hospitals. The 2023 IMIs were generated using AHRQ Version 2024, while previous years' IMIs were generated with older versions of AHRQ software (2022 IMIs by Version 2023, 2021 IMIs by Version 2022, 2020 IMIs by Version 2021, 2019 IMIs by Version 2020, 2016-2018 IMIs by Version 2019, 2014 and 2015 IMIs by Version 5.0, and 2012 and 2013 IMIs by Version 4.5). The differences in the statistical method employed and inclusion and exclusion criteria using different versions can lead to different results. Users should not compare trends of mortality rates over time. However, many hospitals showed consistent performance over years; “better” performing hospitals may perform better and “worse” performing hospitals may perform worse consistently across years. This dataset does not include conditions treated or procedures performed in outpatient settings. Please refer to statewide table for California overall rates: https://data.chhs.ca.gov/dataset/california-hospital-inpatient-mortality-rates-and-quality-ratings/resource/af88090e-b6f5-4f65-a7ea-d613e6569d96

ContextPrior research has faulted the US News and World Report hospital specialty rankings for excessive reliance on reputation, a subjective measure of a hospital's performance.ObjectiveTo determine whether and to what extent reputation correlates with objective measures of research productivity among cancer hospitals.DesignA retrospective observational study.SettingAutomated search of NIH Reporter, BioEntrez, BioMedline and Clinicaltrials.gov databases.ParticipantsThe 50 highest ranked cancer hospitals in 2013's US News and World Report Rankings.ExposureWe ascertained the number of NCI funded grants, and the cumulative funds received by each cancer center. Additionally, we identified the number of phase I, phase II, and phase III studies published and indexed in MEDLINE, and registered at clinicaltrials.gov. All counts were over the preceding 5 years. For published articles, we summed the impact factor of the journals in which they appeared. Trials were attributed to centers on the basis of the affiliation of the lead author or study principal investigator.Main OutcomeCorrelation coefficients from simple and multiple linear regressions for measures of research productivity and a center's reputation.ResultsAll measures of research productivity demonstrated robust correlation with reputation (mean r-squared  = 0.65, median r-squared = 0.68, minimum r-squared = .41, maximum r-squared = 0.80). A multivariable model showed that 93% of the variation in reputation is explained by objective measures.ConclusionContrary to prior criticism, the majority of reputation, used in US News and World Rankings, can be explained by objective measures of research productivity among cancer hospitals.

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.

According to a ranking by Statista and Newsweek, the best hospital in Finland is Helsinki University Hospital in Helsinki. Moreover, Helsinki University Hospital was also ranked as the **** best hospital in the world, among over ****** hospitals in ** countries. Tampere University Hospital in Tampere and Turku University Hospital in Turku were ranked as second and third best respectively in the Finland, while they were ***** and ***** best respectively in the World.

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

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.

The dataset provides performance ratings for two outcome measures for transcatheter aortic valve replacement (TAVR) procedures: in-hospital/30-day mortality and in-hospital/30-day stroke. It includes the number of cases, adverse events, risk-adjusted rates, and performance ratings for hospitals compared to the overall statewide rates. This dataset also contains the location of hospitals that perform TAVR procedures in California.

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.