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.

This dataset shows the the world's best hospital in 2023 issued by the Newsweek and Statista.

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.

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.

According to a ranking by Statista and Newsweek, the best hospital in Sweden is the Karolinska Universitetssjukhuset in Stockholm. Moreover, Karolinska Universitetssjukhuset was also ranked as the seventh-best hospital in the world, among over ****** hospitals in ** countries. Sahlgrenska Universitetssjukhuset in Göteborg and Akademiska Sjukhuset in Uppsala were ranked as second and third best respectively in the Sweden, while they were **** and **** best respectively in the World.

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.

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

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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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...

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

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.

Children's Hospitals Pricing Information

Children's Hospitals Pricing Information

By Amber Thomas [source]

About this dataset

This dataset contains machine-readable hospital pricing information for Children's Hospitals and Clinics of Minnesota. It includes three separate files:

1. 2022-top-25-hospital-based-clinics-list.csv: This file provides the top 25 primary care procedure prices, including procedure codes, fees, and insurance coverage details.
2. 2022-standard-list-of-charges-hospital-op.csv: This file includes machine-readable hospital pricing information, including procedure codes, fees, and insurance coverage details.
3. 2022-msdrg.csv: This file also contains machine-readable hospital pricing information, including procedure codes, fees, and insurance coverage details.

The data was collected programmatically using a custom script written in Node.js and Microsoft Playwright. These files were then mirrored on the data.world platform using the Import from URL option.

If you find any errors in the dataset or have any questions or concerns, please leave a note in the Discussion tab of this dataset or contact supportdata.world for assistance

How to use the dataset

• Dataset Overview:

  • The dataset contains three files: a) 2022-top-25-hospital-based-clinics-list.csv: This file includes the top 25 primary care procedure prices for Children's Hospitals and Clinics of Minnesota, including procedure codes, fees, and insurance coverages. b) 2022-standard-list-of-charges-hospital-op.csv: This file includes machine-readable hospital pricing information for Children's Hospitals and Clinics of Minnesota, including procedure codes, fees, and insurance coverages. c) 2022-msdrg.csv: This file includes machine-readable hospital pricing information for Children's Hospitals and Clinics of Minnesota, including MSDRG (Medicare Severity Diagnosis Related Groups) codes, fees, and insurance coverages.

• Data Collection:

  • The data was collected programmatically using a custom script written in Node.js with the assistance of Microsoft Playwright.
  • These datasets were programmatically mirrored on the data.world platform using the Import from URL option.

• Usage Guidelines:

  • Explore Procedure Prices: You can analyze the top 25 primary care procedure prices by referring to the '2022-top-25-hospital-based-clinics-list.csv' file. It provides information on procedure codes (identifiers), associated fees (costs), and insurance coverage details.

  • Analyze Hospital Price Information: The '2022-standard-list-of-charges-hospital-op.csv' contains comprehensive machine-readable hospital pricing information. You can examine various procedures by their respective codes along with associated fees as well as corresponding insurance coverage details.

  • Understand MSDRG Codes & Fees: The '2022-msdrg.csv' file includes machine-readable hospital pricing information based on MSDRG (Medicare Severity Diagnosis Related Groups) codes. You can explore the relationship between diagnosis groups and associated fees, along with insurance coverage details.

• Reporting Errors:

  • If you identify any errors or discrepancies in the dataset, please leave a note in the Discussion tab of this dataset to notify others who may be interested.
  • Alternatively, you can reach out to the data.world team at supportdata.world for further assistance.

Research Ideas

• Comparative Analysis: Researchers and healthcare professionals can use this dataset to compare the pricing of primary care procedures at Children's Hospitals and Clinics of Minnesota with other hospitals. This can help identify any variations or discrepancies in pricing, enabling better cost management and transparency.
• Insurance Coverage Analysis: The insurance coverage information provided in this dataset can be used to analyze which procedures are covered by different insurance providers. This analysis can help patients understand their out-of-pocket expenses for specific procedures and choose the best insurance plan accordingly.
• Cost Estimation: Patients can utilize this dataset to estimate the cost of primary care procedures at Children's Hospitals and Clinics of Minnesota before seeking medical treatment. By comparing procedure fees across different hospitals, patients can make informed decisions about where to receive their healthcare services based on affordability and quality

Acknowledgements

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

License

**Unknown License - Please chec...

Success.ai’s Healthcare Professionals Data for Healthcare & Hospital Executives in Europe provides a reliable and comprehensive dataset tailored for businesses aiming to connect with decision-makers in the European healthcare and hospital sectors. Covering healthcare executives, hospital administrators, and medical directors, this dataset offers verified contact details, professional insights, and leadership profiles.

With access to over 700 million verified global profiles and data from 70 million businesses, Success.ai ensures your outreach, market research, and partnership strategies are powered by accurate, continuously updated, and GDPR-compliant data. Backed by our Best Price Guarantee, this solution is indispensable for navigating and thriving in Europe’s healthcare industry.

Why Choose Success.ai’s Healthcare Professionals Data?

1. Verified Contact Data for Targeted Engagement

   • Access verified work emails, phone numbers, and LinkedIn profiles of healthcare executives, hospital administrators, and medical directors.
   • AI-driven validation ensures 99% accuracy, reducing data gaps and improving communication effectiveness.

2. Comprehensive Coverage of European Healthcare Professionals

   • Includes profiles of professionals from top hospitals, healthcare organizations, and medical institutions across Europe.
   • Gain insights into regional healthcare trends, operational challenges, and emerging technologies.

3. Continuously Updated Datasets

   • Real-time updates capture changes in leadership roles, organizational structures, and market dynamics.
   • Stay aligned with the fast-evolving healthcare landscape to identify emerging opportunities.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with healthcare professionals and decision-makers in Europe’s hospital and healthcare sectors.
• 70M+ Business Profiles: Access detailed firmographic data, including hospital sizes, revenue ranges, and geographic footprints.
• Leadership Insights: Engage with CEOs, medical directors, and administrative leaders shaping healthcare strategies.
• Regional Healthcare Trends: Understand trends in digital healthcare adoption, operational efficiency, and patient care management.

Key Features of the Dataset:

1. Comprehensive Professional Profiles

   • Identify and connect with key players, including hospital executives, medical directors, and department heads in the healthcare industry.
   • Access data on professional histories, certifications, and areas of expertise for precise targeting.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by hospital size, geographic location, or job function (administrative, medical, or operational).
   • Tailor campaigns to align with specific needs such as digital transformation, patient care solutions, or regulatory compliance.

3. Healthcare Industry Insights

   • Leverage data on operational trends, hospital management practices, and regional healthcare needs.
   • Refine product offerings and outreach strategies to address pressing challenges in the European healthcare market.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes with healthcare professionals.

Strategic Use Cases:

1. Marketing and Outreach to Healthcare Executives

   • Promote healthcare IT solutions, medical devices, or operational efficiency tools to executives managing hospitals and clinics.
   • Use verified contact data for multi-channel outreach, including email, phone, and digital marketing.

2. Partnership Development and Collaboration

   • Build relationships with hospitals, healthcare providers, and medical institutions exploring strategic partnerships or new technology adoption.
   • Foster alliances that drive patient care improvements, cost savings, or operational efficiency.

3. Market Research and Competitive Analysis

   • Analyze trends in European healthcare to refine product development, marketing strategies, and engagement plans.
   • Benchmark against competitors to identify growth opportunities, underserved segments, and innovative solutions.

4. Recruitment and Workforce Solutions

   • Target HR professionals and hiring managers in healthcare institutions recruiting for administrative, medical, or operational roles.
   • Provide workforce optimization platforms, training solutions, or staffing services tailored to the healthcare sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality healthcare professional data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration
   ...

Snapshot img

Hospital Beds Market Size 2025-2029

The hospital beds market size is forecast to increase by USD 2.69 billion, at a CAGR of 9.9% between 2024 and 2029.

The market is experiencing significant growth due to the rising number of medical emergencies and the increase in infectious diseases. The global health crisis has highlighted the importance of having an adequate supply of hospital beds to manage the influx of patients. However, the high cost of automated hospital beds poses a challenge for healthcare providers, as they seek to balance the need for advanced technology with budget constraints. Moreover, the growing prevalence of chronic diseases, such as diabetes and cardiovascular diseases, necessitates long-term hospitalization, further increasing the demand for hospital beds. Additionally, the aging population and their subsequent healthcare needs are also contributing to market growth.
To capitalize on these opportunities, companies can focus on developing cost-effective solutions that offer advanced features, ensuring they cater to the evolving needs of healthcare providers while remaining competitive in the market. Navigating the challenges of cost and affordability will be crucial for market success, as providers seek to optimize their budgets while maintaining the highest level of patient care.

What will be the Size of the Hospital Beds Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The hospital bed market continues to evolve, with dynamic shifts in market trends and applications across various healthcare sectors. Hospital bed frames, a fundamental component of patient care, undergo constant innovation to enhance ergonomics and support systems. Mattresses with advanced pressure distribution technology cater to the unique needs of bariatric patients, while ICU beds integrate intravenous pole systems and height adjustment mechanisms for intensive care. Bedside safety features, such as fall prevention systems and bedside rails, are increasingly integrated into hospital bed designs. Bedside monitors, lighting, and call systems further enhance patient safety and comfort. Hospital bed sustainability is a growing concern, with a focus on recycling and disposal methods, as well as the use of eco-friendly materials in bed covers and linens.

Anti-embolism stockings and durability are essential considerations in hospital bed design, ensuring patient safety and longevity. Hospital bed certification standards continue to evolve, driving innovation in bedside safety and maintenance. The market for hospital bed accessories, such as overbed tables and height adjustment mechanisms, is expanding to cater to diverse patient needs. Ergonomics and aesthetics are increasingly important in hospital bed design, with a focus on patient comfort and satisfaction. The integration of electric actuators and sterilization systems further enhances the functionality and efficiency of hospital beds. The ongoing development of pressure relief systems and anti-decubitus mattresses underscores the continuous pursuit of innovation in this dynamic market.

How is this Hospital Beds Industry segmented?

The hospital beds industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Manual beds
  Semi-automated beds
  Automated beds


Application

  Intensive care
  Acute care
  Home care


End-user

  Hospitals
  Home healthcare
  Elderly care facilities
  Ambulatory surgical centers


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

.

By Product Insights

The manual beds segment is estimated to witness significant growth during the forecast period.

The market encompasses a range of products designed for healthcare settings, including manual and electric beds, bariatric beds, ICU beds, and recovery room beds. These beds prioritize ergonomics, offering mattress support systems, adjustable frames, and pressure distribution systems to ensure patient comfort and support. Hospital bed sustainability is a growing concern, leading to the development of eco-friendly materials and recycling programs for bed components. Bedside tables, rails, and lighting provide added functionality, while certifications ensure safety and compliance. Hospital bed linens and covers, along with anti-embolism stockings, contribute to patient care and hygiene. Fall prevention systems and repair services ensure patient safety and bed longevity.

Operating room tables and electric actuators facilitate efficien

The global sales of hospital consumables are estimated to be worth USD 421.8 billion in 2025 and anticipated to reach a value of USD 578.0 billion by 2035. Sales are projected to rise at a CAGR of 3.2% over the forecast period between 2025 and 2035. The revenue generated by hospital consumables in 2024 was USD 408.8 billion.

Attributes	Key Insights
Historical Size, 2024	USD 408.8 billion
Estimated Size, 2025	USD 421.8 billion
Projected Size, 2035	USD 578.0 billion
Value-based CAGR (2025 to 2035)	3.2%

Semi-Annual Market Update for the Global Hospital Consumables Market

Particular	Value CAGR
H1	3.9% (2024 to 2034)
H2	3.6% (2024 to 2034)
H1	3.2% (2025 to 2035)
H2	2.7% (2025 to 2035)

Analysis of Top Countries Manufacturing and Supplying Hospital Consumables

Countries	Value CAGR (2025 to 2035)
United States	1.5%
Germany	1.7%
China	5.4%
France	2.2%
India	5.8%
Spain	2.9%
Australia & New Zealand	3.1%
South Korea	4.2%

Hospital Consumables Industry Analysis by Top Investment Segments

By Product	Wound Care Products
Value Share (2025)	16.7%

By End User	Hospitals
Value Share (2025)	26.1%

In 2023, Singapore dominated the ranking of the world's health and health systems, followed by Japan and South Korea. The health index score is calculated by evaluating various indicators that assess the health of the population, and access to the services required to sustain good health, including health outcomes, health systems, sickness and risk factors, and mortality rates. The health and health system index score of the top ten countries with the best healthcare system in the world ranged between 82 and 86.9, measured on a scale of zero to 100.

Global Health Security Index  Numerous health and health system indexes have been developed to assess various attributes and aspects of a nation's healthcare system. One such measure is the Global Health Security (GHS) index. This index evaluates the ability of 195 nations to identify, assess, and mitigate biological hazards in addition to political and socioeconomic concerns, the quality of their healthcare systems, and their compliance with international finance and standards. In 2021, the United States was ranked at the top of the GHS index, but due to multiple reasons, the U.S. government failed to effectively manage the COVID-19 pandemic. The GHS Index evaluates capability and identifies preparation gaps; nevertheless, it cannot predict a nation's resource allocation in case of a public health emergency.

Universal Health Coverage Index  Another health index that is used globally by the members of the United Nations (UN) is the universal health care (UHC) service coverage index. The UHC index monitors the country's progress related to the sustainable developmental goal (SDG) number three. The UHC service coverage index tracks 14 indicators related to reproductive, maternal, newborn, and child health, infectious diseases, non-communicable diseases, service capacity, and access to care. The main target of universal health coverage is to ensure that no one is denied access to essential medical services due to financial hardships. In 2021, the UHC index scores ranged from as low as 21 to a high score of 91 across 194 countries. 

VHA hospitals Timely Care Data

Performance on Clinical Measures and Processes of Care

By US Open Data Portal, data.gov [source]

About this dataset

This dataset provides an inside look at the performance of the Veterans Health Administration (VHA) hospitals on timely and effective care measures. It contains detailed information such as hospital names, addresses, census-designated cities and locations, states, ZIP codes county names, phone numbers and associated conditions. Additionally, each entry includes a score, sample size and any notes or footnotes to give further context. This data is collected through either Quality Improvement Organizations for external peer review programs as well as direct electronic medical records. By understanding these performance scores of VHA hospitals on timely care measures we can gain valuable insights into how VA healthcare services are delivering values throughout the country!

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How to use the dataset

This dataset contains information about the performance of Veterans Health Administration hospitals on timely and effective care measures. In this dataset, you can find the hospital name, address, city, state, ZIP code, county name, phone number associated with each hospital as well as data related to the timely and effective care measure such as conditions being measured and their associated scores.

To use this dataset effectively, we recommend first focusing on identifying an area of interest for analysis. For example: what condition is most impacting wait times for patients? Once that has been identified you can narrow down which fields would best fit your needs - for example if you are studying wait times then “Score” may be more valuable to filter than Footnote. Additionally consider using aggregation functions over certain fields (like average score over time) in order to get a better understanding of overall performance by factor--for instance Location.

Ultimately this dataset provides a snapshot into how Veteran's Health Administration hospitals are performing on timely and effective care measures so any research should focus around that aspect of healthcare delivery

Research Ideas

• Analyzing and predicting hospital performance on a regional level to improve the quality of healthcare for veterans across the country.
• Using this dataset to identify trends and develop strategies for hospitals that consistently score low on timely and effective care measures, with the goal of improving patient outcomes.
• Comparison analysis between different VHA hospitals to discover patterns and best practices in providing effective care so they can be shared with other hospitals in the system

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: csv-1.csv | Column name | Description | |:-----------------------|:-------------------------------------------------------------| | Hospital Name | Name of the VHA hospital. (String) | | Address | Street address of the VHA hospital. (String) | | City | City where the VHA hospital is located. (String) | | State | State where the VHA hospital is located. (String) | | ZIP Code | ZIP code of the VHA hospital. (Integer) | | County Name | County where the VHA hospital is located. (String) | | Phone Number | Phone number of the VHA hospital. (String) | | Condition | Condition being measured. (String) | | Measure Name | Measure used to measure the condition. (String) | | Score | Score achieved by the VHA h...

The average for 2019 based on 26 countries was 1.41 nurse to bed ratio. The highest value was in the United Kingdom: 3.09 nurse to bed ratio and the lowest value was in South Korea: 0.42 nurse to bed ratio. The indicator is available from 1980 to 2020. Below is a chart for all countries where data are available.

US Healthcare Readmissions and Mortality

Evaluating Hospital Performance

By Health [source]

About this dataset

This dataset contains detailed information about 30-day readmission and mortality rates of U.S. hospitals. It is an essential tool for stakeholders aiming to identify opportunities for improving healthcare quality and performance across the country. Providers benefit by having access to comprehensive data regarding readmission, mortality rate, score, measure start/end dates, compared average to national as well as other pertinent metrics like zip codes, phone numbers and county names. Use this data set to conduct evaluations of how hospitals are meeting industry standards from a quality and outcomes perspective in order to make more informed decisions when designing patient care strategies and policies

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How to use the dataset

This dataset provides data on 30-day readmission and mortality rates of U.S. hospitals, useful in understanding the quality of healthcare being provided. This data can provide insight into the effectiveness of treatments, patient care, and staff performance at different healthcare facilities throughout the country.

In order to use this dataset effectively, it is important to understand each column and how best to interpret them. The ‘Hospital Name’ column displays the name of the facility; ‘Address’ lists a street address for the hospital; ‘City’ indicates its geographic location; ‘State’ specifies a two-letter abbreviation for that state; ‘ZIP Code’ provides each facility's 5 digit zip code address; 'County Name' specifies what county that particular hospital resides in; 'Phone number' lists a phone contact for any given facility ;'Measure Name' identifies which measure is being recorded (for instance: Elective Delivery Before 39 Weeks); 'Score' value reflects an average score based on patient feedback surveys taken over time frame listed under ' Measure Start Date.' Then there are also columns tracking both lower estimates ('Lower Estimate') as well as higher estimates ('Higher Estimate'); these create variability that can be tracked by researchers seeking further answers or formulating future studies on this topic or field.; Lastly there is one more measure oissociated with this set: ' Footnote,' which may highlight any addional important details pertinent to analysis such as numbers outlying National averages etc..

This data set can be used by hospitals, research facilities and other interested parties in providing inciteful information when making decisions about patient care standards throughout America . It can help find patterns about readmitis/mortality along county lines or answer questions about preformance fluctuations between different hospital locations over an extended amount of time. So if you are ever curious about 30 days readmitted within US Hospitals don't hesitate to dive into this insightful dataset!

Research Ideas

• Comparing hospitals on a regional or national basis to measure the quality of care provided for readmission and mortality rates.
• Analyzing the effects of technological advancements such as telemedicine, virtual visits, and AI on readmission and mortality rates at different hospitals.
• Using measures such as Lower Estimate Higher Estimate scores to identify systematic problems in readmissions or mortality rate management at hospitals and informing public health care policy

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: Readmissions_and_Deaths_-_Hospital.csv | Column name | Description | |:-------------------------|:---------------------------------------------------------------------------------------------------| | Hospital Name ...

BackgroundDiabetes imposes a substantial burden globally in terms of premature mortality, morbidity, and health care costs. Estimates of economic outcomes associated with diabetes are essential inputs to policy analyses aimed at prevention and treatment of diabetes. Our objective was to estimate and compare event rates, hospital utilization, and costs associated with major diabetes-related complications in high-, middle-, and low-income countries.Methods and FindingsIncidence and history of diabetes-related complications, hospital admissions, and length of stay were recorded in 11,140 patients with type 2 diabetes participating in the Action in Diabetes and Vascular Disease (ADVANCE) study (mean age at entry 66 y). The probability of hospital utilization and number of days in hospital for major events associated with coronary disease, cerebrovascular disease, congestive heart failure, peripheral vascular disease, and nephropathy were estimated for three regions (Asia, Eastern Europe, and Established Market Economies) using multiple regression analysis. The resulting estimates of days spent in hospital were multiplied by regional estimates of the costs per hospital bed-day from the World Health Organization to compute annual acute and long-term costs associated with the different types of complications. To assist, comparability, costs are reported in international dollars (Int$), which represent a hypothetical currency that allows for the same quantities of goods or services to be purchased regardless of country, standardized on purchasing power in the United States. A cost calculator accompanying this paper enables the estimation of costs for individual countries and translation of these costs into local currency units. The probability of attending a hospital following an event was highest for heart failure (93%–96% across regions) and lowest for nephropathy (15%–26%). The average numbers of days in hospital given at least one admission were greatest for stroke (17–32 d across region) and heart failure (16–31 d) and lowest for nephropathy (12–23 d). Considering regional differences, probabilities of hospitalization were lowest in Asia and highest in Established Market Economies; on the other hand, lengths of stay were highest in Asia and lowest in Established Market Economies. Overall estimated annual hospital costs for patients with none of the specified events or event histories ranged from Int$76 in Asia to Int$296 in Established Market Economies. All complications included in this analysis led to significant increases in hospital costs; coronary events, cerebrovascular events, and heart failure were the most costly, at more than Int$1,800, Int$3,000, and Int$4,000 in Asia, Eastern Europe, and Established Market Economies, respectively.ConclusionsMajor complications of diabetes significantly increase hospital use and costs across various settings and are likely to impose a high economic burden on health care systems. Please see later in the article for the Editors' Summary

448 Global import shipment records of Hospital Good with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.