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.

Children's Hospitals Pricing Data

Hospital pricing information for Children's Hospitals and Clinics of Minnesota

By Amber Thomas [source]

About this dataset

This dataset provides machine-readable hospital pricing information from Children's Hospitals and Clinics of Minnesota. It includes three files: 2022-top-25-hospital-based-clinics-list.csv, which contains the top 25 primary care procedure prices for hospital-based clinics at Children's Hospitals; 2022-standard-list-of-charges-hospital-op.csv, which comprises the standard charges for outpatient procedures in 2022, including procedure codes, fees, and insurance coverage; and 2022-msdrg.csv, containing machine-readable hospital pricing information specifically related to the 2022 Medicare Severity Diagnosis Related Groups (MS-DRG) codes. These datasets were obtained directly from Children's Hospitals' website as part of their compliance with the Centers for Medicare and Medicaid Services IPPS Final Rule. The data was collected programmatically using a custom script written in Node.js and Microsoft Playwright, then mirrored on the data.world platform. If you come across any errors or discrepancies in this data, please report them in the Discussion tab or contact supportdata.world

How to use the dataset

• Understanding the Files:

  • The dataset consists of three files: 2022-top-25-hospital-based-clinics-list.csv, 2022-standard-list-of-charges-hospital-op.csv, and 2022-msdrg.csv.
  • 2022-top-25-hospital-based-clinics-list.csv contains the top 25 primary care procedure prices for hospital-based clinics at Children's Hospitals and Clinics of Minnesota.
  • 2022-standard-list-of-charges-hospital-op.csv includes the standard list of charges for outpatient procedures at Children's Hospitals and Clinics of Minnesota, including procedure codes, fees, and insurance coverage.
  • The file 2022-msdrg.csv provides machine-readable hospital pricing information specifically related to the Medicare Severity Diagnosis Related Groups (MS-DRG) codes.

• Accessing the Data:

  • The data can be accessed from their source on the Children's Hospitals and Clinics of Minnesota website.

• Data Collection Method:

  • All data in this dataset was collected programmatically using a custom script written in Node.js and utilizing Microsoft Playwright, an open-source library for browser automation.

• How to Handle Errors or Suggestions:

  • If you have found any errors or have suggestions regarding this dataset, you can leave a note on the Discussion tab of this dataset on Kaggle or reach out via email to supportdata.world.

• Dataset Use Cases:

  a) Research & Analysis: Analyze primary care procedure prices at Children's Hospitals and Clinics of Minnesota based on different procedure codes present in the top-25 list from 2022 hospital-based clinics file (2022-top-25-hospital-based-clinics-list.csv).

  b) Cost Comparison: Compare fees and charges for outpatient procedures at Children's Hospitals and Clinics of Minnesota with other healthcare providers using the 2022 standard list of charges file (2022-standard-list-of-charges-hospital-op.csv).

  c) Insurance Coverage Analysis: Investigate insurance coverage details for outpatient procedures at Children's Hospitals and Clinics of Minnesota by referring to the insurance coverage column in the 2022 standard list of charges file (2022-standard-list-of-charges-hospital-op.csv).

  d) Medicare Severity Diagnosis Related Groups (MS-DRG): Explore machine-readable hospital pricing information specifically

Research Ideas

• Price comparison: This dataset can be used to compare the prices of different primary care procedures and outpatient procedures at Children's Hospitals and Clinics of Minnesota. This information can help patients make informed decisions about their healthcare options based on affordability.
• Insurance coverage analysis: The dataset includes information about insurance coverage for each procedure, which can be analyzed to understand which procedures are covered by different insurance providers. This analysis can help patients determine if their insurance will cover a specific procedure or if they will need to pay out-of-pocket.
• Trend analysis: By comparing the pricing information from previous years' datasets, this dataset can be used to analyze trends in healthcare costs over time at Children's Hospitals and Clinics of Minnesota. This analysis can provide insights into how healthcare costs are changing and help identify areas where cost improvements may be needed

...

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.

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.

This dataset tracks the updates made on the dataset "Top 25 MS-DRGs – Individual Hospital (Pivot Profile)" as a repository for previous versions of the data and metadata.

Annual Excel pivot tables display the statewide top 25 MS-DRGs (Medicare Severity-Diagnosis Related Groups) by Average Charge per Stay. Each California hospital can be compared to the statewide benchmarks for those same MS-DRGs.

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 ...

During the financial year 2024/25, the busiest hospital provider in England was the ************************************************ with over *** thousand admissions. This trust encompasses four hospitals in the Birmingham area, one of the largest urban areas in England. The second-busiest trust this year was the ******************************************, with approximately *** thousand admissions. Accident and emergency admissionsIn the second quarter of 2024/25, there were around *** million accident and emergency (A&E) attendees in England (including at A&E departments not in hospitals). After the drop in A&E attendances during the COVID-pandemic, numbers have risen again to previous levels, with a trend towards an increasing number of individuals seeking emergency care. Around ****percent of A&E attendees in England in 2024/5 were first diagnosed with a lower respiratory infection. Furthermore, over**** percent were found to have ‘no abnormality detected’ which could be detrimental to a service that is already stretched. Waiting too longOver the last few years in the A&E department, the NHS has been falling behind the target that ** percent of patients should be seen within **** hours of arrival. The last time this target was reached was back in July 2015. Not just the A&E department, but other services also require lengthy waits. It is no wonder that the levels of satisfaction with the way the NHS runs is at an all-time low.

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?

ImportanceThe Affordable Care Act (ACA) has expanded access to health insurance for millions of Americans, but the impact of Medicaid expansion on healthcare delivery and utilization remains uncertain.ObjectiveTo determine the early impact of the Medicaid expansion component of ACA on hospital and ED utilization in California, a state that implemented the Medicaid expansion component of ACA and Florida, a state that did not.DesignAnalyze all ED encounters and hospitalizations in California and Florida from 2009 to 2014 and evaluate trends by payer and diagnostic category. Data were collected from State Inpatient Databases, State Emergency Department Databases and the California Office of Statewide Health Planning and Development.SettingHospital and ED encounters.ParticipantsPopulation-based study of California and Florida state residents.ExposureImplementation of Medicaid expansion component of ACA in California in 2014.Main outcomes or measuresChanges in ED visits and hospitalizations by payer, percentage of patients hospitalized after an ED encounter, top diagnostic categories for ED and hospital encounters.ResultsIn California, Medicaid ED visits increased 33% after Medicaid expansion implementation and self-pay visits decreased by 25% compared with a 5.7% increase in the rate of Medicaid patient ED visits and a 5.1% decrease in rate of self-pay patient visits in Florida. In addition, California experienced a 15.4% increase in Medicaid inpatient stays and a 25% decrease in self pay stays. Trends in the percentage of patients admitted to the hospital from the ED were notable; a 5.4% decrease in hospital admissions originating from the ED in California, and a 2.1% decrease in Florida from 2013 to 2014.Conclusions and relevanceWe observed a significant shift in payer for ED visits and hospitalizations after Medicaid expansion in California without a significant change in top diagnoses or overall rate of these ED visits and hospitalizations. There appears to be a shift in reimbursement burden from patients and hospitals to the government without a dramatic shift in patterns of ED or hospital utilization.

Adult psychiatry is an important part of medical and mental health treatments in the U.S. As of 2024, the top hospital for adult psychiatry was Massachusetts General Hospital in Boston, Massachusetts, with a score of ** percent. The score represents the percentage of surveyed psychiatric specialists that named select hospitals as the best for challenging patients. Despite hospitals having a wider range of care options for patients, a majority of the mental health treatment facilities in the U.S. are listed as outpatient care centers without day treatment options or partial hospitalization options. Mental Health in the U.S. In the U.S. millions of people are affected by mental illness every year. Mental illnesses can range from mood disorders such as depression and bipolar disorder to schizophrenia and anxiety disorders. Research has indicated that as of 2022 up to a ******* of adults between the ages of 18 and 25 in the U.S. had experienced some sort of mental illness within the past year, with rates of mental illness decreasing with age. A recent survey also indicated that among adults in the U.S. those living in ****** and **** may have the poorest mental health status among all states. Mental Health Treatment in the U.S. Not all mental health treatment requires hospitalization or psychiatric treatment. Most mental health issues can be addressed and treated in individual or group psychotherapy, but treatment differs drastically based on the type of mental illness. Psychotherapy, medication, case management, hospitalization and support groups are just a few of the ways mental illness can be treated. As of 2023 a ****** percentage of U.S. adults utilized prescription medications as opposed to any other kind of therapy. Among adults that sought treatment from a professional for a major depressive episode, a ******** saw a general practitioner or family doctor to treat their mental health issues.

ACT Public Hospitals, top 25 diagnoses for hospital admission by volume, persons aged 14 years or less, 2016–17 ACT Public Hospitals, top 25 diagnoses for hospital admission by volume, persons aged 14 years or less, 2016–17

Characteristics of responding institutions where videolaryngoscopes are available (n = 25).

ObjectiveTo investigate the current patterns of antimicrobial use among nonsurgical inpatients across 25 general hospitals in Shanxi Province and to evaluate the antimicrobial use rate, antimicrobial use density (AUD), days of therapy (DOT), length of therapy (LOT), and the application of cluster analysis in monitoring antimicrobial prescribing practices.MethodsThis study included 25 general hospitals covering 11 cities in Shanxi Province. In total, 2064 hospitalized nonsurgical patients were evaluated for antimicrobial use between December 1, 2022, and January 31, 2023. Data collected included the proportion of antimicrobial prescriptions, antimicrobial use rate, AUD, DOT, and LOT. Statistical analyses were conducted using IBM SPSS version 21.0. Cluster analysis was employed to categorize the 25 hospitals systematically.ResultsAmong the hospitals, the antimicrobial utilization rate ranged from 43.00 to 83.33%. The intensity of antimicrobial use ranged from 40DDDs/ 100pd to 98.99DDDs/100pd. DOT values ranged from 380/1000pd to 713/1000pd, while LOT ranged from 425/1000pd to 1,014/1000pd. The top three antimicrobial classes by AUD were third-generation cephalosporins (15.38 DDDs/100pd), quinolones (13.60 DDDs/100pd), and cephalosporins (11.54 DDDs/100pd). The ICU had the highest antimicrobial use rate and AUD—91.67% and 133.28 DDDs/100pd, respectively —and the longest DOT (1,230/1000 pd). The infection department recorded the highest LOT (988/1000pd). In pediatrics, the AUD and DOT were 53.77DDDs/ 100pd and 1,106/1000pd, respectively. The 25 hospitals were grouped into three distinct clusters via cluster analysis. Statistically significant differences in some antimicrobial indicators were observed among the groups (p 

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, hospitalizations, and associated deaths that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Hospitalization data were collected by the Connecticut Hospital Association and reflect the number of patients currently hospitalized with laboratory-confirmed COVID-19. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported d

Context

How satisfied are U.S. patients? Is a hospital's overall score really determined by how well it provides good customer services? Are there types of hospitals or regions where patient satisfaction is better or worse?

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.

One part of a hospital's overall rating is it's patient satisfaction survey scores. CMS attempts to take into consideration how well patients are treated by the provider. A description of HCAHPS can be found here ***HCAHPS Description.

Content

| Filename | Year | Dataset Rows | Dataset Columns | | --- | --- | --- | --- ] | cms_hospital_patient_satisfaction_2020.csv | 2020 | 442587 | 43 | | cms_hospital_patient_satisfaction_2019.csv | 2019 | 442401 | 43 | | cms_hospital_patient_satisfaction_2018.csv | 2018 | 239650 | 43 | | cms_hospital_patient_satisfaction_2017.csv | 2017 | 264660 | 43 | | cms_hospital_patient_satisfaction_2016.csv | 2016 | 264385 | 43 |

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

NOTE: Some Hospital Medicare IDs have leading zeroes. Be sure to read Facility ID column as a string.

| 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 | | HCAHPS Measure ID | Char(25) | HCAHPS Patient Survey Measure Name | | HCAHPS Question | Char(138) | HCAHPS Patient Survey Question | | HCAHPS Answer Description | Char(118)| HCAHPS Patient Survey Answer | | Patient Survey Star Rating | Char(14) | Overall rating for survey item | | Patient Survey Star Rating Footnote | Char(7) | n/a | | HCAHPS Answer Percent | Char(14) | Percent of surveys with question answered | | HCAHPS Answer Percent Footnote | Char(8) | n/a | | HCAHPS Linear Mean Value | Char(14) | HCAHPS Patient Survey question linear mean value | | Number of Completed Surveys | Char(13) | Number of completed surveys for hospital. N-size. | | Number of Completed Surveys Footnote | Char(8) | n/a | | Survey Response Rate Percent | Char(13) | Hospital survey response rate. | | Survey Response Rate Percent Footnote | Char(8) | n/a | | Start Date | Date | Survey collection period start date | | End Date | Date | Survey collection period end date | | Year | Char(4) | cms data release year | | 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 co...

The results of the SSNAP Acute Organisational Audit 2012 were the first to be published under the auspices of the new national stroke audit, the Sentinel Stroke National Audit Programme (SSNAP). They contain national and hospital level findings on the organisation of stroke services, in particular acute care organisation, specialist roles, staffing, TIA (mini stroke) services, communication between staff groups and with patients and carers, and pathway at discharge. The results reflect the organisation of stroke services as of 2 July 2012. 100% of eligible hospitals in England, Wales and Northern Ireland participated in the audit.

The public tables of named hospital results, available to download below, describe the performance for selected indicators for 163 participating sites in England. The median for each measure is given in the top row of the table to enable benchmarking. NB the national median reflects the results of 190 participating sites in England, Wales and Northern Ireland.

A scoring system was developed to enable sites to compare their organisation of stroke care with other sites. The scores for 8 separate components of organisation each range from 0 to 100 with 100 being the optimal score. A total organisational score is obtained by calculating the average of the 8 domain scores. The 25% of hospitals with the best stroke care organisation are in the upper quartile, the least well organised 25% of hospitals are in the lower quartile. The middle half lie between the two. NB the quartile position is based on the performance of 190 participating sites in England, Wales and Northern Ireland.

The table of named hospital results should be read in context as part of the full SSNAP Acute Organisational Audit Report 2012 which can be downloaded below and the full audit questions (appendix 2 of the full report).

This full report enables the organisation of stroke services at national level to be compared with national standards outlined in the fourth edition of the National Clinical Guideline for Stroke (2012) published by the Intercollegiate Stroke Working Party and the NICE Clinical Guideline, the National Stroke Strategy 2007 and the NICE Quality Standard for Stroke (2010).

This publication reports on Admitted Patient Care activity in England for the financial year 2023-24. This report includes but is not limited to analysis of hospital episodes by patient demographics, diagnoses, external causes/injuries, operations, bed days, admission method, time waited, specialty, provider level analysis and Adult Critical Care (ACC). It describes NHS Admitted Patient Care Activity, Adult Critical Care activity and performance in hospitals in England. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care and may also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. The data source for this publication is Hospital Episode Statistics (HES). It contains final data and replaces the provisional data that are released each month. HES contains records of all admissions, appointments and attendances at NHS-commissioned hospital services in England. The HES data used in this publication are called 'Finished Consultant Episodes', and each episode relates to a period of care for a patient under a single consultant at a single hospital. Therefore, this report counts the number of episodes of care for admitted patients rather than the number of patients. This publication shows the number of episodes during the period, with breakdowns including by patient's age, gender, diagnosis, procedure involved and by provider. Please send queries or feedback via email to enquiries@nhsdigital.nhs.uk. Author: Secondary Care Open Data and Publications, NHS England. Lead Analyst: Karl Eichler

This dataset contains Hospital Chargemasters with prices in effect as of June 1 of their reporting year. Chargemasters consists of a list of average charges for 25 common outpatient procedures, and the estimated percentage change in gross revenue due to price changes each July 1.

For more on HCAI Chargemaster Data.

This statistic displays the top 25 teaching hospitals based on received highest total payments from pharma and medtech companies in the U.S. during 2018. It was found that the City of Hope National Medical Center received a total of around 462 million U.S. dollars from pharmaceutical and medical technology companies, by far the highest amount among all hospitals.