The average number of hospital beds available per 1,000 people in the United States was forecast to continuously decrease between 2024 and 2029 by in total 0.1 beds (-3.7 percent). After the eighth consecutive decreasing year, the number of available beds per 1,000 people is estimated to reach 2.63 beds and therefore a new minimum in 2029. Depicted is the number of hospital beds per capita in the country or region at hand. As defined by World Bank this includes inpatient beds in general, specialized, public and private hospitals as well as rehabilitation centers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the average number of hospital beds available per 1,000 people in countries like Canada and Mexico.

The number of hospitals in the United States was forecast to continuously decrease between 2024 and 2029 by in total 13 hospitals (-0.23 percent). According to this forecast, in 2029, the number of hospitals will have decreased for the twelfth consecutive year to 5,548 hospitals. Depicted is the number of hospitals in the country or region at hand. As the OECD states, the rules according to which an institution can be registered as a hospital vary across countries.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of hospitals in countries like Canada and Mexico.

The number of hospital beds in the United States was forecast to continuously increase between 2024 and 2029 by in total 16.6 thousand beds (+1.75 percent). After the fifteenth consecutive increasing year, the number of hospital beds is estimated to reach 967.9 thousand beds and therefore a new peak in 2029. Notably, the number of hospital beds of was continuously increasing over the past years.Depicted is the estimated total number of hospital beds in the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of hospital beds in countries like Mexico and Canada.

Percentage of emergency admissions to any hospital in England occurring within 30 days of the last, previous discharge from hospital after admission: indirectly standardised by age, sex, method of admission and diagnosis/procedure. The indicator is broken down into the following demographic groups for reporting: ● All years and female only, male only and both male and female (persons). ● <16 years and female only, male only and both male and female (persons). ● 16+ years and female only, male only and both male and female (persons) ● 16-74 years and female only, male only and both male and female (persons) ● 75+ years and female only, male only and both male and female (persons) Results for each of these groups are also split by the following geographical and demographic breakdowns: ● Local authority of residence. ● Region. ● Area classification. ● NHS and private providers. ● NHS England regions. ● Deprivation (Index of Multiple Deprivation (IMD) Quintiles, 2019). ● Sustainability and Transformation Partnerships (STP) & Integrated Care Boards (ICB) from 2016/17. ● Clinical Commissioning Groups (CCG) & sub-Integrated Care Boards (sub-ICB). All annual trends are indirectly standardised against 2013/14.

The Nationwide Inpatient Sample (NIS) is a database focused on hospital stay information. Users are able to use the NIS to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. Background The Nationwide Inpatient Sample (NIS) is maintained by the Healthcare Cost and Utilization Project. The NIS is the largest all-payer inpatient care database in the United States. It contains data from approximately 8 million hospital stays each year. The 2009 NIS contains all discharge data from 1,050 hospitals located in 44 States, approximating a 20-percent stratified sample of U.S. community hospitals. The sampling frame for the 2009 NIS is a sample of hospitals that comprises approximately 95 percent of all hospital discharges in the United States. The NIS is the only national hospital database containing charge information on all patients, regardless of payer, including persons covered by Medicare, Medicaid, private insurance, and the uninsured. User functionality Users must pay to access the database. NIS releases for data years 1988-2009 are available from the HCUP Central Distributor. The 2009 NIS may be purchased for $50 for students and $350 for all others on a single DVD-ROM with accompanying documentation. . Data Notes NIS data are available from 1988 to 2009. The number of states in the NIS has grown from 8 in the first year to 44 at present. Beginning with the 2002 NIS, severity adjustment data elements including APR-DRGs, APS-DRGs, Disease Staging, and AHRQ Comorbidity Indicators, are available. Begi nning with the 2005 NIS, Diagnosis and Procedure Groups Files containing data elements from AHRQ software tools designed to facilitate the use of the ICD-9-CM diagnostic and procedure information are available. Beginning with the 2007 NIS, data elements describing hospital structural characteristics and provision of outpatient services are available in the Hospital Weights file. NIS Release 1 includes data from 8-11 States and spans the years 1988 to 1992. NIS Releases 2 and 3 contain data from 17 States for 1993 and 1994, respectively. NIS Releases 4 and 5 contain data from 19 States for 1995 and 1996. NIS Release 6 contains data from 22 States for 1997. NIS 1998 contains data from 22 States. NIS 1999 contains data from 24 States. NIS 2000 contains data from 28 States. NIS 2001 contains data from 33 States. NIS 2002 contains data from 35 States. NIS 2003 contains data from 37 States. NIS 2004 contains data from 37 States. NIS 2005 contains data from 37 States. NIS 2006 contains data from 38 States. NIS 2007 contains data from 40 States. NIS 2008 contains data from 42 States.

The Healthcare Cost and Utilization Project (HCUP) Kids' Inpatient Database (KID) is the largest publicly available all-payer pediatric inpatient care database in the United States, containing data from two to three million hospital stays each year. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, such as congenital anomalies, as well as uncommon treatments, such as organ transplantation. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The KID is a sample of pediatric discharges from 4,000 U.S. hospitals in the HCUP State Inpatient Databases yielding approximately two to three million unweighted hospital discharges for newborns, children, and adolescents per year. About 10 percent of normal newborns and 80 percent of other neonatal and pediatric stays are selected from each hospital that is sampled for patients younger than 21 years of age. The KID contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes discharge status, diagnoses, procedures, patient demographics (e.g., sex, age), expected source of primary payment (e.g., Medicare, Medicaid, private insurance, self-pay, and other insurance types), and hospital charges and cost. Restricted access data files are available with a data use agreement and brief online security training.

The Nationwide Emergency Department Sample (NEDS) was created to enable analyses of emergency department (ED) utilization patterns and support public health professionals, administrators, policymakers, and clinicians in their decision-making regarding this critical source of care. The NEDS can be weighted to produce national estimates. The NEDS is the largest all-payer ED database in the United States. It was constructed using records from both the HCUP State Emergency Department Databases (SEDD) and the State Inpatient Databases (SID), both also described in healthdata.gov. The SEDD capture information on ED visits that do not result in an admission (i.e., treat-and-release visits and transfers to another hospital). The SID contain information on patients initially seen in the emergency room and then admitted to the same hospital. The NEDS contains 25-30 million (unweighted) records for ED visits for over 950 hospitals and approximates a 20-percent stratified sample of U.S. hospital-based EDs. The NEDS contains information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 75% of patients, regardless of payer, including patients covered by Medicaid, private insurance, and the uninsured. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.

Abstract Background: Hypertension is the main risk factor for cardiovascular diseases. Technical quality of sphygmomanometers is a prerequisite for the correct measurement of arterial pressure. Objectives: To evaluate sphygmomanometers available in emergency services in the city of Belo Horizonte, Brazil. Methods: We performed a cross-sectional, observational, non-interventional study to evaluate characteristics of the sphygmomanometers available in adult emergency services of public and private hospitals in the city of Belo Horizonte, Brazil. We evaluated 337 sphygmomanometers of 25 hospitals - 15 (of 16) public hospitals and 10 (of 12) private hospitals. Results: Twenty-six percent (88/337) of devices were considered inadequate regarding the INMETRO (National Institute of Metrology, Quality and Technology) standards, 39.2% (132/337) for calibration dates, and 54% (188/337) for the mismatching between cuff's and device's brands. In 13 of 25 hospitals (52%), there were no spare cuffs in different sizes for different arm circumferences. Higher adequacy was found for aneroid and mercury sphygmomanometers used in private hospitals (p = 0.038 and p < 0.001, respectively) and electronic devices used in public hospitals (p < 0.001) compared with others. Conclusion: Seventy-eight percent of sphygmomanometers available in emergency services had technical inadequacies, and half of these services had no spare cuffs in different sizes available. These findings serve as a warning of the conditions of the equipment used in healthcare services provided to the general population in Brazil.

This dataset shows individual trust- and unit-level activity and outcomes for hip and knee replacement surgery in 2011 for the NHS and private sector. It has been reproduced from the full NJR 9th Annual Report 2012 and covers the specific period January to December 2011.

The data published on this page only applies to England. The National Joint Registry of England, Wales and Northern Ireland (NI) publishes data from all territories, where achievable, as part of annual reporting process. The full NJR 9th Annual Report includes 2011 results for Welsh Health Boards (NI joined in 2013).

The data shows information relating to how individual trusts and hospitals in England have performed against a range of key measures including whether they have been identified as an ‘outlier’ for revision rates.

Key measures: Hospitals have been awarded a green (≥95%), amber (≥80%) or red (>80%) rating to reflect how well they performed in 2011 based on consent, compliance and linkability. Compliance information is published at trust-level. All other information is published by individual hospital in the NHS and private sector.

Outlier analysis: Outlier analysis aims to identify ‘unusual differences’ in data from ‘normal variations’ which may indicate the need for further investigation. For revision rates, an outlier will be a hospital with an unusually high proportion of revision rates – more than would normally be expected. Outliers are identified by a 'Y.'

The NJR has also listed the following information for each hospital: • Number of consultants • Average ASA grade • Percentage of male patients • Average age at operation • Percentage of 10A rated acetabular hip and femoral hip implants

This is the proportion of older people aged 65 and over offered reablement services following discharge from hospital.

Where the numerator is the number of older people discharged from acute or community hospitals to their own home or to a residential or nursing care home or extra care housing for rehabilitation, with the clear intention that they will move on/back to their own home (including a place in extra care housing or an adult placement scheme setting). Data source: SALT

The denominator will be the total number of older people discharged from hospitals based on Hospital Episode Statistics (HES). This includes all specialities and zero length stays. Data for geographical areas is based on usual residence of patient. Only covers people receiving partly or wholly supported care from their Local Authority and not wholly private, self-funded care. Source: Hospital Episode Statistics.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time. The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

This dataset presents the footprint of the percentage of adults who were admitted to any hospital in the preceding 12 months. The data spans the years of 2013-2017 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).

The data is sourced from the Australian Bureau of Statistics (ABS) 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. It also includes data from previous Patient Experience Surveys conducted in 2013-14, 2014-15 and 2015-16. The Patient Experience Survey is conducted annually by the ABS and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patient Experience Survey collects data on persons aged 15 years and over, who are referred to as adults for this data collection.

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Patient experiences in Australia Data Tables.

Please note:

• AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

• Percentages are calculated based on counts that have been randomly adjusted by the ABS to avoid the release of confidential data.

• As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the ABS using standard error estimates of the proportion.

• Some of the patient experience measures for 2016-17 have age-standardised rates presented. Age-standardised rates are hypothetical rates that would have been observed if the populations studied had the same age distribution as the standard population.

• Crude rates are provided for all years. They should be used for understanding the patterns of actual service use or level of experience in a particular PHN.

• The Patient Experience Survey excludes persons aged less than 15 years, persons living in non-private dwellings and the Indigenous Community Strata (encompassing discrete Aboriginal and Torres Strait Islander communities).

• Data for Northern Territory should be interpreted with caution as the Patient Experience Survey excluded the Indigenous Community Strata, which comprises around 25% of the estimated resident population of the Northern Territory living in private dwellings.

• Rows that contain a "#" in "Interpret with Caution" indicates that the estimate has a relative standard error of 25% to 50%, which indicates a high level of sampling error relative to its value and must be taken into account when comparing this estimate with other values.

• NP - Not available for publication. The estimate is considered to be unreliable. Values assigned to NP in the original data have been set to null.

Percent COVID-19 positive hospitalizations show us the number of COVID-19 patients as a proportion of all patients on a given day that are in DC hospitals. This represents a seven day average of the percentage of COVID-19 positive patients among the total number of hospitalized patients (i.e., the daily hospital census). Daily reporting of inpatients in DC hospitals includes individuals from other jurisdictions, and reflects ongoing data quality improvements.Data is updated Monday-Friday.

The Nationwide Emergency Department Sample (NEDS) was created to enable analyses of emergency department (ED) utilization patterns and support public health professionals, administrators, policymakers, and clinicians in their decision-making regarding this critical source of care. The NEDS can be weighted to produce national estimates. Restricted access data files are available with a data use agreement and brief online security training.

The NEDS is the largest all-payer ED database in the United States. It was constructed using records from both the HCUP State Emergency Department Databases (SEDD) and the State Inpatient Databases (SID), both also described in healthdata.gov. The SEDD capture information on ED visits that do not result in an admission (i.e., treat-and-release visits and transfers to another hospital). The SID contain information on patients initially seen in the emergency room and then admitted to the same hospital.

The NEDS contains 25-30 million (unweighted) records for ED visits for over 950 hospitals and approximates a 20-percent stratified sample of U.S. hospital-based EDs.

The NEDS contains information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 85% of patients, regardless of payer, including patients covered by Medicaid, private insurance, and the uninsured. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.

Number and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.

Data includes: * board information * school information * grade 3 and 6 EQAO student achievements for reading, writing and mathematics * grade 9 EQAO academic and applied student achievements * grade 10 OSSLT student achievement * student demographic percentages on student parents, special education, first language spoken and new students to Canada, Data includes public, Roman Catholic, publicly funded hospitals and provincial schools. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools. How Are We Protecting Privacy? Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented. Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up. The school enrolment totals have been rounded to the nearest 5 in order to better protect and maintain student privacy. The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible. **Sources: ** Board School Identification Database (BSID) / Ontario School Information System (OnSIS) as updated/maintained by boards. Data for Student Population is computed based on the 2016 Census and information as reported in OnSIS, Preliminary 2021-2022 OnSIS: Preliminary as of August 04, 2023, with all schools that met identified criteria with signed-off submissions. Education Quality and Accountability Office (EQAO), 2022-2023 This information is also available on the Ministry of Education's School Information Finder website by individual school. Descriptions for some of the data types can be found in our glossary. School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.

Analysis of ‘TABLE 3.4: HIPE Report: TABLE 3.4 Total Discharges: Number and Percentage of Discharges with a Principal Procedure by Patient Type and Admission Type, 2016’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/a56e9927-10c9-4c1a-a838-010ad1f717b2 on 10 January 2022.

--- Dataset description provided by original source is as follows ---

Provides details of the number and percentage of discharges that had a principal procedure recorded by patient type (day patient and in-patient) and admission type (elective/emergency/maternity). Activity in Acute Public Hospitals in Ireland Annual Report, 2016, is a report on in-patient and day patient discharges from acute public hospitals participating in the Hospital In-Patient Enquiry (HIPE) scheme in 2016. Discharge activity is examined by type of patient (day patient/in-patient), admission type (elective/emergency/maternity) and hospital group, and by demographic parameters (such as age and sex). Particular issues of relevance to the Irish health care system covered in the report relate to the composition of discharges by medical card and public/private status. Discharges are also analysed by diagnoses, procedures, major diagnostic categories, and diagnosis related groups. The analysis is presented at the national level. In 2016 HIPE discharges were coded using ICD-10-AM/ACHI/ACS 8th Edition and grouped into AR-DRG Version 8.0. See the complete Activity in Acute Public Hospitals in Ireland Annual Report 2016 at http://www.hpo.ie/latest_hipe_nprs_reports/HIPE_2016/HIPE_Report_2016.pdf

--- Original source retains full ownership of the source dataset ---

This is the proportion of older people aged 65 and over discharged from hospital to their own home or to a residential or nursing care home or extra care housing for rehabilitation, with a clear intention that they will move on/back to their own home (including a place in extra care housing or an adult placement scheme setting), who are at home or in extra care housing or an adult placement scheme setting 91 days after the date of their discharge from hospital.Those who are in hospital or in a registered care home (other than for a brief episode of respite care from which they are expected to return home) at the three month date and those who have died within the three months are not reported in the numerator. Only covers people receiving partly or wholly supported care from their Local Authority and not wholly private, self-funded care.Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Percentage of emergency admissions to any hospital in England occurring within 30 days of the last, previous discharge from hospital with specific diagnosis: indirectly standardised by age, sex, method of admission and diagnosis group. The following diagnoses are used: ● Fractured proximal femur (based on ICD-10 codes: S72.0, S72.1 and S72.2) for all ages broken down by gender: male only, female only and persons ● Stroke (based on ICD-10 codes: I61* to I64*) for all ages broken down by gender: male only, female only and persons. Results for each of these groups are also split by the following geographical and demographic breakdowns: ● Local authority of residence. ● Region. ● Area classification. ● NHS and private providers. ● NHS England regions. ● Deprivation (Index of Multiple Deprivation (IMD) Quintiles, 2019). ● Sustainability and Transformation Partnerships (STP) & Integrated Care Boards (ICB) from 2016/17. ● Clinical Commissioning Groups (CCG) & sub-Integrated Care Boards (sub-ICB). All datasets are annual trends indirectly standardised against 2013/14.