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TwitterNumber and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.
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TwitterThe dataset contains risk-adjusted mortality rates, quality ratings, and number of deaths and cases for 6 medical conditions treated (Acute Stroke, Acute Myocardial Infarction, Heart Failure, Gastrointestinal Hemorrhage, Hip Fracture and Pneumonia) and 3 procedures performed (Carotid Endarterectomy, Pancreatic Resection, and Percutaneous Coronary Intervention) in California hospitals. The 2023 IMIs were generated using AHRQ Version 2024, while previous years' IMIs were generated with older versions of AHRQ software (2022 IMIs by Version 2023, 2021 IMIs by Version 2022, 2020 IMIs by Version 2021, 2019 IMIs by Version 2020, 2016-2018 IMIs by Version 2019, 2014 and 2015 IMIs by Version 5.0, and 2012 and 2013 IMIs by Version 4.5). The differences in the statistical method employed and inclusion and exclusion criteria using different versions can lead to different results. Users should not compare trends of mortality rates over time. However, many hospitals showed consistent performance over years; “better” performing hospitals may perform better and “worse” performing hospitals may perform worse consistently across years. This dataset does not include conditions treated or procedures performed in outpatient settings. Please refer to statewide table for California overall rates: https://data.chhs.ca.gov/dataset/california-hospital-inpatient-mortality-rates-and-quality-ratings/resource/af88090e-b6f5-4f65-a7ea-d613e6569d96
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This publication of the SHMI relates to discharges in the reporting period March 2023 - February 2024. The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there. The SHMI covers patients admitted to hospitals in England who died either while in hospital or within 30 days of being discharged. To help users of the data understand the SHMI, trusts have been categorised into bandings indicating whether a trust's SHMI is 'higher than expected', 'as expected' or 'lower than expected'. For any given number of expected deaths, a range of observed deaths is considered to be 'as expected'. If the observed number of deaths falls outside of this range, the trust in question is considered to have a higher or lower SHMI than expected. The expected number of deaths is a statistical construct and is not a count of patients. The difference between the number of observed deaths and the number of expected deaths cannot be interpreted as the number of avoidable deaths or excess deaths for the trust. The SHMI is not a measure of quality of care. A higher than expected number of deaths should not immediately be interpreted as indicating poor performance and instead should be viewed as a 'smoke alarm' which requires further investigation. Similarly, an 'as expected' or 'lower than expected' SHMI should not immediately be interpreted as indicating satisfactory or good performance. Trusts may be located at multiple sites and may be responsible for 1 or more hospitals. A breakdown of the data by site of treatment is also provided, as well as a breakdown of the data by diagnosis group. Further background information and supporting documents, including information on how to interpret the SHMI, are available on the SHMI homepage (see Related Links).
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This dataset contains the number of cases, number of in hospital/30 day deaths, observed, expected and risk- adjusted mortality rates for cardiac surgery and percutaneous coronary interventions (PCI) by hospital. Regions represent where the hospitals are located. The initial Health Data NY dataset includes patients discharged between January 1, 2008, and December 31, 2010. Analyses of risk-adjusted mortality rates and associated risk factors are provided for 2010 and for the three-year period from 2008 through 2010. For PCI, analyses of all cases, non-emergency cases (which represent the majority of procedures) and emergency cases are included. Subsequent year reports data will be appended to this dataset. For more information check out: http://www.health.ny.gov/health_care/consumer_information/cardiac_surgery/ or go to the “About” tab.
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TwitterIn the United States from 2022 to 2024, the 30-day mortality rate in hospital at home programs for patients with respiratory infections and inflammations with MCC was around ** deaths per 1,000. In comparison, the mortality rate in comparable hospitals for the same diagnosis related groups was almost *** deaths per 1,000.
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TwitterComplications and deaths - provider data. This data set includes provider-level data for the hip/knee complication measure, the CMS Patient Safety Indicators, and 30-day death rates. NOTICE: Data from the 1st and 2nd quarters of 2020 are not being reported due to the impact of the COVID-19 pandemic. For more information, please reference https://qualitynet.cms.gov/files/5fb838aef61c410025a64709?filename=2020-111-IP.pdf.
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TwitterThese mortality indicators provide information to help the National Health Service (NHS) monitor success in preventing potentially avoidable deaths following hospital treatment.
The National Confidential Enquiry into Patient Outcome and Death (NCEPOD) have, over many years, consistently shown that some deaths are associated with shortcomings in health care. The NHS may be helped to prevent such potentially avoidable deaths by seeing comparative figures and learning lessons from the confidential enquiries, and from the experience of hospitals with low death rates.
The indicators presented measure mortality rates for patients, admitted for certain conditions or procedures, where death occurred either in hospital or within 30 days post discharge.
There are five ‘deaths within 30 days’ indicators:
Operative procedures:
Emergency admissions :
Data are presented for the 10-year period 2005/06 to 2014/15 , and in separate breakdowns for females, males and persons. The indicators are presented at the local government geographies and by individual institution.
These indicators were previously published in the Compendium of Clinical and Health Indicators and are now published on the Health and Social Care Information Centre’s (HSCIC) Indicator Portal as part of the continuing release of this indicator set.
Data, along with indicator specifications providing details of indicator construction, statistical methods and interpretation considerations, can be accessed by visiting the HSCIC’s Indicator Portal and using the menu to navigate to Compendium of population health indicators > Hospital care > Outcomes > Deaths.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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These mortality indicators provide information to help the National Health Service (NHS) monitor success in preventing potentially avoidable deaths following hospital treatment. The National Confidential Enquiry into Patient Outcome and Death (NCEPOD) have, over many years, consistently shown that some deaths are associated with shortcomings in health care. The NHS may be helped to prevent such potentially avoidable deaths by seeing comparative figures and learning lessons from the confidential enquiries, and from the experience of hospitals with low death rates. The indicators presented measure mortality rates for patients, admitted for certain conditions or procedures, where death occurred either in hospital or within 30 days of the emergency admission or operative procedure. There are five 'deaths within 30 days' indicators: Operative procedures: Deaths within 30 days of a hospital procedure: surgery (non-elective admissions) Deaths within 30 days of a hospital procedure: coronary artery bypass graft Emergency admissions: Deaths within 30 days of emergency admission to hospital: fractured proximal femur Deaths within 30 days of emergency admission to hospital: myocardial infarction Deaths within 30 days of emergency admission to hospital: stroke
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TwitterThis statistic shows the improvement in mortality rates 2007-2009 amongst all hospitals in the United States, sorted by mortality rates for inhospital care as well as ** and *** days following hospitalization. In addition to presenting information on improvement in the United States overall, this graph includes further data on hospitals of differing quality ratings. In the United States overall, mortality rates improved by *** percent, but in five-star hospitals, mortality rates improved by **** percent.
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TwitterProvisional count of deaths involving coronavirus disease 2019 (COVID-19) in the United States by week of death and by hospital referral region (HRR). HRR is determined by county of occurrence. Weekly weighted counts of deaths from all causes and due to COVID-19 are provided by HRR overall and for decedents 65 years and older. The weighted counts by HRRs are based on published methods for aggregating county-level data to HRRs. More detail about aggregating to HRRs from counties can be found in the following: https://github.com/Dartmouth-DAC/covid-19-hrr-mapping https://dartmouthatlas.org/covid-19/hrr-mapping/
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TwitterThe dataset contains risk-adjusted mortality rates, and number of deaths and cases for 6 medical conditions treated (Acute Stroke, Acute Myocardial Infarction, Heart Failure, Gastrointestinal Hemorrhage, Hip Fracture and Pneumonia) and 6 procedures performed (Abdominal Aortic Aneurysm Repair, Carotid Endarterectomy, Craniotomy, Esophageal Resection, Pancreatic Resection, Percutaneous Coronary Intervention) in California hospitals. The 2014 and 2015 IMIs were generated using AHRQ Version 5.0, while the 2012 and 2013 IMIs were generated using AHRQ Version 4.5. The differences in the statistical method employed and inclusion and exclusion criteria using different versions can lead to different results. Users should not compare trends of mortality rates over time. However, many hospitals showed consistent performance over years; “better” performing hospitals may perform better and “worse” performing hospitals may perform worse consistently across years. This dataset does not include conditions treated or procedures performed in outpatient settings. Please refer to hospital table for hospital rates: https://data.chhs.ca.gov/dataset/california-hospital-inpatient-mortality-rates-and-quality-ratings
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TwitterThis statistic depicts the 30-day mortality rate for patients with select conditions in U.S. hospitals who were discharged, between 2010 and 2016. Among heart attack, stroke, heart failure and pneumonia patients, the 30-day mortality rate for discharged patients averaged **** percent between 2013 and 2016.
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TwitterComplications and deaths - state data. This data set includes state-level data for the hip/knee complication measure, the CMS Patient Safety Indicators, and 30-day death rates.
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TwitterComplications and deaths - provider data. This data set includes provider data for the hip/knee complication measure, the Agency for Healthcare Research and Quality (AHRQ) measures of serious complications, and 30-day death rates.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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BackgroundAlthough sepsis is the leading cause of death from infection, there are few population-level epidemiological sepsis reports. The impact of sepsis-related deaths on all-cause hospital mortality is insufficiently described, in particular in Europe where data are non-existent. The objective of this study was to provide nationwide epidemiological results on sepsis hospitalizations in Norway and to estimate sepsis’ contribution to overall hospital mortality in a European setting.MethodsWe performed a retrospective study using data from the Norwegian Patient Registry and Statistics Norway. The occurrence, patient characteristics and outcomes of sepsis hospitalizations during the years 2011 and 2012 were estimated and compared with Norwegian population data. Sepsis was defined as organ dysfunction caused by a dysregulated host response to infection and identified with International Classification of Diseases 10th revision codes.ResultsWe identified 18 460 sepsis admissions occurring in 13 582 individuals. The annual population incidence of hospitalized sepsis was 140 patients per 100 000 inhabitants; ranging from 10 to 2270 per 100 000 in different age groups and with statistically significant male predominance in all adult cohorts. Hospital mortality for sepsis admissions was 19.4% and overall, 26.4% of the included patients died while hospitalized for sepsis. Sepsis related deaths constituted 12.9% of all hospital fatalities, while hospitalizations with sepsis accounted for 1.0% of the total number of admissions and 3.5% of the total admission days during 2011 and 2012.ConclusionsThis study confirms that hospitalized sepsis is frequent in Norway and a major contributor to hospital fatalities in a European setting. The incidence is higher among men than women. Sepsis is in particular a disease of the elderly, and its impact on health-care will assumingly continue to increase in parallel with an aging population. Improvements in treatment and survival of sepsis could influence population mortality, and sepsis should receive greater attention in official death statistics in the future.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This table presents a wide variety of historical data in the field of health, lifestyle and health care. Figures on births and mortality, causes of death and the occurrence of certain infectious diseases are available from 1900, other series from later dates. In addition to self-perceived health, the table contains figures on infectious diseases, hospitalisations per diagnosis, life expectancy, lifestyle factors such as smoking, alcohol consumption and obesity, and causes of death. The table also gives information on several aspects of health care, such as the number of practising professionals, the number of available hospital beds, nursing day averages and the expenditures on care. Many subjects are also covered in more detail by data in other tables, although sometimes with a shorter history. Data on notifiable infectious diseases and HIV/AIDS are not included in other tables.
Data available from: 1900
Status of the figures:
2025: The available figures are definite.
2024: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, hiv, aids; - causes of death.
2023: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, HIV/AIDS; - diagnoses at hospital admissions; - number of hospital discharges and length of stay; - number of hospital beds; - health professions; - perinatal and infant mortality. Figures are revised provisional for: - expenditures on health and welfare.
2022: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, HIV/AIDS; - diagnoses at hospital admissions; - number of hospital discharges and length of stay; - number of hospital beds; - health professions. Figures are revised provisional for: - expenditures on health and welfare.
2021: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, HIV/AIDS; Figures are revised provisional for: - expenditures on health and welfare.
2020 and earlier: Most available figures are definite. Due to 'dynamic' registrations, figures for notifiable infectious diseases, HIV/AIDS remain provisional.
Changes as of 4 July 2025: The most recent available figures have been added for: - population on January 1; - live born children, deaths; - persons in (very) good health; - notifiable infectious diseases, HIV/AIDS; - diagnoses at hospital admissions; - use of medication; - sickness absence; - lifestyle; - use of health care services; - number of hospital discharges and length of stay; - number of hospital beds; - health professions; - expenditures on health and welfare; - healthy life expectancy; - causes of death.
Changes as of 18 december 2024: - Due to a revision of the statistics Health and welfare expenditure 2021, figures for expenditure on health and welfare have been replaced from 2021 onwards. - Revised figures on the volume index of healthcare costs are not yet available, these figures have been deleted from 2021 onwards.
When will new figures be published? December 2025.
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TwitterThe Summary Hospital-level Mortality Indicator (SHMI) reports on mortality at trust level across the NHS in England using a standard and transparent methodology. It is produced and published monthly as a National Statistic by NHS Digital.
The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there.
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TwitterNumber and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.