Provides basic information for general acute care hospital buildings such as height, number of stories, the building code used to design the building, and the year it was completed. The data is sorted by counties and cities. Structural Performance Categories (SPC ratings) are also provided. SPC ratings range from 1 to 5 with SPC 1 assigned to buildings that may be at risk of collapse during a strong earthquake and SPC 5 assigned to buildings reasonably capable of providing services to the public following a strong earthquake. Where SPC ratings have not been confirmed by the Department of Health Care Access and Information (HCAI) yet, the rating index is followed by 's'. A URL for the building webpage in HCAI/OSHPD eServices Portal is also provided to view projects related to any building.

MyHospitals provides performance information for public and private hospitals in Australia. You can also compare the performance of these hospitals and find information about hospitals near you.

The annual average number of beds available to be used by an admitted patient was grouped into the following categories: fewer than 50, 50-100, 100-200, 200-500 and more than 500. These data are as reported by states and territories to the NPHED, and are referred to in statistical publications (including Australian hospital statistics) as 'average available beds'. The average number of available beds presented may differ from counts published elsewhere. For example, counts based on bed numbers at a specified date such as 30 June may differ from the average available beds over the reporting period. Comparability of bed numbers can be affected by the range and types of patients treated by a hospital. For example, hospitals may have different proportions of beds available for general versus special purposes (such as beds or cots used exclusively for intensive care). Bed counts also include chairs for same-day admissions.

Data is current as of December 2015. Data sourced from: http://www.myhospitals.gov.au/about-the-data/download-data

On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement.

Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information.

There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

This indicator compares the odds of mortality within 30 days of admission for patients admitted at the weekend (Saturday and Sunday) to the odds of mortality within 30 days of admission for patients admitted midweek (Tuesday, Wednesday and Thursday). Corresponding results comparing patients admitted during the transition period (Monday and Friday) to patients admitted midweek are also provided as contextual information, along with results including only emergency admissions. The results are presented as odds ratios. The methodology used in the analysis presented here was developed by University Hospitals Birmingham NHS Foundation Trust. It is based on the methodology presented in Freemantle et al. (Freemantle N, Ray D, Mcnulty D, et al. Increased mortality associated with weekend hospital admission: a case for expanded seven day services? BMJ 2015; 351: h4596) with some modifications to facilitate the measurement of variation in mortality outcomes for patients admitted at the weekend compared to those admitted during the week at the level of individual hospital trusts. From April 2020, the Department of Health and Social Care (DHSC) is no longer commissioning NHS Digital to produce these indicators. Therefore, no further publications in this series are planned. Notes: 1. There is a shortfall in the number of records for Tameside and Glossop Integrated Care NHS Foundation Trust (trust code RMP) and University College London Hospitals NHS Foundation Trust (trust code RRV) meaning that results for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. From this publication onwards, the adjustment for deprivation uses the 2019 version of the Index of Multiple Deprivation (IMD). Previous releases of this indicator used the 2015 version. Further information is available in the statement of methodological changes (see Resources). 3. The following mergers took place on 1st October 2019: Cumbria Partnership NHS Foundation Trust (trust code RNN) merged with North Cumbria University Hospitals NHS Trust (trust code RNL). The new trust is called North Cumbria Integrated Care NHS Foundation Trust (trust code RNN). Aintree University Hospital NHS Foundation Trust (trust code REM) merged with Royal Liverpool and Broadgreen University Hospitals NHS Trust (trust code RQ6). The new trust is called Liverpool University Hospitals NHS Foundation Trust (trust code REM). However, as we received notification of these changes after data processing for this publication began, separate indicator values have been produced for this publication. The next publication in this series will reflect the updated organisation structures. 4. Further information on data quality can be found in the Seven-day Services background quality report, which can be downloaded from the ‘Resources’ section of the publication page. Further guidance on the interpretation of the indicators is also available to download from that page. 5. This tool is in Microsoft Power BI which does not fully support all accessibility needs. If you need further assistance, please contact us for help.

California Health and Safety Code section 1288.55(a)(1) requires general acute care hospitals to report all cases of methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI) identified in their facilities to the California Department of Public Health (CDPH). MRSA BSI data are submitted by hospitals to the Centers for Disease Control and Prevention National Healthcare Safety Network (NHSN). CDPH downloads California hospital MRSA BSI data from NHSN and analyzes the data to describe prevention progress in an annual public report of healthcare-associated infections. CDPH publishes annual MRSA BSI data reported by each California hospital in the datasets below. The following datasets include the number of MRSA BSI reported by each California hospital in the specified reporting year. Beginning in 2016 for each California hospital, the annual MRSA BSI dataset includes the number of MRSA BSI that were predicted to occur in each hospital based on its specific facility-level characteristics. The observed (reported) number of MRSA BSI are then compared to the predicted number of MRSA BSI in a ratio called the Standardized Infection Ratio or SIR. The SIR is a metric that summarizes an individual hospital’s MRSA BSI prevention progress compared with the national baseline and California state-specific prevention goals. The datasets also include the associated 95% confidence intervals for the SIR and statistical interpretation to show whether MRSA BSI incidence was the same (no different), better (lower) or worse (higher) than the national baseline. Another performance measure in this dataset allows for tracking hospital progress in meeting national HAI reduction goals. Hospitals must have an SIR at or below incremental targets each year to be considered on track. Detailed information about the variables included in each dataset are described in the accompanying data dictionaries for the year of interest. For more information about the SIR and NHSN’s statistical models that are used to calculate the predicted number of MRSA BSI for each hospital, please review “NHSN’s Guide to the SIR”: https://www.cdc.gov/nhsn/ps-analysis-resources/index.html For general information about NHSN, surveillance definitions, and reporting requirements for MRSA BSI, please visit: https://www.cdc.gov/nhsn/index.html To link the CDPH facility IDs with those from other Departments, including HCAI, please reference the "Licensed Facility Cross-Walk" Open Data table at: https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk. For information about healthcare-associated infection prevention progress in California hospitals and statewide prevention goals, please visit: https://www.cdph.ca.gov/Programs/CHCQ/HAI/Pages/AnnualHAIReports.aspx

California Health and Safety Code section 1288.55(a)(1) requires general acute care hospitals to report all cases of Clostridioides difficile infections (CDI) identified in their facilities to the California Department of Public Health (CDPH). CDI data are submitted by hospitals to the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN). CDPH downloads California hospital CDI data from NHSN and analyzes the data to describe prevention progress in an annual public report of healthcare-associated infections CDPH publishes annual CDI data reported by each California hospital in the datasets below. The following datasets include the number of CDI reported by each California hospital in the specified reporting year. Beginning in 2016 for each California hospital, the annual CDI dataset includes the number of CDI that were predicted to occur in each hospital based on its specific facility-level characteristics. The observed (reported) number of CDI are then compared to the predicted number of CDI in a ratio called the Standardized Infection Ratio or SIR. The SIR is a metric that summarizes an individual hospital’s CDI prevention progress compared with the national baseline and California state-specific prevention goals. Detailed information about the variables included in each dataset are described in the accompanying data dictionaries for the year of interest. For more information about the SIR and NHSN’s statistical models that are used to calculate the predicted number of CDI for each hospital, please review “NHSN’s Guide to the SIR”: https://www.cdc.gov/nhsn/ps-analysis-resources/index.html For general information about NHSN, surveillance definitions, and reporting requirements for CDI, please visit: https://www.cdc.gov/nhsn/index.html To link the CDPH facility IDs with those from other Departments, including HCAI, please reference the "Licensed Facility Cross-Walk" Open Data table at: https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk. For information about healthcare-associated infection prevention progress in California hospitals and statewide prevention goals, please visit: https://www.cdph.ca.gov/Programs/CHCQ/HAI/Pages/AnnualHAIReports.aspx

This dataset contains the location of hospitals that performed Coronary Artery Bypass Graft (CABG) surgery in California from 2011 to 2022. It also provides performance ratings for the following risk-adjusted outcome measures related to the CABG surgery: operative mortality for isolated CABG and CABG plus valve, post-operative stroke, and 30-day all cause readmission. The dataset also includes the number of cases and adverse events for each CABG outcome measure. The methodology, including risk models that generated the rates and performance ratings differed among years. Users should exercise caution when comparing trends of rates over time (see metadata for more information).

California Health and Safety Code section 1288.55(a)(1) requires general acute care hospitals to report all cases of methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI) identified in their facilities to the California Department of Public Health (CDPH). MRSA BSI data are submitted by hospitals to the Centers for Disease Control and Prevention National Healthcare Safety Network (NHSN).

CDPH downloads California hospital MRSA BSI data from NHSN and analyzes the data to describe prevention progress in an annual public report of healthcare-associated infections. CDPH publishes annual MRSA BSI data reported by each California hospital in the datasets below.

The following datasets include the number of MRSA BSI reported by each California hospital in the specified reporting year. Beginning in 2016 for each California hospital, the annual MRSA BSI dataset includes the number of MRSA BSI that were predicted to occur in each hospital based on its specific facility-level characteristics. The observed (reported) number of MRSA BSI are then compared to the predicted number of MRSA BSI in a ratio called the Standardized Infection Ratio or SIR. The SIR is a metric that summarizes an individual hospital’s MRSA BSI prevention progress compared with the national baseline and California state-specific prevention goals.

The datasets also include the associated 95% confidence intervals for the SIR and statistical interpretation to show whether MRSA BSI incidence was the same (no different), better (lower) or worse (higher) than the national baseline. Another performance measure in this dataset allows for tracking hospital progress in meeting national HAI reduction goals. Hospitals must have an SIR at or below incremental targets each year to be considered on track.

Detailed information about the variables included in each dataset are described in the accompanying data dictionaries for the year of interest.

For more information about the SIR and NHSN’s statistical models that are used to calculate the predicted number of MRSA BSI for each hospital, please review “NHSN’s Guide to the SIR”: https://www.cdc.gov/nhsn/ps-analysis-resources/index.html

For general information about NHSN, surveillance definitions, and reporting requirements for MRSA BSI, please visit: https://www.cdc.gov/nhsn/index.html

To link the CDPH facility IDs with those from other Departments, including HCAI, please reference the "Licensed Facility Cross-Walk" Open Data table at: https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk.

For information about healthcare-associated infection prevention progress in California hospitals and statewide prevention goals, please visit: https://www.cdph.ca.gov/Programs/CHCQ/HAI/Pages/AnnualHAIReports.aspx

This dataset contains counts and rates (per 10,000 residents) of asthma hospitalizations among Californians statewide and by county. The data are stratified by age group (all ages, 0-17, 18+, 0-4, 5-17, 18-64, 65+) and race/ethnicity (white, black, Hispanic, Asian/Pacific Islander, American Indian/Alaskan Native). The data are derived from the Department of Health Care Access and Information Patient Discharge Data. These data include hospitalizations from all licensed hospitals in California. These data are based only on primary discharge diagnosis codes. On October 1, 2015, diagnostic coding for asthma transitioned from ICD-9-CM (493) to ICD-10-CM (J45). Because of this change, CDPH and CDC do not recommend comparing data from 2015 (or earlier) to 2016 (or later). NOTE: Rates are calculated from the total number of asthma hospitalizations (not the unique number of individuals).