This dataset is not being updated as hospitals are no longer mandated to report COVID Hospitalizations to CDPH.

Data is from the California COVID-19 State Dashboard at https://covid19.ca.gov/state-dashboard/

Note: Hospitalization counts include all patients diagnosed with COVID-19 during their stay. This does not necessarily mean they were hospitalized because of COVID-19 complications or that they experienced COVID-19 symptoms.

Note: Cumulative totals are not available due to the fact that hospitals report the total number of patients each day (as opposed to new patients).

The dataset contains hospitalization counts and rates, statewide and by county, for 10 ambulatory care sensitive conditions plus 4 composite measures. Hospitalizations due to these medical conditions are potentially preventable through access to high-quality outpatient care. The conditions include: diabetes short-term complications; diabetes long-term complications; chronic obstructive pulmonary disease (COPD) or asthma in older adults (age 40 and over); hypertension; heart failure; community-acquired pneumonia; urinary tract infection; uncontrolled diabetes; asthma in younger adults (age 18-39); and lower-extremity amputation among patients with diabetes. The composite measures include overall, acute conditions, chronic conditions, and diabetes (new, 2016). The data provides a good starting point for assessing quality of health services in the community. The data does not measure hospital quality. Note: In 2015, HCAI (formerly OSHPD) only released the first three quarters of data due to a change in the reporting of diagnoses from ICD-9-CM to ICD-10-CM codes, effective October 1, 2015. Due to the significant differences resulting from the code change, the ICD-9-CM data is distinguished from the ICD-10-CM data in the data file beginning in 2016.

(See Note below regarding 2015 data). The dataset contains hospitalization counts and rates (age 18+), statewide and by county, for 7 potentially-preventable adverse events that occur during a hospital stay. They provide a perspective on complications and iatrogenic events and help assess total incidence within a region. The measures, based upon the Agency for Healthcare Research and Quality’s (AHRQ’s) Patient Safety Indicators (PSIs), include: retained surgical item or unretrieved device fragment, iatrogenic pneumothorax, central venous catheter-related blood stream infection, postoperative wound dehiscence, accidental puncture or laceration, transfusion reaction, and perioperative hemorrhage or hematoma. Note: HCAI is only releasing the first 3 quarters of 2015 data due to a change in the reporting of diagnoses/procedures from ICD-9-CM to ICD-10-CM/PCS effective October 1, 2015, and the inability of the AHRQ software to handle both code sets concurrently.

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).

Abstract

The State Ambulatory Surgery Databases (SASD), State Inpatient Databases (SID), and State Emergency Department Databases (SEDD) are part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP).

HCUP's state-specific databases can be used to investigate state-specific and multi-state trends in health care utilization, access, charges, quality, and outcomes. PHS has several years (2008-2011) and datasets (SASSD, SED and SIDD) for HCUP California available.

Usage

The State Ambulatory Surgery and Services Databases (SASD) are State-specific files that include data for ambulatory surgery and other outpatient services from hospital-owned facilities. In addition, some States provide ambulatory surgery and outpatient services from nonhospital-owned facilities. The uniform format of the SASD helps facilitate cross-State comparisons. The SASD are well suited for research that requires complete enumeration of hospital-based ambulatory surgeries within geographic areas or States.

The State Inpatient Databases (SID) are State-specific files that contain all inpatient care records in participating states. Together, the SID encompass more than 95 percent of all U.S. hospital discharges. The uniform format of the SID helps facilitate cross-state comparisons. In addition, the SID are well suited for research that requires complete enumeration of hospitals and discharges within geographic areas or states.

The State Emergency Department Databases (SEDD) are a set of longitudinal State-specific emergency department (ED) databases included in the HCUP family. The SEDD capture discharge information on all emergency department visits that do not result in an admission. Information on patients seen in the emergency room and then admitted to the hospital is included in the State Inpatient Databases (SID)

SASD, SID, and SEDD each have **Documentation **which includes:

• Description of the Database
• Restrictions on Use
• File Specifications and Load Program
• Data Elements
• Additional Resources for Data Elements
• ICD-10-CM/PCS Data Included in the Dataset Starting with 2015
• Known Data Issues
• HCUP Tools: Labels and Formats
• HCUP Supplemental Files
• Obtaining HCUP Data

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Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

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We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

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Documentation

The HCUP California inpatient files were constructed from the confidential files received from the Office of Statewide Health Planning and Development (OSHPD). OSHPD excluded inpatient stays that, after processing by OSHPD, did not contain a complete and “in-range” admission date or discharge date. California also excluded inpatient stays that had an unknown or missing date of birth. OSHPD removes ICD-9-CM and ICD-10-CM diagnoses codes for HIV test results. Beginning with 2009 data, OSHPD changed regulations to require hospitals to report all external cause of injury diagnosis codes including those specific to medical misadventures. Prior to 2009, OSHPD did not require collection of diagnosis codes identifying medical misadventures.

**Types of Facilities Included in the Files Provided to HCUP by the Partner **

California supplied discharge data for inpatient stays in general acute care hospitals, acute psychiatric hospitals, chemical dependency recovery hospitals, psychiatric health facilities, and state operated hospitals. A comparison of the number of hospitals included in the SID and the number of hospitals reported in the AHA Annual Survey is available starting in data year 2010. Hospitals do not always report data for a full calendar year. Some hospitals open or close during the year; other hospitals have technical problems that prevent them from reporting data for all months in a year.

**Inclusion of Stays in Special Units **

Included with the general acute care stays are stays in skilled nursing, intermediate care, rehabilitation, alcohol/chemical dependency treatment, and psychiatric units of hospitals in California. How the stays in these different types of units can be identified differs by data year. Beginning in 2006, the information is retained in the HCUP variable HOSPITALUNIT. Reliability of this indicator for the level of care depends on how it was assigned by the hospital. For data years 1998-2006, the information was retained in the HCUP variable LEVELCARE. Prior to 1998, the first

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Orange County, CA (DISCONTINUED) (DMPCRATE006059) from 2008 to 2015 about preventable; Orange County, CA; admissions; hospitals; Los Angeles; CA; 5-year; rate; and USA.

As of 9/12/2024, we will begin reporting on hospitalization data again using a new San Francisco specific dataset. Updated data can be accessed here.

On 5/1/2024, hospitalization data reporting will change from mandatory to optional for all hospitals nationwide. We will be pausing the refresh of the underlying data beginning 5/2/2024.

A. SUMMARY Count of COVID+ patients admitted to the hospital. Patients who are hospitalized and test positive for COVID-19 may be admitted to an acute care bed (a regular hospital bed), or an intensive care unit (ICU) bed. This data shows the daily total count of COVID+ patients in these two bed types, and the data reflects totals from all San Francisco Hospitals.

B. HOW THE DATASET IS CREATED Hospital information is based on admission data reported to the National Healthcare Safety Network (NHSN) and provided by the California Department of Public Health (CDPH).

C. UPDATE PROCESS Updates automatically every week.

D. HOW TO USE THIS DATASET Each record represents how many people were hospitalized on the date recorded in either an ICU bed or acute care bed (shown as Med/Surg under DPHCategory field).

The dataset shown here includes all San Francisco hospitals and updates weekly with data for the past Sunday-Saturday as information is collected and verified. Data may change as more current information becomes available.

E. CHANGE LOG

• 9/12/2024 -Hospitalization data are now being tracked through a new source and are available here.
• 5/1/2024 - hospitalization data reporting to the National Healthcare Safety Network (NHSN) changed from mandatory to optional for all hospitals nationwide. We will be pausing the refresh of the underlying data beginning 5/2/2024.
• 12/14/2023 – added column “hospitalreportingpct” to indicate the percentage of hospitals who submitted data on each report date.
• 8/7/2023 - In response to the end of the federal public health emergency on 5/11/2023 the California Hospital Association (CHA) stopped the collection and dissemination of COVID-19 hospitalization data. In alignment with the California Department of Public Health (CDPH), hospitalization data from 5/11/2023 onward are being pulled from the National Healthcare Safety Network (NHSN). The NHSN data is updated weekly and does not include information on COVID suspected (PUI) patients.
• 4/9/2021 - dataset updated daily with a four-day data lag.

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.

Data is from the California Department of Public Health (CDPH) Respiratory Virus Weekly Report. The report is updated each Friday. Laboratory surveillance data: California laboratories report SARS-CoV-2 test results to CDPH through electronic laboratory reporting. Los Angeles County SARS-CoV-2 lab data has a 7-day reporting lag. Test positivity is calculated using SARS-CoV-2 lab tests that has a specimen collection date reported during a given week. Laboratory surveillance for influenza, respiratory syncytial virus (RSV), and other respiratory viruses (parainfluenza types 1-4, human metapneumovirus, non-SARS-CoV-2 coronaviruses, adenovirus, enterovirus/rhinovirus) involves the use of data from clinical sentinel laboratories (hospital, academic or private) located throughout California. Specimens for testing are collected from patients in healthcare settings and do not reflect all testing for influenza, respiratory syncytial virus, and other respiratory viruses in California. These laboratories report the number of laboratory-confirmed influenza, respiratory syncytial virus, and other respiratory virus detections and isolations, and the total number of specimens tested by virus type on a weekly basis. Test positivity for a given week is calculated by dividing the number of positive COVID-19, influenza, RSV, or other respiratory virus results by the total number of specimens tested for that virus. Weekly laboratory surveillance data are defined as Sunday through Saturday. Hospitalization data: Data on COVID-19 and influenza hospital admissions are from Centers for Disease Control and Prevention’s (CDC) National Healthcare Safety Network (NHSN) Hospitalization dataset. The requirement to report COVID-19 and influenza-associated hospitalizations was effective November 1, 2024. CDPH pulls NHSN data from the CDC on the Wednesday prior to the publication of the report. Results may differ depending on which day data are pulled. Admission rates are calculated using population estimates from the P-3: Complete State and County Projections Dataset provided by the State of California Department of Finance (https://dof.ca.gov/forecasting/demographics/projections/). Reported weekly admission rates for the entire season use the population estimates for the year the season started. For more information on NHSN data including the protocol and data collection information, see the CDC NHSN webpage (https://www.cdc.gov/nhsn/index.html). CDPH collaborates with Northern California Kaiser Permanente (NCKP) to monitor trends in RSV admissions. The percentage of RSV admissions is calculated by dividing the number of RSV-related admissions by the total number of admissions during the same period. Admissions for pregnancy, labor and delivery, birth, and outpatient procedures are not included in total number of admissions. These admissions serve as a proxy for RSV activity and do not necessarily represent laboratory confirmed hospitalizations for RSV infections; NCKP members are not representative of all Californians. Weekly hospitalization data are defined as Sunday through Saturday. Death certificate data: CDPH receives weekly year-to-date dynamic data on deaths occurring in California from the CDPH Center for Health Statistics and Informatics. These data are limited to deaths occurring among California residents and are analyzed to identify influenza, respiratory syncytial virus, and COVID-19-coded deaths. These deaths are not necessarily laboratory-confirmed and are an underestimate of all influenza, respiratory syncytial virus, and COVID-19-associated deaths in California. Weekly death data are defined as Sunday through Saturday. Wastewater data: This dataset represents statewide weekly SARS-CoV-2 wastewater summary values. SARS-CoV-2 wastewater concentrations from all sites in California are combined into a single, statewide, unit-less summary value for each week, using a method for data transformation and aggregation developed by the CDC National Wastewater Surveillance System (NWSS). Please see the CDC NWSS data methods page for a description of how these summary values are calculated. Weekly wastewater data are defined as Sunday through Saturday.

Context

I will be using this dataset to attempt to propose solutions to iatrogenics in California Healthcare systems at Stanford's Health++ competition.

Content

The dataset contains hospitalization counts and rates (age 18+), statewide and by county, for 7 potentially-preventable adverse events that occur during a hospital stay. They provide a perspective on complications and iatrogenic events and help assess total incidence within a region. The measures, based upon the Agency for Healthcare Research and Quality’s (AHRQ’s) Patient Safety Indicators (PSIs), include: retained surgical item or unretrieved device fragment, iatrogenic pneumothorax, central venous catheter-related blood stream infection, postoperative wound dehiscence, accidental puncture or laceration, transfusion reaction, and perioperative hemorrhage or hematoma.

Acknowledgements

Office of Statewide Health Planning & Development

California's Office of Statewide Health Planning and Development (OSHPD) is the leader in collecting data and disseminating information about California's healthcare infrastructure. OSHPD promotes an equitably distributed healthcare workforce, and publishes valuable information about healthcare outcomes. OSHPD also monitors the construction, renovation, and seismic safety of hospitals and skilled nursing facilities and provides loan insurance to assist the capital needs of California's not-for-profit healthcare facilities. Data: https://data.chhs.ca.gov/organization/office-of-statewide-health-planning-development

Inspiration

I want to spread this dataset collected by the OSHPD to strive for prevention of many issues of iatrogenics.

This dataset details the percentage of COVID-19 positive patients in hospitals and ICUs for COVID-19 related reasons, and for reasons other than COVID-19.

Data includes:

• reporting date
• percentage of COVID-19 positive patients in hospital admitted for COVID-19
• percentage of COVID-19 positive patients in hospital admitted for other reasons
• percentage of COVID-19 positive patients in ICU admitted for COVID-19
• percentage of COVID-19 positive patients in ICU admitted for other reasons

**Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool **

Due to incomplete weekend and holiday reporting, data for hospital and ICU admissions are not updated on Sundays, Mondays and the day after holidays.

This dataset is subject to change.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Los Angeles County, CA (DISCONTINUED) (DMPCRATE006037) from 2008 to 2015 about preventable; admissions; Los Angeles County, CA; hospitals; Los Angeles; CA; 5-year; rate; and USA.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Alameda County, CA (DISCONTINUED) (DMPCRATE006001) from 2008 to 2015 about Alameda County, CA; preventable; admissions; hospitals; San Francisco; CA; 5-year; rate; and USA.

The datasets include severe sepsis information on 1) the number of severe sepsis cases, percent of hospital-acquired and non-hospital-acquired severe sepsis cases, and the percent of in-hospital severe sepsis deaths; 2) the average length of stay for severe sepsis hospitalizations, the respective median charge per day, and the expected payer for severe sepsis hospitalizations; 3) the severe sepsis patients who were alive at discharge and died within 30 days of discharge; and 4) the hospital-acquired severe sepsis in different type of hospitals (hospital size, location, teaching, and ownership). ICD-9-CM codes were used for data before October 1, 2015, and ICD-10-CM codes were used for data on or after October 1, 2015.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Sutter County, CA (DISCONTINUED) (DMPCRATE006101) from 2008 to 2015 about Sutter County, CA; Yuba City; preventable; admissions; hospitals; CA; 5-year; rate; and USA.

Nonbirth hospitalizations by medical condition.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Marin County, CA (DISCONTINUED) (DMPCRATE006041) from 2008 to 2015 about Marin County, CA; preventable; admissions; hospitals; San Francisco; CA; 5-year; rate; and USA.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Del Norte County, CA (DISCONTINUED) (DMPCRATE006015) from 2008 to 2015 about Del Norte County, CA; preventable; admissions; hospitals; CA; 5-year; rate; and USA.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Stanislaus County, CA (DISCONTINUED) (DMPCRATE006099) from 2008 to 2015 about Stanislaus County, CA; Modesto; preventable; admissions; hospitals; CA; 5-year; rate; and USA.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in San Francisco County, CA (DISCONTINUED) (DMPCRATE006075) from 2008 to 2015 about preventable; San Francisco County/City, CA; admissions; hospitals; San Francisco; CA; 5-year; rate; and USA.