AndreaBozzo/ceres-open-data-index huggingface dataset:
Infant Mortality, Deaths Per 1,000 Live Births (LGHC Indicator)

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/.
Infant Mortality is defined as the number of deaths in infants under one year of age per 1,000 live births. Infant mortality is often used as an indicator to measure the health and well-being of a community, because factors affecting the health of entire populations can also impact the mortality rate of infants. Although California’s infant mortality rate is better than the national average, there are significant disparities, with African American babies dying at more than twice the rate of other groups.
Data are from the Birth Cohort Files. The infant mortality indicator computed from the birth cohort file comprises birth certificate information on all births that occur in a calendar year (denominator) plus death certificate information linked to the birth certificate for those infants who were born in that year but subsequently died within 12 months of birth (numerator). Studies of infant mortality that are based on information from death certificates alone have been found to underestimate infant death rates for infants of all race/ethnic groups and especially for certain race/ethnic groups, due to problems such as confusion about event registration requirements, incomplete data, and transfers of newborns from one facility to another for medical care. 
Note there is a separate data table "Infant Mortality by Race/Ethnicity" which is based on death records only, which is more timely but less accurate than the Birth Cohort File.
Single year shown to provide state-level data and county totals for the most recent year. Numerator: Infants deaths (under age 1 year). Denominator: Live births occurring to California state residents. Multiple years aggregated to allow for stratification at the county level.
For this indicator, race/ethnicity is based on the birth certificate information, which records the race/ethnicity of the mother. The mother can “decline to state”; this is considered to be a valid response. These responses are not displayed on the indicator visualization.
Infectious Diseases by Disease, County, Year, and Sex

These data contain case counts and rates for selected communicable diseases—listed in the data dictionary—that met the surveillance case definition for that disease and was reported for California residents, by disease, county, year, and sex. The data represent cases with an estimated illness onset date from 2001 through the last year indicated from California Confidential Morbidity Reports and/or Laboratory Reports. Data captured represent reportable case counts as of the date indicated in the “Temporal Coverage” section below, so the data presented may differ from previous publications due to delays inherent to case reporting, laboratory reporting, and epidemiologic investigation.
Influenza Surveillance

This dataset contains the following files for California influenza surveillance data: 1) Outpatient Influenza-like Illness Surveillance Data by Region and Influenza Season from volunteer sentinel providers; 2) Clinical Sentinel Laboratory Influenza and Other Respiratory Virus Surveillance Data by Region and Influenza Season from volunteer sentinel laboratories; and 3) Public Health Laboratory Influenza Respiratory Virus Surveillance Data by Region and Influenza Season from California public health laboratories.
The Immunization Branch at the California Department of Public Health (CDPH) collects, compiles and analyzes information on influenza activity year-round in California and produces a weekly influenza surveillance report during October through May. The California influenza surveillance system is a collaborative effort between CDPH and its many partners at local health departments, public health and clinical laboratories, vital statistics offices, healthcare providers, clinics, emergency departments, and the Centers for Disease Control and Prevention (CDC). California data are also included in the CDC weekly influenza surveillance report, FluView, and help contribute to the national picture of Influenza activity in the United States. The information collected allows CDPH and CDC to: 1) find out when and where influenza activity is occurring; 2) track influenza-related illness; 3) determine what influenza viruses are circulating; 4) detect changes in influenza viruses; and 5) measure the impact influenza is having on hospitalizations and deaths.
Languages Spoken by Patients and Hospital-Based Providers in California

The dataset contains percentages of languages spoken for patient encounters in an inpatient setting, the emergency room, and hospital-based ambulatory surgery centers as well as languages spoken by the hospital-based workforce. There are also patient encounter-to-provider license ratios for each language by county. The patient encounter to provider license ratio can serve as an indicator for patient demand or need for services from a provider in a specific language. Smaller ratios indicate fewer patient encounters per provider license and less demand. Larger ratios of patient encounters per provider license indicate greater need for services in that language. This analysis features 45 languages that overlap between the patient-level data and health workforce data. These languages are grouped into the following language groups: African Languages, Asian and Pacific Islander Languages, European Languages, Middle Eastern Languages, Navajo Language, Spanish Language, and Sign Languages.
California Independent Living and Traumatic Brain Injury Center Locations

This dataset include individual locations of the Independent Living Section of the Department of Rehabilitation (DOR).  Independent Living Centers (ILC) and Traumatic Brain Injury (TBI) locations are dedicated to the ideal that communities become fully accessible and integrated so that all persons with disabilities can live, work, shop, and play where they choose, without barriers.  This data is public information and also shared on the DOR website.
Licensed Bed Classification and Designations Trends

This dataset contains information by licensed facility including number of patient days, hospital discharges, licensed bed days, and intra-hospital transfer from critical care by the six licensed bed classifications, including General Acute Care, Chemical Dependency Recovery, Acute Psychiatric, Skilled Nursing, Intermediate Care, and Intermediate Care/Developmentally Disabled.  The General Acute Care classification is further defined by bed designation categories that include Medical/Surgical (includes GYN/DOU), Perinatal (includes LDRP, excludes nursery), Pediatric Acute, Intensive Care, Coronary Care, Acute Respiratory Care, Burn Center, Intensive Care Newborn Nursery, and Rehabilitation Center bed designations.  2015 data are preliminary, are as reported and have not been audited.  See the Healthcare Facility Bed Types and Counts dataset for complimentary information at: https://chhs.data.ca.gov/Facilities-and-Services/Healthcare-Facility-Bed-Types-And-Counts/f9pb-6m2b
Hospital Characteristics List for California Providers

The dataset provides a list of 15 characteristics for California hospitals for State Fiscal Year 2019-20, including; Department of Health Care Access and Information (HCAI) ID, HCAI Provider Name, Designated Neonatal Intensive Care Unit status as defined by DHCS, Designated Public Hospital status, Non-designated Public Hospital, HCAI Rural Hospital status, DHCS Designated Remote Rural status, Cost–to-Charge Ratio, Wage Index Value, Wage Index Value-Adjusted for California Neutrality Factor, Unadjusted Statewide Base Rate, Wage-Adjusted Statewide Base Rate, Rehab Rate, Admin 2 190 Rate and Admin 2 199 Rate. This dataset does not include psychiatric hospitals, alcohol and drug rehabilitation facilities, or designated public hospitals.
Living Wage

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns.  Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance.  The percent of families below the living wage was calculated using data from the [Living Wage Calculator](http://livingwage.mit.edu/) and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes.  Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity.  More information about the data table and a data dictionary can be found in the About/Attachments section.
Medi-Cal Managed Care Capitation Rates – County Organized Health Systems (COHS) Model

__This page is considered archival. please refer to the new data landing page at [Medi-Cal Managed Care Capitation Rates by Managed Care Plan Models](https://data.chhs.ca.gov/dataset/medi-cal-managed-care-capitation-rates-by-managed-care-plan-models-consolidated).__

This dataset displays reimbursement rates paid to Medi-Cal Managed Care health plans in the COHS model, by State Fiscal Year. The COHS serve beneficiaries in 22 counties. In the COHS model counties, the Department of Health Care Services (DHCS) contracts with a health plan created by the county Board of Supervisors.  In a COHS county, all Medi-Cal members are enrolled in the same managed care health plan.
Medi-Cal Managed Care Capitation Rates - Geographic Managed Care (GMC)

__This page is considered archival. please refer to the new data landing page at [Medi-Cal Managed Care Capitation Rates by Managed Care Plan Models](https://data.chhs.ca.gov/dataset/medi-cal-managed-care-capitation-rates-by-managed-care-plan-models-consolidated).__

Medi-Cal Managed Care Capitation Rates – Geographic Managed Care (GMC) by State Fiscal Year. Medi- Cal managed care health plans in the Sacramento and San Diego counties.
Medi-Cal Managed Care Capitation Rates – Regional Model/Rural Expansion

__This page is considered archival. please refer to the new data landing page at [Medi-Cal Managed Care Capitation Rates by Managed Care Plan Models](https://data.chhs.ca.gov/dataset/medi-cal-managed-care-capitation-rates-by-managed-care-plan-models-consolidated).__

This dataset displays reimbursement rates paid to Medi-Cal Managed Care health plans in the Regional model, by State Fiscal Year. The Regional Model serves beneficiaries in 28 rural counties: Alpine, Amador, Butte, Calaveras, Colusa, Del Norte, El Dorado, Glenn, Humboldt, Inyo, Imperial, Lake, Lassen, Mariposa, Mendocino, Modoc, Mono, Nevada, Placer, Plumas, San Benito, Sierra, Siskiyou, Sutter, Tehama, Trinity, Tuolumne, and Yuba. The Department of Health Care Services (DHCS) contracts with two Commercial plans to provide services in each county. San Benito is the only exception where beneficiaries can choose either the managed care plan or (fee-for-service) Medi-Cal.
Medi-Cal Managed Care Capitation Rates – Two-Plan Model

__This page is considered archival. please refer to the new data landing page at [Medi-Cal Managed Care Capitation Rates by Managed Care Plan Models](https://data.chhs.ca.gov/dataset/medi-cal-managed-care-capitation-rates-by-managed-care-plan-models-consolidated).__

This dataset displays reimbursement rates paid to Medi-Cal Managed Care health plans in Two-Plan model counties for State Fiscal Years 2015-16 to 2019-20 . In Two-Plan model counties, the Department of Health Care Services (DHCS) contracts with a local initiative (county organized) and a commercial plan.
Mental and Behavioral Health Diagnoses in Emergency Department and Inpatient Discharges by Healthy Places Index Ranking

This dataset provides counts and percentages of diagnoses broken down by each patient’s Healthy Places Index percentile ranking (based on ZIP code of residence). Healthcare encounters are categorized into four diagnosis groups: mental health disorders, substance use disorders, co-occurring disorders, and all other diagnoses. To view and interact with a fully functioning version of the HPI map and data used in these HCAI analyses of behavioral health, please click the link to visit https://map.healthyplacesindex.org/.
Methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI) in California Hospitals

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 OSHPD, 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/HAIreport.aspx
Licensed and Certified Healthcare Facility Crosswalk

The California Department of Public Health (CDPH), Center for Health Care Quality, Licensing and Certification (L&C) Program licenses and certifies more than 30 types of healthcare facilities. The Electronic Licensing Management System (ELMS) is a CDPH data system created to manage state licensing-related data and enforcement actions.

This dataset provides a California healthcare facilities interdepartmental crosswalk using the Department of Health Care Access and Information (HCAI) assigned licensed facility identification numbers linked with matched California Department of Public Health (CDPH), Licensing and Certification facility lists based on license number housed in the Electronic Licensing Management System (ELMS) and/or the CMS Certification Number (CCN) from the Federal Automated Survey Process Environment (ASPEN) databases. This is not a comprehensive matched list, facility identification numbers that did not match are also included from both the HCAI and CDPH lists. Facility Status or Facility Level designations may explain some HCAI non-matches, for additional information contact HCAI directly. Please contact CDPH directly for more information regarding un-matched facility identifiers that do not have corresponding OSHPD identifiers.
Modeling Data for California’s Behavioral Health Workforce

This dataset contains the output of HCAI’s Supply and Demand Model for California’s Behavioral Health Workforce. It includes the estimated supply and demand for providers in Full-Time Equivalent (FTE) for each role or role group included in the model for the years 2022-2023. These metrics can be compared by role, region, county, and year. For in-depth details on our modeling methodology, please see our online comprehensive methodology documentation at https://hcai.ca.gov/wp-content/uploads/2025/05/Public-Modeling-Methodology-v.1.1_5-2025.pdf.
Modeling Data for California's Nursing Workforce

This dataset contains the output of HCAI’s Supply and Demand Model for California’s Nursing Workforce. It includes the estimated supply and demand for providers in Full-Time Equivalent (FTE) for each role or role group included in the model for the years 2022-2023. These metrics can be compared by role, region, county, and year. For in-depth details on our modeling methodology, see our online comprehensive methodology documentation  at https://hcai.ca.gov/wp-content/uploads/2025/05/Public-Modeling-Methodology-v.1.1_5-2025.pdf. 

Additional documentation is also provided on HCAI’s use of Lightcast data within the Supply & Demand model.
Modified Retail Food Environment Index

This table contains data on the modified retail food environment index for California, its regions, counties, cities, towns, and census tracts.   An adequate, nutritious diet is a necessity at all stages of life. Pregnant women and their developing babies, children, adolescents, adults, and older adults depend on adequate nutrition for optimum development and maintenance of health and functioning. Nutrition also plays a significant role in causing or preventing a number of illnesses, such as cardiovascular disease, some cancers, obesity, type-2 diabetes, and anemia. Peoples’ food choices and their likelihood of being overweight or obese are also influenced by their food environment: the foods available in their neighborhoods including stores, restaurants, schools, and worksites.  

The modified retail food environment index table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf  

The format of the modified retail food environment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.
Notice of Inaction (NOI) Report

This dataset includes monthly counts of Notice of Inaction (NOI) sent to Medi-Cal applicants whose pending application is reaching 45 days due to an improper delay by the county that is processing the application. A NOI is not issued when the application delay is due to the applicant failing to provide requested information to the county, which is considered a proper delay. The monthly counts include the total Medi-Cal and Covered California applications received and the total number/percentage of Medi-Cal applications pending 45 days, including both proper and improper application processing delays.  Data Sources: California Healthcare Eligibility, Enrollment and Retention System (CalHEERS) and Statewide Automated Welfare Systems (SAWS).
Number of Cancer Surgeries (Volume) Performed in California Hospitals

The dataset contains the number (volume) for 11 types of cancer (bladder, breast, brain, colon, esophagus, liver, lung, pancreas, prostate, rectum, and stomach) surgeries performed in California hospitals.  Data are reported for January – September 2015 due to coding changes from ICD-9-CM to ICD-10-CM/PCS for procedures, which began 10/1/2015. Comparisons across years should be made with caution since previous years’ results are based on 12 months of data, while this analysis is based on 9 months of data. The 2015 data may differ from previous years due to the coding change.  For all types of cancer surgeries, except breast cancer, the dataset contains surgeries performed in the inpatient hospital setting.  For breast cancer surgeries, this dataset includes procedures performed in inpatient and outpatient settings.
Number of Selected Inpatient Medical Procedures in California Hospitals

This dataset contains the number (volume) of 6 selected inpatient procedures (Esophageal Resection, Pancreatic Resection, Abdominal Aortic Aneurysm Repairs (AAA Repairs), Carotid Endarterectomy, Coronary Artery Bypass Graft Surgery, Percutaneous Coronary Intervention) performed in California hospitals. Data are reported for January – September 2015 due to coding changes from ICD-9-CM to ICD-10-CM/PCS for procedures, which began 10/1/2015. Comparisons across years should be made with caution since other years’ results are based on 12 months of data, while 2015 analysis is based on 9 months of data. The data starting 2015 may differ from previous years due to the coding change. This dataset does not include procedures performed in outpatient settings.
Number of Weight Loss Surgeries Performed in California Hospitals

The dataset contains the number for five types of weight loss (bariatric) surgeries (Open Roux-en-Y gastric bypass, laparoscopic Roux-en-Y gastric bypass , laparoscopic adjustable gastric banding, vertical sleeve gastrectomy , and biliopancreatic diversion ) performed in California hospitals.  The 2015 Data are reported for January-September due to coding changes from ICD-9-CM to ICD-10-CM/PCS, which began October 1, 2015. Caution should be taken before making comparisons  across years  since previous years' results are based on 12 months of data, while results for year 2015 are based on 9 months of data. This dataset does not include surgeries performed in outpatient settings.