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WA-APCD Quality and Cost Summary Report: County Cost
healthdata.gov | Last Updated 2023-07-26T12:05:29.000ZWA-APCD - Washington All-Payer Claims Database The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018. Download the attachment for the data dictionary and more information about WA-APCD and the data.
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Immunizations in Child Care by Academic Year
healthdata.gov | Last Updated 2024-06-06T04:00:30.000ZThis dataset contains immunization status of child care facility enrollees aged 2 years to 4 years 11 months in California in facilities with 10 or more children enrolled. Smaller schools were excluded to help protect privacy. Explanation of the different immunizations is in the attached data dictionary. The California Health and Safety Code Section 120325-75 requires students to provide proof of immunization for school and child care entry. Additionally, California Health and Safety Code Section 120375 and California Code of Regulation Section 6075 require all schools and child care facilities to assess and report annually the immunization status of their enrollees. The annual child care assessment is conducted each fall to monitor compliance with the California School Immunization law. Results from this assessment are used to measure immunization coverage among children entering licensed child care facilities. This data set presents results from the child care assessment and immunization coverage in licensed child care facilities by county. Not all facilities reported. To review individual child care facility coverage and exemption rates in a separate lookup format, go to the School Lookup page at the Immunization Branch's Shots for School website: http://www.shotsforschool.org/lookup/ See the full PDF reports by year here:https://www.shotsforschool.org/child-care/reporting-data/ See the attached file 'Notes on Methods' for data suppression in the '2016-17 academic year and beyond'. For earlier years of data: https://www.shotsforschool.org/child-care/reporting-data/
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Newly Eligible Individuals by Insurance Affordability Program (IAP)
healthdata.gov | Last Updated 2024-06-14T04:00:20.000ZThis dataset includes the total number of newly eligible individuals by Insurance Affordability Program (IAP), by reporting period. IAPs include Medi-Cal, Covered California subsidized and unsubsidized Qualified Health Plans (QHP), and the Medi-Cal Access Program (MCAP). Covered California subsidized and unsubsidized QHP newly eligible data includes those who selected and enrolled in a QHP, and paid their first premium. This dataset is part of public reporting requirements set forth by the California Welfare and Institutions Code 14102.5.
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NCHS - Drug Poisoning Mortality by County: United States
healthdata.gov | Last Updated 2023-07-25T17:57:16.000ZThis dataset contains model-based county estimates for drug-poisoning mortality. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8). REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm. 2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html. 3. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013. 4. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014. 5. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf. 6. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e. 7. National Center for Health Statistics. County geog
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WA-APCD Quality and Cost Summary Report: Practice Quality
healthdata.gov | Last Updated 2023-07-26T01:43:40.000ZWA-APCD - Washington All-Payer Claims Database The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018. Download the attachment for the data dictionary and more information about WA-APCD and the data.
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Death Profiles by County
healthdata.gov | Last Updated 2024-06-26T04:00:17.000ZThis dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data. The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years. The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.
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NCHS - Drug Poisoning Mortality by State: United States
healthdata.gov | Last Updated 2023-07-25T18:24:08.000ZThis dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances. REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm. 2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.
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Older Americans Act Title IIIC-1 Nutrition Services - Congregate Meals Program and Participants
healthdata.gov | Last Updated 2023-07-25T20:41:32.000ZThis data set represents the total number of Californians age 60 and over who were provided a meal from the Older Americans Act Title IIIC-1 Nutrition Services Program – Congregate Meals. Key sociodemographic variables include: age, high risk nutrition status, low income, lives alone and minority/non-minority.
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SHIP Life Expectancy 2010-2021
healthdata.gov | Last Updated 2024-02-23T04:01:37.000ZLife Expectancy - This indicator shows life expectancy from birth, in years. Life expectancy is a summary measure used to describe overall health. Life expectancy at birth is the average number of years a newborn is expected to live given current conditions. The life expectancy in the US is the highest in recorded history thanks to public health interventions such as improvements in sanitation and food safety, development and use of vaccines, and health promotion efforts. <a href ="https://health.maryland.gov/pophealth/Documents/SHIP/SHIP%20Lite%20Data%20Details/Life%20Expectancy.pdf" > Link to Data Details </a>
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MD COVID-19 - Probable Deaths by Gender Distribution
healthdata.gov | Last Updated 2024-06-26T04:01:31.000Z<b>Note:</b> Starting April 27, 2023 updates change from daily to weekly. <b>Summary</b> The cumulative number of probable COVID-19 deaths among Maryland residents by gender: Female; Male; Unknown. <b>Description</b> The MD COVID-19 - Probable Deaths by Gender Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by gender. A death is classified as probable if the person's death certificate notes COVID-19 to be a probable, suspect or presumed cause or condition. Probable deaths are not yet been confirmed by a laboratory test. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Confirmed deaths are available from the MD COVID-19 - Confirmed Deaths by Gender Distribution data layer. <b>Terms of Use</b> The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.