Asthma ED Visit Rates by ZIP

Counts and Rates by Age Group in California

By Health [source]

About this dataset

This dataset presents a comprehensive look into the prevalence of asthma among Californian residents in terms of emergency department visits. Using age-adjusted rates and county FIPS codes, it offers an accurate snapshot of the prevalence rates per 10,000 people and provides key insights into how this condition affects certain age groups by ZIP Code. With its easy to use associated map view, this dataset allows users to quickly gain deeper knowledge about this important health issue and craft meaningful solutions to address it

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How to use the dataset

This dataset contains counts and rates of asthma related emergency department visits by ZIP Code and age group in California. This data can be useful when doing research on asthma related trends or attempting to find correlations between environmental factors, prevalence of disease and geography.

• Select a year for analysis - the latest year for which data is available is the default selection, but other years are also listed in the dropdown menu.
• Select an Age Group to analyze - use the provided dropdown menus to select one or more age groups (all ages, 0-17, 18+) if you wish to analyze two different age groups in your analysis.
• Define a geographical area by selecting a ZIP code or County Fips code from which you wish to obtain your dataset from based on its availability or importance in your research question .
• View and download relevant data - after selecting all of the desired criteria (year,Age group(s), ZIP code/County FIPS Code) click “View Data” then “Download” at the bottom right corner of window that opens up
  5 Analyze information found - use software such as Microsoft Excel or open source programs like Openoffice Calc to gain insight into your downloaded dataset through statistics calculations, graphs etc.. In particular look out for anomalies that could signify further investigation

Research Ideas

• Identifying the geographic clusters of asthma sufferers by analyzing the rate of emergency department visits with geographic mapping.
• Developing outreach initiatives to areas with a high rate of ED visits for asthma to provide education, interventions and resources designed towards increasing preventive care and reducing preventable complications due to lack of access or knowledge about available services in these communities.
• Assessing disparities in ED visit rates for asthma between age groups as well as between urban and rural areas or different socio-economic groups within counties or ZIP codes in order to identify areas where there is a need for increased interventions, services and other resources related to asthma care in order to reduce the burden or severity of this chronic condition among particularly vulnerable population groups

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: Asthma_Emergency_Department_Visit_Rates_by_ZIP_Code.csv | Column name | Description | |:----------------------|:------------------------------------------------------------------------------------------------------------------| | Year | The year the data was collected. (Integer) | | ZIP code | The ZIP code of the area the data was collected from. (String...

Archived as of 6/26/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset provides information related to emergency visit claims. It contains information about the total number of recipients, total number of claims, and total dollar amount paid, grouped by recipient zip code and age group of recipient Restricted to claims with service date between 01/2012 to 12/2017. Restricted to top 100 most frequent primary diagnostic codes in ER claims from 2012 - 2017. ER claims are defined as claims with CPT codes 99281, 99282, 99283, 99284, and 99285. Providers are billing providers. If multiple diagnostic codes are attached to a claim, primary diagnosis is used. This data is for research purposes and is not intended to be used for reporting. Due to differences in geographic aggregation, time period considerations, and units of analysis, these numbers may differ from those reported by FSSA.

This dataset contains FEMA applicant-level data for the Individuals and Households Program (IHP). All PII information has been removed. The location is represented by county, city, and zip code. This dataset contains Individual Assistance (IA) applications from DR1439 (declared in 2002) to those declared over 30 days ago. The full data set is refreshed on an annual basis and refreshed weekly to update disasters declared in the last 18 months. This dataset includes all major disasters and includes only valid registrants (applied in a declared county, within the registration period, having damage due to the incident and damage within the incident period). Information about individual data elements and descriptions are listed in the metadata information within the dataset.rnValid registrants may be eligible for IA assistance, which is intended to meet basic needs and supplement disaster recovery efforts. IA assistance is not intended to return disaster-damaged property to its pre-disaster condition. Disaster damage to secondary or vacation homes does not qualify for IHP assistance.rnData comes from FEMA's National Emergency Management Information System (NEMIS) with raw, unedited, self-reported content and subject to a small percentage of human error.rnAny financial information is derived from NEMIS and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations and application of business rules, this financial information may differ slightly from official publication on public websites such as usaspending.gov. This dataset is not intended to be used for any official federal reporting. rnCitation: The Agency’s preferred citation for datasets (API usage or file downloads) can be found on the OpenFEMA Terms and Conditions page, Citing Data section: https://www.fema.gov/about/openfema/terms-conditions.rnDue to the size of this file, tools other than a spreadsheet may be required to analyze, visualize, and manipulate the data. MS Excel will not be able to process files this large without data loss. It is recommended that a database (e.g., MS Access, MySQL, PostgreSQL, etc.) be used to store and manipulate data. Other programming tools such as R, Apache Spark, and Python can also be used to analyze and visualize data. Further, basic Linux/Unix tools can be used to manipulate, search, and modify large files.rnIf you have media inquiries about this dataset, please email the FEMA News Desk at FEMA-News-Desk@fema.dhs.gov or call (202) 646-3272. For inquiries about FEMA's data and Open Government program, please email the OpenFEMA team at OpenFEMA@fema.dhs.gov.rnThis dataset is scheduled to be superceded by Valid Registrations Version 2 by early CY 2024.

The Housing Assistance Program Data Owners dataset is generated by FEMA's Individual Assistance (IA) reporting team to share data on FEMA's Housing Assistance program for house owners within the state, county, and zip code where the registration is valid for the declarations, starting with disaster declaration DR1439 (declared in November 2002). It contains aggregated, non-PII data. Core data elements include number of applicants, county, zip code, inspections, severity of damage, and assistance provided.The FEMA Individual Assistance Renters dataset was generated by FEMA's Individual Assistance (IA) reporting team to share data on FEMA's Housing Assistance program for house renters within the state, county, and zip code where the registration is valid for the declarations, starting with disaster declaration DR1439 (declared in 2002). It contains aggregated, non-PII data. Core data elements include number of applicants, county, zip code, inspections, severity of damage, and assistance provided.The following disclaimer applies to both Individual Housing Assistance datasets: Data is self-reported and subject to human error. For example, when an applicant registers online, they enter their street and city address. While the county is inferred by the system, it may be overridden by the applicant. Similarly, with a call center registration, the Human Services Specialist (HSS) representatives are instructed to ask in what county the applicant resides, but the applicant has the right to choose the county. To learn more about disaster assistance please visit https://www.fema.gov/individual-disaster-assistance.The financial information is derived from NEMIS and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations and how business rules are applied, this financial information may differ slightly from official publication on public websites such as usaspending.gov; this dataset is not intended to be used for any official federal financial reporting.The Individual and Household Program Registrations dataset contains FEMA applicant-level data for the Individuals and Households Program (IHP). All PII information has been removed. The location is represented by county, city, and zip code. This dataset contains IA applications from DR1439 (declared in 2002) to those declared over 30 days ago. The full data set is refreshed on an annual basis; the last 18 months of data are refreshed weekly. This dataset includes all major disasters and includes only valid registrants (applied in a declared county, within the registration period, having damage due to the incident and damage within the incident period). IHP is intended to meet basic needs and supplement disaster recovery efforts. See https://www.fema.gov/assistance/individual/program/eligibility for more information. Valid registrants may be eligible for IA assistance, which is intended to meet basic needs and supplement disaster recovery efforts. IA assistance is not intended to return disaster-damaged property to its pre-disaster condition. Disaster damage to secondary or vacation homes does not qualify for IHP assistance. Data comes from FEMA's National Emergency Management Information System (NEMIS) with raw, unedited, self-reported content and is subject to a small percentage of human error.The Individual Assistance Large Disasters data set contains detailed non-PII data on the Individuals and Households Program (IHP). FEMA provides assistance to individuals and households through the IA program, comprised of two categories of assistance: Housing Assistance (HA) and Other Needs Assistance (ONA).The Registration Intake and Individual Household Program dataset contains aggregated, non-PII data from Housing Assistance Program reporting authority within FEMA’s Recovery Directorate to share data on registrations and Individuals and Households Program (IHP) for declarations starting from disaster declaration number 4116, segmented by city where registration is valid. Additional core data elements include: valid call center registrations, valid web registrations, valid mobile registrations, IHP eligible, IHP amount, HA eligible, HA amount, ONA eligible, and ONA amount.

This dataset contains annual Excel pivot tables that identify where a facility’s patients come from (Patient Origin) and where patients from a specific area go to (Market Share) for hospital inpatient, emergency department, and ambulatory surgery treatment. The Patient Origin Report shows the ZIP codes of origin (based on a selected facility or facility county) and the Market Share Report lists the destination facilities (based on a selected patient ZIP code or patient county). Note: Physician-owned ambulatory surgery clinics do not report their data to HCAI and, therefore, are not included here.

The Texas Department of Insurance (TDI) collects and reports information about billing rates for emergency service providers within political subdivisions as reported by those political subdivisions. The Zone Improvement Plan (ZIP) code is a unique seven-digit identification number for postal delivery in the United States. This dataset relates political subdivisions and ZIP codes they contain by year. There is a row for each ZIP code within a political subdivision. Subdivisions containing more than one ZIP code or providers operating in more than one subdivision will be listed in multiple rows. The data includes the year the information applies to as well as the date the political subdivision submitted their report. The Texas Legislature first authorized political subdivisions to submit rates for emergency medical services in 2023 under Senate Bill 2476. In 2025, the Texas legislature extended the statute by passing Senate Bill 916, which allows a political subdivision to annually adjust a rate submitted under Insurance Code section 38.006, subject to certain limits. ► For contact information, refer to dataset:  Emergency Services Billing Rates - Contact List. ► For procedure codes rates, refer to dataset:  Emergency Services Billing Rates - Code Rates. ► For National Provider Identifier Standard (NPI) information reported in each political subdivision, refer to dataset: Emergency Services Billing Rates - NPI. Information in this dataset is subject to change. Visit TDI’s web site disclaimer for more information. For more information related to this data, visit TDI’s FAQ page.

UK Postcode-Level Flood Risk Data

Risk Level, Suitability, and Geographic Coordinates

By GetTheData [source]

About this dataset

The underlying source material has been compiled from open datasets including 'Risk of Flooding from Rivers and Sea', 'Open Postcode Geo' - all held under licence in agreement with Crown copyright & Database right (2017) & Royal Mail copyright & Database right (2017). The methodology used would combine each one of these datasets points into polygons with first identifying each risk area then mapping out corresponding postcode points within them which then could be tracked for its related longitude, latitude easting and northing positions. Through this comprehensive process you could get a better understanding regarding what individual postcodes are within high & low level flooding areas as well as find out from the latest publication date - when was it last issued? Ultimately this profound dataset comes in handy for prevention or even planning purposes informing citizens how serious some situations could become during extreme weather events such as floods or major storms allowing them to estimate potential risks before disaster ensues!

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How to use the dataset

In order to effectively use this dataset there are several key pieces of terminology that you should be familiar with:

• FID – a unique identifier number associated with each record in the database.
• Postcode – an alphanumeric code used to identify a specific geographic region within the country; consists of two parts: an outward code (e.g., RG4) and an inward code (e.g., 8DN).
• PROB_4BAND – The flood risk level based on four categories represented in this field assigned by location - High, Medium, Low or Very Low; or None if outside of a high-risk area
• SUITABILITY – The suitability rating determined by location; either suitable or not suitable for development based on constraints for building in a floodplain
• Publication Date(PUB DATE) - The date that this information was made publicly available

• Risk For Insurance SOP (Risk_For_Insurance_SOP) - A ranking system from 1-5 used as guidance only when offering advice before taking out insurance cover over certain property located in certain very extreme area

  You will also need to be aware of some mathematical values associated with each postcode:

  • Easting – An eastward grid coordinate reference point corresponding to determining latitude/ longitude coordinates at specified points along an arc created by measuring distances between two other known points

  • Northing– A northward grid coordinate reference forming part of a geographical survey’s grid system

    Finally, here is how you can get started working with this amazing dataset:

    1. Download it onto your computer from Kaggle's website (www.kaggle/datasets/UK Postecode Level Flood Risk Data).

       2

Research Ideas

• Creating a custom application that provides users with real-time flood risk and safety advice based on postcode.
• Developing a map-based interface that integrates flood risk levels directly into Google Maps to assist people in planning trips and relocating in safer areas.
• Developing an app that tracks the geographically accurate position of every property within each postcode, allowing for better risk assessment for businesses and insurers

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: open_flood_risk_by_postcode.csv | Column name | Description | |:--------------|:--------------------------------| | TR23 0PR | Postcode area (String) | | \N | FID (Integer) | | None | PROB_4BAND (String) | | \N.1 | SUITABILITY (String) | | \N.2 | PULD_DATE (Date) | | \N.3 | RISK_FOR_INSURANCE_SOP (String) | | 87897 | Easting (Integer) | | 15021 | Northing (Integer) | | 49.953605 | Latitude (Float) | | -6.352647 | Longitude (Float) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit GetTheData.

This dataset tracks the updates made on the dataset "Medicaid Potentially Preventable Emergency Visit (PPV) Rates by Zip Code: Beginning 2011" as a repository for previous versions of the data and metadata.

This dataset contains the properties that were mitigated by projects funded under the Hazard Mitigation Assistance (HMA) grant programs. FEMA administers three programs that provide funding for eligible mitigation planning and projects to reduce disaster losses and protect life and property from future disaster damages. The three programs are the Hazard Mitigation Grant Program (HMGP), Flood Mitigation Assistance (FMA) grant program, and Pre-Disaster Mitigation (PDM) grant program. This dataset also contains data from the HMA grant programs that were eliminated by the Biggert Water Flood Insurance Reform Act of 2012 (BW-12): Repetitive Flood Claims (RFC) grant program and Severe Repetitive Loss (SRL) grant program. For more information on the Hazard Mitigation Assistance grant programs, please visit: https://www.fema.gov/grants/mitigation.rnrnThe dataset contains properties by project identifier, city, zip code, state and region and does not contain any Personally Identifiable Information (PII). The mitigated property dataset can be joined to the OpenFEMA Hazard Mitigation Assistance Funded Project dataset by the Project Identifier field. Note, not all projects in the Hazard Mitigation Assistance Funded Project dataset will have mitigated properties (e.g., Planning and Management Cost projects). In some cases data was not provided by the subgrantee (sub-recipient), grantee (recipient) and/or entered into the FEMA mitigation grant systems. The information is likely available as part of the paper file which is considered the file of record.rnrnThis is raw, unedited data from FEMA's mitigation grant systems (NEMIS-MT and e-Grants) and as such is subject to a small percentage of human error. The financial information is derived from FEMA's mitigation grant systems and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations and how business rules are applied, this financial information may differ slightly from official publication on public websites such as www.usaspending.gov; this dataset is not intended to be used for any official federal financial reporting.rnrnMissing values - In some cases data was not provided by the subgrantee (subrecipient), grantee (recipient) and/or entered into the FEMA mitigation grant systems. The information is likely available as part of the paper file which is considered the file of record.rnrnA newer version of this OpenFEMA data set has been released. This older dataset version will no longer be updated and will be archived by the end of April 2020. The following page details the latest version of this data set:https://www.fema.gov/openfema-data-page/hazard-mitigation-assistance-mitigated-properties-v2. CSV and JSON Files can be downloaded from the 'Full Data' section.rnrnTo access the dataset through an API endpoint, visit the 'API Endpoint' section of the above page. Accessing data in this fashion permits data filtering, sorting, and field selection. The OpenFEMA API Documentation page provides information on API usage. rnrnIf you have media inquiries about this dataset, please email the FEMA News Desk FEMA-News-Desk@dhs.gov or call (202) 646-3272. For inquiries about FEMA's Hazard Mitigation Assistance grant program data and Open government program, please contact the OpenFEMA team via email OpenFEMA@fema.dhs.gov and FEMA-HMAAnalytics@fema.dhs.gov.

Total emergency department visits, and visits and admissions for influenza-like and/or pneumonia illness by modified ZIP code tabulation area of patient residence.

Identify neighborhood vulnerability to disasters and climate change with Aterio's Climate Risk Index.

This dataset contains counts and rates (per 10,000 residents) of asthma emergency department (ED) visits among Californians. The table “Asthma Emergency Department Visit Rates by County” contains statewide and county-level data 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 table “Asthma Emergency Department Visit Rates by ZIP Code” contains zip-code level data stratified by age group (all ages, 0-17, 18+). The data are derived from the Department of Health Care Access and Information emergency department database. These data include emergency department visits 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 ICD9-CM (493) to ICD10-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 emergency department visits (not the unique number of individuals).

Mobile Home Park Locations

Locations and details of mobile home parks in the United States

By Homeland Infrastructure Foundation [source]

About this dataset

The Mobile Home Parks Inventory dataset provides a comprehensive list of mobile home parks across the United States. This dataset is crucial for emergency preparedness and evacuation planning, as mobile home parks are inhabited by a vulnerable population that is particularly susceptible to natural disasters such as hurricanes, tornadoes, and flooding.

The dataset includes detailed information about each mobile home park, including its location coordinates (longitude and latitude), address details (street address, city, state, ZIP code), and additional address information if available. It also provides contact details such as telephone numbers and websites for further information about each park.

Furthermore, the dataset contains essential attributes related to the characteristics of mobile home parks. These attributes include the number of units (mobile homes) within each park, allowing authorities to assess capacity during emergency situations. Additionally, it categorizes the type of each park (e.g., recreational vehicle parks), its status (e.g., operational or closed), and its size classification.

To ensure data accuracy and reliability, various validation methods have been implemented. The validation process includes verifying the data sources from where this information was obtained along with dates when data was sourced or validated.

Moreover, this comprehensive inventory incorporates geographical references with FIPS codes for counties in which these mobile home parks are located. Furthermore,the NAICS code provides an additional industry classification system describing these facilities in greater detail.

Lastly,this Mobile Home Parks Inventory recognizes that reverse geocoding has been employed for gathering precise spatial coordinates.Because vulnerability differs across regions,state boundaries have also been included to facilitate analysis at a higher level.Alongside state boundaries,this dataset acknowledges country-level variations which could be valuable while comparing international mobile homes inventories .

By utilizing this extensive collection of accurate and up-to-date information on mobile home parks in the United States policymakers,government agencies,and emergency responders can effectively plan evacuation strategies,mobile resource allocation,and disaster response efforts for ensuring public safety during natural calamities.This valuable knowledge will ultimately enhance disaster mitigation and the overall resilience of these vulnerable communities

How to use the dataset

• Understanding the Columns:

  • X and Y: These columns represent the longitude and latitude coordinates of each mobile home park. They can be used for geographical analysis and mapping purposes.
  • NAME: This column provides the name of each mobile home park. It is useful for identifying specific parks.
  • ADDRESS: The street address where each mobile home park is located.
  • ADDRESS2: Additional address information (if available) for each mobile home park.
  • CITY: The city where each mobile home park is situated.
  • STATE: The state where each mobile home park is located.
  • ZIP and ZIP4: These columns contain the ZIP code information for each mobile home park, including additional ZIP code details if available.
  • TELEPHONE: The contact telephone number for each mobile home park, which can be useful for making inquiries or gathering more information directly from them.
  • TYPE: This column indicates the type of the mobile home park (e.g., permanent residential, seasonal).
  • STATUS: The status of a particular mobile home park (e.g., open, closed).
  • COUNTY and COUNTYFIPS:The county where each mobile h0me_1park is situated along with its associated FIPS code.

• Analyzing Park Characteristics: UNITS & SIZE columns provide insights into various aspects: UNITS represents the number of individual dwelling units within a given Mobile Home Park SIZE describes its physical size.

• Demographic Analysis: By referring to NAICS_CODE & NAICS_DESC columns ,you'll get an idea about the associated industries and business activities in the vicinity of each park.

• Geographical Analysis: The LATITUDE and LONGITUDE coordinates allow you to map out mobile home parks on various GIS (Geographic Information System) platforms. You can analyze the distribution of mobile home parks across different states, cities, or counties.

• Emergency Preparedness: ...

SBA Disaster Loan Data provides verified loss and approved loan amount totals for both home and business disaster loans, segmented by city, county, zip code and state.

Datasets show emergency department visit claims, categorized by diagnosis code, provider, recipient age group, race, gender, and ZIP code.

This dataset tracks the updates made on the dataset "All Payer Potentially Preventable Emergency Visit (PPV) Rates by Patient Zip Code (SPARCS): Beginning 2011" as a repository for previous versions of the data and metadata.

Asthma emergency department visit rate among children ages 0-17, Santa Clara County, 2009-2013. Office of Statewide Health Planning and Development, 2009-2013 Emergency Department Data; State of California, Department of Finance, Race/Ethnic Population .

SBA Disaster Loan Data for Superstorm Sandy provides verified loss and approved loan amount totals for both home and business disaster loans, segmented by city, county, zip code and state.

The dataset contains Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for Medicaid beneficiaries by zip code beginning in 2011.

The Potentially Preventable Visits (PPV) obtained from software created by 3M Health Information Systems are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.

The rates were calculated using Medicaid inpatient and outpatient data for the numerator and Medicaid enrollment in the county or zip code for the denominator.

The observed, expected and risk adjusted rates for PPV are presented by either resident county (including a statewide total) or resident zip code (including a statewide total). For more information, check out: http://www.health.ny.gov/health_care/medicaid/. The "About" tab contains additional details concerning this dataset.

This Hospitals point feature class dataset contains the location and name of the hospitals in Hillsborough County. The attribute information includes name, type, street address, zip code, city and indicating whether the hospital has Helipad or not. The dataset was derived from the information provided by Florida Department of Health and The Office of Emergency Management, Hillsborough County. The location for Hospital point was established by geocoding the street addresses and by manual comparison to aerial photography. This dataset was also intersected with current hurricane evacuation zone dataset to identify the evacuation zone in which they are located. This data set is updated annually, or as needed. The Office of Emergency Management is responsible for planning and coordinating actions to prepare, respond, and recover from natural or man-made disasters in Hillsborough County. The Office manages the County Emergency Operations Center, conducts emergency training, and helps coordinate the Citizen Emergency Response Teams and Citizen’s Corps. To find out more information, please visit the website http://www.hillsboroughcounty.org/residents/public-safety/emergency-management or office at 9450 E. Columbus Dr., Tampa, FL 33619.