(1) is primarily engaged in providing, by or under the supervision of physicians, to inpatients
(A) diagnostic services and therapeutic services for medical diagnosis, treatment, and care of injured, disabled, or sick persons, or (B) rehabilitation services for the rehabilitation of injured, disabled, or sick persons;(...)
(5) provides 24-hour nursing service rendered or supervised by a registered professional nurse, and has a licensed practical nurse or registered professional nurse on duty at all times; ...
(...)
(7) in the case of an institution in any State in which State or applicable local law provides for the licensing of hospitals,
(A) is licensed pursuant to such law or (B) is approved, by the agency of such State or locality responsible for licensing hospitals, as meeting the standards established for such licensing;(Excerpt from Title XVIII of the Social Security Act [42 U.S.C. § 1395x(e)], <http://www4.law.cornell.edu/uscode/html/uscode42/usc_sec_42_00001395---x000-.html>)
Included in this dataset are General Medical and Surgical Hospitals, Psychiatric and Substance Abuse Hospitals, and Specialty Hospitals (e.g., Children's Hospitals, Cancer Hospitals, Maternity Hospitals, Rehabilitation Hospitals, etc.).
Hospitals operated by the Veterans Administration (VA) are included, even if the state they are located in does not license VA Hospitals.
Nursing homes and Urgent Care facilities are excluded because they are included in a separate dataset. Locations that are administrative offices only are excluded from the dataset.
Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results.
All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.
The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 12/29/2005 and the newest record dates from 05/15/2007.
This dataset was created by TechniGraphics, Inc. for the Florida Division of Emergency Management.
Use Cases: Use cases describe how the data may be used and help to define and clarify requirements.
1) A disaster has overwhelmed local medical facilities and capacity must be found in the surrounding area.
2) A threat against hospitals has been identified and measures must be taken to protect the hospital.
3) An assessment as to the adequacy of the total capacity to handle emergency medical care in a given area needs to be made as part of a disaster mitigation plan.
4) A disaster has occurred, or is in the process of occurring, and facilities in the vicinity with people needing evacuation assistance must be identified.
Critical Facilities
To assist in emergency response and planning, the GIS Lab, working with local, state, and federal agencies maintains shelters, emergency operations centers, critical facilities, and hazardous material facilities datasets.
"Critical facilities" are defined as those structures from which essential services and functions for victim survival, continuation of public safety actions, and disaster recovery are performed or provided. Shelters, emergency operation centers, public health, public drinking water, sewer and wastewater facilities are examples of critical facilities. Though not explicitly included in the definition, supporting life-line infrastructure essential to the mission of critical facilities must also be included in the inventory when appropriate.
"Critical infrastructure" is defined as those systems and assets, whether physical or virtual, so vital that the incapacity or destruction of such systems and assets would have a debilitating impact on security, economy, public health or safety, or any combination of these elements.
The domain of the GIS Lab is specifically related to "critical facilities", while working closely with Florida's Regional Domestic Security Task Forces to ensure a safe and secure Florida.
Several critical facilities data layers are maintained by other agencies, and the GIS Lab works closely with these agencies to make sure updated data is readily available. Examples include:
* Drinking Water Facilities - Florida Department of Environmental Protection * Environmental Health Facilities - Florida Department of Health * Fire Stations - Florida State Fire Marshal * Health Care Facilities - Agency for Health Care Administration * Petroleum Storage Tanks - Florida Department of Environmental Protection * Schools - Florida Department of Education * Solid Waste Facilities - Florida Department of Environmental Protection
Other data layers, like Hazardous Materials Facilities, Mobile Home Parks, and Hotel/Motels, while not specifically critical facilities, are facilities of interest for emergency managers, and the GIS Lab is also actively involved in facilitating access to these data layers.
Homeland Security Infrastructure Program
The Homeland Security Infrastructure Program (HSIP) is a collection of base map layers and homeland security related geospatial data. Currently, the emphasis of this program is on sharing and improving data to create uniform state & federal information. Working with contractors, the GIS Lab is providing data from state and local sources for QA/QC under the HSIP Freedom project.
* Correctional Facilities - delivered April 2007 * Emergency Operations Centers - July 2007 * Fire Stations - t.b.a. * Police Stations - t.b.a. * Emergency Medical Services - t.b.a. * Hospitals - t.b.a. * Urgent Care Facilities - t.b.a.
Emergency Management GIS Data Downloads
At this time, FDEM does not provide datasets for download, but may be contacted (Richard Butgereit 850-413-9907) for further information.
A note about data scale:
Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data.
1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger.
Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: <http://geoplan.ufl.edu/education.html>
Florida Division of Emergency Management <http://www.floridadisaster.org/index.asp> <http://www.floridadisaster.org/gis>
For entities that were contacted, the name, address, city, state, and five (5) digit zip codes were verified to be correct as of the date indicated by the [CONTDATE] attribute. The existence of the entity was also verified, as well as whether or not it met the criteria for inclusion in this dataset. Four (4) digit zip code extensions were derived from USPS (United States Postal Service) data and were not verified.
ID Check: The [ID] attribute is not blank and all IDs are unique.
Coordinate Check: Coordinates are not null or zero and the x and y fields match the shape.
Basic Address Check: Physical addresses were verified to be non blank and to not be a "PO Box", "General Delivery", "Highway Contract", or "Rural Route" address.
Highway Address without Type Check: Physical addresses containing the word "Highway" or "Route" were verified to also contain a type designator such as "State", "US", or "County", if one actually exists for the highway or route. These type designators are often missing from addresses, leading to confusion if more than one "Highway" of the given number exists in an area.
Basic Name Check: Entity name is not blank, is not the same as entity city, and has a minimum of 2 characters. Name does not contain punctuation characters that can interfere with database operations, such as " (quote) and * (asterisk).
Basic Phone Check: All phone numbers (including the area code) are ten (10) numeric digits. Alphabetic characters have been converted to the corresponding numeric digit.
City Check: Entity city is not blank and is found in the named places file within 25 miles.
County FIPS to State Compare Check: The county represented by the tabular FIPS Code attribute is actually in the state specified by the state attribute.
County Name to State Compare Check: The county represented by the tabular county name attribute is actually in the state specified by the state attribute.
Phone Number Format Check: Phone numbers (including area code) were verified to be formatted as nnn-nnn-nnnn.
NPA_NXX Check: Area codes (sometimes called "Number Planning Areas", or NPA's) and central office codes (sometimes known as exchanges, or NXX's) were validated against data from the North American Number Planning Administration (NANPA). In some cases, NPA-NXX combinations did not show up in the NANPA data but were verified to work.
Area Code Distance Check: Area code (NPA) is valid and is within its area code boundary.
Zip Code Check: The zip code is five (5) or nine (9) numeric digits, is listed in the postal database, is in the same state as indicated by the entity's [STATE] attribute, and is not a PO Box only zip code.
Zip City Check: The entity's zip code and its city were verified to match according to the USPS Address Information System (AIS).
Collocation Check: Entities with different addresses must not share the exact same geospatial location.
Geographic Spell Check: Words that appear in the entity name were checked against a standard English word list (and Spanish word list for entities in Puerto Rico). Words not appearing in these standard word lists were then checked against names appearing in the Geographic Names Information System (GNIS) of geographic features that are located within 25 miles of the entity. Proper names were manually reviewed for correct spelling.
Included in this dataset are General Medical and Surgical Hospitals, Psychiatric and Substance Abuse Hospitals, and Specialty Hospitals (e.g., Children's Hospitals, Cancer Hospitals, Maternity Hospitals, Rehabilitation Hospitals, etc.).
Hospitals operated by the Veterans Administration (VA) are included, even if the state they are located in does not license VA Hospitals.
Nursing homes and Urgent Care facilities are excluded because they are included in a separate dataset. Locations that are administrative offices only are excluded from the dataset.
The basic attribution (name, address, city, state, zip code, and telephone number) came from this dataset, unless the entity was updated by TGS during this processing. For entities that were previously manually processed by TGS, their geospatial information was used as a reference when automatically determining their location relative to the latest streets.
This was used as a source for hospitals in Florida during the Q307 processing.
NAVTEQ streets were used as a reference in the automatic geocoding and manual geolocating of entities during processing.
1) Verified name, physical address, and phone numbers by contacting the entityor an authority responsible for the entity.
2) Determined or verified the geospatial location for the entity through contactwith entity or authority responsible for entity. Entities were asked to describe their geospatial location relative to land marks visible in ortho imagery.
3) All text fields were set to upper case. 4) Leading and trailing spaces were trimmed from all text fields. These spacescan interfere with some database queries.
5) Non printable and diacritic characters were removed from all text fields. Thesevalues have been found to prevent data from being loaded into some spatial database engines.
The original dataset projection was: Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Geographic: Latitude_Resolution: 0.000000 Longitude_Resolution: 0.000000 Geographic_Coordinate_Units: Decimal degrees Geodetic_Model: Horizontal_Datum_Name: D_WGS_1984 Ellipsoid_Name: WGS_1984 Semi-major_Axis: 6378137.000000 Denominator_of_Flattening_Ratio: 298.257224
The dataset was renamed to: fdem_hospitals_aug07.shp
The dataset was reprojected to the FGDL Albers NAD83 HARN projection.
The dataset features were matched to their 1-kilometer United States National Grid (USNG) address via a spatial join, the USNG address can be found in the USNG_FL_1K field.
The USNG is an alpha-numeric reference system based on the UTM coordinate system and is similar to the Military Grid Reference System. Use of the USNG ensures a uniform grid mapping and positional reporting system for search and rescue, emergency planning, response, and recovery.
How to Read a United States National Grid (USNG) Spatial Address <http://www.fgdc.gov/usng/how-to-read-usng/index_html>
Three additional fields were added. DESCRIPT field based on NAME FGDLAQDATE field based on the date the data was acquired by FGDL from the source. AUTOID field based on FID + 1, GeoPlan Center feature identification number.
Finally the attribute table was upper-cased and the metadata was updated.
Sometimes an entity may report a city that is not accepted by the USPS, and although TGS has tried to replace those cities with an acceptable alternative, some of them may remain in this dataset.
NAICS Descriptions (and NAICS Codes) have been assigned based upon the entity's primary function, regardless of the function that qualified it to be included in this dataset.
The values for this attribute were provided by individual states and TGS did not verify these values.
The values for this attribute were provided by the Post, Buckley, Schuh, and Jernigan, Incorporated (PBSJ) and TGS did not verify these values.