2016-2017 enrollments for all publicly funded schools in Pennsylvania as reported by school districts, area vocational-technical schools, charter schools, intermediate units, and state operated educational facilities. Local education agencies were asked to report those students who were enrolled and attending as of October 3, 2016.
County and Statewide Totals Notes:
Statewide and county totals include counts of students attending education classes on a full-time basis outside their parents' district of residence. This data was obtained from the Bureau of Special Education (PENNDATA 2016).
Intermediate Unit and CTC Part-day enrollments are excluded from county and state totals.
Statewide and county totals are unique counts of students being educated by public Local Education Agencies. LEA and School level reports may not sum to the County and Statewide totals.
Source: Pennsylvania Information Management System (PIMS)
Crash data reported to the Pennsylvania Department of Transportation. Includes data involving drivers, passengers, and motor vehicles for researching highway safety. This data can be used to investigate traffic crashes, fatalities and injuries statewide and in specific counties or municipalities.
An incident that occurs on a highway or traffic way that is open to the public by right or custom and involved
at least one motor vehicle in transport. An incident is reportable if it involves:
Injury to or death of any person, or
Damage to any vehicle to the extent that it cannot be driven under its own power in its
customary manner without further damage or hazard to the vehicle, other traffic elements, or
the roadway, and therefore requires towing.
Crash data does not include non-reportable crashes or near misses
Crash data may not contain complete information, some elements may be unknown
Data fields that may help with CODE4PA 2018 event Leveraging Data to help Fight the Opioid Epidemic
DRUG_RELATED At least one Driver or Pedestrian with Drugs reported or suspected NUMBER
This is a flag that defines whether the crash involved a driver or pedestrian was suspected of using drugs or was actually tested and had drugs in their system. If a driver or pedestrian is suspected and were tested, but the test results show no drugs, this situation would not be included.
DRUGGED_DRIVER At least one Driver with Drugs reported or suspected NUMBER
This flag is similar to drug_related, but it only applies to drivers. It defines whether the crash involved a driver suspected of using drugs or was actually tested and had drugs in their system. If a driver is suspected and were tested, but the test results show no drugs, this situation would not be included.
ILLEGAL_DRUG_RELATED At Least 1 Driver or Pedestrian had reported or suspected Illegal Drug Use NUMBER
This flag is similar to drug_related, but it only applies to illegal drugs. It defines whether the crash involved a driver or pedestrian suspected of using illegal drugs. If a driver is suspected and were tested, but the test results show no drugs, this situation would not be included.
IMPAIRED_DRIVER At least One Driver was Impaired by Drugs or Alcohol NUMBER
This flag is similar to drug_related, but it includes both alcohol and drugs and it only applies to drivers. It defines whether the crash involved a driver suspected of using drugs or alcohol or was actually tested and had drugs or alcohol in their system. If a driver is suspected and were tested, but the test results show no drugs, this situation would not be included.
* For additional information please review the Crash Data Information pdf attachment in the About This Dataset section of the Primer on this dataset.
This dataset is used to produce the School Performance Profile scores found at http://paschoolperformance.org. It is for School Year 2015. School Performance Profile scores are calculated for all open public schools in Pennsylvania. These include regular schools, charter schools, cyber charter schools, and full-time career and technical education centers. The scores reflect one of many indicators of a school’s academic performance.
The Quarterly Census of Employment and Wages (QCEW) dataset provides information about the number of establishments within a geographic area by industry as well as the average number of employees and average weekly wages paid. QCEW is the universe of employment covered under Pennsylvania’s unemployment insurance laws. QCEW employment is based on the location of the position not where the person resides.
Represents a comprehensive collection of occupational wage data available for Pennsylvania. Data are collected through the Occupational Employment Statistics program in cooperation with the U.S. Department of Labor’s Bureau of Labor Statistics. Occupational wage information can be used as a reference by educators, PACareerLink® staff, career counselors, Workforce Development Boards, economic developers, program planners, and others.
Occupational wages do not represent a time series. Due to the prescribed production methodology, current occupational wages are not comparable to previously published occupational wages.
This dataset reports number of successful naloxone reversals by police officers, as self-reported by municipal police departments, Capitol Police, and Pennsylvania State police. The data is stratified by county and by year. Note that there is no legislation mandating that law enforcement report naloxone reversals to DDAP; these data represent voluntary self-reports from departments.
NA - Not applicable. No FIPS code or county code exist for Pennsylvania State Police and Capitol Police. Also, counties labelled “NA” do not have municipal police departments and are only covered by Pennsylvania State Police.
The data represents the percent change in wages for an individual who has wages recorded in the Unemployment Compensation (UC) wage record file in the quarter in which they completed Industry Partnership training and wages found in the UC wage record file for that individual four quarters later. The change could be an increase or a decrease in wages. For example, if an individual completed training in the third quarter of 2013 and earned $5,000 in that quarter and earned $7,500 in the third quarter of 2014 the percent change for that individual would be 50%. The file incudes a count of all individuals who benefited from industry partnership training, the workforce development area of the industry partnership, the training program completed and the percentage change in wages per individual training. The top line of the file includes the overall percentage change for all trainings.
*The goal for Labor & Industry is based on receiving $10 million to fund Industry Partnerships.
This dataset is for Program Year 2013-2017 and will be updated annually due to federal release schedule.
There are many reasons why an individual’s wage may have changed dramatically. Some of the reasons for negative wage changes or large increases in wages are listed below (not an exhaustive list).
• An individual may have left the job, was laid off, or retired within the year after they were trained.
• An individual may have become ill and left work.
• An individual may have accepted a job in or moved to another state.
• An individual may have been working two jobs and switched to one, or vice versa.
• An individual’s hours may have been reduced/increased during a quarter.
• Overtime hours may have been reduced/increased during a quarter.
• An individual may have taken family leave.
• A bonus could have been paid right after training was completed.
• Wage records may not have been reported.
• An employer may have closed and laid off all of their employees.
The data depicts each training opportunity completed by individuals through Industry Partnership training funding by Program Year (PY). The file includes all training and the number of individuals that benefited from the training and the workforce development area in which the industry partnership is organized. The data show the amount of training that is driven by employer demand to ensure PA’s employers remain competitive and workers retain employment and enhance their career opportunities.
This is Department of Labor and Industry(DLI) dataset.
There are 5 other Workforce training files from Department of Community and Economic Development (DCED) that when combined with this file support the Governor's Workforce Development Goal of training 340,000 individuals by 2020
This data set provides an estimate of the number of people living with Human Immunodeficiency Virus (HIV) Disease at the end of each year for 2012 through 2016 and the number of these persons who have injection drug use identified as the primary risk for having acquired the infection. The data sets also provides the number of new diagnoses of HIV Disease by county among all persons and among those with injection drug identified as the primary risk. These data are derived through HIV surveillance activities of the Pennsylvania Department of Health. Laboratories and providers are required to report HIV test results for all individuals with a result that indicates the presence of HIV infection. These include detectable viral load results and CD4 results below 200 cells. These data are reported electronically to the Pennsylvania National Electronic Disease Surveillance System. The most recent patient address information obtained from all reports (both HIV and non-HIV reports) is used to identify last known county of residence in 2016. Cases are also matched to lists that identify individuals who have been reported to be living outside of Pennsylvania by the US Centers for Disease Control and Prevention (CDC) to remove cases that are presumed to have moved from Pennsylvania. Address data for Philadelphia County cases are extracted from the Pennsylvania enhanced HIV/AIDS Reporting System.
IDU: use of non-prescribed injection drugs (e.g., heroin, fentanyl, cocaine, etc.)
HIV Disease: Confirmed infection with the Human Immunodeficiency Virus (HIV). Acquired Immunodeficiency Syndrome (AIDS) is a stage of HIV Disease marked by a low CD4 count and/or certain co-morbid conditions.
Percent of Pennsylvania newborn hospital stays, categorized by the presence or absence of Neonatal Abstinence Syndrome (NAS), with Medicaid as the Anticipated Primary Payer.
Neonatal Abstinence Syndrome, or neonatal drug withdrawal, is an array of problems that develops shortly after birth in newborns who were exposed to addictive drugs, most often opioids, while in the mother’s womb. Withdrawal signs develop because these newborns are no longer exposed to the drug for which they have become physically dependent.
This analysis is restricted to newborns with Pennsylvania-state residence who were hospitalized in Pennsylvania hospitals.
PHC4’s database contains statewide hospital discharge data submitted to PHC4 by Pennsylvania hospitals. Every reasonable effort has been made to ensure the accuracy of the information obtained from the Uniform Claims and Billing Form (UB-82/92/04) data elements. Computer collection edits and validation edits provide opportunity to correct specific errors that may have occurred prior to, during or after submission of data. The ultimate responsibility for data accuracy lies with individual providers.
PHC4 agents and staff make no representation, guarantee, or warranty, expressed or implied that the data received from the hospitals are error-free, or that the use of this data will prevent differences of opinion or disputes with those who use published reports or purchased data. PHC4 will bear no responsibility or liability for the results or consequences of its use.