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Rate of Dependent Children Removed from their Home Where Parental Drug Use was Factor FFY 2017 - Current Human Services
data.pa.gov | Last Updated 2022-02-21T17:56:36.000ZThis dataset summarizes the number of dependent children (less than 18 years old) removed from households due to parental drug abuse. The data indicates if the dependent children were placed in kinship care or not. The total number of children in this data set are provided by the U.S. Census Bureau’s American Community Survey (ACS), which publishes 5 year estimates of the population. The most recent year of entries in this data set may be available before the corresponding ACS population estimates for that year are published. In that case, the data set uses values from the most recently published ACS estimates and notes the year from which those estimates are pulled. These values are updated once the Census Bureau releases the most recent estimates.” *Kinship care refers to the care of children by relatives or, in some jurisdictions, close family friends (often referred to as fictive kin). Relatives are the preferred resource for children who must be removed from their birth parents because it maintains the children's connections with their families. *The Adoption and Foster Care Analysis and Reporting System (AFCARS) definition of parental drug abuse is “Principal caretaker’s compulsive use of drugs that is not of a temporary nature.”
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Workforce Innovation Opportunity Act (WIOA) Title III Performance Accountability Metrics PY 2017-2018 - Current Annual Labor and Industry
data.pa.gov | Last Updated 2022-06-09T15:50:25.000ZA comprehensive collection of data that assesses the effectiveness of Pennsylvania in achieving positive outcomes for individuals served by the workforce development system’s Title III Wagner-Peyser (Labor Exchange) program. Data is compiled in compliance with US Department of Labor’s Employment and Training Administration guidance on Workforce Innovation and Opportunity Act (WIOA) Performance Accountability. Data is available for the state and each of the CareerLink® offices in the commonwealth.
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Uninsured Population Census Data 1-year estimates 2017-Current Statewide Human Services and Insurance
data.pa.gov | Last Updated 2022-02-21T19:25:46.000ZThe American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates for Health Insurance Coverage in Pennsylvania and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. A blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area. Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level. While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015).
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Maternal Opioid Use Hospital Stays 2016-2017 County Health Care Cost Containment Council (PHC4)
data.pa.gov | Last Updated 2022-10-17T20:23:36.000ZCountywide counts of maternal hospital stays with opioid use and countywide rates of maternal hospital stays with opioid use per 1,000 maternal stays. Maternal stays include those involving a delivery, as well as other pregnancy-related stays. Opioid use, or opioid use disorder, is a diagnosis indicating opioid dependence, abuse, or use. Some opioid drugs may be prescribed as part of medication-assisted treatment to relieve withdrawal symptoms and psychological cravings often associated with opioid use disorders. Opioid use during pregnancy can lead to Neonatal Abstinence Syndrome (NAS) for newborns. This analysis is restricted to maternal hospital stays for Pennsylvania-state residents who were hospitalized in Pennsylvania hospitals. Disclaimer: 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.
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Annual Hospitalizations by Gender
data.pa.gov | Last Updated 2022-07-07T19:09:18.000ZThis indicator includes the rate of hospitalization per 1,000 individuals estimated to have Opioid Use Disorder (OUD) for Opioid Use Disorder, Intracranial and intraspinal Abscess, Osteomyelitis, Endocarditis, Soft skin tissue infection, and Viral Hepatitis (B, C, and D) for individuals diagnosed with OUD in the same calendar year. Analyses were completed by the University of Pittsburgh using data from the PA Health Care Cost Containment Council and in cooperation with PA DOH. 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.
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Uninsured Population Census Data 5-year estimates for release years 2017-Current County Human Services and Insurance
data.pa.gov | Last Updated 2022-02-21T19:25:39.000ZThe American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates by county for Health Insurance Coverage and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. The 5-year estimates are used to provide detail on every county in Pennsylvania and includes breakouts by Age, Gender, Race, Ethnicity, Household Income, and the Ratio of Income to Poverty. An blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area. Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level. While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015). In the case of ACS multiyear estimates, the period is 5 calendar years (e.g., the 2011–2015 ACS estimates cover the period from January 2011 through December 2015). Therefore, ACS estimates based on data collected from 2011–2015 should not be labeled “2013,” even though that is the midpoint of the 5-year period. Multiyear estimates should be labeled to indicate clearly the full period of time (e.g., “The child poverty rate in 2011–2015 was X percent.”). They do not describe any specific day, month, or year within that time period.
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Newly Identified Confirmed Chronic Hepatitis C Age 15-34 Year 2007-2016 Health
data.pa.gov | Last Updated 2022-10-17T20:05:23.000ZThis data set provides an estimate of the number of people aged 15-34 years with newly identified confirmed chronic (or past/present) hepatitis C infection, by county and by year. The dataset is limited to persons aged 15 to 34 because hepatitis C infection is usually asymptomatic for decades after infection occurs. Cases are usually identified because they have finally become symptomatic, or they were screened. Until very recently, screening for hepatitis C was not routinely performed. This makes it very challenging to identify persons with recent infection. Limiting the age of newly identified patients to 15-34 years makes it more likely that the cases included in the dashboard were infected fairly recently. It is not meant to imply that the opioid crisis’ effect on hepatitis C transmission is limited to younger people. The process by which case counts are determined is as follows: Case reports, which include lab test results and address data, are sent to Pennsylvania’s electronic disease surveillance system (PA-NEDSS). Confirmation status is determined by public health investigators who evaluate test results against the CDC case definition for hepatitis C in place for the year in which the patient was first reported (https://wwwn.cdc.gov/nndss/conditions/hepatitis-c-chronic/). Reportable disease data, including hepatitis C, is extracted from PA-NEDSS, combined with similar data sent by the Philadelphia Department of Public Health (PDPH, which uses a separate surveillance system), and sent to CDC. Case data sent to CDC (from PA-NEDSS and PDPH combined) are used to create a statewide reportable disease dataset. This statewide file was used to generate the dashboard dataset. Note that the term that CDC has used to denote persons with hepatitis C infection that is not known to be acute has switched back and forth between “Hepatitis C, past or present” and “Hepatitis C, chronic” over the past several years. The CDC case definition for hepatitis C, chronic (or past or present) changed in 2005, 2010, 2011, 2012, and 2016. Persons reported as confirmed in one year may not have been considered confirmed in another year. For example, patients with a positive radioimmunoblot assay (RIBA) or elevated enzyme immunoassay (EIA) signal-to-cutoff level were counted as confirmed in 2012, but not counted as confirmed in 2016. Data sent to CDC’s National Notifiable Disease Surveillance System use a measure for aggregating cases by year called the MMWR year. The MMWR, or the Morbidity and Mortality Weekly Report, is an official publication by CDC and the means by which CDC has historically presented aggregated case count data. Since data in the MMWR are presented by week, the MMWR year always starts on the Sunday closest to Jan 1 and ends on the Saturday closest to Dec 31. The most recent year for which case counts are finalized is 2016. Annual case counts are finalized in May of the following year. The patient zip code, as submitted to PA-NEDSS, is used to determine the case’s county of residence at the time of initial case report. In some instances, the patient zip code is unavailable. In those circumstances, the zip code of the provider that ordered the lab test is used as a proxy for patient zip code. Users should note that the state prison system routinely screens all incoming inmates for hepatitis C. If these inmates are determined to be confirmed cases, they are assigned to the county in which they were incarcerated when their confirmed hepatitis C was first identified. Hepatitis C case counts in counties with state prisons should be interpreted cautiously in light of this enhanced screening activity.
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Governor's Executive Budget Program Measures SFY 2017 - Current Annual Statewide Health
data.pa.gov | Last Updated 2023-03-22T22:37:44.000ZThe information included in this dataset is for the Governor’s Executive Budget and provides key Program Measures by Agency or Office. <br> The mission of the Department of Health is to promote healthy behaviors, prevent injury and disease, and to assure the safe delivery of quality health care for all people in Pennsylvania.<br> To accomplish this mission, the department works collaboratively with public and private community partners to facilitate the development of an effective public health system. The department licenses and regulates a variety of health facilities, and provides outreach, education, prevention and treatment services. Community-based groups receive grants to provide essential services to the commonwealth’s citizens including programs for women and children, nutrition, immunization, diagnosis and treatment of certain blood and communicable diseases, cancer control and prevention.
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Rate of Newborn Hospital Stays with Withdrawal Symptoms from Maternal Use of Drugs of Addiction or Maternal Substance Exposure CY 2016-Current County Health Care Cost Containment Council (PHC4)
data.pa.gov | Last Updated 2022-10-17T20:13:28.000ZThis dataset summarizes the rate of newborn/neonatal hospital stays in which there is a diagnosis of withdrawal symptoms from maternal use of drugs of addiction or diagnosis of maternal substance exposure in the first 28 days of life, relative to the total number of birth hospitalizations. Analyses were completed by the University of Pittsburgh using data from the PA Health Care Cost Containment Council and in cooperation with PA DOH. 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.
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Individuals with Medical Assistance (MA) receiving Medication-Assisted Treatment (MAT) CY 2015-Current Annual County Human Services
data.pa.gov | Last Updated 2024-03-22T12:18:10.000ZThis dataset contains the count of individuals with Medical Assistance coverage (MA) receiving any form of MAT (Medication-Assisted treatment) by case county. The counts cover calendar years 2015 - 2018. If a count field is null, then the count is suppressed due to low numbers. If the county is null, then the county is unknown.