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Case Closing without a New Offense CY 2018 By County as Reported by the Juvenile Court Judges' Commission
data.pa.gov | Last Updated 2022-10-17T20:21:58.000ZThe juvenile justice system has a responsibility to protect the community from known juvenile offenders. Juveniles who do not commit a new offense while under court supervision have a higher probability of remaining crime free. This data represents the number and percentage of juveniles who successfully completed supervision without a new offense resulting in a Consent Decree, Adjudication of Delinquency, ARD, Nolo Contendere, or finding of guilt in a criminal procedure. <br/> CY - Calendar Year This dataset is contained within the Juvenile Court Judges' Commission’s 2018 Statewide Juvenile Justice Outcome Measure report: this report reflects outcomes of juvenile offenders whose cases were closed during the report period and who have received a period of supervision from a county juvenile probation department. These reported outcomes are associated with community protection, accountability, and competency development; three core goals of Pennsylvania's juvenile justice system. Since 2009, county juvenile probation departments have supervised and closed 126,006 cases. The proportion of cases closed successfully (without a new offense) during this time is 84.1%. For the year 2018, the proportion of cases closed successfully was 85.4%.
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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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Uninsured Population Census Data CY 2009-2014 Human Services
data.pa.gov | Last Updated 2022-10-18T14:19:11.000ZThis data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 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.
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COVID-19 Federal Pharmacy Partners Long Term Care Facility Vaccine Clinics Current Health
data.pa.gov | Last Updated 2024-05-08T15:07:19.000ZThe long-term care facility clinic data shows the facilities that have clinics scheduled for a certain week. These clinics will be held by either CVS or Walgreens through their work to vaccinate within the Federal Pharmacy Partnership. The federal pharmacy partners dataset represents the clinics that CVS and Walgreens are holding for a given week at long-term care facilities that are part of the federal pharmacy mission. These are nursing homes, assisted living facilities, and other long-term care facilities receiving vaccinations. <br> For the Pfizer vaccination the clinics are 3-weeks apart. For the Moderna vaccination the clinics are 4-weeks apart.<br> This dataset will be updated Wednesday’s at 12:00pm.
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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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Dangerous Dogs 1996-Current County Agriculture
data.pa.gov | Last Updated 2020-02-27T14:35:08.000ZHistorical results of Dangerous Dogs in Pennsylvania. A dangerous dog is one that has: (1) Inflicted severe injury on a human being without provocation on public or private property. (2) Killed or inflicted severe injury on a domestic animal, dog or cat without provocation while off the owner’s property. (3) Attacked a human being without provocation. (4) Been used in the commission of a crime. And the dog has either or both of the following: (1) A history of attacking human beings and/or domestic animals, dogs or cats without provocation. (2) A propensity to attack human beings and/or domestic animals, dogs or cats without provocation. *A propensity to attack may be proven by a single incident. Severe injury is defined as, [3 P.S. § 459-102] “Any physical injury that results in broken bones or disfiguring lacerations requiring multiple sutures or cosmetic surgery.” More information can be found here - https://www.agriculture.pa.gov/Animals/DogLaw/Dangerous%20Dogs/Pages/default.aspx More information on Chapter 27 Regulations - https://www.agriculture.pa.gov/Animals/DogLaw/Dangerous%20Dogs/Documents/Chapter%2027%20Dangerous%20Dogs.pdf PDF's for Chapter 27 and Pennsylvania Dog Laws are attached to the metadata
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Drug and Alcohol Treatment Get Help Now Intake Hotline November 2016 - Current Statewide Drug and Alcohol Programs
data.pa.gov | Last Updated 2023-09-19T14:35:29.000ZThis dataset reports statewide and county numbers of calls and intakes by individuals seeking treatment from hotline staff since the inception of Pennsylvania’s Get Help Now Hotline, text line, and chat line in November 2016. When a field is blank the information is not available; these data were not collected at the time of the phone call.
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COVID-19 Aggregate Hospitalizations Current Weekly County Health NO FURTHER UPDATES
data.pa.gov | Last Updated 2024-05-08T14:27:07.000ZWeekly updates have finished with the June 28th update. “Note: Beginning 7/13/2022, the hospitals are no longer reporting data on airborne isolation beds resulting in null values being displayed for the airborne isolation bed metrics.” This dataset contains aggregate hospitalization data related to COVID-19 patient which includes availability of ICU beds, patients on ventilators, ventilators in use, and total patients hospitalized data at the state and county level for Pennsylvania residents. Data will be updated between 11:30 am to 1:30pm each Wednesday.
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Find Naloxone at a Pharmacy Near Me Current Statewide Department of State and Health
data.pa.gov | Last Updated 2022-10-18T16:13:27.000ZNaloxone is a life-saving medication that can reverse an overdose that is caused by an opioid drug (i.e. prescription pain medication or heroin). Naloxone may be obtained at a pharmacy using the statewide standing order (https://www.health.pa.gov/topics/Documents/Opioids/General%20Public%20Standing%20Order.pdf) signed by Secretary of Health, Dr. Rachel Levine. Naloxone may be covered by insurance and consumers are encouraged to check with their insurers to understand their insurance coverage for naloxone. Individuals covered by Medicaid can obtain naloxone without a copay. A video demonstrating how to administer nasal spray naloxone may be found here - https://www.youtube.com/watch?v=v26cDao4AcI&feature=youtu.be <br> More information about how naloxone works as a medication and frequently asked questions about obtaining and using naloxone may be found on the Department of Health’s Naloxone webpage (https://www.health.pa.gov/topics/disease/Opioids/Pages/Naloxone.aspx) <br> *This is a comprehensive listing of all pharmacies registered with the Department of State in Pennsylvania and does not guarantee that the pharmacy listed will have naloxone in stock.
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Chart - Annual Amount of Drugs Seized by type State Police
data.pa.gov | Last Updated 2024-04-08T19:00:21.000ZThis dataset contains summary information on opioid drug seizures and arrests made by Pennsylvania State Police (PSP) personnel, stationed statewide, on a quarterly basis. Every effort is made to collect and record all opioid drug seizures and arrests however, the information provided may not represent the totality of all seizures and opioid arrests made by PSP personnel. Data is currently available from January 1, 2013 through most current data available. Seizure Opioids seized as a result of undercover buys, search warrants, traffic stops and other investigative encounters. An incident is a Pennsylvania State Police (PSP) recorded violation of the Controlled Substance Act and an entry into the PSP Statistical Narcotics System. By regulation, entry is made by the PSP as stated in PSP Administrative Regulation 9-6: When violations of The Controlled Substance, Drug, Device and Cosmetic Act are reported, the required statistical information concerning the incident shall be entered into the Statistical Narcotic Reporting System (SNRS). Incidents may include undercover buys, search warrants, traffic stops and other investigative encounters So, an “incident” is not based on any arrest, but on a reported violation, though it often can include arrests. The incidents that are selected and forwarded to the portal are those that include a record of one or more seizures of the opioid drugs. In turn, a subset of those selected incidents also contains a record of one or more arrests. This is PSP data only, it would not include any Federal case/incident data.