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This data set includes the estimated number of individuals in Pennsylvania with Drug Use Disorder, which is an approximation for Opioid Use Disorder prevalence. The estimates are developed by applying mortality weights derived from the CDC’s National Center for Health Statistics to statewide illicit drug use estimates from the National Survey on Drug Use and Health (NSDUH, sponsored by the Substance Abuse and Mental Health Services Administration).
Updated
March 18 2021
Views
777
This dataset contains the total counts of PA Department of Human Services (DHS) Medical Assistance (MA) individuals diagnosed with Opioid Use Disorder (OUD) or OUD Poisoning. Also included are individuals receiving MAT (Medication assisted treatment - the use of medications in combination with counseling and behavioral therapies for the treatment of substance use disorders.) NOT diagnosed in the same period. Counts are reported by case county and cover calendar years 2015 - 2018.
Updated
September 14 2020
Views
852
This 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.
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.
Updated
September 20 2018
Views
397
This dataset is quarterly data by county, including inmate admissions, average Texas Christian University Drug Screen II (TCU) score, number and percent of inmate admissions who identify opioids as top three drug of choice, inmates with a substance abuse problem, and number and percent who used opioids in the year prior to admission.
This data is available starting with the first Quarter of Calendar Year 2016.
This data is available starting with the first Quarter of Calendar Year 2016.
Updated
April 2 2020
Views
944
This 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.
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.
Updated
March 2 2020
Views
237
The county aggregate number of individuals on Medical Assistance (MA, Medicaid) who have filled a Naloxone Prescription. This includes all individuals on Medicaid. Naloxone is an opioid antagonist. It acts on the CNS to block the effects of narcotics, especially the "high'' feeling that makes you want to use them. It will not produce any narcotic-like effects or cause mental or physical dependence. Numbers are for the Calendar Year and updated with as current as possible until the next data refresh.
Updated
September 14 2020
Views
435
Filtered View
This 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.
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.
Updated
May 20 2020
Views
92
This dataset contains the total counts of PA Department of Human Services (DHS) Medical Assistance (MA) individuals diagnosed with Opioid Use Disorder (OUD) or OUD Poisoning. Also included are individuals receiving MAT (Medication assisted treatment - the use of medications in combination with counseling and behavioral therapies for the treatment of substance use disorders.) NOT diagnosed in the same period. Limited to the Newly Eligible (Under the Medical Assistance Expansion Program. Find more information here: http://www.dhs.pa.gov/cs/groups/webcontent/documents/document/c_257436.pdf) segment of DHS population. Internally defined as DHS Category of Assistance = MG (Modified Adjusted Gross Income - MAGI) MG and Program Status = 91 (Newly Eligible). Counts are reported by Pennsylvania case county and covers calendar years 2015 -2018.
Updated
September 15 2020
Views
707
Filtered View
This data set includes the estimated number of individuals in Pennsylvania with Drug Use Disorder, which is an approximation for Opioid Use Disorder prevalence. The estimates are developed by applying mortality weights derived from the CDC’s National Center for Health Statistics to statewide illicit drug use estimates from the National Survey on Drug Use and Health (NSDUH, sponsored by the Substance Abuse and Mental Health Services Administration).
Updated
March 18 2021
Views
143
View annual counts of Accidental or Undetermined overdose deaths for 2012 forward, including provisional estimates of annual counts of overdose deaths for recent years, as noted with an asterisk and the month the data was pulled.
NOTE: Finalized death records for overdose deaths are often delayed by 3-6 months. Counties labeled “no value” have data suppressed because the counts are between 1 and 9.
- Overdose Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are identified using underlying cause-of-death codes X40–X44, and Y10–Y14, and include the following:
- R99 when the Injury Description indicates an overdose death.
- X49 when literal COD is Mixed or Combined or Multiple Substance Toxicity, as these are likely drug overdoses
- X47 when substance indicated is difluoroethane, alone or in combination with other drugs
- Source Pennsylvania Prescription Drug Monitoring Program*
* These data were supplied by the Bureau of Health Statistics and Registries, Harrisburg, Pennsylvania. The Bureau of Health Statistics and Registries specifically disclaims responsibility for any analyses, interpretations or conclusions.
- Estimates are broken down by type of drugs involved in the overdose
- Any Drug Overdose Death - all drug overdose deaths, regardless of type of drug involved, excluding alcohol only deaths
- Opioid Overdose Death - any overdose death involving opioids, prescription or illegal
NOTE: Finalized death records for overdose deaths are often delayed by 3-6 months. Counties labeled “no value” have data suppressed because the counts are between 1 and 9.
- Overdose Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are identified using underlying cause-of-death codes X40–X44, and Y10–Y14, and include the following:
- R99 when the Injury Description indicates an overdose death.
- X49 when literal COD is Mixed or Combined or Multiple Substance Toxicity, as these are likely drug overdoses
- X47 when substance indicated is difluoroethane, alone or in combination with other drugs
- Source Pennsylvania Prescription Drug Monitoring Program*
* These data were supplied by the Bureau of Health Statistics and Registries, Harrisburg, Pennsylvania. The Bureau of Health Statistics and Registries specifically disclaims responsibility for any analyses, interpretations or conclusions.
- Estimates are broken down by type of drugs involved in the overdose
- Any Drug Overdose Death - all drug overdose deaths, regardless of type of drug involved, excluding alcohol only deaths
- Opioid Overdose Death - any overdose death involving opioids, prescription or illegal
Updated
March 16 2021
Views
214
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