The Food and Drug Administration (FDA) conducts careful inspections of regulated facilities to determine a firm's compliance with regulations and the Food, Drug and Cosmetic Act.

This dataset is extracted from the record of medical equipment advertisements registered by various county and city health bureaus. The displayed fields are limited to those open in the system. However, this dataset may be subject to subsequent modifications at the discretion, and does not mean that the products of the disposed entity are illegal. Please use it with caution.

This dataset provides annual statistics on violations found during on-site audits of controlled drugs and is updated annually for use by the general public and other users.

When it is consistent with the public protection responsibilities of the agency and depending on the nature of the violation, it is the Food and Drug Administration's (FDA's) practice to give individuals and firms an opportunity to take voluntary and prompt corrective action before it initiates an enforcement action. Warning Letters are issued to achieve voluntary compliance and to establish prior notice. The use of Warning Letters and the prior notice policy are based on the expectation that most individuals and firms will voluntarily comply with the law. See http://www.fda.gov/ICECI/ComplianceManuals/RegulatoryProceduresManual/uc... for additional infomation on Warning Letters.

This data set is extracted from the records of drug advertising handled by the health bureaus of various counties and cities. The displayed fields are limited to those open to the system. However, this data set may be subject to subsequent revisions and discretion, and does not necessarily mean that the products of the subject of the disposal are illegal. Please use caution when referring to it.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Dataset 0002 (DS0002) contains the data from the State Design Data. This file contains 7 variables and 82,139 cases. The state identifier in the State Design file reflects the participant's state of residence at the time of selection and recruitment for the PATH Study. Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1012 (DS1012) contains the data from the Wave 1 Youth and Parent Questionnaire. This file contains 1,431 variables and 13,651 cases. Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 1, which is also their state of residence at the time of recruitment. Dataset 1611 (DS1611) contains the Tobacco Universal Product Code (UPC) data from Wave 1. This data file contains 32 variables and 8,601 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 1. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used

Provide the relevant information on the drug abuse urine testing agency approved by this department for public reference.

Analysis of ‘💉 Opioid Overdose Deaths’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/opioid-overdose-deathse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

Opioid addiction and death rates in the U.S. and abroad have reached "epidemic" levels. The CDC's data reflects the incredible spike in overdoses caused by drugs containing opioids.

The United States is experiencing an epidemic of drug overdose (poisoning) deaths. Since 2000, the rate of deaths from drug overdoses has increased 137%, including a 200% increase in the rate of overdose deaths involving opioids (opioid pain relievers and heroin). Source: CDC

In-the-News:

• STAT: 26 overdoses in just hours: Inside a community on the front lines of the opioid epidemic
• NPR: Organ Donations Spike In The Wake Of The Opioid Epidemic, Deadly Opioid Overwhelms First Responders And Crime Labs in Ohio
• Scientific American: Wave of Overdoses with Little-Known Drug Raises Alarm Amid Opioid Crisis
• Washington Post: A 7-year-old told her bus driver she couldn’t wake her parents. Police found them dead at home.
• Wall Street Journal: For Small-Town Cops, Opioid Scourge Hits Close to Home
• Food & Drug Administration: FDA launches competition to spur innovative technologies to help reduce opioid overdose deaths

This data was compiled using the CDC's WONDER database. Opioid overdose deaths are defined as: deaths in which the underlying cause was drug overdose, and the ICD-10 code used was any of the following: T40.0 (Opium), T40.1 (Heroin), T40.2 (Other opioids), T40.3 (Methadone), T40.4 (Other synthetic narcotics), T40.6 (Other and unspecified narcotics).

Age-adjusted rate of drug overdose deaths and drug overdose deaths involving opioids
http://i.imgur.com/ObpzUKq.gif" alt="Opioid Death Rate" style="">
Source: CDC

What are opioids?
Opioids are substances that act on opioid receptors to produce morphine-like effects. Opioids are most often used medically to relieve pain. Opioids include opiates, an older term that refers to such drugs derived from opium, including morphine itself. Other opioids are semi-synthetic and synthetic drugs such as hydrocodone, oxycodone and fentanyl; antagonist drugs such as naloxone and endogenous peptides such as the endorphins.[4] The terms opiate and narcotic are sometimes encountered as synonyms for opioid. Source: Wikipedia

contributors-wanted See comment in Discussion

Footnotes

• The crude rate is per 100,000.
• Certain totals are hidden due to suppression constraints. More Information: http://wonder.cdc.gov/wonder/help/faq.html#Privacy.
• The population figures are briged-race estimates. The exceptions being years 2000 and 2010, in which Census counts are used.
• v1.1: Added Opioid Prescriptions Dispensed by US Retailers in that year (millions).

Citation: Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Cause of Death 1999-2014 on CDC WONDER Online Database, released 2015. Data are from the Multiple Cause of Death Files, 1999-2014, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. Accessed at http://wonder.cdc.gov/mcd-icd10.html on Oct 19, 2016 2:06:38 PM.

Citation for Opioid Prescription Data: IMS Health, Vector One: National, years 1991-1996, Data Extracted 2011. IMS Health, National Prescription Audit, years 1997-2013, Data Extracted 2014. Accessed at NIDA article linked (Figure 1) on Oct 23, 2016.

Data Use Restrictions:
The Public Health Service Act (42 U.S.C. 242m(d)) provides that the data collected by the National Center for Health Statistics (NCHS) may be used only for the purpose for which they were obtained; any effort to determine the identity of any reported cases, or to use the information for any purpose other than for health statistical reporting and analysis, is against the law. Therefore users will:
Use these data for health statistical reporting and analysis only.
For sub-national geography, do not present or publish death counts of 9 or fewer or death rates based on counts of nine or fewer (in figures, graphs, maps, tables, etc.).
Make no attempt to learn the identity of any person or establishment included in these data.
Make no disclosure or other use of the identity of any person or establishment discovered inadvertently and advise the NCHS Confidentiality Officer of any such discovery.
Eve Powell-Griner, Confidentiality Officer
National Center for Health Statistics
3311 Toledo Road, Rm 7116
Hyattsville, MD 20782
Telephone 301-458-4257 Fax 301-458-4021

This dataset was created by Health and contains around 800 samples along with Crude Rate, Crude Rate Lower 95% Confidence Interval, technical information and other features such as: - Year - Deaths - and more.

How to use this dataset

• Analyze Crude Rate Upper 95% Confidence Interval in relation to Prescriptions Dispensed By Us Retailers In That Year (millions)
• Study the influence of State on Crude Rate
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Health

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Citation United States Department of Health and Human Services (DHHS), Public Health Service (PHS), Centers for Disease Control (CDC) / Food and Drug Administration (FDA), Vaccine Adverse Event Reporting System (VAERS) 1990 - 08/05/2022, CDC WONDER On-line Database. Accessed at http://wonder.cdc.gov/vaers.html on Aug 18, 2022 1:33:27 AM

Query Criteria:Event Category:Death State / Territory:California Vaccine Manufacturer:PFIZER\BIONTECH Vaccine Products:COVID19 VACCINE (COVID19) VAERS ID:All Group By:Symptoms; Vaccine Type; Age; VAERS ID; State / Territory

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Disclaimer

VAERS accepts reports of adverse events that occur following vaccination. Anyone, including healthcare providers, vaccine manufacturers, and the public, can submit reports to the system. While very important in monitoring vaccine safety, VAERS reports alone cannot be used to determine if a vaccine caused or contributed to an adverse event or illness. Vaccine providers are encouraged to report any clinically significant health problem following vaccination to VAERS even if they are not sure if the vaccine was the cause. In some situations, reporting to VAERS is required of healthcare providers and vaccine manufacturers. VAERS reports may contain information that is incomplete, inaccurate, coincidental, or unverifiable. Reports to VAERS can also be biased. As a result, there are limitations on how the data can be used scientifically. Data from VAERS reports should always be interpreted with these limitations in mind. The strengths of VAERS are that it is national in scope and can often quickly detect an early hint or warning of a safety problem with a vaccine. VAERS is one component of CDC's and FDA's multifaceted approach to monitoring safety after vaccines are licensed or authorized for use. There are multiple, complementary systems that CDC and FDA use to capture and validate data from different sources. VAERS is designed to rapidly detect unusual or unexpected patterns of adverse events, also referred to as "safety signals." If a possible safety signal is found in VAERS, further analysis is performed with other safety systems, such as the CDC’s Vaccine Safety Datalink (VSD) and Clinical Immunization Safety Assessment (CISA) Project, or in the FDA BEST (Biologics Effectiveness and Safety) system. These systems are less impacted by the limitations of spontaneous and voluntary reporting in VAERS and can better assess possible links between vaccination and adverse events. Additionally, CDC and FDA cannot provide individual medical advice regarding any report to VAERS. Key considerations and limitations of VAERS data:

The number of reports alone cannot be interpreted as evidence of a causal association between a vaccine and an adverse event, or as evidence about the existence, severity, frequency, or rates of problems associated with vaccines. Reports may include incomplete, inaccurate, coincidental, and unverified information. VAERS does not obtain follow up records on every report. If a report is classified as serious, VAERS requests additional information, such as health records, to further evaluate the report. VAERS data are limited to vaccine adverse event reports received between 1990 and the most recent date for which data are available. VAERS data do not represent all known safety information for a vaccine and should be interpreted in the context of other scientific information.

VAERS data available to the public include only the initial report data to VAERS. Updated data which contains data from medical records and corrections reported during follow up are used by the government for analysis. However, for numerous reasons including data consistency, these amended data are not available to the public.

Additionally, reports to VAERS that appear to be false or fabricated with the intent to mislead CDC and FDA may be reviewed before they are added to the VAERS database. Knowingly filing a false VAERS report is a violation of Federal law (18 U.S. Code § 1001) punishable by fine and imprisonment.