Overview of the Prevention Agenda Dashboard

  • The New York State Prevention Agenda Dashboard is an interactive visual presentation of the most current tracking indicator data to track progress of the New York State’s Health Improvement Plan at state and county levels. It serves as a key source for monitoring progress that communities around the state have made regarding meeting the Prevention Agenda objectives.
  • Prevention Agenda State Dashboard
  • The state dashboard home page provides a quick view of the most currently available data and the 2030 objectives for nearly one hundred tracking indicators (n=92). Among these are the tracking indicators for the Prevention Agenda 2025-2030 (n=84), as well as selected important public health indicators related to premature deaths, preventable hospitalizations, and healthcare (n=8). On this page, indicators are grouped by domain and the most current data are compared to the previous data period to assess the annual progress for each indicator. From here, historical (trend) data for the tracking indicators are easily accessed. We have also enhanced the state level dashboard for 54 indicators, with drill-down data and visualizations by major socio-demographic characteristics such as age group, race and ethnicity, sex, region, health insurance status, level of education, etc., where available. These visualizations and data can be accessed from the state dashboard link above.
  • Prevention Agenda County Dashboard
  • The county dashboard home page includes the most current data available for 55 tracking indicators, again grouped by domain. Each county in the state has its own dashboard that can be accessed via the "Select County" dropdown menu at the top of the county dashboard. County maps and graphs and comparison across counties are available. Data at sub-county level, including ZIP Code and Minor Civil Division/Community District, are available for 8 indicators. These visualizations and data can be accessed from the county dashboard link above.

Prevention Agenda 2025-2030 Data Export Links

Baseline Data and Objectives

Select domain(s) and/or indicator(s) from the dropdown lists and click "Apply Filters" to filter the table. Click "Reset" to return the table to its original view.

*Data for baseline years reflected on the most current dashboard are subject to small changes/variation to the original baseline due to systematic updates/corrections from the data source.

**Objectives are based on a percentage change improvement from baseline. In the event baseline data is updated, the objectives shown on the current dashboard may change slightly versus the original Prevention Agenda document.

Technical Notes

 Definition of Indicators
Dynamic Prevention Agenda Filters

Select domain(s) and/or indicator(s) from the dropdown lists and click “Apply Filters” to filter the table. Click “Reset” to return the table to its original view.

a Vital Records (Vital Statistics):
Vital Event Registration:
New York State consists of two registration areas, New York City and New York State Exclusive of New York City (also referred to as Rest of State). New York City (NYC) includes the five counties of Bronx, Kings (Brooklyn), New York (Manhattan), Queens and Richmond (Staten Island); the remaining 57 counties comprise New York State Exclusive of New York City. The Bureau of Vital Records, New York State Department of Health (NYSDOH), processes data from live birth, death, fetal death and marriage certificates recorded in New York State Exclusive of New York City. Through a cooperative agreement, the New York State Department of Health receives data on live births, deaths, fetal deaths and marriages recorded in New York City from the New York City Department of Health and Mental Hygiene (NYCDOHMH). The New York State Department of Health also receives data, from other states and Canada, on live births and deaths recorded outside of New York State to residents of New York State.

Vital Event indicators for NYC geographical areas reported by NYSDOH and NYCDOHMH may be different since the former may include all NYC residents' events regardless of where they occurred and the latter reports only events to NYC residents that occurred in NYC. The indicators may also differ due to timing and/or completeness of data.

The counts of births and deaths may be influenced by specific reporting issues each year. The specific issues are reported in the NYSDOH Annual Vital Statistics Tables, in the Report Measures section of their Technical Notes.

All the vital statistics presented in this report are based on the county/borough of residence.

b Statewide Planning and Research Cooperative System (SPARCS):
Information about hospitalizations is collected through the hospital inpatient discharge data system. Each hospitalization receives an ICD-10-CM code at discharge that indicates the primary reason for the hospitalization. There are also up to 24 other diagnosis codes recorded to further describe the hospitalization. Statistics presented in these tables are based on the primary diagnosis unless otherwise noted. This data system does not include information about events that did not result in a hospitalization, such as cases that were only treated in a hospital emergency room. The SPARCS data do not include visits/discharges by people who sought care from hospitals outside of New York State, which may lower numbers and rates for some counties, especially those which border other states. Numbers and rates are based on the number of hospitalizations that occurred and not the number of individuals who were hospitalized. SPARCS measures provided are generated based on patient residence county at time of discharge.

c Behavioral Risk Factor Surveillance System (BRFSS):
The BRFSS is an annual statewide random telephone and cellular surveillance survey designed by the Centers for Disease Control and Prevention (CDC). The survey is conducted in all 50 states and US territories. BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population.

County level data. The Expanded BRFSS (EBRFSS) augments the annual CDC Behavioral Risk Factor Surveillance System Survey (BRFSS). The goal of the Expanded BRFSS is to collect county-specific data on preventative health practices, risk factors, injuries and preventable chronic and infectious diseases. County level data are currently available for 2002-03, 2008-09, 2013-14, 2016 and 2018.

The New York State BRFSS website has further information.
 Methodology and Limitations

Index

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Types of Estimates

  1. Percentage/age-adjusted percentage:  Percentages are calculated per 100 population (e.g. the percentage of infants exclusively breastfed in the hospital represents the number of infants that were fed exclusively with breast milk among 100 live infants born in the hospital).
    The percentages were age-adjusted to the U.S. 2000 standard population using appropriate age distributions. 1 Age-adjustment is a process that is performed to allow communities with different age structures to be compared.2
  2. Weighted percentage/age-adjusted weighted percentage:  Weighted percentages were generated for survey data (e.g., Behavioral Risk Factor Surveillance System, Youth Tobacco Survey, Youth Risk Behavior Surveillance System) which ensures that the data are as representative of New York's population as possible. Weighted estimates are shown as a percentage (%) and corresponding 95% confidence intervals (CI) are presented when available.
    The weighted percentages were age-adjusted to the U.S. 2000 standard population using appropriate age distributions. 1 Age-adjustment is a process that is performed to allow communities with different age structures to be compared.2
  3. Rate/age-adjusted rate:  A rate is a measure of the frequency with which an event occurs in a defined population over a specified time-period. Rates used for the Prevention Agenda tracking indicators are per 1,000, 10,000 or 100,000 population.
    The rates were age-adjusted to the U.S. 2000 standard population using appropriate age distributions. 1 Age-adjustment is a process that is performed to allow communities with different age structures to be compared.2
  4. Ratio:  A ratio is the relative magnitude of two quantities or a comparison of any two values. The ratios that are included in the Prevention Agenda are calculated by dividing the percentage or rate of one racial ethnic group (i.e., Black non-Hispanic or Hispanic) by the percentage or rate for the White non-Hispanic group.
  5. Rate/percentage difference:  The rate/percentage difference is the absolute difference between two rates/percentages. Among the Prevention Agenda tracking indicators, the rate/percentage difference is used as a measure when comparing the percentage of premature deaths among (a) the Black non-Hispanic population versus the White non-Hispanic population and (b) the Hispanic population versus the White non-Hispanic population.

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Population Estimates

Population estimates are developed by the US Census Bureau.

Estimates for 2020 and earlier are from Bridged Race Categories files, developed by the Census Bureau for the National Center for Health Statistics. The 2018 population estimates are used to calculate rates for 2019 and 2020.

Estimates for 2021 and later are from annual Special Tabulations from the US Census Population and Housing Unit Estimates Program. Pursuant to Chapter 745 of 2021 of the Laws of New York, this report does not include separate tabulations for the required Asian or Pacific Islander ethnic groups and languages, nor does it include separate tabulations for the required Middle Eastern or Northern African ethnic groups and languages. Data was determined to be insufficient for publication due to small cell sizes that result in unreliable/unstable estimates and/or are vulnerable to patient identifiability.

See this document for information about why different estimates were used, the differences in these estimates, and why 2018 estimates were used to calculate rates for 2019 and 2020.

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Regional Schemas

Data are presented on this dashboard according to multiple regional/sub-regional schemas that group counties together into larger geographic regions of the state.

The Census Informed Sub-regional (CISR) schema was developed by the Office of Science (OS) Center for Population Health Science (CPHS) for visualization of population health data. The schema maintains the integrity of the Department’s four Regional Offices and their boundaries and is informed by core based statistical areas (CBSA) delineated every 10 years by the Office of Management and Budget. Please see this document for information on how the CISR schema was developed.

The Delivery System Reform Incentive Payment Program (DSRIP) schema was initially developed for the purpose of implementing the Medicaid Redesign Team (MRT) Waiver Amendment in New York State. Since then, the schema has been adopted for use by many other programs within the Department and is still used by New York State’s Medicaid program on their dashboards to visualize Medicaid utilization data even though the DSRIP Program ended in March 2020. For more information about the MRT, please see Redesigning New York's Medicaid Program.

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Unstable Estimates

Multiple years of data were combined to generate more stable estimates when the number of events for an indicator was small (i.e., rare conditions).
The relative standard error (RSE) is a tool for assessing reliability of an estimate. A large RSE is produced when estimates are calculated based on a small number of cases.2 Estimates with large RSEs are considered less reliable than estimates with small RSEs. The National Center for Health Statistics recommends that estimates with RSEs greater than 30% should be considered unreliable/unstable.3

The RSE is calculated by dividing the standard error of the estimate by the estimate itself, then multiplying that result by 100. The RSE is expressed as a percent of the estimate.

For the Prevention Agenda dashboard, an asterisk (*) is used to indicate that a percentage, rate, or ratio is unreliable/unstable. This usually occurs when there are less than 10 events in the numerator (RSE is greater than 30%).

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Direction of Indicator Estimates

Prevention Agenda tracking indicators fall into two categories with regard to the desirable direction of their estimates. Sometimes lower estimates are better (e.g., the percentage of premature deaths before age 65 years, or the age-adjusted rate of potentially preventable hospitalizations among adults) and in other cases higher estimates are better (e.g., the percentage of the population with health insurance, or the percentage of infants exclusively breastfed in the hospital).

The desirable direction of the Prevention Agenda tracking indicator is important to note because the county bar chart, map, concern level and visual distribution use color categories that are based on the direction of the Prevention Agenda tracking indicator. The assessment of indicator performance is also based on the direction of the Prevention Agenda tracking indicator.

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Grouping County Estimates into Three Categories for the County Visual Distributions, County Maps, and County Bar Charts

Color Categories Defined

For each Prevention Agenda tracking indicator, county visual distributions, maps and bar charts are generated when there are enough counties with data different from each other so that county visual distributions, maps and charts can show meaningful differences among the counties. In particular, county visual distributions, maps and charts are not generated if 46 or more counties have rates that are equal to 0 or are missing, or if more than half the counties have the same rate. County visual distributions, maps and charts are generated all other times. Tables are generated for all indicators in all counties, regardless of rate values.

When county visual distributions, maps and charts are generated, county estimates are grouped into three categories: light green, blue-green, and dark blue. These categories are displayed consistently in the county visual distribution, the bar chart, and the New York State map for each tracking indicator.

The three colors represent the quartile distribution of estimates for the counties ordered from those doing the best to those doing the worst.

For Prevention Agenda tracking indicators where lower estimates are better (e.g., percentage of premature deaths before age 65 years or the age-adjusted rate of potentially preventable hospitalizations among adults):

  • The LIGHT GREEN category includes counties that are performing the best (i.e., 50% of counties with the lowest estimates; those in quartile 1 and quartile 2) and is the most favorable category or least concern for a county's estimate to be in.
  • The BLUE-GREEN category includes counties that are performing in the middle (i.e., 25% of counties or those in quartile 3).
  • The DARK BLUE category includes counties that are performing the worst (i.e., 25% of counties with the highest estimates; those in quartile 4) and is the least favorable or high concern category for a county's estimate to be in.

For Prevention Agenda tracking indicators where higher estimates are better (e.g., the percentage of the population with health insurance or the percentage of infants exclusively breastfed in the hospital):

  • The LIGHT GREEN category includes counties that are performing the best (i.e., 50% of counties with the highest estimates; those in quartile 3 and quartile 4) and is the most favorable or least concern category for a county's estimate to be in.
  • The BLUE-GREEN category includes counties that are performing in the middle (i.e., 25% of counties or those with estimates in quartile 2).
  • The DARK BLUE category includes counties that are performing the worst (i.e., 25% of counties with the lowest estimates; those in quartile 1) and is the least favorable or high concern category for a county's estimate to be in.

Length of Color Categories in the County Visual Distribution

The length of each color in the county visual distribution represents the minimum and maximum values or cut-off points for the three categories. If the area is very big, this indicates that the range of county estimates is large; while a small area indicates a small range of county estimates.

For example, the county visual distribution for the asthma emergency department visit rate per 10,000 for those aged 0-17 years in Albany County in 2023 shows a very large dark blue area which ranges from 64.8 to 244.7; while the light green area ranges from 21.0-<44.0 and has a much narrower width; similarly, the blue-green area has a narrow range of estimates from 44.0-<61.8.

the asthma emergency department visit rate per 10,000 for those aged 0-17 years in Albany County shows a very wide dark blue category

Color Switch in County Visual Distribution Based on Direction of Indicator Estimates

For Prevention Agenda tracking indicators where lower estimates are better (e.g., potentially preventable hospitalizations among adults, age-adjusted rate per 10,000), the dark blue category is displayed on the right side of the county visual distribution.
indicators where lower estimates are better
For Prevention Agenda tracking indicators where higher estimates are better (e.g., percentage of adults who are physically active), the dark blue category is displayed on the left side of the county visual distribution.
indicators where higher estimates are better

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Comparing the Prevention Agenda Estimates with the Prevention Agenda Objectives

A green color in bar charts or for a number displayed in a data table indicates that the current value for the Prevention Agenda tracking indicator met the Prevention Agenda 2030 Objective. A red color in bar charts or for a number displayed in a data table indicates that the current value for the Prevention Agenda tracking indicator did not meet the Prevention Agenda 2030 Objective.

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Assessing the Indicator Performance

Three different methods were used to assess indicator performance.

  1. Conduct one-sided z-test to assess the change (decrease/increase or improve/worsen) in estimates between the two most recent time periods. The p-value for rejecting the null hypothesis is less than or equal to 0.05 and the critical value for the one-sided test (p-value at 0.05) is 1.645. 4
  2. A comparison of confidence intervals of estimates for the two most recent time periods was performed where this method was more appropriate. 4 A confidence interval is a range around an estimate that conveys how precise the estimate is. Differences between estimates are considered “statistically significant” when the estimates being compared do not have overlapping confidence intervals. For the purposes of this dashboard, in cases where the confidence intervals overlap, the difference is interpreted as not statistically significant at the 95% confidence level. For survey related indicators, estimates and the two-sided 95% confidence intervals were obtained and used. In some instances for count data (e.g., births, deaths, hospitalizations, and emergency department visits), we calculated the one-sided 95% confidence intervals for the estimates and used them for comparison to evaluate the indicator performance.5
    NOTE: This method is an approximation of a statistical test and may result in a more conservative finding. In some cases, an appropriate statistical test would indicate a statistically significant difference even though the confidence intervals overlap and falsely imply no significant difference. When two confidence intervals do not overlap, though, a comparable statistical test would always indicate a statistically significant difference.6
  3. Simple comparison was conducted where the two estimates were directly compared to each other based on their magnitude. This was performed when there was not a sufficient amount of data to conduct significance testing; or if confidence intervals could not be calculated; or if there is some overlap of the two time intervals being compared (e.g., 2018-2022 and 2017-2021 maternal mortality indicators).

    The categories for the Indicator Performance are as follows:
    • Significantly improved
    • Significantly worsened
    • No significant change
    • Improved^
    • Worsened^
    • No change^
    • Baseline data

The "^" sign indicates that the performance was determined using simple comparison and not statistical tests.

The most recent data available during the planning phase were used as a baseline to set the Prevention Agenda 2030 Objective/Target. “Indicator Performance” is not assessed if there are no available data points that are more recent than the baseline data. Therefore, the “Indicator Performance” is labeled as "Baseline data" until updated data are available.

See Table 1 below for statistical significance techniques used for each type of data source to assess the indicator performance.

Use caution when interpreting significance. For more common conditions (i.e., high incidence rates), there is a higher likelihood that a relatively small change could be detected as statistically significant. Conversely, for rare conditions, the likelihood of detecting a statistically significant change is low even for reasonable changes.

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Data Filters

Several data filters are available on state and county views to quickly select indicators based on commonly desired criteria. Multiple filters can be selected simultaneously.

  1. State data filters: two data filters are available for state level indicators
    • Filter on meeting 2030 objective target: This filter displays indicators, where the most recent state level data meeting or not meeting the Prevention Agenda 2030 objectives.
    • Filter on indicator performance over time: The performance status for each indicator is generated by comparing state level data for the two most recent time periods. This filter displays indicators based on indicator performance categories selected.
  2. County data filters: three data filters are available for county level indicators
    • Filter on meeting 2030 objective target: This filter displays indicators, where the most recent specific county data meeting or not meeting the Prevention Agenda 2030 objectives.
    • Filter on indicator performance over time: The performance status for each indicator is generated by comparing estimates for the two most recent time periods for a specific county. This filter displays indicators based on indicator performance categories selected.
    • Filter on county’s position of concern level: This filter displays indicators based on how a county is doing in comparison to other counties in a quartile distribution.

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Sub-county Data

To better serve the needs for more local level data, we have assessed the availability of sub-county level data for the existing county level indicators. Depending on the availability of the information from the data sources, sub-county level data are presented in one of the following three geographic levels: ZIP Code or minor civil division (MCD)/community district (CD).

  • ZIP Code:  For indicators generated from SPARCS (inpatient and outpatient) data, ZIP Code refers to resident address ZIP Code. If a ZIP Code crosses county borders, the ZIP Code is assigned to the county which has the largest proportion of the population of that ZIP Code. ZIP Code level population estimates used for calculating rates were obtained by the New York State Department of Health (NYSDOH) from the Claritas Corporation.
  • Minor Civil Division (MCD)/Community District (CD):  Birth and death certificate data for counties outside of New York City (NYC) are presented by MCD. Data for NYC boroughs are presented by CD. There are 59 CDs within the five NYC boroughs.
    Note: A small percent of records did not have an assigned MCD or CD, but the records had other geographic identifiers. For NYC records with missing CD, ZIP Code information was used to look up and assign the CD location utilizing NYC Department of Planning geographic data linking ZIP Codes to CDs. This linked file contains a small number of ZIP Codes, which were completely contained within a single CD. Records with those ZIP codes were assigned to those CDs. For records of residents from the rest of the state (ROS), outside of NYC, with a missing MCD, the New York State Gazetteer code* was used to look up the MCD code. DOH staff linked the Gazetteer codes to MCDs, and the linkage was used to assign records outside of NYC to an MCD.
    *The New York State Gazetteer was prepared by the New York State Department of Health (see: health.data.ny.gov/Health/New-York-State-Gazetteer/cpcx-4uew)

Based on further assessment of the stability of the estimates and the impact of data suppression, the following eight indicators were selected for incorporating into the current PA tracking dashboard.

  • ZIP Code level:
    • Potentially preventable hospitalizations among adults, age-adjusted rate per 10,000
    • Number of people living in HUD-subsidized housing in the past 12 months
    • Asthma emergency department visits, rate per 10,000, aged 0-17 years
  • MCD/CD level:
    • Percentage of premature deaths (before age 65 years)
    • Percentage of people living in poverty
    • Percentage of people living in poverty, aged 65 years and older
    • Percentage unemployed, aged 16 years and older
    • Percentage of infants who are exclusively breastfed in the hospital among all infants

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Data Suppression for Confidentiality

Results are not shown (i.e., suppressed) when issues of confidentiality exist. Suppression rules vary depending on the data source and the indicator.

Table 1. Summary of data suppression and statistical evaluation significance for the Prevention Agenda Indicators by data source

Data Sources Suppression Criteria Statistical Significance Techniques
Sample Surveys
Pregnancy Risk Assessment Monitoring System Denominator <30 95% CI comparison
BRFSS and Expanded BRFSS Numerator <6 or Denominator <50 95% CI comparison
US Census   90% CI comparison
National Survey on Drug Use and Health   95% CI comparison
Youth Risk Behavior Surveillance System Denominator <30 95% CI comparison
Youth Tobacco Survey   95% CI comparison
Population Count Data
Death Single Year: Denominator population <50;
Three-Year Combined: Denominator population <30		 Rate/percentage: one sided chi-square test with p-value <0.05
Rate difference: one sided 95% CI comparison
Birth Single Year: Denominator total Births <50 One sided chi-square test with p-value <0.05
SPARCS Numerator between 1 - 5 cases Rate/percentage: one sided chi-square test with p-value <0.05;
Ratio/Rate difference: one sided 95% CI comparison
Prescription Monitoring Program (PMP) Registry Numerator between 1 - 5 cases One sided chi-square test with p-value <0.05

CI:  Confidence Interval
BRFSS:  Behavioral Risk Factor Surveillance System
SPARCS:  Statewide Planning and Research Cooperative System

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Data Limitations

Table 2. Summary of Limitations for Data Presented on the Prevention Agenda Dashboard

Data Source Limitations
Vital Records Through a cooperative agreement, the New York State Department of Health (NYSDOH) receives data on live births, deaths, fetal deaths and marriages recorded in New York City from the New York City Department of Health and Mental Hygiene (NYCDOHMH). The NYSDOH also receives data, from other states and Canada, on live births and deaths recorded outside of New York State to residents of New York State.
Vital Event indicators for NYC geographical areas reported by NYSDOH and NYCDOHMH may be different since the former may include all NYC residents' events regardless of where they occurred and the latter reports only events to NYC residents that occurred in NYC. The indicators may also differ due to timing and/or completeness of data.
The counts of births and deaths may be influenced by specific reporting issues each year. The specific issues are reported in the NYSDOH Annual Vital Statistics Tables, in the Report Measures section of their Technical Notes.
All the vital statistics presented in this report are based on the county/borough of residence.
Statewide Planning and Research Cooperative System (SPARCS) The recent data may be incomplete and should be interpreted with caution. Health Care Facilities licensed in New York State (NYS), under Article 28 of the Public Health Law, are required to submit their inpatient and/or outpatient data to SPARCS. Per NYS Rules and Regulations, Section 400.18 of Title 10, data are required to be submitted: (1) monthly, (2) 95% within 60 days following the end of the month of patient’s discharge/visit, and (3) 100% are due 180 days following the end of the month of the patient discharge/visit. The accuracy of indicators, which are based on diagnosis codes (ICD-10- CM on or after Oct. 1, 2015) reported by the facilities, is limited by the completeness and quality of reporting and coding by the facilities. The SPARCS data do not include discharges of people who sought care from hospitals outside of New York State, which may lower numbers and rates for some counties, especially those which border other states.
At the ZIP Code level, very unusual distributions in population denominator and/or numerator (possibly due to multiple hospitalizations per individual) may result in extreme age adjusted rates, therefore, these estimates are suppressed or to be interpreted with caution.
Youth Risk Behavior Surveillance System (YRBSS) First, data are self-reported, and the extent of underreporting or overreporting of behaviors cannot be determined. Second, the national, state, and local school-based survey data apply only to youth who attend school and, therefore, are not representative of all persons in this age group due to a small portion of youth not enrolled in a high school program or who had not completed high school. Third, whereas YRBSS is designed to produce information to help assess the effect of broad national, state, and local policies and programs, it was not designed to evaluate the effectiveness of specific interventions (e.g., a professional development program, school curriculum, or media campaign).
https://www.cdc.gov/mmwr/pdf/rr/rr6201.pdf
Pregnancy Risk Assessment Monitoring System (PRAMS) In New York State, PRAMS data are independently collected by the New York City Department of Health and Mental Hygiene (NYCDOHMH) for residents in New York City (NYC) and by the New York State Department of Health (NYSDOH) for residents outside of NYC.
The PRAMS survey is asked of individuals 3-9 months postpartum. The questions are based on self-report and rely on respondents’ recall of their behaviors in the time period immediately before, during, and after pregnancy, thus responses may be potentially impacted by recall bias.
National Survey of Children’s Health (NSCH) NSCH data are reported by a parent or guardian with knowledge of the health and health care of the sampled child. The estimates, numerators, and denominators presented are weighted to account for the probability of selection and non-response, and adjusted to represent the non-institutionalized population of children in the U.S. and each state who live in housing units. Standard errors account for the complex survey design. For more information on the NSCH methodology and limitations, visit https://mchb.hrsa.gov/data/national-surveys
National Survey of Drug Use and Health (NSDUH) In NSDUH, data are based on self-report, so there may be some under- or overreporting. The target population is defined as the civilian, non-institutionalized population of the U.S.; active-duty members of the military, individuals in institutional group quarters (such as hospitals, prisons, nursing homes, and treatment centers), and unhoused people not in shelters are excluded. Additionally, changes in survey methodology over time limit comparability of estimates across years.
https://www.samhsa.gov/data/data-we-collect/nsduh-national-survey-drug-use-and-health/datafiles/2022
Office of Addiction Services and Supports (OASAS) Client Data System (CDS) CDS includes data for individuals served in the OASAS-certified treatment system. It does not have data for individuals who do not enter treatment, get treated by the U.S. Department of Veterans Affairs, go outside New York State for treatment, are admitted to hospitals but not to substance use disorder (SUD) treatment, get diverted to other systems, or receive an addiction medication from a physician outside the OASAS system of care. OASAS-certified substance use disorder treatment programs are required to submit their admissions data to the CDS no later than the fifth of the month following the clinical admission transaction. Data are considered to be substantially complete five months after the due date but are able to be updated indefinitely. The accuracy of measures, which are based on data reported by the programs, is limited by the completeness, consistency and quality of reporting and coding by the programs. The sensitivity and specificity of these indicators may vary by provider, program, and possible substances reported. Opioid admissions data are not direct measures of the prevalence of opioid use. The availability of substance use disorder treatment services within a county may affect the number of admissions of county residents to programs offering those services.
Prescription Monitoring Program (PMP) Registry For all PMP indicators, several exclusions were applied. Prescriptions for out-of-state patients or without a valid patient’s New York ZIP Code were removed from the analysis. Data from veterinarians and prescription drugs administered to animals were not included in the analysis of PMP data. Prescriptions filled for opioids that have supply days greater than 90 were eliminated from the analysis. Also, opioids not typically used in outpatient settings and cold formulations including elixirs, antitussives, decongestants, antihistamines and expectorants were not included in the analyses. The Bureau of Narcotic Enforcement conducts an annual update of the National Drug Code (NDC) file used to identify select opioids, benzodiazepines, and stimulants in the PMP data. The historic prescription data is updated using the most recent NDC file each year. The application of the updated NDC file to the historic data may result in modifications to previous years data.

Note: When examining historical or trend data, please note that the 2018 population estimates are used to calculate rates for 2019 and 2020.

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References

  1. Klein RJ, Schoenborn CA. Age adjustment using the 2000 projected U.S. population. Healthy People Statistical Notes, no. 20. Hyattsville, Maryland: National Center for Health Statistics. January 2001. (see: www.cdc.gov/nchs/data/statnt/statnt20.pdf)
  2. About Age Adjusted Rates, 95% Confidence Intervals and Unstable Rates (see: www.health.ny.gov/statistics/cancer/registry/age.htm)
  3. Klein RJ, Proctor SE, Boudreault MA, Turczyn KM. Healthy People 2010 criteria for data suppression. Statistical Notes, no 24. Hyattsville, Maryland: National Center for Health Statistics. June 2002. (see: www.cdc.gov/nchs/data/statnt/statnt24.pdf)
  4. Statistical Significance (see: www.health.ny.gov/statistics/chac/chai/docs/statistical_significance.pdf)
  5. One-sided 95% confidence interval (see: http://www.graphpad.com/guides/prism/6/statistics/index.htm?one_sided_confidence_intervals.htm)
  6. Guidelines for using confidence intervals for public health assessment, Washington State Department of Health, (see: www.doh.wa.gov/Portals/1/Documents/1500/ConfIntGuide.pdf)

User's Guide

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Contact Us

If you have questions about the reports, please contact:

Center for Population Health Science at: prevention@health.ny.gov