The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).
The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality.
All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures.

The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).
The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality.
All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures.

The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).
The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality.
All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures.

The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).
The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality.
All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures.

The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for IQIs generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).
The IQIs are a set of measures that provide a perspective on hospital quality of care using hospital administrative data. These indicators reflect quality of care inside hospitals and include inpatient mortality for certain procedures and medical conditions; utilization of procedures for which there are questions of overuse, underuse, and misuse; and volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality.
All the IQI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) IQI measures.

The mortality, volume and utilization measures IQIs are presented by hospital as rates or counts. Area-level utilization measures are presented by county as rates.

Note: This dataset is no longer being updated. For continued updates related to this information, please visit: https://www.health.ny.gov/statistics/opioid/#i_one. This dataset is a summary of inpatient discharges and outpatient visit data for opioid-related diagnosis. The data reflects selected diagnosis codes that include a range of poisonings by opiates, opium, heroin, methadone, and other related narcotics. Please refer to the data dictionary in the “About” section for information on the current data available.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain hospital discharges counts (numerators, denominators, volume counts), observed, expected and risk-adjusted rates with corresponding 95% confidence intervals for Patient Safety Indicators generated using methodology developed by Agency for Healthcare Research and Quality (AHRQ).

The PSIs are a set of indicators providing information on potential in hospital complications and adverse events following surgeries, procedures, and childbirth. The PSIs were developed by AHRQ after a comprehensive literature review, analysis of ICD-9-CM codes, review by a clinician panel, implementation of risk adjustment, and empirical analyses.

All PSI measures were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data beginning 2009. US Census data files provided by AHRQ were used to derive denominators for county level (area level) PSI measures.

The mortality, volume and utilization measures PSIs are presented by hospital as rates or counts. Area-level measures are presented by county as rates.

The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011.

The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.

The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient and outpatient data and Claritas population information.

The observed, expected and risk adjusted rates for PPV are presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011.

The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.

The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient and outpatient data and Claritas population information.

The observed, expected and risk adjusted rates for PPV are presented by either resident county (including a statewide total) or resident zip code (including a statewide total). For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.

The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.

New York State Baby Names are aggregated and displayed by the year, county, or borough where the mother resided as stated on a New York State or New York City (NYC) birth certificate. The frequency of the baby name is listed if there are 5 or more of the same baby name in a county outside of NYC or 10 or more of the same baby name in a NYC borough.

This column chart shows performance measure rates for behavioral health by Health Home for follow-up after hospitalizations. The base dataset contains measures that evaluate the quality of care delivered by Health Homes for the Centers for Medicare & Medicaid Services (CMS) Core Set and Health Home State Plan Amendment (SPA). To support ongoing assessment of the effectiveness of the Health Home model, the CMS has established a recommended Core Set of health care quality measures that it intends to promulgate in the rule making process.
Please refer to the Overview document for additional information.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older.

Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available.

For more information, check out http://www.health.ny.gov/statistics/brfss/.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older.

Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available.

For more information, check out http://www.health.ny.gov/statistics/brfss/.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older.

Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available.

For more information, check out http://www.health.ny.gov/statistics/brfss/.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older. Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available. For more information, check out http://www.health.ny.gov/statistics/brfss/.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older. Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available. For more information, check out http://www.health.ny.gov/statistics/brfss/.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older. Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available. For more information, check out http://www.health.ny.gov/statistics/brfss/.

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual statewide telephone surveillance system designed by the Centers for Disease Control and Prevention (CDC). BRFSS monitors modifiable risk behaviors and other factors contributing to the leading causes of morbidity and mortality in the population. New York State's BRFSS sample represents the non-institutionalized adult household population, aged 18 years and older. Although the overall number of respondents in the BRFSS is more than sufficiently large for statistical inference purposes, subgroup analyses can lead to estimates that are unreliable. Interpreting and reporting weighted numbers that are based on a small, unweighted number of respondents can mislead the reader into believing that a given finding is much more precise than it actually is. The BRFSS follows a rule of not reporting or interpreting percentages based upon a denominator of fewer than 50 respondents (unweighted sample). Both a csv and sas data files are available. For more information, check out http://www.health.ny.gov/statistics/brfss/.