The datasets contain number of Medicaid PQI hospitalizations (numerator), county Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) for Medicaid enrollees beginning in 2011.

The dataset contains Potentially Preventable Readmission observed, expected, and risk adjusted rates by hospital for Medicaid enrollees beginning in 2011.

This dataset is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

Note: The final update to this dataset was on 7/31/2023. The dataset is representative of financial incentive payments disbursed to Eligible Professionals (EPs) and Eligible Hospitals (EHs) by the NY Medicaid Electronic Health Records (EHR) Incentive Program, a CMS Promoting Interoperability Program. Authorized by the American Recovery and Reinvestment Act (ARRA) of 2009, this program provides multi-year financial incentives to EPs and EHs who adopt, implement, or upgrade, and subsequently demonstrate meaningful use of Certified Electronic Health Record Technology (CEHRT).

This dataset contains information on selected chronic health conditions in the Medicaid population at the county level. The chronic health conditions were identified through 3M Clinical Risk Group software and Medicaid enrollment/eligibility, encounter, claim and pharmacy data over a 12-month period.

The datasets contain number of Medicaid PDI hospitalizations (numerator), county or zip Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) for Medicaid enrollees beginning in 2011. The Agency for Healthcare Research and Quality (AHRQ) Pediatric Quality Indicators (PDIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. Both the Urinary Tract Infection and Gastroenteritis PDIs include admissions for patients aged 3 months through 17 years. The asthma PDI includes admissions for patients aged 2 through 17 years. Eligible admissions for the Diabetes Short-term Complications PDI includes admissions for patients aged 6 through 17 years.

Behavioral Risk Factor Surveillance System (BRFSS) sample data were used to generate annual percentages of non-institutionalized adult (18+) NYS residents with/without health insurance coverage. Health care coverage percentages are provided for 2011 forward, and are available for a range of demographic and geographic categories (New York City/Rest of State; DSRIP Region; Sex; Race/Ethnicity; Age; Education; Income; Limitation Status (through 2017); Disability Status (beginning in 2016); Employment Status; and Mental Health Status).
BRFSS is a random digit dialing (RDD) phone survey of the health status and health behaviors of adult NYS residents. The sample covers between 6,800 and 36,000 completed interviews annually through this timeframe.

This dataset aggregates and displays the number of New York State Medicaid enrollees by eligibility year and month within each NYS Economic Region, health insurance plan information, and enrollee demographics.

This is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. This dataset is at the county level. The Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. All PQIs apply only to adult populations (over the age of 18 years). The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information.

The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

This data set contains statewide Medicaid beneficiary counts by valid NYS five-digit zip code. Also in this file are counts of beneficiaries who are dual eligible for Medicaid and Medicare, total inpatient admissions, and total emergency room visits.

The datasets contain number of Medicaid PQI hospitalizations (numerator), county Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) for Medicaid enrollees beginning in 2011.

The datasets contain number of Medicaid PDI hospitalizations (numerator), county or zip Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) for Medicaid enrollees beginning in 2011.

This dataset includes Medicaid clinical metrics for Clinical Improvement Projects (Domain 3) of the Delivery System Reform Incentive Payment (DSRIP) Program. The DSRIP program will promote community-level collaborations and focus on system reform, specifically a goal to achieve a 25 percent reduction in avoidable hospital use over five years. As a part of the DSRIP program, Performing Provider System will employ multiple projects both to transform health care delivery as well as to address the broad needs of the population that the performing provider system serves. These projects described in Attachment J are grouped into different strategies, such as behavioral health, within each Domain (System Transformation Projects (Domain 2), Clinical Improvement Projects (Domain 3), and Population-wide Projects (Domain 4). For each strategy, there is a set of metrics that the performing provider system will be responsible for if they do any one of the projects within that strategy. This dataset includes only Domain 3 Clinical Metrics.

This dataset is a summary of hospital inpatient discharges from every hospital including Article 28 facilities; Ambulatory Surgery and Emergency Department visits, from the Statewide Planning and Research Cooperative System (SPARCS). The data is rolled up by patient county of residence. This dataset was modified in September 2013 to be in sync with the release of the Hospital Inpatient Discharges (SPARCS De-Identified) datasets. Please refer to the data dictionary for information on the current data available.

The SPARCS data has been divided into two distinct datasets: Hospital Discharges by Patient County of Residence and Hospital Discharges by Facility. This is to preserve the confidentiality of identifiable individual information.This dataset does not include facility names.

The dataset shows Potentially Preventable Complication (PPC) measures for the 36 major PPCs combined; providing observed, expected, and risk-adjusted rates and counts for all payer discharges by hospital and statewide, beginning in 2013.

Potentially Preventable Complications (PPC), obtained from software created by 3M Health Information Systems, are defined as harmful events or negative outcomes that develop or occur during hospitalization and may result from processes of care and treatment rather than from natural progression of the underlying illness.

The PPCs were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data.

The dataset contains Potentially Preventable Readmission observed, expected, and risk adjusted rates by hospital for all payer beneficiaries beginning in 2009.

This data set contains information on selected chronic health conditions in the Medicaid population at the zip code level. The chronic health conditions were identified through 3M Clinical Risk Group software and Medicaid enrollment/eligibility, encounter, claim and pharmacy data over a 12-month period.

The dataset contains observed, expected, and risk-adjusted rates for the Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) beginning in 2009. The AHRQ PDIs are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. Both the Urinary Tract Infection and Gastroenteritis PDIs include admissions for patients aged 3 months through 17 years. The asthma PDI includes admissions for patients aged 2 through 17 years. Eligible admissions for the Diabetes Short-term Complications PDI includes admissions for patients aged 6 through 17 years.

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

The observed, expected, risk-adjusted rates, and difference in rates, for each AHRQ PDI are presented by resident zip code (including a statewide total).

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 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 dataset contains Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for Medicaid beneficiaries by patient county 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 dataset contains observed, expected, and risk-adjusted rates for the Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) beginning in 2009.
The AHRQ PDIs are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. Both the Urinary Tract Infection and Gastroenteritis PDIs include admissions for patients aged 3 months through 17 years. The asthma PDI includes admissions for patients aged 2 through 17 years. Eligible admissions for the Diabetes Short-term Complications PDI includes admissions for patients aged 6 through 17 years.

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

The observed, expected, risk-adjusted rates, and difference in rates, for each AHRQ PDI are presented by resident county (including a statewide total).

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 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 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.