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.

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).

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).

The chart shows risk adjusted Potentially Preventable Readmission rates by hospital for Medicaid enrollees beginning in 2011.
The Potentially Preventable Readmission (PPR) software created by 3M Health Information Systems, identifies hospital admissions clinically related to an initial admission within a specified time period. For this dataset, readmissions were evaluated within a 30-day time period from the discharge date of the initial hospital admission. A PPR may have resulted from a deficiency in the process of care and treatment at the initial hospitalization or lack of post discharge follow up. PPRs are not defined by unrelated events that occur post-discharge, such as admissions for trauma.
For each hospital, the total number of at risk admissions, the total number of observed PPR chains, the observed PPR rate, the expected PPR rate, and risk adjusted PPR rate are presented by year. For more information, check out http://www.health.ny.gov/health_care/medicaid/. The "About" tab contains additional details concerning this dataset.

The chart shows observed vs. expected Potentially Preventable Readmission rates by hospital for Medicaid enrollees in 2014.
The Potentially Preventable Readmission (PPR) software created by 3M Health Information Systems, identifies hospital admissions clinically related to an initial admission within a specified time period. For this dataset, readmissions were evaluated within a 30-day time period from the discharge date of the initial hospital admission. A PPR may have resulted from a deficiency in the process of care and treatment at the initial hospitalization or lack of post discharge follow up. PPRs are not defined by unrelated events that occur post-discharge, such as admissions for trauma.
For each hospital, the total number of at risk admissions, the total number of observed PPR chains, the observed PPR rate, the expected PPR rate, and risk adjusted PPR rate are presented by year. For more information, check out http://www.health.ny.gov/health_care/medicaid/. The "About" tab contains additional details concerning this dataset.

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.

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 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.

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.

This chart shows the overall risk adjusted rate per 100,000 for Medicaid prevention quality indicators for pediatric discharges by county and year.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.

The rates were calculated using Medicaid inpatient hospital data for the numerator and Medicaid enrollment in the county or zip code for the denominator.

The observed counts and rates, expected counts and rates, risk-adjusted rates and the difference between the number of observed and expected PDI hospitalizations for each AHRQ PDI 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/health_care/medicaid/. The "About" tab contains additional details concerning this dataset.

This chart shows the potentially preventable emergency visit (PPV) risk adjusted rates per 100 for Medicaid beneficiaries by patient county and year. The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for Medicaid 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 Medicaid inpatient and outpatient data for the numerator and Medicaid enrollment in the county or zip code for the denominator.

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/health_care/medicaid/. The "About" tab contains additional details concerning this dataset.

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 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.

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 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 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.

This layered map shows the locations of Creating Healthy Places interventions that are targeted towards children and the percentage of students (elementary, middle, and high school) who are obese (95th percentile or higher) by county (source: Student Weight Status Category Reporting System). The purpose of the Creating Healthy Places initiative is to implement community level interventions to promote healthy lifestyles to prevent obesity and type 2 diabetes. The lighter shaded counties have a lower percentage of obese students. The darker shaded counties have a higher percentage of obese students. This map can help identify areas that could benefit from more community level and school level interventions like the ones implemented through the Creating Healthy Places Initiative. The "About" tab contains additional details concerning this dataset.

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.

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 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.