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65 Results
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The dataset contains hospital stroke designation and Coverdell registry participation status, acute stroke discharges counts (numerators, denominators), observed, expected and risk-adjusted acute stroke in-hospital/30-day post admission mortality rates with corresponding 95% confidence intervals. Mortality rates risk adjustment was based on the methodology developed by the New York State Department of Health.
The purpose of this data set is reporting of hospital-specific risk adjusted acute stroke mortality rates (RAMR) to inform hospitals, to aid initiatives to improve hospital quality performance and measurement, and to identify performance outliers for public reporting. The "About" tab contains additional details concerning this dataset.
Updated
August 24 2016
Views
47,223
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-Identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data contains basic record level detail regarding the discharge; however, the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Updated
September 13 2019
Views
114,526
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges, and costs.This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Updated
September 13 2019
Views
35,420
The dataset contains hospital stroke designation and Coverdell registry participation status, acute stroke discharges counts (numerators, denominators), observed, expected and risk-adjusted acute stroke in-hospital/30-day post admission mortality rates with corresponding 95% confidence intervals. Mortality rates risk adjustment was based on the methodology developed by the New York State Department of Health.
The purpose of this data set is reporting of hospital-specific risk adjusted acute stroke mortality rates (RAMR) to inform hospitals, to aid initiatives to improve hospital quality performance and measurement, and to identify performance outliers for public reporting.
Updated
February 9 2017
Views
43,162
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges and costs. This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Updated
September 13 2019
Views
23,525
The dataset contains Potentially Preventable Readmission observed, expected, and risk adjusted rates by hospital for Medicaid enrollees beginning in 2011.
Updated
December 16 2016
Views
56,340
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 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.
Updated
August 24 2016
Views
54,378
This line chart compares the median cost vs. median charge for chest pain with a minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
61,384
This line chart compares the median cost vs. median charge for normal newborn or neonate w other problem with minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
58,829
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 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.
Updated
August 24 2016
Views
53,956
This line chart compares the median cost vs. median charge for vaginal deliveries with a minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
78,328
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.
Updated
December 16 2016
Views
52,596
The charts shows risk adjusted rates of Potentially Preventable Readmissions by hospital for all payers beginning in 2009.
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/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
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/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
January 24 2018
Views
45,853
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges, and costs. This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Updated
September 13 2019
Views
20,122
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Updated
September 13 2019
Views
20,397
This line chart compares the median cost vs. median charge for cesarean deliveries with a minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset..
Updated
December 4 2019
Views
67,613
This line chart compares the median cost vs. median charge for chronic obstructive pulmonary disease with a moderate severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided. For more information, check out: http://www.health.ny.gov/statistics/sparcs/.
Updated
December 4 2019
Views
62,017
This chart shows the trend in statewide observed rates of Potentially Preventable Complications (PPC) for all payer beneficiaries beginning in 2013.
The chart is based on a dataset that contains Potentially Preventable Complications (PPC) observed, expected, and risk-adjusted rates for all payer beneficiaries by hospital beginning in 2009.
The Potentially Preventable Complications (PPC), obtained from software created by 3M Health Information Systems, are harmful events or negative outcomes that develop after hospital admission and may result from processes of care and treatment rather than from natural progression of the underlying illness and are therefore potentially preventable.
The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data.
The observed, expected and risk adjusted rates for PPC are presented by hospital (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.
http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
August 14 2023
Views
42,811
This line chart compares the median cost vs. median charge for bipolar disorders with a moderate severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
62,085
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.
Updated
August 24 2016
Views
53,849
This line chart compares the median cost vs. median charge for heart failure with a moderate severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
61,325
This line chart compares the median costs vs. median charges for schizophrenia with a moderate severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
59,227
This line chart compares the median cost vs. median charge for cellulitis & other bacterial skin Infections with a moderate severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
62,012
This line chart compares the median cost vs. median charge for septicemia and disseminated Infections with a major severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
December 4 2019
Views
31,925
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
Note: The full dataset may be downloaded in a smaller, compressed file format from the attachments section.
Updated
December 7 2023
Views
4,031
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