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35 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
47,222
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
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).
Updated
January 27 2023
Views
63,161
The charts shows observed vs. expected Potentially Preventable Readmission rates by hospital for all payer beneficaries.
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
45,725
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
45,849
This line chart shows the observed vs. expected Potentially Preventable Complication (PPC) rates for all payer beneficiaries by hospital.
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).
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
43,188
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).
Updated
January 26 2023
Views
69,370
This chart shows risk adjusted rates per 10,000 discharges of Potentially Preventable Complications (PPC) for all payer beneficiaries by hospital.
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 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
44,519
This chart shows the overall risk adjusted rate per 100,000 for hospital inpatient prevention quality indicators (all payers) for pediatric discharges by county and year. The dataset contains observed, expected, and risk-adjusted rates for Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) beginning in 2009.
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 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 either resident county (including a statewide total). To view the data presented by resident zip code (including a statewide tota), go to: https://health.data.ny.gov/Health/Hospital-Inpatient-Prevention-Quality-Indicators-P/2xc5-n3zd. For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.
Updated
January 25 2023
Views
20,326
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.
Updated
August 14 2023
Views
41,984
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
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.
Updated
June 2 2023
Views
46,273
The dataset contains Potentially Preventable Readmission observed, expected, and risk adjusted rates by hospital for all payer beneficiaries beginning in 2009.
Updated
March 22 2018
Views
45,608
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 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).
Updated
January 25 2023
Views
15,156
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).
Updated
January 25 2023
Views
17,733
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).
Updated
June 2 2023
Views
43,053
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.
Updated
March 22 2018
Views
11,397
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 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.
Updated
December 7 2023
Views
13,223
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.
Updated
December 7 2023
Views
12,976
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 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.
Updated
February 16 2018
Views
11,892
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 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.
Updated
November 16 2020
Views
11,631
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.
Updated
December 7 2023
Views
11,144
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 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.
Updated
December 7 2023
Views
10,774
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.
Updated
December 7 2023
Views
10,691
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.
Updated
June 2 2023
Views
53,114
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