The dataset groups 66 individual Potentially Preventable Complication (PPC) measures into 8 different categories, providing observed and risk-adjusted rates 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 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 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 datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011.

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

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

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

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

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

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).

This file contains the observations collected in the experiment for each of the test-suite of programs for the other allocators (basic, fast, greedy, pbqp), generating code for the Sparc architecture

This file contains the summarized data from the 500 observations for all the programs, generating code for the Sparc architecture.

Now that I have your attention, please up-vote this dataset and read the following!!!

What is SParC?

SParC is a dataset for cross-domain Semantic Parsing in Context. It is the context-dependent/multi-turn version of the Spider task, a complex and cross-domain text-to-SQL challenge. SParC consists of 4,298 coherent question sequences (12k+ unique individual questions annotated with SQL queries annotated by 14 Yale students), obtained from user interactions with 200 complex databases over 138 domains.

Why SParC?

SParC is built upon the Spider dataset. Comparing to other existing context-dependent semantic parsing/text-to-SQL datasets such as ATIS, it demonstrates: complex contextual dependencies (annotated by 15 Yale computer science students) has greater semantic diversity due to complex coverage of SQL logic patterns in the Spider dataset. requires generalization to new domains due to its cross-domain nature and the unseen databasest time.

Dara Source:

https://yale-lily.github.io/sparc

Paper:

https://arxiv.org/abs/1906.02285

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This file contains the execution times for all the allocator, generating code for the Sparc architecture.

This file contains the confidence intervals for observations of the GRRA allocator, generating code for the Sparc architecture.

This file contains the confidence intervals for observations of the GRRA allocator, generating code for the x86 architecture.

The dataset shows each of the 65 individual Potentially Preventable Complication (PPC) measures, providing observed and risk-adjusted rates for all payer discharges by hospital and statewide, beginning in 2013. To view a statistical brief on PPCs, visit: https://www.health.ny.gov/statistics/sparcs/sb/docs/sb1.pdf

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. For more information about SPARCS data, visit: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional information.

The dataset shows each of the 65 individual Potentially Preventable Complication (PPC) measures, providing observed and risk-adjusted rates for all payer discharges by hospital and statewide, beginning in 2013. To view a statistical brief on PPCs, visit: https://www.health.ny.gov/statistics/sparcs/sb/docs/sb1.pdf

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. For more information about SPARCS data, visit: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional information.

The dataset shows each of the 65 individual Potentially Preventable Complication (PPC) measures, providing observed and risk-adjusted rates for all payer discharges by hospital and statewide, beginning in 2013. To view a statistical brief on PPCs, visit: https://www.health.ny.gov/statistics/sparcs/sb/docs/sb1.pdf

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. For more information about SPARCS data, visit: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional information.