Comparative effectiveness of real-time and episodic hospital surgical performance evaluation

实时与间歇式医院手术绩效评估的效果比较

基本信息

  • 批准号:
    9370221
  • 负责人:
  • 金额:
    $ 4.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-07-01 至 2018-04-30
  • 项目状态:
    已结题

项目摘要

Project Summary/Abstract Contemporary surgical quality improvement (QI) programs provide hospitals with episodic feedback. There are two main limitations associated with this approach. The first is the time required for data abstraction, analysis, and subsequent feedback creating a built-in time lag between when a hospital is having a decrement in performance and when the hospital receives this information. The second is the inability of current episodic analytic methods to explicitly account for the impact of time as variable (i.e.: the occurrence of a cluster of events in a short period of time). Episodic data put hospitals' local QI teams at a disadvantage because their response to declining performance must be reactive rather than proactive. Furthermore, patients treated in the interval between when performance is declining and when this decrement is appreciated are potentially at risk for exposure to suboptimal perioperative care processes. The cumulative sum (CUSUM) is an industrial statistical process control method traditionally used for monitoring the quality of a production process and for ensuring that process is operating efficiently, effectively, and at full potential. The CUSUM is well-suited for ascertaining variation over time for rare outcomes, is resilient to multiple statistical testing, and explicitly accounts for the impact of time as a variable. It has been used for health care evaluation and shown to provide early, meaningful, performance-based feedback. The objective of this proposal is to compare the effectiveness of a risk-adjusted, time-to- event CUSUM for the early detection of hospitals with outlier performance in terms of 30-day morbidity and mortality relative to the standard of episodic observed-to-expected (O-E) methodology used by the VA Surgical Quality Improvement Program (VASQIP) and the American College of Surgeons National Surgical Quality Improvement Program. Using national VASQIP data, we intend to: 1.) evaluate whether the CUSUM identifies similar outlier hospitals relative to the O-E approach and to compare differences in timing for outlier identification; 2.) estimate the number of at risk surgical procedures and post-operative patient days using CUSUM compared to O-E hospital performance evaluation. The data from this proposal will inform a future prospective evaluation of the CUSUM within the VA's existing surgical QI framework and infrastructure with the ultimate goal being eventual integration of CUSUM into VASQIP reporting. Providing hospitals with more timely data would benefit local QI efforts and could shift the paradigm away from a reactive response to episodic data to a proactive approach based on a more real-time evaluation of performance. Identifying opportunities to correct errant care processes when performance is declining rather than when it has already reached an unacceptable level could decrease the number of surgical patients at risk for unintended outcomes, decrease the costs associated with correcting errant care processes and treating potentially preventable morbidity, and make surgical care safer.
项目总结/文摘

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Nader Nabile Massarweh其他文献

Examining Care Fragmentation After PAD Interventions: The Readmission Event
  • DOI:
    10.1016/j.jvs.2022.11.019
  • 发表时间:
    2023-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Olamide Alabi;Nader Nabile Massarweh;Xinyan Zheng;Jialin Mao;Yazan Duwayri
  • 通讯作者:
    Yazan Duwayri

Nader Nabile Massarweh的其他文献

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{{ truncateString('Nader Nabile Massarweh', 18)}}的其他基金

Using Modern Data Science Methods and Advanced Analytics to Improve the Efficiency, Reliability, and Timeliness of Cardiac Surgical Quality Data
使用现代数据科学方法和高级分析来提高心脏手术质量数据的效率、可靠性和及时性
  • 批准号:
    10364433
  • 财政年份:
    2022
  • 资助金额:
    $ 4.99万
  • 项目类别:
Using Modern Data Science Methods and Advanced Analytics to Improve the Efficiency, Reliability, and Timeliness of Cardiac Surgical Quality Data
使用现代数据科学方法和高级分析来提高心脏手术质量数据的效率、可靠性和及时性
  • 批准号:
    10542758
  • 财政年份:
    2022
  • 资助金额:
    $ 4.99万
  • 项目类别:
Enhancing the Efficiency of Data Collection for Surgical Quality Improvement
提高数据收集效率以提高手术质量
  • 批准号:
    10641658
  • 财政年份:
    2021
  • 资助金额:
    $ 4.99万
  • 项目类别:
Enhancing the Efficiency of Data Collection for Surgical Quality Improvement
提高数据收集效率以提高手术质量
  • 批准号:
    10334529
  • 财政年份:
    2021
  • 资助金额:
    $ 4.99万
  • 项目类别:
Enhancing the Efficiency of Data Collection for Surgical Quality Improvement
提高数据收集效率以提高手术质量
  • 批准号:
    10187843
  • 财政年份:
    2021
  • 资助金额:
    $ 4.99万
  • 项目类别:
Enhancing the Efficiency of Data Collection for Surgical Quality Improvement
提高数据收集效率以提高手术质量
  • 批准号:
    10547734
  • 财政年份:
    2021
  • 资助金额:
    $ 4.99万
  • 项目类别:
Comparative Effectiveness of Alternative Strategies for Monitoring Hospital Surgical Performance
监测医院手术表现的替代策略的比较有效性
  • 批准号:
    10186540
  • 财政年份:
    2018
  • 资助金额:
    $ 4.99万
  • 项目类别:
Comparative Effectiveness of Alternative Strategies for Monitoring Hospital Surgical Performance
监测医院手术表现的替代策略的比较有效性
  • 批准号:
    9692259
  • 财政年份:
    2018
  • 资助金额:
    $ 4.99万
  • 项目类别:
A Population-Based Analysis of Care and Outcomes for Hepatocellular Carcinoma
基于人群的肝细胞癌护理和结果分析
  • 批准号:
    7541665
  • 财政年份:
    2008
  • 资助金额:
    $ 4.99万
  • 项目类别:
A Population-Based Analysis of Care and Outcomes for Hepatocellular Carcinoma
基于人群的肝细胞癌护理和结果分析
  • 批准号:
    7812042
  • 财政年份:
    2008
  • 资助金额:
    $ 4.99万
  • 项目类别:

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