{"title":"缩小感染预防人员配备建议方面的差距:APIC 人员配置计算器测试版的结果。","authors":"Rebecca Bartles, Sara Reese, Alexandr Gumbar","doi":"10.1016/j.ajic.2024.09.004","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Published literature suggests \"one-size-fits-all\" infection prevention and control (IPC) staffing recommendations do not sufficiently account for program complexity needs. This project's objective was to create and validate a calculator utilizing risk and complexity factors to generate individualized IPC staffing ratios.</p><p><strong>Methods: </strong>An online survey-based calculator was created that incorporated factors intended to predict staffing needs and multiple investigative questions to allow for optimization of factors in the algorithm. Hospital characteristics, staffing ratios, staffing perception, and outcomes were analyzed to determine the optimal questions and benchmarks for future releases.</p><p><strong>Results: </strong>The median infection preventionist full-time equivalent to bed ratio was 121.0 beds for 390 participating hospitals. The calculator deemed 79.2% of respondent staffing as below expected. Significant association existed between higher standard infection ratio ranges and staffing status for central line-associated bloodstream infection (P = .02), catheter-associated urinary tract infections (P = .001), Clostridioides difficile infections (P = .003), and colon surgical site infections (P = .0001).</p><p><strong>Conclusions: </strong>This novel approach allows facilities to staff their IPC program based on individual factors. Future versions of the calculator will be optimized based on the findings. Future research will clarify the impact of staffing on patient outcomes and staff retention.</p>","PeriodicalId":7621,"journal":{"name":"American journal of infection control","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Closing the gap on infection prevention staffing recommendations: Results from the beta version of the APIC staffing calculator.\",\"authors\":\"Rebecca Bartles, Sara Reese, Alexandr Gumbar\",\"doi\":\"10.1016/j.ajic.2024.09.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Published literature suggests \\\"one-size-fits-all\\\" infection prevention and control (IPC) staffing recommendations do not sufficiently account for program complexity needs. This project's objective was to create and validate a calculator utilizing risk and complexity factors to generate individualized IPC staffing ratios.</p><p><strong>Methods: </strong>An online survey-based calculator was created that incorporated factors intended to predict staffing needs and multiple investigative questions to allow for optimization of factors in the algorithm. Hospital characteristics, staffing ratios, staffing perception, and outcomes were analyzed to determine the optimal questions and benchmarks for future releases.</p><p><strong>Results: </strong>The median infection preventionist full-time equivalent to bed ratio was 121.0 beds for 390 participating hospitals. The calculator deemed 79.2% of respondent staffing as below expected. Significant association existed between higher standard infection ratio ranges and staffing status for central line-associated bloodstream infection (P = .02), catheter-associated urinary tract infections (P = .001), Clostridioides difficile infections (P = .003), and colon surgical site infections (P = .0001).</p><p><strong>Conclusions: </strong>This novel approach allows facilities to staff their IPC program based on individual factors. Future versions of the calculator will be optimized based on the findings. Future research will clarify the impact of staffing on patient outcomes and staff retention.</p>\",\"PeriodicalId\":7621,\"journal\":{\"name\":\"American journal of infection control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of infection control\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.ajic.2024.09.004\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of infection control","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.ajic.2024.09.004","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Closing the gap on infection prevention staffing recommendations: Results from the beta version of the APIC staffing calculator.
Background: Published literature suggests "one-size-fits-all" infection prevention and control (IPC) staffing recommendations do not sufficiently account for program complexity needs. This project's objective was to create and validate a calculator utilizing risk and complexity factors to generate individualized IPC staffing ratios.
Methods: An online survey-based calculator was created that incorporated factors intended to predict staffing needs and multiple investigative questions to allow for optimization of factors in the algorithm. Hospital characteristics, staffing ratios, staffing perception, and outcomes were analyzed to determine the optimal questions and benchmarks for future releases.
Results: The median infection preventionist full-time equivalent to bed ratio was 121.0 beds for 390 participating hospitals. The calculator deemed 79.2% of respondent staffing as below expected. Significant association existed between higher standard infection ratio ranges and staffing status for central line-associated bloodstream infection (P = .02), catheter-associated urinary tract infections (P = .001), Clostridioides difficile infections (P = .003), and colon surgical site infections (P = .0001).
Conclusions: This novel approach allows facilities to staff their IPC program based on individual factors. Future versions of the calculator will be optimized based on the findings. Future research will clarify the impact of staffing on patient outcomes and staff retention.
期刊介绍:
AJIC covers key topics and issues in infection control and epidemiology. Infection control professionals, including physicians, nurses, and epidemiologists, rely on AJIC for peer-reviewed articles covering clinical topics as well as original research. As the official publication of the Association for Professionals in Infection Control and Epidemiology (APIC)