Literature DB >> 21345859

Infrastructure for quality transformation: measurement and reporting in veterans administration intensive care units.

Marta L Render1, Ron W Freyberg, Rachael Hasselbeck, Timothy P Hofer, Anne E Sales, James Deddens, Odette Levesque, Peter L Almenoff.   

Abstract

BACKGROUND Veterans Health Administration (VA) intensive care units (ICUs) develop an infrastructure for quality improvement using information technology and recruiting leadership. METHODS Setting Participation by the 183 ICUs in the quality improvement program is required. Infrastructure includes measurement (electronic data extraction, analysis), quarterly web-based reporting and implementation support of evidence-based practices. Leaders prioritise measures based on quality improvement objectives. The electronic extraction is validated manually against the medical record, selecting hospitals whose data elements and measures fall at the extremes (10th, 90th percentile). results are depicted in graphic, narrative and tabular reports benchmarked by type and complexity of ICU. RESULTS The VA admits 103 689±1156 ICU patients/year. Variation in electronic business practices, data location and normal range of some laboratory tests affects data quality. A data management website captures data elements important to ICU performance and not available electronically. A dashboard manages the data overload (quarterly reports ranged 106-299 pages). More than 85% of ICU directors and nurse managers review their reports. Leadership interest is sustained by including ICU targets in executive performance contracts, identification of local improvement opportunities with analytic software, and focused reviews. CONCLUSION Lessons relevant to non-VA institutions include the: (1) need for ongoing data validation, (2) essential involvement of leadership at multiple levels, (3) supplementation of electronic data when key elements are absent, (4) utility of a good but not perfect electronic indicator to move practice while improving data elements and (5) value of a dashboard.

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Year:  2011        PMID: 21345859     DOI: 10.1136/bmjqs.2009.037218

Source DB:  PubMed          Journal:  BMJ Qual Saf        ISSN: 2044-5415            Impact factor:   7.035


  8 in total

1.  Implications of Heterogeneity of Treatment Effect for Reporting and Analysis of Randomized Trials in Critical Care.

Authors:  Theodore J Iwashyna; James F Burke; Jeremy B Sussman; Hallie C Prescott; Rodney A Hayward; Derek C Angus
Journal:  Am J Respir Crit Care Med       Date:  2015-11-01       Impact factor: 21.405

2.  Temporal Changes in the Influence of Hospitals and Regional Healthcare Networks on Severe Sepsis Mortality.

Authors:  Hallie C Prescott; Kyle M Kepreos; Wyndy L Wiitala; Theodore J Iwashyna
Journal:  Crit Care Med       Date:  2015-07       Impact factor: 7.598

3.  Comparing Catheter-Associated Urinary Tract Infection Prevention Programs Between Veterans Affairs Nursing Homes and Non-Veterans Affairs Nursing Homes.

Authors:  Lona Mody; M Todd Greene; Sanjay Saint; Jennifer Meddings; Barbara W Trautner; Heidi L Wald; Christopher Crnich; Jane Banaszak-Holl; Sara E McNamara; Beth J King; Robert Hogikyan; Barbara S Edson; Sarah L Krein
Journal:  Infect Control Hosp Epidemiol       Date:  2016-12-05       Impact factor: 3.254

Review 4.  Using existing data to address important clinical questions in critical care.

Authors:  Colin R Cooke; Theodore J Iwashyna
Journal:  Crit Care Med       Date:  2013-03       Impact factor: 7.598

5.  The Veterans Affairs Cardiac Risk Score: Recalibrating the Atherosclerotic Cardiovascular Disease Score for Applied Use.

Authors:  Jeremy B Sussman; Wyndy L Wiitala; Matthew Zawistowski; Timothy P Hofer; Douglas Bentley; Rodney A Hayward
Journal:  Med Care       Date:  2017-09       Impact factor: 2.983

6.  Perception Versus Actual Performance in Timely Tissue Plasminogen Activation Administration in the Management of Acute Ischemic Stroke.

Authors:  Cheryl B Lin; Margueritte Cox; DaiWai M Olson; Gavin W Britz; Mark Constable; Gregg C Fonarow; Lee Schwamm; Eric D Peterson; Bimal R Shah
Journal:  J Am Heart Assoc       Date:  2015-07-22       Impact factor: 5.501

7.  Development and usability testing of an audit and feedback tool for anesthesiologists.

Authors:  Atilio Barbeito; Noa Segall
Journal:  JAMIA Open       Date:  2019-02-04

8.  Variation in model performance by data cleanliness and classification methods in the prediction of 30-day ICU mortality, a US nationwide retrospective cohort and simulation study.

Authors:  Theodore J Iwashyna; Cheng Ma; Xiao Qing Wang; Sarah Seelye; Ji Zhu; Akbar K Waljee
Journal:  BMJ Open       Date:  2020-12-02       Impact factor: 2.692

  8 in total

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