eLetters

49 e-Letters

published between 2014 and 2017

  • A simple example of a practical solution to make patient-feedback more useful

    With great interest we read the article of Flott et. al. (1), describing the challenges of using patient-reported feedback. We recognize the challenges described and performed a bachelorproject in the intensive care unit (ICU) in the University Medical Center Groningen (UMCG). We think the results from our project provide a potential promising practical solution to make feedback more useful.
    In 2013 the UMCG participated in an independent multi-center study conducted among relatives of ICU patients (2). In the open questions of the questionnaire more dissatisfaction than expected was found, which fueled the quest for an alternative, simple and continuous feedback system. In this study we compared the quality and amount of feedback gathered by an oral survey during the first two weeks and an app during the consecutive two weeks.
    Between February 20th and March 18th 2017, patients above sixteen years old, listed for discharge from the ICU that day and their relatives were approached to participate in this study. The oral survey consisted of two simple questions: “How satisfied are you with your stay in the ICU? (grade 1-10)” and ”Do you have specific suggestions of improvement for the ICU?”. The RateIt app (Rate It Limited®, Hong Kong) was used consisting of the same two questions as in the oral survey.
    A total of 208 responses (133 patients and 75 relatives) were included. The median satisfaction score was 8. Despite this high score many suggestions for...

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  • SPC and Complexity

    As you point out Root Cause Analysis will often fail with hospital adverse event (AE) data because it was not designed to deal with data arising in a complex system.1 The same can be said for Pareto analysis. Statistical process control (SPC) methods are often used to summarise AE data, particularly hospital infection data such as surgical site infections (SSIs) and bacteraemias.2 Standard SPC also frequently fails to summarise these complex data correctly.
    With binary SSI data an approximate expected rate is frequently available so cumulative observed minus expected and CUSUM analysis are appropriate.2 However, the changing observed rate is not seen unless the numbers of procedures is large enough for them to be grouped by months or quarters. This is often infrequent. Even when such aggregation is possible difficulties arise as the number of procedures in each month may differ markedly. This problem can be dealt with, at least approximately, by employing a generalised additive model (GAM) analysis to the binary data that predicts the observed AE rate at various places in the time series.
    Count and rate data such as bacteraemias or new isolates of an antibiotic-resistant organism will usually not have an expected rate available. These data are often grouped by months and a Shewhat chart used for their display. This chart requires a stable centre-line about which reliable control limits can be drawn. Often the mean value is used as the expected rate even though...

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  • Promoting Improvement and Learning through Embedded Research

    Vindrola-Padros and colleagues provide a helpful examination of co-production of quality improvement knowledge by university-based researchers in cooperation with members of service organizations. Another important type of embedded researcher consists of “fully embedded,” researchers, who are academically trained but employed by large care delivery systems. These individuals typically work in research units in the delivery systems. Their work is funded both by the systems themselves and by external, private and public organizations, such as the Agency for Healthcare Research and Quality (AHRQ). These fully embedded researchers contribute actively to national professional forums and journals and sometimes collaborate with embedded researchers in other systems.

    AHRQ leverages relationships with fully embedded researchers because of their deep and nuanced knowledge of internal system data and operations. Health systems-based researchers’ ready access to care sites within which to test new approaches, and to data sources that permit rapid analysis of results of those tests, are of great value to AHRQ as we seek to find solutions to real-world problems in areas of national importance. AHRQ-supported work of this kind demonstrates the value of health delivery organizations becoming “learning health systems”(1) – using their own internal data and resources to drive quality improvement and sharing their findings with other organizations.

    AHRQ’s collaboration w...

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  • Why are the EMRs not named?

    This study uses rigorous analysis to obtain important insights about the realtime information that our patients are handed at discharge. It is puzzling that the EMRs used were not named. One can infer from a look through the MSU website that they have both Cerner and Epic, but why is that necessary? The heart of quality/safety work is one of transparency balanced by humility, i.e. we shouldn't expect our IT systems to be any more perfect than we are, but they won't improve if we don't have more openness. The lack of scientific foundations and published post-marketing surveillance for our EHRs, especially the ascendant ones, was initially surprising. However, as they achieve complete market dominance, with less overt scientific review and public guidance and commentary, the silence is deafening. Is the BMJQS's failure to simply identify the names (or maybe I missed the citations) an oversight, or part of nondisclosure agreements with the vendors at the MSU institutions or at BMJQS?

  • The contributions of pediatric hospitals to highly reliable healthcare
    Richard J. Brilli, MD

    To the Editor:

    In this article, the authors propose that little evidence exists in healthcare to show that application of Highly Reliable Organization (HRO) principles has resulted in significant or sustained improvement in performance. Further, they attribute the problem partially to under- recognizing the role of habit in the process. While we fully agree that forming habitual behavior is essential to creating...

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  • Healthcare Complaints: a valid metric for quality of care?
    Adam M Ali

    I read with interest the paper by Gillespie and Reader presenting the Healthcare Complaints Analysis Tool (HCAT) (1). The authors suggest that the HCAT could be used "as an alternative metric of success in meeting standards" and as a way "to benchmark units or regions". However, this makes the assumption that the volume and strength of complaints received is an accurate reflection of the standard of care being delivered....

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  • Authors response: Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors
    Olivia Ferrandez Quirante

    To the Editor,

    We have read with great interest the article by Schiff G D et al.,1 in which 6.1% of errors reported to the United States Pharmacopeia MEDMARX reporting system were classified as being related to the computerized prescription order entry (CPOE) system, representing the third most frequently reported errors in this notification system.

    Similarly, in a study conducted in our hospital, appro...

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  • Weekend Effect (again) and Erudite Company
    Andrew Stein

    In this paper, Professor Sutton's team attribute higher hospital death rates at the weekend to the patients being sicker. Sutton is joining very erudite company (Prof Hawking, Prof Winston and the BMA). This group is rapidly becoming the 'climate change deniers' of healthcare. Not including this study, there have been 50 very large studies (>100,000 patients) published so far in this area (supplied on request). 44 show...

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  • SPC Versus GAM for hospital adverse events arising in a complex system
    Anthony P Morton

    Statistical process control works well when there is independence and linearity. Complex systems produce data that are often not independent, often nonlinear and display self-organisation and emergent behaviour. To say that statistical process control works when behaviour is emergent may make little sense. Increasingly adverse events like colonisation with antibiotic-resistant organisms arise in a complex system. Although...

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  • Improving safety culture to reduce adverse events
    Girish Swaminathan

    Reynolds et al1 reported the impact of providing prescriber feedback in reducing prescribing errors. The authors have concluded that reducing prescribing errors needs a multifaceted approach and feedback alone is not sufficient. Medication errors are often preventable and inappropriate prescribing is identified as an important contributing factor to medication errors.2 It is interesting to note that despite regular feedb...

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