Displaying 1-10 letters out of 91 published
Why do we love to hate ourselves?
Dhaliwal's comment  on Zwaan et al  nicely refutes what has been called "the hypothesis of special cause"  - the notion that when things turn out wrong, the cognitive processes leading to that outcome must have been fundamentally different (ie, error-prone) from when they turn out right. Dhaliwal's argument recapitulates thinking that is over 100 years old; one of the early contributors to psychology, Ernst Mach, wrote (in 1905): "Knowledge and error flow from the same mental source; only success can tell one from the other" .
What is interesting here is not that the hypothesis of special cause is wrong, but rather the question of why has it been so popular and persistent. What is it about the notion of humans as fundamentally irrational, poor decision-makers that gives this idea such wide appeal? After all, broad acceptance of this sort is not the norm for most psychological or medical research; controversy, argument, or outright disbelief are much more common . Christensen-Szalanski and Beach surveyed decision-making studies in psychology and reported that, although the studies' conclusions were roughly evenly divided between finding good or poor decision-making performance (56% vs 44%), studies reporting human performance as flawed were cited almost 6 times more frequently than those reporting it good. Citations outside of psychology journals were overwhelmingly used to advance the claim that people are poor decision-makers .
One reason for this strange popularity is that the people-are-irrational claim provides benefits for those who have rationality to sell: guideline authors, health care managers, and other proponents of scientific-bureaucratic medicine [6,7]. Another is that it paradoxically provides individual benefits: once we understand the clever puzzles of heuristics and biases problems, even in retrospect, we tend to feel that we must be pretty clever also. And a final, and likely strongest influence, is that it protects organizations and elites: attributing adverse events to flawed mental processes at the front lines serves as a kind of lightning rod, conducting the harmful consequences of bad outcomes down an organizationally safe pathway .
Unfortunately, the history of patient safety to date does not suggest that cautions such as Dhaliwal's will have much effect; such cautions have been raised and ignored before [9-12]. Patient safety's fixation on 'medical error' as the fundament of medical harm serves many (perhaps extraneous) purposes, but is based on an ontological will-of-the-wisp [3,13,14]. Given general agreement on the meagre progress of the patient safety movement to date [15-18], a fundamental re-thinking of our basic premises and hidden assumptions is desperately needed if we are to move forward. And as with many fixations, a sea-change of this sort is not likely to come from within the present patient safety movement, but must come from the outside [19,20]. We can only hope 'these barbarians' challenge us sooner rather than later .
1. Dhaliwal G. Premature closure? Not so fast. BMJ Quality & Safety 2016 bmjqs-2016-005267:online ahead of print.
2. Zwaan L, Monteiro S, Sherbino J, Ilgen J, Howey B, Norman G. Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups. BMJ Quality & Safety 2016.
3. Hollnagel E. Safety-I and Safety-II: The Past and Future of Safety Management. Farnham, UK: Ashgate; 2014, 187 pages.
4. Mach E. Knowledge and Error. Translated by Foulkes P, McCormack TJ. Dordrecht, Netherlands: Reidel Publishing Co; 1905 (English translation 1976), 393 pages.
5. Lopes LL. The Rhetoric of Irrationality. Theory & Psychology 1991;1(1):65-82.
6. Harrison S, Moran M, Wood B. Policy emergence and policy convergence: the case of 'scientific-bureaucratic medicine' in the United States and United Kingdom. The British Journal of Politics & International Relations 2002;4(1):1-24.
7. Wears RL, Hunte GS. Seeing patient safety 'Like a State'. Safety Science 2014;67:50-57.
8. Cook RI, Nemeth C. "Those found responsible have been sacked": some observations on the usefulness of error. Cogn Technol Work 2010;12(1):87-93.
9. Henriksen K, Kaplan H. Hindsight bias, outcome knowledge and adaptive learning. Qual Saf Health Care 2003;12(Suppl 2):ii46-ii50.
10. Dekker SWA. Patient Safety: A Human Factors Approach. Boca Raton, FL: CRC Press; 2011, 250 pages.
11. Hollnagel E. Does human error exist? In: Senders JW, Moray NP, eds. Human Error: Cause, Prediction, and Reduction. Hillsdale, NJ: Lawrence Erlbaum Associates; 1991: pp 153.
12. Wears RL. The error of chasing 'error'. Northeast Florida Medicine 2007;58(3):30-31.
13. Dekker SWA. Is it 1947 yet? http://www.safetydifferently.com/is-it-1947-yet/, accessed 19 May 2015.
14. Woods DD, Dekker SWA, Cook RI, Johannesen L, Sarter N. Behind Human Error. 2nd ed. Farnham, UK: Ashgate; 2010, 271 pages.
15. National Patient Safety Foundation. Free From Harm: Accelerating Patient Safety Improvement Fifteen Years after To Err Is Human. Cambridge, MA: National Patient Safety Foundation; 2015, http://www.npsf.org/custom_form.asp?id=03806127-74DF-40FB-A5F2-238D8BE6C24C, accessed 8 December 2015, 59 pages.
16. Pronovost PJ, Ravitz AD, Stoll RA, Kennedy SB. Transforming Patient Safety: A Sector-Wide Systems Approach: Report of the WISH Patient Safety Forum 2015. Qatar: World Innovation Summit for Health; 2015, http://dpnfts5nbrdps.cloudfront.net/app/media/1430, accessed 18 February 2015, 52 pages.
17. Baker GR, Black G. Beyond the Quick Fix. Toronto, ON: University of Toronto; 2015, http://ihpme.utoronto.ca/wp-content/uploads/2015/11/Beyond-the-Quick-Fix-Baker-2015.pdf, accessed 12 November 2015, 32 pages.
18. Illingworth J. Continuous improvement of patient safety: the case for change in the NHS. London, UK: The Health Foundation; 2015, http://www.health.org.uk/sites/default/files/ContinuousImprovementPatientSafety.pdf, accessed 12 November 2015, 40 pages.
19. De Keyser V, Woods DD. Fixation Errors: Failures to Revise Situation Assessment in Dynamic and Risky Systems. In: Colombo AG, de Bustamante AS, eds. Systems Reliability Assessment: Springer Netherlands; 1990: pp 231-251.
20. Woods DD, Cook RI. Perspectives on human error: hindsight biases and local rationality. In: Durso FT, Nickerson RS, Schvaneveldt RW, et al., eds. Handbook of Applied Cognition. 1st ed. New York, NY: John Wiley & Sons; 1999: pp 141-171.
21. Cavafy C. Waiting for the Barbarians. http://www.cavafy.com/poems/content.asp?id=119&cat=1 . accessed 6 March 2014.
Conflict of Interest:
Statistical Process Control and Interrupted Time Series
I read Fretheim and Tomic's article  with interest as I trained in frequentist stastistics and now work primarily with Stastistical Process Control (SPC) in quality improvement (QI) initiatives.
I concur that there are missed opportunities for using Interrupted Time Series (ITS) in QI; however, I note cautions in doing so:
Regression models applied in ITS often have the assumption of homoscedasticity - i.e. that the process is no more or less variable over time. In evaluation of QI initiatives we are seeking to violate that assumption in that we wish to change a variable and non-performing system into a reliable and highly performing system. This means that the ordinary least squares estimators would not be best linear unbiased, with a risk of overestimating the goodness of fit. This can be addressed using generalised least squares estimators. 
Applying an ITS break point immediately on "intervening" assumes that the intervention is immediately and consistently applied from that point on. This might be true for a total replacement of one drug with another, but is less clear for behavioural change interventions, such as hand hygiene in hospitals. A similar case can be made for care bundle interventions - one may start bundle in all cases, yet all aspects of the bundle may not be consistently conducted.
I suspect that, as with statistics in general, that care is required in selecting one's test, which will depend on the purpose required.
Perhaps a mixed method of SPC and ITS could be preferred?
 A. Fretheim, O.Tomic. Statistical process control and interrupted time series: a golden opportunity for impact evaluation in quality improvement. BMJ Quality and Safety 2015;24:748-752
 A. H. Welsh, R. J. Carroll, D. Ruppert, Fitting Heteroscedastic Regression Models. Journal of the American Statistical Association 1994;89:100-116
Conflict of Interest:
Hand Washing is about Respect for Patients
The paper by Redelmeier and Shafir resonated strongly with me because I have always believed that there are important factors that motivate some physicians to wash their hands while others behave differently. I agree completely that this is a more complex issue than has been previously noted. I always wash my hands in front of patients and have done so for over 40 years. This has very little to do with the risks of healthcare associated infections and much more to do with respect for patients and a commitment to patient-centered care.
I was a pediatric resident at Boston Children's Hospital in the mid- 1970's and as nonchalant about hand washing as everyone else. Fortunately, I had a wonderful mentor whose example changed me. Professor Charles A. Janeway was a renaissance figure in international pediatrics and an excellent teacher. Though in the twilight of his career Prof Janeway would make rounds once a week with one of the senior residents and ward team, examining a patient or two and then discussing the diagnosis and management of each child.
One day we presented the case of a toddler with chronic inflammatory arthritis. As Prof Janeway entered the patient's room, he washed his hands, introducing himself to the child's mother, and then sat and talked calmly with her, once holding her hand when she became tearful. He asked if he might examine her child who was sitting in her lap and clinging to her. Before examining the child he washed his hands a second time. After the exam and further discussions with the mother, he washed his hands again, a third time, before leaving the room.
In a small conference room we began to discuss the case, and one of the students asked Professor Janeway why he washed his hands three times. He slowly looked around at all of us, and said something to the effect of the following.
"I washed my hands on entering and leaving the room because I did not want to bring any infectious agents into or out of the room. I washed my hands again, the second time before examining this frightened child, because there is something about washing hands that sends a message about caring. It is an honor and privilege to practice medicine and hand washing sends a message about respect. The sound of water flowing and the warmth of hands after washing conveys sensitivity and compassion, and patients find this comforting."
I never forgot this lesson and have always washed my hands in front of patients, not so much because of my fears of infection transmission, but because of the message it sends to them. It's not all that complicated really.
Ref: 1. Redelmeier DA, Shafir E. Why even good physicians do not wash their hands. BMJ Qual Saf 2015;24:744-747.
Conflict of Interest:
What did Albert Einstein ever do?
Reed and Card's essay on the problem of valuing action over thought could not have come at a better time. For years, quality and safety mavens have been paraphrasing Goethe -- "Knowing is not enough ... we must do". But the resulting culture of 'do, do, do' has brought us quite a lot of doo-doo.
To counter this, consider the question, "What did Einstein ever do?" He invented nothing, patented nothing, created no research teams, built no institutions, presided over nothing. He published a few academic papers, but funding agencies today don't care about academic papers -- they want action, and so they get -- doo-doo.
Conflict of Interest:
Patient-centered bedside rounds-Exploring patient preferences before patient-centered care
It was with great interest that we read the study of O'Leary et al published in the December issue of the journal and were quite surprised by their findings that patient centered- rounds had no impact on patients' perceptions of shared decision making, activation, and satisfaction with care.1
Previous studies have shown that patients prefer their rounding team conduct rounds at the bedside 2-5and based on these studies, one would expect that if bedside rounds were conducted, patients would feel more satisfied with their care and be more engaged in medical decision making compared to other forms of rounding.
The findings of this study do make us pause and reconsider some of our perceived beliefs regarding patient benefits from bedside rounds. The authors propose several explanations to support their findings. However, before abandoning patient-centered bedside rounding (PCBR), one must consider several potential issues that may make this study less generalizable. One explanation not explored might be the possibility of patients being asleep at that time of the day (7.30 am) and they may not have wanted or have been in a position to participate in PCBR. Additionally, the control group was cared for by a small team: one of the units was a cardiac type unit where patients were being admitted to initiate and monitor medications. It is possible that the small care team, type of patients on that unit, and the general structure of the control team was designed so patients may have had positive perceptions about their care, which might explain their findings. It is also possible that the language used by the team during PCBR after the initial few weeks of mentoring may have contained medical jargon or the script used to invite patient participation may not have been r conducive to patient engagement. These potential factors could have affected the perception by patients.
An important critique of the study is that patients were not given a choice of whether they in fact wanted PCBR. In our experience of querying Veterans at our institution, while the majority state they would prefer PCBR "If they have something to say, I want to hear it", a sizable minority prefer NOT to have PCBR, as they are uncomfortable with medical uncertainty and hearing worst case scenarios "You're the doctor. You tell me". Perhaps a better approach would be to ask every patient upon admission if they prefer team rounds at the bedside or outside the room. The teams should ask the patient how much they would like to participate in their care, and whether they'd be comfortable if there were other patients in the hospital room, and then proceed accordingly. It is essential to explain what these rounds entail and possible roles the patient can assume. Once patients are provided this information they may be in better position to think through their choice of actively participating or not in becoming informed customers; they may be able to make the choice that best suits their preferences. Given the challenges of executing PCBR and O'Leary's findings perhaps PCBR should only be done on those that actually want them. As simplistic as it sounds, patients should actually be asked in a patient-centered manner whether they actually want patient centered bedside rounding.
1. O'Leary, KJ, et al, Effect of patient-centered bedside rounds on hospitalized patients' decision control, activation and satisfaction with care, BMJ Qual Saf 2015;0:1-8. doi:10.1136/bmjqs-2015-004561
2. Wang-Cheng, R.M., et al., Bedside case presentations: why patients like them but learners don't. J Gen Intern Med, 1989. 4(4): p. 284-7
3 Rogers, H.D., J.D. Carline, and D.S. Paauw, Examination room presentations in general internal medicine clinic: patients' and students' perceptions. Acad Med, 2003. 78(9): p. 945-9. 4. Gonzalo, J.D., et al., The return of bedside rounds: an educational intervention. J Gen Intern Med, 2010. 25(8): p. 792-8.
5. Lehmann, L.S., et al., The effect of bedside case presentations on patients' perceptions of their medical care. N Engl J Med, 1997. 336(16): p. 1150-5.
Conflict of Interest:
The problem with incident reporting
Dear Sir or Madam
I read with interest the editorial by Carl Macrae on incident reporting. I wonder if, in making a detailed comparison with the aviation and other industries, Macrae loses sight of one important reason why health services staff report incidents. My experience suggests that often the purpose of reports is not to learn from incidents but for staff to pre -emptively give their version of events in case punitive sanctions follow from an incident. Defensive actions and fear of blame seem to commonly drive reporting. In such circumstances biased reporting and telling your boss are understandable responses.
Conflict of Interest:
Re:More information on safety culture in long-term care
We appreciate Dr. Singer's point about a more thorough discussion of the large literature on safety climate and tools for assessing it. Although we did include two of the articles she refers to; not all were included. While acknowledging and discussing other instruments for measuring Patient Safety Climate (PSC), would have made our article more complete, the findings and conclusions of the study would not have changed. For instance, we would have still chosen the Safety Attitude Questionnaire (SAQ) to measure PSC in nursing and residential homes, as we aimed to benchmark our findings with other health care settings (inpatient, ICU, ambulatory care) in the Netherlands and abroad. The results for benchmarking constitute a substantial part of our findings and discussion. The SAQ is a frequently used survey in multiple healthcare settings and is often used as a foundation for other PSC surveys. Thus, we chose the SAQ so that our assessment of PSC in nursing and residential homes in The Netherlands would not stand in isolation, but could be considered in the context of international results. In conclusion, we should have discussed more recent literature on other possible PSC surveys and explained better why we chose the SAQ. But, we believe this oversight does not affect the substance of our findings--nor apparently does Dr Singer.
Conflict of Interest:
More information on safety culture in long-term care
To the Editor: I was a little surprised to see Buljac-Samardzic et al. in their recent article on safety culture in long-term care state that few tools are available to evaluate the effectiveness of initiatives to improve safety culture in nursing and residential homes. While there may be fewer tools available for nursing and residential homes than inpatient settings, there are several safety climate instruments that are worthy of note [1-5]. Additionally, the authors provide weak support for their reliance on their instrument of choice. To conclude that one survey is the best available general climate measure based on a review from 2005seems incomplete. While I agree with the authors that we need more instruments for measurement in nursing and residential homes and believe the authors selected a fine measure of safety climate, the authors do themselves and their study a disservice by not providing a more thorough acknowledgement of previous research.
1 Handler SM, Castle NG, Studenski SA, et al. Patient safety culture assessment in the nursing home. Quality and Safety in Health Care 2006; 15:400-4. doi:10.1136/qshc.2006.018408
2 Hughes CM, Lapane KL. Nurses"and nursing assistants" perceptions of patient safety culture in nursing homes. Int J Qual Health Care 2006; 18:281-6. doi:10.1093/intqhc/mzl020
3 Singer SJ, Kitch BT, Rao SR, et al. An Exploration of Safety Climate in Nursing Homes. J Patient Saf 2012; 8:104-24. doi:10.1097/PTS.0b013e31824badce
4 Hartmann CW, Meterko M, Zhao S, et al.Validation of a novel safety climate instrument in VHA nursing homes. Medical Care Research and Review 2013; 70:400-17. doi:10.1177/1077558712474349
5 Bonner AF, Castle NG, Perera S, et al. Patient Safety Culture: A Review of the Nursing Home Literature and Recommendations for Practice. Ann Longterm Care 2008; 16:18-22.
Conflict of Interest:
Statistical analysis of differences in turnover times among operating theatres
Overdyk et al. used remote video auditing with real-time feedback in a surgical suite . As part of their randomized trial clustered by theatre, they report less turnover times among "fast rooms," those generally including 3 or greater cases per day.
Successive turnover times between scheduled cases within theatres on the same date tend to be correlated (e.g., caused by same surgeon, nurses, and anaesthetist). This was shown in Dexter et al. 2005 and Austin et al. 2014 [2,3]. Overdyk et al.'s description of their statistical model seems not to describe consideration of correlations of turnover times within the same theatre on the same day. This can be rectified by including the theatre-day combination as a fixed or random effect. Alternatively, and typically, analyses take the simpler approach of batching (binning) by each day, week, 2 week, or 4-week period, and then comparing the periods (e.g., week) pairwise between control (i.e., no feedback) and intervention (i.e., feedback) theatres (e.g., Reference ). When the authors sort the turnover times in sequence of date, then theatre, and then start time, do the authors have statistically significant lag 1 correlation? If yes, then, when analyses are repeated by either including that correlation in the statistical model or by making comparison pairwise by week (or other suitable interval), what are the revised results of the authors' Table 2?
Turnovers that are occurring simultaneously among theatres on the same day can be correlated if personnel are shared (e.g., housekeepers and anaesthesia technicians) [4,5]. For example, Wang et al. found most turnovers greater than 1 hour occurred at their studied surgical suite when there were >2 simultaneous turnovers . Overdyk et al.'s description of their statistical model does not seem to describe consideration of correlations of turnover times on the same day and time among theatres. Although this can be rectified by including a fixed effect of the time varying number of simultaneous turnovers, usually analyses compensate by batching (binning) by each day, week, etc. [2-5]. Do the authors have significant correlation between numbers of simultaneous turnovers at each time and turnover times? If yes, then when analyses are repeated, what are the revised results of the authors' Table 2?
References 1 Overdyk FJ, Dowling O, Newman S, et al. Remote video auditing with real- time feedback in an academic surgical suite improves safety and efficiency metrics: a cluster randomised study. BMJ Qual Saf 2015; PMID: 26658775 2 Dexter F, Epstein RH, Marcon E, et al. Estimating the incidence of prolonged turnover times and delays by time of day. Anesthesiology 2005;102:1242-8 3 Austin TM, Lam HV, Shin NS, et al. Elective change of surgeon during the OR day has an operationally negligible impact on turnover time. J Clin Anesth 2014;26:343-9 4 Dexter F, Marcon E, Aker J, et al. Numbers of simultaneous turnovers calculated from anesthesia or operating room information management system data. Anesth Analg 2009;109:900-5 5 Wang J, Dexter F, Yang K. A behavioral study of daily mean turnover times and first case of the day start tardiness. Anesth Analg 2013;116:1333-41
Conflict of Interest:
Financial disclosure: Arrowsight paid the University of Iowa's Department of Anesthesia for consulting by Dr. Dexter in 2012 (see http://www.FranklinDexter.net/FAQ.htm).
Public website for interrupted time series and segmented regression
We agree with the authors that interrupted time series should be used more often (1). We also agree that the statistics are difficult. We find segmented regression to be the preferable form of interrupted time series (ITS) as traditional ITS with the Davies tests only looks for a change in slope at the breakpoint. This works well if there is not a simultaneous change or shift in the level of the outcome at the breakpoint; however, when both a change in slope and a shift in level occur, the Davies test is problematic. In addition to segmented regression, we use multivariable linear regression to detect secular trends in outcomes over time.
In response to the difficulties, we have placed online at http://qitools.github.io/ a resource for using and teaching segmented regression. The website accepts data sets by pasting or uploading values.
The underlying source code is written in R and is publicly available at GitHub (https://github.com/qitools/charts). In addition to being open-source, the code is implemented online at openCPU so users do not have to install R on their own computers. The combination of GitHub and openCPU allows for crowdsourcing improvements or alternative versions. We encourage other investigators to improve the source code at https://github.com/qitools/charts for implementation that we have started.
1. Fretheim A, Tomic O. Statistical process control and interrupted time series: a golden opportunity for impact evaluation in quality improvement. BMJ Qual Saf. 2015 Dec;24(12):748-52. doi: 10.1136/bmjqs-2014-003756. PMID: 26316541
Conflict of Interest:
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