I read Fretheim and Tomic's article [1] 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
homoscedastici...
I read Fretheim and Tomic's article [1] 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. [2]
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?
[1] 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
[2] A. H. Welsh, R. J. Carroll, D. Ruppert, Fitting Heteroscedastic
Regression Models. Journal of the American Statistical Association
1994;89:100-116
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 healthc...
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.
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 n...
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.
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...
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.
REFERENCES:
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.
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...
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.
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....
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.
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...
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.
References
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.
Overdyk et al. used remote video auditing with real-time feedback in
a surgical suite [1]. 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)....
Overdyk et al. used remote video auditing with real-time feedback in
a surgical suite [1]. 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 [3]). 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 [5]. 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).
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; howev...
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.
References:
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
We were very interested to read the recent article by Feudtner et a,1
which has stated that Tall Man lettering has not changed the rate of look-
alike sound-alike (LASA) related prescription or dispensing medication
errors significantly in 42 children`s hospitals form 2004 to 2012.
Feudtner et al`s study is a very valuable work because they performed an
extensive statistical analysis on routine medication pairs of their
h...
We were very interested to read the recent article by Feudtner et a,1
which has stated that Tall Man lettering has not changed the rate of look-
alike sound-alike (LASA) related prescription or dispensing medication
errors significantly in 42 children`s hospitals form 2004 to 2012.
Feudtner et al`s study is a very valuable work because they performed an
extensive statistical analysis on routine medication pairs of their
hospital, and punctually discussed limitation of their results.
It is well-documented that drugs whose names are spelled or sound similar
may cause potentially dangerous medication errors. LASA errors are
prevalent both in the hospital and in the outside the hospital but they
are more dangerous in the latter, because the patients are not readily
available.2
We have encountered frequent out-patient cases with LASA errors in our
clinical practice in recent years including: 32 year old woman was
prescribed Dilantin (phenytoin) for subarachnoid hemorrhage (SAH) but
received Daonil (glibenclamide); A 35 year old woman was prescribed
prednisone 5 mg for allergic disorder but prednisolone 50 was given
instead; A 65 year old woman visited an internist for her digestive
complications, she was administered "Digestive" tablets, but the pharmacy
filled her prescription with digoxin. Unfortunately some of these errors
undetected for several days to months and resulted to hospital admission.
Various factors can increase the risk of LASA errors especially poor
handwriting can be a potential cause of LASA errors, 3 therefore
implementation of computerized physician order entry
(CPOE) has decreased this type of errors4 and after implementation of CPOE
we are not able to accurately conclude whether or not Tall Man lettering
is an efficient way to reduce rate of LASA errors.
Furthermore, none of single reported methods could prevent these errors
effectively; therefore to decrease the risk of LASA errors a
multidimensional and integrated method should be implemented. Some of
these methods included appropriate nomination of new drugs with
comprehensive statistical methods, using generic names of drugs in
prescriptions, more advanced drug distribution systems, and educating
patients, physicians, and pharmacists, CPOE, and Tall Man lettering.5
According to our clinical experiences and extensive literature references,
we conclude that there is not still enough evidence to reject the
effectiveness of Tall Man lettering strategy. For better estimation it is
suggested to perform a comprehensive investigation and other intervening
and important factors is considered.
1. Zhong W, Feinstein JA, Patel NS, et al. Tall Man lettering and
potential prescription errors: a time series analysis of 42 children's
hospitals in the USA over 9 years.BMJ Qual Saf 2015 doi:10.1136/bmjqs-2015
-004562 [Published Online First: 3 November 2015]
2. Ciociano N, Bagnasco L: Look alike/sound alike drugs: a literature
review on causes and solutions. Int J Clin Pharm 2014; 36:233-42.
3. Knudsen P, Herborg H, Mortensen AR, et al. Preventing medication errors
in community pharmacy: root?cause analysis of transcription errors. Qual
Saf Health Care 2007; 16(4): 285-90.
4. Hernandez F, Majoul E, Montes-Palacios C, et al. An Observational Study
of the Impact of a Computerized Physician Order Entry System on the Rate
of Medication Errors in an Orthopaedic Surgery Unit. PLoS One 2015;
10(7):e0134101. doi: 10.1371/journal.pone.0134101. eCollection 2015.
5. Ostini R, Roughead EE, Kirkpatrick CMJ, et al. Quality Use of Medicines
- medication safety issues in naming; look-alike, sound-alike medicine
names. International Journal of Pharmacy Practice 2012; 20: 349-57.
I read Fretheim and Tomic's article [1] 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 homoscedastici...
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 healthc...
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 n...
Dear Editor,
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...
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...
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....
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...
Overdyk et al. used remote video auditing with real-time feedback in a surgical suite [1]. 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)....
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; howev...
We were very interested to read the recent article by Feudtner et a,1 which has stated that Tall Man lettering has not changed the rate of look- alike sound-alike (LASA) related prescription or dispensing medication errors significantly in 42 children`s hospitals form 2004 to 2012. Feudtner et al`s study is a very valuable work because they performed an extensive statistical analysis on routine medication pairs of their h...
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