Healthcare Consulting Services
October 2, 2012
Test Results: Everyone's Worst Nightmare
Last month there was a news article on Bloomberg.com about a test results follow up error that was an absolute nightmare for a patient and her family, a physician, and a laboratory (Langreth 2012).
In the unfortunate case presented in the article, a woman with a history of breast cancer was prepared to undergo bilateral prophylactic mastectomy if she had the BRCA1 or BRCA2 breast cancer gene mutations that predispose to breast and ovarian cancer. That would also have potential implications for other family members who might also have these gene mutations and be at risk for cancer. After some difficulties getting insurance authorization for the test to be done she finally underwent the testing. Her physician told her the test was negative and the patient was quite relieved. However, almost 3 years later she found another breast lump and turned out to have advanced breast cancer. She underwent bilateral mastectomies and removal of her uterus and ovaries and received chemotherapy. When her new oncologist recommended genetic counseling, the genetic counselor called for the results of the prior testing and, to the surprise of the patient, the main test done 3 years earlier had in fact been “positive for a deleterious mutation”.
Here is where the details get cloudy, perhaps because the article could not get complete information from the original physician and the laboratory, both of whom seemed reluctant to provide full information perhaps out of concern about potential litigation. But it appears that there were actually two types of testing done by the lab. The first test looking for “large rearrangements”, which account for 6-9% of the BRCA mutations, was reported as saying “no mutations detected”. The second test, which detects mutations that account for an 84% risk of breast cancer and 27% risk of ovarian cancer, was “positive for deleterious mutation”. The 2 tests were apparently sent to the physician approximately 2 weeks apart. The article specifies the report of the positive test was sent via Federal Express and does not specify how the negative test result, which apparently was the one sent later, was delivered. The only response given by the physician to the reporter in the article was that he felt it was quite likely he had never seen the report with the positive result. The article implies that he had circled and initialed the “negative” report but no sheets with his initials on a “positive” report were found (note that the physician only provided a copy of the “negative” report for the article). The lab did note they had contacted the physician’s office about a week after the second report was sent and left a voice message for the RN in the office to “clarify test results”. And to complicate matters, it appears that the second test (the “negative” one) may not have even been ordered but rather added on by the lab as a free test.
The article included commentary from Ellen Matloff of the Yale Cancer Center who has coauthored several excellent articles on adverse events associated with cancer genetic testing (see Brierly 2012). Those adverse events include wrong tests being ordered, test results being misinterpreted, unnecessary costly tests being done, inadequate genetic counseling, and ethical issues. They discuss the factors contributing to these adverse events, focusing on inadequate physician training in this field, time pressures, case complexity, and poor communication. They also discuss some of the marketing practices promoting use of genetic testing.
Genetic testing issues aside, this is one of those cases where it would be extremely useful to publish a root cause analysis of the event(s). While there would undoubtedly be lots of finger pointing and blaming during any legal proceedings, it is very clear that there are problems with the system here. And while we concur with the general theme of the article that there is a widespread lack of physician understanding of genetic testing (we actually think that all but the simplest of genetic tests should require formal genetic counseling and ordering by someone who has credible credentials to do so), this very unfortunate case raises multiple issues about the system for test tracking. More importantly, we’re not sure that this error could not occur even in those practices where we have implemented what we think are best practices for test tracking to ensure patient safety.
The case uncovers a fundamental flaw in most test tracking systems, whether they are electronic or paper-based. The flaw is in how we handle test results that entail more than one report. This case is similar in many regards to the lab error we discussed in our March 6, 2012 Patient Safety Tip of the Week ““Lab” Error”. That case was from the February 2012 issue of AHRQ Web M&M (Mohta 2012) that illustrates an error in a situation that likely occurs frequently and may be underappreciated: the amended lab report. In that case a young pregnant woman was admitted to a hospital with hypertension and protein on urinary dipstick testing. A 24-hour urine for protein was initially (erroneously) reported as negative for significant proteinuria. A resident was preparing the patient for discharge when the attending physician fortunately double-checked the result. In fact, the initial erroneous report had been amended and did, in fact, show significant proteinuria. That confirmed a diagnosis of pre-eclampsia and significantly altered the clinical management of the patient.
In both cases it is likely that “closure” would have taken place in the clinician’s mind once receiving the “negative’ or “normal” result in a formal report that is not designated as an interim or preliminary report or an addendum. If you had a paper-based or electronic test tracking system or other sort of “tickler” you’d probably check that test off as “done” and it would disappear from you list (and from your mind).
In the cancer case, it is also not surprising that receipt of a second report stating “no mutations detected” (even after a first report stating that deleterious mutation were detected) might be misinterpreted to mean the patient did not have the dangerous gene mutations.
If one were doing a root cause anaylsis (RCA) on the case at hand two issues that would undoubtedly be addressed are (1) why were there 2 reports? and (2) why was there not direct communication with the physician?
Unless there is a compelling urgency to report such results immediately it makes sense to wait until all the related test results are available and can be reported in total. Having just one report would reduce the likelihood of overlooking or missing half of the relevant report. However, if it is clearly known that the “test” actually involves multiple tests then each individual test should be flagged in your test results tracking system so you know when some test results have not yet returned.
However, the second issue is even more important. Significant findings should require verbal notification or other form of MD notification that can confirm recipient acknowledgment of the result. The College of American Pathologists and Association of Directors of Anatomic and Surgical Pathology have issued a consensus statement about communication of urgent diagnoses and significant unexpected diagnoses in surgical pathology and cytopathology (Nakhleh 2012). While the genetic testing above is not technically in that realm, the principles should be the same. Essentially, they state that each organization should establish a policy for which test results that may significantly impact on patient care should be reported directly to physicians and what the time frame for that communication should be. They recommend communicating verbally and directly with physicians but note that other satisfactory methods of communication might be used. If the receiving physician were able to acknowledge, for example via secure email, that he has received and read the report and understands it, such might be an acceptable mode of communication. However, given the complexities of genetic testing as noted in the Brierly study one would think a direct verbal communication with the physician would be wisest.
And there should be a backup plan for circumstances where the physician is unavailable. They also note that the pathologist should document that communication in some fashion.
We think the same should apply to laboratories doing genetic testing. And we would be that BRCA1 and BRCA2 gene test results would be near the top of any list developed where such communication should be required.
We hope you will read the Bloomberg.com article (Langreth 2012) because we can’t describe the human impact on the patient and her family like they do in the article. No one in healthcare wants that to happen.
But the real lesson here is that we know certain errors are predictable. It is very predictable that reports sent to an office might never reach the office, might not be seen by the appropriate provider, might be put in the “inbox” and stick to another report, might be misfiled, etc. When the report is one that has potential life and death implications or other significant health implications, it is imperative that communications systems be reliable in ensuring the provider that needs to know the result actually knows the result.
Some of our other columns on errors related to laboratory studies:
See also our other columns on communicating significant results:
Langreth R. Fumbled DNA Tests Mean Peril for Breast-Cancer Patients. Bloomberg.com September 10, 2012
Brierley KL, Blouch E, Cogswell, W, et al. Adverse Events in Cancer Genetic Testing: Medical, Ethical, Legal, and Financial Implications. Cancer Journal 2012; 18(4): 303-309, July/August 2012
Mohta VJ. Amended Lab Results: Communication Slip. AHRQ Web M&M February 2012
Nakhleh RE, Myers JL, Allen TC, et al. Consensus Statement on Effective Communication of Urgent Diagnoses and Significant, Unexpected Diagnoses in Surgical Pathology and Cytopathology From the College of American Pathologists and Association of Directors of Anatomic and Surgical Pathology. Arch Pathol Lab Med. 2012; 136: 148–154
October 9, 2012
Call for Focus on Diagnostic Errors
Recently Mark Graber, whose work on diagnostic error we have often cited, along with Bob Wachter and Christine Cassel issued a call for a new focus on diagnostic error in patient safety efforts (Graber 2012). Diagnostic error has been very much underrepresented in research and the literature on patient safety. You’ve all undoubtedly heard the oft-quoted statistic that the seminal IOM report “To Err is Human…” cites medication errors some 70 times yet mentions diagnostic errors only twice. Yet diagnostic errors occur frequently in all care settings. In fact, on the ambulatory side they are the leading cause for malpractice claims. And we do very little in educating medical students and residents/fellows about recognizing and preventing diagnostic errors. Graber et al. call for action at the medical school, residency, specialty society and policy levels to address the issue of diagnostic error and promote research on best practices to avoid diagnostic error.
We’ve already done several columns on diagnostic error, including our Patient Safety Tips of the Week for September 28, 2010 “Diagnostic Error” and November 29, 2011 “More on Diagnostic Error” and May 15, 2012 “Diagnostic Error Chapter 3” plus several others listed at the end of today’s Tip on the way(s) we think and the various cognitive biases that impact our clinical decision making.
System errors may play an important role in leading to errors in diagnosis or delay in diagnosis. Last week’s Patient Safety Tip of the Week “Test Results: Everyone’s Worst Nightmare” had links to many of our prior columns on failures in followup of test results. Such system errors have received attention in the patient safety literature. But errors in the cognitive aspects of the diagnostic process have received far less attention.
It is very clear that diagnostic error occurs at virtually all levels of our continuum of care. A recent study in the UK showed almost a third of preventable hospital inpatient deaths were due to diagnostic error (Hogan 2012) and diagnostic errors occurred at all stages of the diagnostic process.
A systematic review of autopsy studies on ICU patients (Winters 2012) found that 28% of all autopsies on such patients revealed at least one misdiagnosis and 8% showed potentially lethal errors in diagnosis. Most commonly misdiagnosed were pulmonary embolism, myocardial infarction, pneumonia and aspergillosis.
Gehring and colleagues (Gehring 2012) used a survey methodology to assess the frequency of various patient safety incidents in primary care settings. While diagnostic errors were not the most frequent events in the study, error in diagnosis or delay in diagnosis were the most common cause of events associated with at least minor harm and the most frequent cause of events leading to severe harm or death.
Our May 15, 2012 Patient Safety Tip of the Week “Diagnostic Error Chapter 3” focused on diagnostic error in ambulatory settings. We noted a paper on diagnostic errors in primary care (Ely 2012) highlighting that diagnostic errors were often preceded by common symptoms and common, relatively benign initial diagnoses. The three most common lessons learned in their review were (1) consider diagnosis X in patients presenting with symptom Y (2) look beyond the initial, most obvious diagnosis and (3) be alert to atypical presentations of disease. The authors note how mental shortcuts and cognitive biases such as anchoring, premature closure, and diagnostic momemtum frequently lead to diagnostic errors. Broadening the differential diagnosis and always considering the “don’t miss” diagnoses were important themes. They recommend de-biasing strategies such as diagnostic timeouts and use of checklists, noting that these strategies have still not been well developed with an evidence base.
Another recent study focused on early warning signs for diagnostic errors (Balla 2012). They identified the initiation and closure of the cognitive process as those most exposed to the risk of diagnostic error. At initiation of the diagnostic process “framing” occurs and sets the frame for subsequent information search. Biases occurring at the initiation, such as framing bias, can ultimately influence errors that occur at the end of the process. One of the warning signs they identified was presenting with a diagnosis label. That could refer either to a patient coming to you already labeled with a specific diagnosis or the clinician simply jumping to an “obvious” diagnosis without thinking about what else it could be. Another is the psychosocial or behavioral label. We’ve done campaigns at hospitals to avoid the practice of “negative labeling” because all too often we’ve seen patient with serious conditions suffer delayed diagnosis because staff chalked them up to some label applied because of prior interactions. Another was ignoring red flags. Confirmation bias includes not only putting weight on information that confirms your impression but also discounting disconfirming evidence or information. They note many cases of ignoring red flags or critical clues because the approach taken was “ruling in” the early diagnosis rather than “ruling out” the more serious possible condition. Another is ignoring the possibility of serious disease with low probability. Another is using wrong clinical features to rule out a condition. The example given was not considering ectopic pregnancy in a patient presenting with bleeding but lacking pain (pain being a cardinal symptom of ectopic pregnancy in the clinician’s mind). And, lastly, ignoring gut feelings should be a warning sign.
While we have talked about the dangers of many biases that appear early in our diagnostic reasoning, we’ve often stressed the importance of not ignoring the “gut feeling” that something is wrong. The aviation safety literature often talks about the “queezy” feeling that often alerts pilots to something going wrong. Van den Bruel and colleagues, who have done much work on recognizing serious infections in children, recently wrote about the role clinician’s gut feelings play in such recognition (van den Bruel 2012). They noted that acting on the “gut feeling” had the potential to prevent two serious infections being missed at the expense of 44 false alarms. Moreover, compared to the clinical impression the gut feeling was consistently more specific regardless of the child’s age or diagnosis or the seniority of the physician (though more experienced clinician’s were less likely to experience gut feelings).
Note also that when we teach students, residents, and nurses about ways to get around medical hierarchy barriers, one of the methods we recommend is the simple but very powerful statement “I’ve just got this uneasy feeling that something is not right…”. That will usually get even the most detached attending to refocus.
And many of us have learned that the patient with very vague symptoms who, nevertheless, conveys a “feeling of impending doom” must be taken extremely seriously. It’s akin to the “gut feeling” that healthcare workers or families may also convey. These are very important “red flags” that we simply cannot ignore.
The Balla article (Balla 2012) provides a nice algorithm that might be used to incorporate these warning signs into reflective reasoning.
Another recent study (Ogdie 2012) looked at cognitive biases that may lead to diagnostic errors but also included a great discussion on how contextual issues interplay with those biases. Though the study focused on diagnostic errors encountered by internal medicine residents, the findings are applicable to all providers and all settings. Anchoring and availability bias and framing effect were the most common biases identified but all the ones we’ve discussed in previous columns were seen. In discussing the contextual factors, they broke them down into team and provider factors, system and environmental factors, and patient-related factors. For example, context greatly influenced the framing effect. It was often associated with the patient providing a vague history, being too busy or having too many patients, providing only temporary coverage for a patient, or a patient being transferred from one service to another. They did not include premature closure as its own bias (because it is so strongly influenced by the other cognitive biases) but did note that premature closure may be influenced by such contextual factors as blind obedience (to the hierarchy), overreliance on a consultant, lack of interest in a patient’s case, or even lack of confidence.
Even though diagnostic error remains a domain grossly underemphasized in the patient safety literature there have been excellent contributions on cognitive thinking and the diagnostic process by individuals like Mark Graber, Pat Croskerry, John Ely, Gordon Schiff, Hardeep Singh, Jerry Groopman, Gary Klein and many others. You can find many of these in our previous columns mentioned below.
Some of our prior Patient Safety Tips of the Week on diagnostic error:
Graber ML, Wachter RM, Cassel CK. Bringing Diagnosis Into the Quality and Safety Equations. JAMA 2012; 308(12): 1211-1212
Hogan H, Healey F, Neale G, et al. Preventable deaths due to problems in care in English acute hospitals: a retrospective case record review study. BMJ Qual Saf 2012; 21(9): 737-745 doi:10.1136/bmjqs-2011-001159
Winters B, Custer J, Galvagno SM, et al. Diagnostic errors in the intensive care unit: a systematic review of autopsy studies. BMJ Qual Safe 2012; published online first 21 July 2012
Gehring K, Schwappach DLB, Battaglia M, et al. Frequency of and Harm Associated With Primary Care Safety Incidents. Am J Manag Care. 2012; 18(9): e323-e337
Balla J, Heneghan C, Goyder C, Thompson M. Identifying early warning signs for diagnostic errors in primary care: a qualitative study. BMJ Open 2012; 2: e001539
Van den Bruel A, Thompson M, Buntinx F, Mant D. Clinicians’ gut feeling about serious infections in children: observational study. BMJ 2012; 345: e6144 (Published 25 September 2012)
Ogdie AR, Reilly JB, Pang WG, et al. Seen Through Their Eyes: Residents’ Reflections on the Cognitive and Contextual Components of Diagnostic Errors in Medicine. Academic Medicine 2012; 87(10): 1361-1367, October 2012
Ely JW, Graber M, Croskerry P. Checklists to reduce diagnostic errors. Academic Medicine 2011; 86(3): 307-313
October 16, 2012
What is the Evidence on Double Checks?
Frequent readers of our columns know that although we sometimes recommend double checks as patient safety interventions we usually classify them as “weak” interventions. In our March 27, 2012 Patient Safety Tip of the Week “Action Plan Strength in RCA’s” we put together a set of slides lumping action interventions into weak, intermediate or strong categories in a visual analogy with the success of various traffic signs in slowing speeders. Click here to see them (remember: images are more likely to be remembered than words!) Importantly, double checks are listed as weak interventions that are only slightly better than the very weakest ones.
A new systematic review (Alsulami 2012) searched for studies on double checking and dose calculations in adults and children and found only 16 articles that met the inclusion criteria. Almost all were qualitative studies, reflecting information gleaned from interviews, surveys, etc. Only 3 studies had quantitative data and showed relative reductions in the 30% range for medication administration and pharmacy dispensing errors. The authors conclude that there is insufficient evidence to either support or refute the practice of double checking the administration of medicines and that clinical trials are needed to establish whether double checking medicines are effective in reducing medication errors.
Double checks are often recommended when we are dealing with administration of high-risk medications. Even though we have emphasized that double checks are a relatively weak intervention (we also know from other industries that the error rate when a supervisor checks someone else’s work may be 10% or higher), the literature suggests a medication error reduction of about 30% when using a double check system (see our July 15, 2008 Patient Safety Tip of the Week “Heparin Flushes.....Again!”). Also, for any high-risk medications you need to do truly independent double checks (see our March 30, 2010 Patient Safety Tip of the Week “Publicly Released RCA’s: Everyone Learns from Them” for a description of independent double checks). Another nice article on independent double checks in preventing medication errors (ISMP Canada 2005) describes the independent double check process and calculates that independent double checks would reduce the error rate of a process having an error rate of 5% all the way down to 1 in 400.
Our January 2010 What’s New in the Patient Safety World column “ISMP Article on Double Checks” highlighted an article “Santa checks his list twice. Shouldn’t we?” that puts the independent double check process in perspective. They cite some studies done in community pharmacies that show double checks found errors in 2.6% to 4.2% of cases, about half of which were potentially significant. And the “average’ error checking rate is about 5%. But they also discuss how difficult it is for someone to pick up their own errors (because of phenomena such as confirmation bias) and point out that double checks work best when they are performed truly independently.
They recommend that double checks be limited to hi-alert medications (like insulin, heparin, chemotherapy, TPN, etc.) and to very complex processes or hi-risk patient populations. Don’t use double checks when some more fundamental re-engineering of the system is needed. And learn from errors uncovered during the double check process. They do suggest continuation of “natural” double checks you are already doing, such as when a nurse checks the accuracy after a pharmacist has dispensed a drug. We’ll second that one - particularly since over-reliance on computers often discourages those double checks (see our November 3, 2009 Patient Safety Tip of the Week “Medication Safety: Frontline to the Rescue Again!”).
So what can go wrong during double checks? Armitage (Armitage 2008) looked at incident reports of medication errors and did semi-structured interviews with healthcare workers across multiple disciplines to qualitatively assess issues related to double checks. The incident reports showed that medication errors occurred despite double checking and that seldom was there ever any review as to why the double checking failed to prevent the errors. The interviews revealed several themes that staff felt contributed to the failure of double checks to prevent medication errors. One theme was deference to authority. This occurs when the individual being asked to perform the double check perceives the first checker to be above them in the “hierarchy”. Note that sometimes it was the other person’s formal title or status that put them “above” in the hierarchy. For example, it could be the new hire double checking the work of an experienced worker. But at other times it was a perceived skill, often their ability to perform mathematical calculations rapidly, that put them in a position of authority!
A second theme was reduction of responsibility. This is the complacency that tends to occur when someone feels that someone else will catch any mistakes that they made. We’ll actually take that a step further and note that we all have a tendency in the information age to think that “the computer says it’s ok so it must be ok”. But the other phenomenon he included under reduction of responsibility was that social interactions and unrelated conversations often interfere with the double checking process. The latter reminds us of the use of “the sterile cockpit” in aviation in which no extraneous conversation is allowed to occur during high risk activities such as takeoff and landing.
A third theme as auto-processing. This might involve two people standing together with one reading item by item and the other simply nodding assent to each. The fourth theme was lack of time.
Many of the above themes become less salient if one makes sure the process is truly an independent double check. Having the two parties do their checks separated from each other by both distance and time prevents them from both following the same error. Theoretically that separation could also keep the identity of the first checker unknown to the second checker, thus avoiding the deference to authority factor. Realistically, however, in most healthcare environments today there are so few workers at one time that it would be very difficult to avoid knowledge of the identities of both parties.
Armitage borrows heavily on the aviation safety literature for potential solutions. One suggested solution is use of checklists. ISMP provides a simple checklist of items to be considered during the independent double check (ISMP 2008). This checklist adds a key element often missing in double checks: a cognitive element that asks questions like “does this drug make sense for this patient’s diagnosis?” and “has appropriate monitoring been put in place?”. You’ll find that checklist helpful.
Indeed, checklists have been used successfully in the double checking process but there is a science to developing such checklists (White 2010). White and colleagues looked at the independent double checking process for administering outpatient chemotherapy medications. They used a very realistic simulation environment to observe nurses administering chemotherapy using two different checklists. While use of the two checklists did not differ significantly in detection of pump programming errors, there was a significant difference in the ability to detect other types of errors. They found that using very specific items, rather than more general warnings, significantly improved certain error types. For example, more errors occurred with a checklist that simply told them to check the medication label against the original order than with a checklist that specified the exact elements to check on the label and the order. Also, a general reminder to “think critically” and “remember the 5 rights” had virtually no impact. (We love the concept in John Nance’s book mentioned in our June 2, 2009 Patient Safety Tip of the Week “Why Hospitals Should Fly…John Nance Nails It!” where everyone always asks themselves “Could what I’m about to do cause harm to this patient?” but this article by White et al. would suggest that won’t actually have much of an impact). White et al. conclude that for independent double checking the most important factor is completion by the second individual of a well-designed checklist with specific items for each high-risk error. They provide a nice table of 7 important steps in developing such checklists.
Tamuz and Harrison (Tamuz 2006) apply to healthcare some concepts from other industries and two leading complimentary theories of safety we’ve talked about in the past – High Reliability Theory and Normal Accident Theory. They point out that double checks are a form of social redundancy and basically require one fallible person to monitor the work of another fallible person. They also note that when people hear and see what they expect to see, their effectiveness is reduced. They note that although double checks do share many desirable attributes of the High Reliability Organization they are seldom carried out as recommended. They cite a study (Smetzer 2003) that showed norms for double checking high-hazard medications were routinely followed in only 45% of hospitals. They also note that such double checking often becomes a “superficial routine task” and people may lose sight of its importance. They also note that Normal Accident Theory would note that people who are aware others are duplicating their efforts may diffuse responsibility and lead some individuals to overlook safety checks.
One medical center found that despite having the double check policy, medication events continued to occur (Brannan 2010). Investigation of those events found inconsistencies in how staff were completing the double check and that there were no defined processes included in their policy on how to complete an independent double check. So they revised their policy to include the actual procedure and they also added a forcing function in their electronic medical record that forces the nurse to obtain a witness prior to documenting medication administration and bag changes.
We also came across a great slide set on independent double checks for high-alert medications that incorporates several short video vignettes showing the wrong way and right way to do independent double checks (Intermountain University). You’ll find these very helpful. They highlight many of the errors commonly encountered with high-risk drugs like insulin and opiates and show how the independent double check, done correctly, can help avoid some of these common errors.
Another interesting application of the double check is doing such checks in a homecare setting via televideo monitoring (Bradford 2012). Basically, with a desktop PC and a webcam one can verify the drug name, dose, and gradations on syringes greater than 1 unit with close to 100% accuracy. However, reading expiration dates on vials proved more difficult, with rates of 63%. While that was a homecare initiative, one might wonder whether similar technologies could be utilized in the acute care or long-term care settings for administration of certain drugs.
The bottom line: double checks remain a relatively weak safety intervention and they are prone to errors but, done correctly, the independent double check probably does provide an additional element to our defenses against errors. So we recommend you audit those processes for which you require double checks, see how often you are actually doing them and doing them correctly, and then put some structure into your double check process (eg. checklists, forcing functions, etc.). But we agree with the conclusions of Alsulami et al. that further research is needed to determine in a more scientific way best practices and what parts of double checks are effective in reducing errors.
Alsulami Z, Conroy S, Choonara I. Original article: Double checking the administration of medicines: what is the evidence? A systematic review. Arch Dis Child 2012; 97: 833-837
ISMP Canada. Lowering The Risk Of Medication Errors: Independent Double Checks. ISMP Canada Safety Bulletin 2005; 5(1): 1-2, Janauary 2005
ISMP. Santa checks his list twice. Shouldn’t we? Medication Safety Alert. Acute Care Edition. December 17, 2009
Armitage G. Double checking medicines: defence against error or contributory factor? J Eval Clin Pract 2008; 14(4): 513-519
ISMP. Conducting an independent double-check. Medication Safety Alert. Nurse Advise-ERR 2008; 6(12): 1, December 2008
White RE, Trbovich PL, Easty AC, et al. Checking it twice: an evaluation of checklists for detecting medication errors at the bedside using a chemotherapy model. Qual Saf Health Care 2010; 19(6): 562–567
Tamuz M, Harrison MI. Improving Patient Safety in Hospitals: Contributions of High-Reliability Theory and Normal Accident Theory. Health Services Research 2006; 41(4 Pt. 2): 1654-1676
Smetzer JL, Vaida AJ, Cohen MR, et al. Findings from the ISMP Medication Safety Self-Assessment for Hospitals. Joint Commission Journal on Quality and Safety 2003; 29 (11): 586–97.
Brannan B. University of Maryland Medical Center. Maryland Patient Safety Center. MPSC 2010 Annual Conference Solution Submission. Implementation of a Standardized Double Check Process. 2010
Intermountain University. Medication High-Alert Double Check. Using an independent medication double check to keep your patients safe.
Bradford N, Armfield NR, Young J, Smith AC. Feasibility and accuracy of medication checks via Internet video. Journal of Telemedicine & Telecare 2012; 18(3): 128-132
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October 23, 2012
Latent Factors Lurking in the OR
Adverse events and untoward outcomes in any industry, including healthcare, are almost always the result of a cascade of errors rather than a single error. And seldom is the adverse event related purely to human error by one individual but rather to the interaction of a variety of factors that come together to enable those errors to lead to the unwanted results. We usually refer to the latter factors as latent factors. The classic example of a latent factor was described in what we think of as one of the first-ever patient safety books, Steven Casey’s “Set Phasers on Stun” (Casey 1993). In that case, a broken intercom system that had not been repaired prevented the patient, who knew something wrong was happening, from communicating with the radiation technologist who might have been able to stop the procedure. It, of course, had been not functioning for some time but in other cases no adverse events occurred. Had the intercom been repaired the fatal outcome might have been averted. Of course, there were multiple other latent factors in that case described by Casey.
Latent factors may be of a variety of types. Last month there were two excellent articles that looked at such contributing factors in surgical settings. One group, using the SEIPS model, identified safety hazards in cardiovascular operating rooms (Gurses 2012). Another group used the LOTICS scale to identify a variety of latent factors in university hospital operating rooms (van Beuzekom 2012).
The cardiovascular study was done as part of the Locating Errors Through Network Surveillance (LENS) project (Martinez 2010). That project brings together contributors from multiple disciplines (organizational sociology, industrial psychology, human factors engineering, clinical medicine, informatics, epidemiology and biostatistics, economics and health services research). The project is designed to identify hazards in healthcare settings and develop risk reduction interventions. A key philosophy is development of a peer-to-peer assessment process, akin to what occurs in the nuclear industry. That means that peers who work in similar settings come to an organization to do a safety assessment and share feedback in a confidential fashion rather than having such assessments done by external regulatory agencies. It is focused on learning rather than judging and part of the project is to develop tools to use in such assessments. One such tool involves direct observation of processes and events as they actually occur rather than simply reviewing what written policies state should occur.
The current study (Gurses 2012) involved a sampling of hospitals participating in the LENS project who perform cardiovascular surgery. In addition to the direct observational method noted above the researchers also did contextual interviews with healthcare workers to get further insight into some of the events they witnessed. They also took photographs of the physical aspects of the environment and some of the tools and technologies used. This is all done using the Systems Engineering Initiative for Patient Safety (SEIPS) model (Carayon 2006) that articulates that hazards can emerge from any of multiple components of the healthcare system and from the interactions amongst these various components. Some of those components include care providers, tasks, tools and technologies, care processes, physical environment, organization, and other processes.
Gurses and colleagues observed 20 cardiac surgeries at the 5 centers selected and identified 59 hazard categories. They did not include portions of the pre-op process such as case scheduling and only followed the patients to the handoff to the post-anesthesia care unit or recovery unit. They developed a classification tool and provide examples of hazards identified in each of those categories. Though these were cardiac surgical procedures observed you will see that most of the hazards are likely present in your OR’s regardless of what types of surgery you are doing. If you have access to the article go to the online tables and spend some time looking at the categories identified and examples provided. You’ll find yourself saying “Yup. That happens here all the time”.
Note that some of the examples given actually fit under more than one category. For example, they include under inadequate knowledge and skills due to lack of education, experience or training an instance where a technician is unaware of a newly purchased piece of equipment. The same example appears under the category of organization/education and training.
One example under the providers category was use of non-standardized approaches. There were often substantial practice variations and preferences that led to confusion for other healthcare workers and often led to workarounds. They also identified many examples of “unprofessional” behavior among care providers that encompass most of the more subtle forms of disrespectful behaviors Luician Leape has emphasized (see our July 2012 What’s New in the Patient Safety World column “A Culture of Disrespect”).
Under tasks they identified the usual problems of interruptions, time pressures, workload demands, and non-value-added tasks. Here they also found numerous examples of poor planning leading to delays. Many of the latter might be avoidable with better use of pre-op huddles. Examples of non-value-added tasks included things like anesthesiologists preparing most of their own medication doses rather than having them prepared by pharmacy.
Under tools and technology they note one of our favorite pet peeves: multiple different types of IV pumps in different areas of the hospital. Problems with alarms, hardware and software malfunctions were also common.
Under the workspace design category were frequent examples cluttered or congested workplaces and of how such physical design elements added to the workload of various workers such as someone having to physically change position to reach another item.
The organization category included not only issues related to training and education but also purchasing, planning, ancillary service provision, policies and procedures, and safety and teamwork culture.
Some of the suggested solutions to the identified hazards include:
The second study (van Beuzekom 2012) used the previously validated Leiden Operating Theatre and Intensive Care Safety (LOTICS) scale to assess the impact of an intervention of multiple latent factors in the OR. The LOTICS scale identifies latent risk factors in the OR and includes many of the same categories and elements found in the tools used in the Gurses study. Among them are communication, design, maintenance, material resources, planning and coordination, teamwork, procedures, situational awareness, team instructions, training, staffing resources, and error reporting. Based on LOTICS scale results and other staff input they decided to focus on Material Resources, Training, and Staffing Resources in an intervention. The intervention included much training on latent risk factors but also really focused on standardization and reduction of variation of materials and equipment. Using a pre/post design (with a comparable unit at another university hospital serving as a control group) they were able to demonstrate a reduction in the perceived incident rate and fewer problems related to material and staffing resources. And the contribution of technical factors to incident causation decreased significantly.
Undoubtedly, hazards in many of the same categories of both the Gurses and van Beuzekom studies would be found if they had also analyzed the pre-and post-surgical parts of surgical care.
We encourage you to use some of the tools developed or used in these two studies and do your own observational assessments of your OR’s (or any other unit in your hospital for that matter). It’s critical that these be done in an open approach making it clear that the goal is learning and identifying hazards so that ultimate improvements can be made not only in patient safety and patient outcomes but also staff safety and work satisfaction, and organizational outcomes.
Casey S. Set Phasers on Stun and Other True Tales of Design, Technology, and Human Error. Santa Barbara California: Aegean Publishing Company, 1998 (first published in 1993)
Gurses AP, Kim G, Martinez EA, et al. Identifying and categorising patient safety hazards in cardiovascular operating rooms using an interdisciplinary approach: a multisite study. BMJ Qual Saf 2012; 21: 810-818
Carayon P, Hundt AS, Karsh B-T, et al. Work system design for patient safety: the SEIPS model. Qual Saf Health Care 2006; 15(suppl 1): i50-i58
Martinez EA, Marsteller JA, Thompson DA, et al. The Society of Cardiovascular Anesthesiologists’ FOCUS Initiative: Locating Errors Through Networked Surveillance (LENS) Project Vision. Anesthesia & Analgesia 2010; 110(2): 307-311
van Beuzekom M, Boer F, Akerboom S, Hudson P. Patient safety in the operating room: an intervention study on latent risk factors. BMC Surgery 2012, 12: 10 (22 June 2012)
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October 30, 2012
Surgical Scheduling Errors
Last week we discussed latent factors in the OR and other things that can go wrong in the OR itself (see our October 23, 2012 Patient Safety Tip of the Week “Latent Factors Lurking in the OR”. This week we are going to discuss some of the issues that occur well before the patient goes to the OR that may have an impact on patient safety, patient outcomes, and even hospital finances. And in a future column we’ll deal with issues related to postoperative care.
Our August 2011 What’s New in the Patient Safety World column “New Wrong-Site Surgery Resources” highlighted the Joint Commission Center for Transforming Healthcare’s Wrong Site Surgery Project. This was a collaborative done in conjunction with 8 healthcare systems. They basically identified many of the key factors contributing to cases of wrong-site or wrong-patient surgery, then planned and tested interventions aimed at eliminating or mitigating those factors. They found important factors in scheduling, the pre-op/holding area, the OR itself, and organizational factors that were important contributors to wrong-site surgery. The “fact sheet” they provide lists the contributing factors in each domain along with identified solutions and the “storyboards” walk you through the steps they used in each domain, identifying “defective cases” and measuring the improvement over time in the rates of defective cases.
One of the areas quite vulnerable to contributing to wrong site surgery was the surgical booking and scheduling process. Some of the booking and scheduling issues predisposing to wrong site surgery (their list plus some of our own) are:
In a study looking at factors related to wrong site surgery Clarke et al. found the most commonly implicated factor reported to the development of wrong-site errors was scheduling of the procedure with the OR but it was implicated in only a minority of events that actually touched the patient (Clarke 2007).
A new study (Wu 2012) did a qualitative and quantitative analysis of errors occurring during the surgical booking/scheduling process and identified not only patient safety issues but also analyzed the costs associated with the delays such errors end up causing. Looking at over 17,000 surgeries they found a booking error rate of 0.86%. Of the booking errors wrong side was listed on 36%. Another 25% were incomplete and may not have included the laterality. Wrong approach (eg. laparoscopic rather than open) accounted for 17% of the errors. Other booking errors included wrong patient information, wrong procedure, wrong site, and even wrong patient.
The type of booking error was influenced by the nature of the surgical specialty. For example, most wrong approach errors were in general surgery but laterality errors were more common in plastic surgery, orthopedic, ophthalmologic, and ENT procedures.
Most of the errors were caught in the holding area or the OR but some were caught in the admission/registration area or assessment areas. The errors were discovered about equally between the first case of the day, the rest of the morning, and afternoon. We’ll see later that the time of catching the error also impacts on the costs associated with that error.
They did focus groups with OR nurses and technicians to address the impact of such errors and identify potential solutions. Such scheduling errors create additional paperwork and lead to time pressures, hurriedness, and delays. The time delays depended on the type of surgery. For example, a wrong approach booking error in general surgery might take 15-30 minutes to correct and even longer if the case is in the afternoon when other ongoing cases might create staffing and equipment issues. On the other hand, ophthalmology booking errors might take seconds to 15 minutes to correct.
On average, the delay was about 20 minutes. They calculated that at OR costs of $16 per minute the average cost per delay was $320. That does not include potential costs for overtime (if the case was late in the afternoon) or costs for extra equipment (if two separate surgical setups were required). So the costs of these errors can add up considerably. This is another reason you want to bring your CFO to your quality meetings and patient safety rounds!
Hospitals can start by limiting the number of sites or persons that can do surgical bookings and then use checklists or other tools for verification that all appropriate materials have been received and are accurate.
Your surgical booking process should require specific items be filled in and specific documents received before giving that case a final time slot. For example, you should require a copy of the informed consent and the history and physical before booking so that you can match the information on those against the scheduled procedure. Note that having a copy of the history and physical will also allow you to identify cases in which the H&P will “expire” before the 30-day Joint Commission requirement. You should also include pre-op orders where appropriate (eg. for prophylactic antibiotics).
The Wu paper notes that the Minnesota Alliance for Patient Safety created a sample booking form that contains a section which must be filled out by the physician performing the surgery (i.e. that cannot be delegated to staff). The Minnesota Alliance for Patient Safety has several other valuable resources as part of its Surgery Scheduling and Verification Pilot Project. These include algorithms for scheduling for either the hospital or ambulatory surgery center and for the clinic or physician office, and verification checklists for both sites. The Pennsylvania Patient Safety Authority also has a sample OR scheduling form as part of its extensive resources on preventing wrong site surgery plus a checklist for the surgeon’s office.
Your booking form should also have an area any needed special equipment or implants can be recorded. We also recommend you have an area that indicates whether a surgical specimen (for pathology) is anticipated.
Abbreviations on booking logs and forms can be problematic and should not be used. Ophthalmologists like to use OD/OS for right eye and left eye in their notes. They should spell out right eye and left eye. We’ve seen cases where “OD” gets misinterpreted as “AD” and antibiotic drops get put in the right ear instead of the right eye. Similarly, some of us like to indicate right or left or bilateral by using circles around an “R”, “L”, or “B” respectively. That is particularly dangerous in scheduling since it is very easy to mistake these for the wrong side. Note that fax artifacts can further lead to misinterpretation of some abbreviations (see our June 19, 2012 Patient Safety Tip of the Week “More Problems with Faxed Orders” for a discussion on types of errors related to faxes and how to avoid them). So you really shouldn’t use abbreviations at all on your booking forms. Similarly, you should not use acronyms on your scheduling forms since all parties may not understand those.
Surgical procedure codes may not match the description of the procedure being scheduled. For those who enter a procedure code on the scheduling form we always recommend a written description also be included so that staff can cross check to make sure what the intended procedure is and reconcile any discrepancies.
If more than one procedure is being scheduled on the patient, be sure that the consent form includes all the procedures (and that the other information for that subsequent procedure is also included if relevant).
Availability of imaging studies is another important facet to be considered during scheduling. Some hospitals or ASC’s include a checkbox on their booking form for the need for images to be present in the OR and clarify who is responsible for being sure those images are present. The same applies to copies of office notes. Having copies of office notes available may become critical when a discrepancy is noted when the patient is in the pre-op area or OR.
In one of their earliest studies on wrong site surgery the Pennsylvania Patient Safety Authority noted that discrepancies in information obtained from the surgeon’s office was common in both near-misses and actual wrong site cases (PPSA 2007).
The sample verification checklists available at the Minnesota Alliance for Patient Safety website for its Surgery Scheduling and Verification Pilot Project are tools you should be using at your hospital/ASC and your physician offices, respectively.
The Clarke study pointed out that the patient, family, and preoperative nurse were the most important protections against wrong site surgery. They noted that nurses doing verification and reconciliation in the preoperative holding area were most effective in catching errors before they might reach the patient. But they also point out important roles for the surgeon and anesthesiologist. We’ve emphasized over and over the importance of the pre-op huddle. That is the brief meeting of the surgeon, anesthesiologist, and OR nurse that should occur before every case before the patient is taken into the OR itself. That is where many of the wrong site/wrong patient/wrong procedure errors can be identified and where missing equipment or missing implant issues can be identified. We recommend you develop checklists to guide those pre-op huddles and the checklists can be tailored for the specific type of surgery being done (i.e. the needs for an ob/gyn surgery pre-op huddle will differ considerably from an orthopedic one).
The Wu study also identified 3 other potential areas/times where booking errors might be identified before the pre-op huddle or OR timeout. These include when the patient first arrives and checks in, when the patient is admitted and has an identification bracelet put on, and when the nursing assessment is being done.
Some scheduling errors may occur outside the traditional surgical booking process. Add-on cases and last minute scheduling changes can also be problematic. Where verbal requests are being accepted (as above, we don’t recommend you accept such verbal requests but sometimes in emergent situations you have no choice) “hearback” and “readback” should be utilized just as you would taking a verbal order via telephone. Day of surgery changes in the order of cases is also a practice that may lead to errors. Cases where the schedule is changed to accommodate an angry patient who thought he was going to be the first case of the day have been known to result in wrong patient procedures.
Because wrong site surgery remains a relatively rare occurrence it is, of course, difficult to monitor the success of your interventions to prevent it. However, as in the Joint Commission collaborative, you can audit the error rates in the individual processes that may contribute to wrong site surgery. So formally auditing your surgical scheduling processes and identifying errors is a good practice.
Some of our prior columns related to wrong-site surgery:
Patient Safety Tip of the Week columns:
September 23, 2008 “Checklists and Wrong Site Surgery”
June 5, 2007 “ Patient Safety in Ambulatoy Surgery”
March 11, 2008 “Lessons from Ophthalmology”
September 14, 2010 “Wrong-Site Craniotomy: Lessons Learned”
November 25, 2008 “Wrong-Site Neurosurgery”
January 19, 2010 “Timeouts and Safe Surgery”
June 8, 2010 “Surgical Safety Checklist for Cataract Surgery”
December 6, 2010 “More Tips to Prevent Wrong-Site Surgery”
June 6, 2011 “Timeouts Outside the OR”
What’s New in the Patient Safety World columns:
July 2007 “Pennsylvania PSA: Preventing Wrong-Site Surgery”
August 2011 “New Wrong-Site Surgery Resources”
Joint Commission Center for Transforming Healthcare. Wrong Site Surgery Project.
Clarke JR, Johnston J, Finley ED. Getting surgery right. Ann Surg 2007; 246(3): 395-405
Wu RL, Aufses AH. Characteristics and costs of surgical scheduling errors. Am J Surg 2012; 204(4): 468-473, October 2012
Minnesota Alliance for Patient Safety. Surgery Scheduling and Verification Pilot Project.
The Pennsylvania Patient Safety Authority. Wrong Site Surgery tools.
sample OR scheduling form http://patientsafetyauthority.org/EducationalTools/PatientSafetyTools/PWSS/Documents/orschedule.pdf
checklist for the surgeon’s office
PPSA (Pennsylvania Patient Safety Authority). Insight into Preventing Wrong-Site Surgery. PA PSRS Patient Saf Advis 2007; 4(4): 109, 112-23
Print “Surgical Scheduling Errors”
November 6, 2012
Using LEAN to Improve Stroke Care
For over 15 years we have had an effective treatment for acute ischemic stroke (thrombolytic therapy with tPA) but this must be given within a very narrow time window to be both efficacious and safe. That time window had been 3 hours from time of onset of the first symptoms or signs of stroke but now has been extended in some circumstances to 4.5 hours or longer (IST-3 2012). The sooner a patient can be given tPA the better the chance he/she will not have a residual neurological deficit. Nevertheless, it has proven challenging first to get patients into the hospital within that time frame and then get all the necessary procedures and tasks done within that narrow window. Nationwide, only 3.7% to 5.2% of patients potentially eligible for thrombolytic therapy actually get it (Adeoye 2011). Numerous barriers have contributed to our suboptimal performance.
We faced many of the same challenges many years ago when we first began using thrombolytic therapy for acute MI patients. The improvement in acute MI patients also is better the sooner thrombolytic therapy is administered. The first protocols back then required cardiologist involvement in the decision to proceed and then there were delays due to storage and preparation of the thrombolytic agents. Then we finally said “hey, emergency physicians know how to read EKG’s and have good clinical judgment” and we also addressed the pharmacy bottlenecks. As a result we were able to re-engineer our protocols so that today’s target of door-to-needle times of less than 30 minutes is very doable in most ER’s.
So how do we re-engineer our policies and procedures for stroke care to allow more patients with acute ischemic stroke to receive thrombolytic therapy during that short window? The stroke team at Washington University and Barnes-Jewish Hospital in St. Louis has the answers. They applied the LEAN/Toyota Production System approach to streamline the processes and achieved a dramatic reduction in the door-to-needle time for thrombolytic therapy in acute ischemic stroke patients (Ford 2012). Though they were a designated stroke center and had a stroke team that was promptly activated, their door-to-needle time for thrombolytic therapy averaged 58 minutes
They brought together a team not just of doctors and nurses but everyone involved in care of the patient, from the pre-hospital crews to the clerical and registration staff, and radiology technologists. They began with the well-known LEAN technique of value stream mapping. Their team flowcharted all the processes involved (for process flow, information flow and patient flow) and identified both steps that added no value and steps that were taking place serially that could be done in parallel. Value stream maps for both the current state and the future state were developed.
Some of the barriers and bottlenecks included delays in getting the imaging studies done and read by the radiologist, getting lab work results promptly, getting an accurate history about the time of onset of symptoms and signs (often from witnesses at the patient’s home or other site), and getting the history and physical and neurological evaluation done promptly.
Their biggest bottleneck was related to imaging requirements. Among non-value-added steps they noted that patients were often moved from one room to another location (eg. to the CT or MRI suite) then back again. So they developed a change in flow so that the patient is brought directly to the radiology suite by the ambulance crew. That sort of thinking is a crucial step in getting away from our old “That’s the way we’ve always done it” thinking or our thinking that “We can’t send them there. What if they are not stable?” Well the Barnes/Washington University team obviously was able to address the patient safety issue and incorporated this into their measurement strategy. Their results were pretty dramatic. In a table presented by this group at the International Stroke Conference 2012 (Panagos 2012) the average time from door to head CT scan completed dropped from 25 minutes down to 8 minutes.
Their other major bottleneck was getting required lab results (INR, platelet count, glucose level) back in a reasonable time (Panagos 2012). On average it was taking 33 minutes for those tests to come back. So they initiated point-of-care (POC) testing for INR and glucose levels, effectively alleviating their second big bottleneck.
They also identified clinical activities that could be performed simultaneously rather than one after the other. For example, the neurologist and the emergency physician could both do parts of their evaluations at the same time. Similarly, one nurse could get together needed medications while another nurse started an IV.
To get an accurate assessment of the time of onset of symptoms or signs of stroke they assigned a social worker to make contact with family or other pertinent witnesses. A great way to make use of all the valuable members of your healthcare team and free up others to do the things they do best!
With the new re-engineered system in place they reduced the door-to-needle time from an average of 58 minutes down to 37 minutes. And the percentage of patients who received tPA during the “golden hour” (the first 60 minutes after onset of stroke symptoms and signs) increased from 52% to 78%. And all this was accomplished without an increase in unwanted side effects or complications of treatment.
Our July 2012 What’s New in the Patient Safety World column “Another LEAN Success Story” noted a tool we have not previously commented on – the swim lane diagram (Green 2010). Such a diagram plots workflows as they may typically occur in silos and gives you a good picture of what workflows are often going on in parallel. Arrows between lanes can show where the processes in one “lane” can impact the flow in another “lane”. It is thus helpful in showing you how such workflows can give rise to bottlenecks in other “swim lanes”. You can easily see how swim lane diagrams could help you determine what steps are now being done serially that could better be done in parallel.
Our Patient Safety Tips of the Week October 11, 2011 “LEAN in the Lab” and May 1, 2012 “More LEAN Successes” highlighted some of the successful applications of LEAN thinking in improving workflows in the lab, emergency department, OR, etc. LEAN, borrowed largely from Taiichi Ohno and Kiichiro Toyoda and the Toyota Production System, is both a performance improvement tool and a unique culture. And our July 2012 What’s New in the Patient Safety World column “Another LEAN Success Story” highlighted another LEAN success story making a significant improvement in OR turnover time (TOT) and turnaround time (TAT).
The Barnes Jewish/Washington University group also note another important offshoot of the LEAN/TPS implementation: development of teamwork and enduring relationships. One of the key principles of LEAN/TPS is that everyone involved is important and they all have ideas that are valuable. These principles have led to many improvements now in a variety of industries. Healthcare just happens to be one of the late adopters.
Kudos to the team at Barnes Jewish/Washington University for a job well done and for sharing their successes with the rest of us!
See our previous columns on LEAN/Toyota Production System for good references and resources to get you started learning about how LEAN can help transform your work:
October 11, 2011 “LEAN in the Lab”
May 1, 2012 “More LEAN Successes”
July 2012 “Another LEAN Success Story”
The IST-3 collaborative group. The benefits and harms of intravenous thrombolysis with recombinant tissue plasminogen activator within 6 h of acute ischaemic stroke (the third international stroke trial [IST-3]): a randomised controlled trial. The Lancet 2012; 379(9834): 2352 - 2363, 23 June 2012
Adeoye O, Hornung R, Khatri P, Kleindorfer D. Recombinant Tissue-Type Plasminogen Activator Use for Ischemic Stroke in the United States: A Doubling of Treatment Rates Over the Course of 5 Years. Stroke. 2011; 42: 1952-1955
Ford AL, Williams JA, Spencer M, McCammon C, Khoury N, Sampson T, Panagos P, Lee J-M. Reducing door-to-needle times using Toyota’s lean manufacturing principles and value stream analysis. To be published in Stroke as per press release by Purdy MC. Stroke patients benefit from carmaker’s efficiency. (Washington University press release) October 18, 2012
Panagos P, Ford A, Williams J, Khoury N, Sampson T, McCammon C, Lee J-M. Applying Toyota Lean Manufacturing Principles to Stroke Care: Accelerating Door-to-Needle Times. AHA (American Heart Association) International Stroke Conference 2012. February 2012 (ISC 2012 New Orleans)
Green B. How to Create a Swim Lane Diagram. The Lean Logistics Blog.
September 1, 2010
November 13, 2012
The 12-Hour Nursing Shift: More Downsides
When we first reviewed the available literature on the impact of 12-hour shifts for nursing (see our November 9, 2010 Patient Safety Tip of the Week “12-Hour Nursing Shifts and Patient Safety”) we concluded the literature to date really did not answer the question as to whether those shifts had a detrimental impact on patient outcomes. Then in our February 2011 What’s New in the Patient Safety World column “Update on 12-hour Nursing Shifts” we highlighted a study (Trinkoff 2011) that attempted to correlate patient outcomes with the duration of the nursing shift using a number of AHRQ Quality Indicators at hospitals in two states where they had data on nursing shifts. They found that a number of undesirable outcomes, including mortality for select conditions like pneumonia, were higher in those hospitals where nurses reporting the longer shifts. Just as significant was the association between such undesirable outcomes and nurses’ lack of time off.
Now 2 new studies using a multi-state nursing database (Stimpfel 2012a, Stimpfel 2012b) show further evidence that quality of patient care suffers when nurses work longer shifts. Furthermore, there is also a detrimental impact on nurses themselves. The researchers, from the University of Pennsylvania School of Nursing, analyzed data from over 500 acute care general hospitals in 4 states (California, Pennsylvania, New Jersey, and Florida) participating in the Multi-State Nursing Care and Patient Safety Study.
We knew that there has been a steady trend in hospitals using 12-hour nursing shifts. That’s why we originally began looking at the issue back in 2010. However, we’re surprised at the magnitude of that trend. In fact, the most common shift length in the study is 12-13 hours, worked by 65% of nurses responding to the surveys (Stimpfel 2012a)! Those long shifts were even more commonly worked by ICU nurses.
The nurses in the first study (Stimpfel 2012a) were asked to rate both nursing care quality and hospital safety. (Note that McHugh et al. 2012 have shown nurses’ ratings of hospital quality and safety correlate well with more formal measures.) There was a significant correlation between longer shift length and nurses reporting nursing care quality as “fair or poor”. Similarly, there was a correlation between longer shift length and nurses reporting poor hospital safety grades. The odds of a nurse reporting poor quality or safety ratings were double in those nurses working the longest shifts compared to those working 8-9 hour shifts. The findings persisted even after adjustment for variables such as nurses’ age, gender, unit specialty, staffing patterns, hospital bed size, etc.
Their study also looked at breaks and break length. There was substantial variability by state since some states (eg. California) have mandated a 30-minute meal break and additional 30-minute break for those working beyond 8 hours. However, overall the study confirmed that most nurses are not regularly taking breaks during the workday. Though this study did not specifically correlate quality and safety ratings with absence of breaks, they cite other studies (Rogers 2004) showing that longer breaks reduce error rates.
In the second study using the same database (Stimpfel 2012b) the investigators demonstrated that nurses working the longer shifts were more dissatisfied and had higher burnout rates. Moreover, patient satisfaction scores on multiple measures captured by the HCAHPS survey were lower when the proportion of nurses working shifts longer than 13 hours was high. They found nurses working shifts of ten hours or longer were up to two and a half times more likely than nurses working shorter shifts to experience burnout and job dissatisfaction and to intend to leave the job.
But there’s a real paradox here. The overwhelming majority of nurses responding to the multi-state survey report that they are satisfied with their schedules and like the flexibility they provide. Yet the likelihood of job dissatisfaction, burnout and intent to leave the job is much higher in those working these long shifts.
It’s, of course, not surprising that the HCAHPS scores were lower. We have long known that staff dissatisfaction often leads to poorer performance on many HCAHPS measures.
However, there remain questions still not resolved. The problem with almost all research to date on the issue is that there are too many confounding variables in retrospective studies. In the multi-state database shift duration was calculated by asking the nurses what was the duration of their last shift worked. It’s not clear to us then whether those longer shifts were voluntary (i.e. regularly scheduled 12-hours shifts) or involuntary (i.e. overtime). Similarly, we don’t know about other factors such as time off and whether nurses are working the same shift each day or rotating shifts or whether they are also working other jobs on their days off. There are also other issues in interpreting data from large databases such as the multi-state nursing database (Welton 2011).
As we’ve said before, the only way we are going to be able to answer that question is to do a randomized controlled trial where the only variable changing is the duration of the individual shift. It would require a well-designed study with hard outcome parameters done in a setting where a legitimate control group can be used (for example, implementing 12-hour shifts on one or several med/surg floors where the other comparable floors maintain their current 8-hour shifts). That will be a difficult study to actually carry out. But the time has come to get those critical answers.
The issue basically is the same one we contend with in assessing the impact of housestaff work hours and patient safety and quality outcomes. Theoretically, we are balancing the negative impact of fatigue and inattention due to long hours against the potentially positive impact of better continuity and fewer handoffs. But we also cannot ignore the impact of long hours on staff well-being and job satisfaction. There is a plethora of literature on negative personal impacts from long hours (see our November 9, 2010 Patient Safety Tip of the Week “12-Hour Nursing Shifts and Patient Safety”), including needlestick injuries, musculoskeletal and other work-related injuries, increased rates of motor vehicle collisions or near-misses while driving home from extended shifts and potential health consequences of long-term sleep deprivation.
Stimpfel et al. (Stimpfel 2012b) suggest that policies regulating work hours for nurses, similar to those set for resident physicians, may be warranted and that we need to respect nurses’ days off and vacation time, promote nurses’ prompt departure at the end of a shift, and allow nurses to refuse to work overtime without retribution.
We recommend you read our November 9, 2010 Patient Safety Tip of the Week “12-Hour Nursing Shifts and Patient Safety” to see some of the excellent prior work that has been done by Geiger-Brown and colleagues (Geiger-Brown 2010) and Fallis and colleagues (Fallis 2011) regarding some of the strategies to mitigate nurse fatigue and also our columns listed below on the impact of fatigue in healthcare and other industries and use of strategies such as power naps.
Some of our other columns on the role of fatigue in Patient Safety:
November 9, 2010 “12-Hour Nursing Shifts and Patient Safety”
April 26, 2011 “Sleeping Air Traffic Controllers: What About Healthcare?”
February 2011 “Update on 12-hour Nursing Shifts”
September 2011 “Shiftwork and Patient Safety
November 2011 “Restricted Housestaff Work Hours and Patient Handoffs”
January 3, 2012 “Unintended Consequences of Restricted Housestaff Hours”
June 2012 “June 2012 Surgeon Fatigue”
November 2012 “The Mid-Day Nap”
Trinkoff AM, Johantgen M, Storr C, et al. Nurses' Work Schedule Characteristics, Nurse Staffing, and Patient Mortality. Nursing Research 2011; 60: 1-8
Stimpfel AW, Aiken LH. Hospital Staff Nurses' Shift Length Associated With Safety and Quality of Care. Journal of Nursing Care Quality 2012; Published ahead of print POST AUTHOR CORRECTIONS, 27 September 2012
Stimpfel AW, Sloane DM, Aiken LH. The Longer The Shifts For Hospital Nurses, The Higher The Levels Of Burnout And Patient Dissatisfaction. Health Affairs 2012; 31(11): 2501-2509, November 2012
McHugh MD, Stimpfel AW. Nurse reported quality of care: A measure of hospital quality. Research in Nursing & Health 2012; Article first published online: 21 AUG 2012
Rogers AE, Hwang W-T, Scott LD. The Effects of Work Breaks on Staff Nurse Performance. Journal of Nursing Administration 2004; 34(11): 512-519, November 2004
Welton JM. Nurse Staffing and Inpatient Mortality: Is the Question Outcomes or Nursing Value? Medical Care 2011; 49(12): 1045-1046, December 2011
Geiger-Brown J, Trinkoff AM. Is It Time to Pull the Plug on 12-Hour Shifts? Part 3. harm reduction strategies if keeping 12-Hour Shifts. Journal of Nursing Administration 2010; 40(9): 357-9, 2010 Sep
Fallis, WM, McMillan DE, Edwards MP. Napping During Night Shift: Practices, Preferences, and Perceptions of Critical Care and Emergency Department Nurses
Crit Care Nurse March 31, 2011 vol. 31 no. 2 e1-e11
November 20, 2012
Update on Perioperative Management of Obstructive Sleep Apnea
Okay, so you finally agree with us that identification of patients at risk for obstructive sleep apnea (OSA) is important when contemplating surgery (see our Patient Safety Tips of the Week for May 22, 2012 “Update on Preoperative Screening for Sleep Apnea” and August 17, 2010 “Preoperative Consultation – Time to Change” plus our multiple other columns listed at the end of today’s column). Now what?
We’ve pointed out several times that there is a paucity of evidence-based recommendations for care of surgical patients with suspected or known OSA. The American Society of Anesthesiologists (ASA) practice guidelines for the perioperative management of patients with OSA (ASA 2006) were an important contribution but were written in the era before preoperative screening for OSA became more commonly used and before monitoring standards changed. In addition, it has become apparent that more patients at-risk for OSA are having surgery done on an ambulatory basis. As a result, a couple other groups have stepped up with more up-to-date recommendations for the perioperative management of patients with known or suspected OSA. The Society for Ambulatory Anesthesia published a Consensus Statement on Preoperative Selection of Adult Patients with Obstructive Sleep Apnea Scheduled for Ambulatory Surgery (Joshi 2012). And the American Society of PeriAnesthesia Nurses (ASPAN) published The ASPAN Obstructive Sleep Apnea in the Adult Patient Evidence-Based Practice Recommendation (ASPAN 2012).
Both the guidelines focus on a few key principles in managing patients with suspected OSA:
The Society for Ambulatory Anesthesia Consensus Statement (Joshi 2012) specifically notes that many of the recommendations are based upon surrogate measures (like oxygen desaturation, need for additional monitoring, etc.) and that there has been no correlation between such surrogate measures and mortality or clinical significant adverse outcomes.
Both the new guidelines recommend screening for OSA but may differ on the tool(s) used. The Society for Ambulatory Anesthesia recommends use of the STOP-Bang questionnaire whereas the ASPAN guideline recommends either the STOP-Bang or the ASA OSA checklist and notes that the Berlin Questionnaire has limited application in the perianesthetic population. Note that in our for May 22, 2012 Patient Safety Tip of the Week “Update on Preoperative Screening for Sleep Apnea” we cited two papers from Frances Chung and her group in Toronto (Chung 2012a, Chung 2012b) that, taken together, suggest a potential strategy for identifying patients with OSA preoperatively without having to do a formal polysomnogram by using the STOP-Bang questionnaire followed by nocturnal oximetry in appropriate cases.
Both new guidelines recommend use of regional techniques (epidural or nerve blocks) and multimodal approaches (eg. NSAID’s, acetaminophen, tramadol, COX2 inhibitors, ketamine, and nonpharmacologic measures) for analgesia in attempt to avoid opiates. If opiates are needed, careful titration is recommended and if PCA is to be used basal opioid infusions should be avoided.
The ASPAN guideline discusses positioning of the patient, recommending the lateral, lateral recumbent or sitting positions and avoidance of the supine position. They note that CPAP or BiPAP used early in the recovery period reduces respiratory effort and may reduce other complications.
Monitoring is obviously critical. In our frequent discussions on monitoring patients receiving opiates we have talked about the pitfalls and false sense of security with pulse oximetry, particularly in patients on supplemental oxygen. Continuous capnography is rapidly becoming the standard for monitoring patients at risk for respiratory depression and those with sleep apnea in the perioperative period. Many facilities have not implemented capnography because of cost concerns. But, interestingly, a post on the Physician-Patient Alliance for Health & Safety (PPAHS) website (see our October 2012 What’s New in the Patient Safety World column “Another PCA Pump Safety Checklist”) showed that for management of surgical patients with OSA implementation of a continuous capnography program in one year resulted in a 70% reduction in operating costs as well as improving patient safety (Wong 2012)!
The ASPAN guideline anticipates a minimum observation period in the PACU of 2-6 hours, on the average 3 hours longer than for non-OSA patients, and it the possibility of more prolonged observation should always be anticipated. Before considering discharge, the patient’s oxygen saturation on room air should have returned to baseline and there should have been no hypoxia or obstruction when the patient is left undisturbed for at least 30 minutes. In addition, for those who do have episodes of obstruction or desaturation the period of observation should be extended for at least an additional 7 hours beyond each such episode. Patients not requiring hi-dose opioids may be considered for discharge home once oxygen saturation is at 94% (or baseline) for at least 2 hours and patient’s level of consciousness has returned to baseline, and the patient is able to use CPAP at home (if previously on CPAP). For patients needing oral opiates discussion should take place between the anesthesiologist and surgeon. Making sure that a responsible adult caregiver be with them overnight after discharge is also advisable.
Patients and their families should be counseled that the increased risk may extend for a few days to as long as a week after surgery. Those already on CPAP need to be educated on the importance of CPAP, which should be used any time the patient sleeps, not just at night. They should also be reminded not to sleep in the supine position. They should also be counseled about not taking excessive doses of analgesics or sedatives, including over-the-counter drugs. For those only suspected of having OSA emphasizing the need to undergo polysomnography testing for confirmation of the diagnosis and then appropriate management is important.
That same October 2012 issue of the Journal of PeriAnesthesia Nursing had a focus on OSA and included several other very useful articles. An Evidence-Based Checklist for the Postoperative Management of Obstructive Sleep Apnea (Gammon 2012) also provides very useful guidelines. It contains most of the recommendations noted in the ASPAN guideline but also includes criteria for extubation of the OSA patient. These include ensuring that the patient is fully awake by following commands, can sustain a head tilt for more than 5 seconds, has a vital capacity greater than 15cc/kg, a negative inspiratory force less than -25 cm H2O, and a respiratory rate greater than 12 per minute. They also recommend putting the patient in a 30 degree reverse Trendelenburg position immediately after extubation.
One study (Setaro 2012), based on a failure mode and effects analysis (FMEA), identified multiple opportunities to improve perioperative management of patients with suspected OSA. One step included in their improved process was to make available results of the screening (STOP) questionnaire on their electronic medical record so it was available to all caring for the patient. Similarly, for handoffs from the OR to the PACU they added OSA as a specific item to their SBAR form. They also developed written educational guidelines to provide the patients at the time of discharge, both for those with known OSA and those with suspected OSA. They required patients with suspected or known OSA to be monitored in the PACU for a minimum of 4 hours after general anesthesia. Patients with prolonged periods of oxygen desaturation would be admitted to monitored inpatient beds. Availability of such inpatient monitored beds was a concern raised but to date had not been problematic. In the first 3 months after implementation of changes they found a 5% increase in identification of patients at high risk for OSA and 2% of high risk patients required admission.
Another (Diffee 2012) had a good discussion on the pathophysiology of OSA and how anesthesia impacts on OSA plus recommendations regarding management. Of note, they point out that inhalational gases and intravenous hypnotics, analgesics, and narcotics all may produce both respiratory depression and airway obstruction that are out of proportion to the level of sedation. This makes the transition from a controlled airway in the OR to spontaneous breathing a particularly unstable period in patients with OSA. Airway problems may first manifest in the PACU after extubation and most airway emergencies occur during the first 24-48 hours postoperatively, noting that the period of REM rebound after perioperative sleep deprivation is also a risky period for OSA respiratory complications. While they emphasize the importance of ensuring compliance with home CPAP prior to surgery, they also note as we have that the evidence base for improvement in outcomes with postoperative use of CPAP is scant (see our November 22, 2011 Patient Safety Tip of the Week “Perioperative Management of Sleep Apnea Disappointing”). They also note that patients at risk for OSA also often have difficult to manage airways and that is an important part of the pre-op evaluation. Because anesthetic effects last into the recovery period they recommend use of local anesthetics, peripheral nerve blocks, spinal or epidural anesthesia, and light-to-moderate sedation rather than general anesthesia where possible. They recommend capnography regardless of type of anesthesia. And they emphasize ensuring full reversal of any neuromuscular blockade before considering extubation. They strongly suggest organizations have written guidelines or protocols for managing patients with known or suspected OSA. They point out that so many procedures today are being performed outside traditional OR’s (eg. in specialty areas) so having those protocols available to all nursing staff is valuable. We concur with that. Even though endoscopy suites, for example, should have the same standards for monitoring all patients we seldom see the same level of surveillance in those areas.
When your screening identifies a patient as being at high risk for OSA you need to decide whether to confirm the diagnosis with polysomnography and begin management prior to surgery. That, of course, usually depends on the urgency of the surgery. If it is elective nonurgent surgery it makes sense to delay the surgery, get polysomnography, get the patient started on CPAP, and maybe even lose some weight if obesity is one of the risk factors for OSA. However, there is little evidence for or against that approach vs. just assuming the patient has OSA and managing him as such.
The next question is usually about the setting in which the surgery is best done. The decision about suitability for ambulatory surgery depends upon patient-related factors, procedure-related factors, and facility-related factors. Among patient-related factors, degree of control of comordities is probably the most important. Because obesity is common in patients with OSA or suspected OSA, many have hypertension, diabetes and coexisting heart disease. In those with known OSA their degree of compliance with home CPAP is important. If they are poorly compliant, they may be expected to be poorly compliant with CPAP postoperatively and may be better managed under surveillance as an inpatient.
Among procedure-related factors the most important is the likelihood that the procedure will require opiates for management of postoperative pain. If it is considered likely that regional anesthesia techniques and non-opioid analgesics (eg. multimodal interventions) can adequately manage post-op pain, then ambulatory surgery may be considered. However, if it is highly likely that post-op opiates will be needed then inpatient admission is advisable.
Among facility-related factors, the most important one is the monitoring capability. These patients need continuous pulse oximetry and capnography. And the ability to perform more extended monitoring and management of patients who do get complications should be another concern.
So, once again, we recommend you consider setting up a screening program for likely OSA prior to scheduled surgery. The STOP-Bang questionnaire is easy to administer in a few minutes and could be done at the time of surgical booking or other time the surgical team contacts the patient. Having a clinical guideline and formal protocols for dealing with those who score high on the STOP-Bang would be wise, keeping in mind that many of those recommendations are still consensus-based rather than evidence-based.
Our prior columns on obstructive sleep apnea in the perioperative period:
Patient Safety Tips of the Week:
June 10, 2008 “Monitoring the Postoperative COPD Patient”
August 18, 2009 “Obstructive Sleep Apnea in the Perioperative Period”
August 17, 2010 “Preoperative Consultation – Time to Change”
July 13, 2010 “Postoperative Opioid-Induced Respiratory Depression”
February 22, 2011 “Rethinking Alarms”
November 22, 2011 “Perioperative Management of Sleep Apnea Disappointing”
May 22, 2012 “Update on Preoperative Screening for Sleep Apnea”
What’s New in the Patient Safety World columns:
November 2010 “More on Preoperative Screening for Obstructive Sleep Apnea”
American Society of Anesthesiologists (ASA). Practice Guidelines for the Perioperative Management of Patients with Obstructive Sleep Apnea. A Report by the American Society of Anesthesiologists Task Force on Perioperative Management of Patients with Obstructive Sleep Apnea. Anesthesiology 2006; 104: 1081–93
Joshi GP, Ankichetty SP, Gan TJ, Chung F. Special Article: Society for Ambulatory Anesthesia Consensus Statement on Preoperative Selection of Adult Patients with Obstructive Sleep Apnea Scheduled for Ambulatory Surgery. Anesth Analg 2012; 115: 1060-1068; published ahead of print August 10, 2012
ASPAN OSA PR Strategic Work Team. The ASPAN Obstructive Sleep Apnea in the Adult Patient Evidence-Based Practice Recommendation. Journal of PeriAnesthesia Nursing 2012; 27(5): 309-315
Chung F, Subramanyam R, Liao P, Sasaki E, Shapiro C, Sun Y. High STOP-Bang score indicates a high probability of obstructive sleep apnoea. British Journal of Anaesthesia 2012; 108 (5): 768–75 (2012)
Chung F, Liao P, Elsaid H, et al. Oxygen Desaturation Index from Nocturnal Oximetry: A Sensitive and Specific Tool to Detect Sleep-Disordered Breathing in Surgical Patients. Anesthesia & Analgesia 2012; 114(5): 993-1000 Published online before print February 24, 2012
Wong M. Improving Hospital Efficiency and Patient Safety: Bedside Monitoring with Capnography Achieves Better Management of Surgical Patients with Obstructive Sleep Apnea. Physician-Patient Alliance for Health & Safety (PPAHS) website. Posted April 5, 2012
Gammon BT, Ricker KF. An Evidence-Based Checklist for the Postoperative Management of Obstructive Sleep Apnea. Journal of PeriAnesthesia Nursing 2012; 27(5): 316-322
Setaro J. Obstructive Sleep Apnea: A Standard of Care That Works. Journal of PeriAnesthesia Nursing 2012; 27(5): 323-328
Diffee PD, Beach MM, Cuellar NG. Caring for the Patient With Obstructive Sleep Apnea: Implications for Health Care Providers in Postanesthesia Care. Journal of PeriAnesthesia Nursing 2012; 27(5): 329-340
November 27, 2012
Dealing with Distractions
Distractions and interruptions are frequent contributing factors to errors in any industry and especially so in healthcare. Learning to deal with them and having strategies to minimize their impact is essential. Some people are innately better than others at dealing with them. Many of us proudly tout our ability to multitask. But the bottom line is that even those who are good at multitasking are vulnerable to the effects of interruptions and distractions. Good design of work environments and workflows may help minimize distractions and interruptions and make everyone less prone to errors.
One organization recently implemented a “bundle” to reduce interruptions that may lead to medication errors (Freeman 2012). After analyzing medication errors occurring on their cardiac/thoracic stepdown unit, which might administer over 25,000 medication doses in a month, they reviewed the literature on interruptions and analyzed their own unit for factors contributing to interruptions. Their unit had both private and semiprivate rooms. The latter were more prone to interruptions given the increased traffic of providers, family and visitors.
The “bundle” of interventions they chose consisted of the following:
The lighted lanyards were chosen over several other potential methods as the means of identifying the nurse who should not be interrupted. The other methods considered were vests, hats, sashes, or lighted armbands.
Turning the medication room into a “No Interruption Zone” was also challenging. They note it is common for such rooms to have a “water cooler” atmosphere where casual conversations are common. Signage, staff education, and direct observation helped convert the “water cooler” atmosphere to more of a “sterile cockpit” atmosphere.
They used the classic PDSA quality improvement model to roll out the initiative and used a direct observation methodology to measure interruptions. The rate of interruptions during medication preparation and administration averaged 3.29 interruptions prior to implementation of the new model. After implementation the rate of interruptions dropped to 1.18. In addition, there was a change in the distribution of sources of interruption. The top 3 causes of interruptions after implementation were patients, other nurses, and pagers. Prior to the implementation family members had been the third leading cause of interruptions and these dropped dramatically. There was also a substantial decrease in the number of reported medication errors after implementation.
Sustainability is key to any quality improvement intervention. Unfortunately, there was some dropoff in adherence to all the elements of the “bundle” over time. Specifically, there was some resistance to use of the lighted lanyards and the “No Interruption Zone” regressed somewhat toward its pre-implementation milieu. Continued reminders to staff about components of the program were thus necessary.
Our August 28, 2012 Patient Safety Tip of the Week “New Care Model Copes with Interruptions Better” highlighted another innovative process redesign at University of Pittsburgh Medical Center (UPMC) that improved care while handling interruptions (Kowinsky 2012).
That’s the nursing side. There’s also been more interest in mitigating the effects of interruptions on the physician side. A new study (Campbell 2012) used direct observation of anesthetists and anesthesiologists as they cared for patients from the time the anesthetist and patient entered the anesthetic room until recovery. They found an average of 0.23 interruptions per minute overall but the interruption rate differed during various stages of the overall process. During induction there were 0.29 interruptions per minute, during transfer of the patient into the operating room 0.33 interruptions per minute, and during emergence 0.5 interruptions per minutes. During the maintenance phase of anesthesia there were only 0.15 interruptions per minute. Interruptions came from a variety of sources (internal team members, external team members, equipment-related issues, workspace design issues, noise, teaching responsibilities, patient-related problems, and items such as pagers and mobile phones).
The authors did note that not all interruptions have negative impact. In fact, 3.3% had a positive impact (i.e. the distraction or interruption facilitated either the procedure or the safety of the patient).
They also noted that some interruptions and distractions may occur together. They provide a couple examples in graphic form of how multiple interruptions and distractions may interplay and lead to either a negative or positive consequence.
They also did semi-structured interviews with the anesthetists and these were particularly helpful in identifying strategies used to manage distractions and interruptions. Several commented on the relatively high rate of distractions and interruptions during the emergence phase and felt that other team members may not understand that emergence is just as important as induction. They note that many of the other team members have finished their work on the case and fail to recognize that the anesthetist’s work in not done. (One cannot ignore the obvious analogy to aviation where takeoff and landing are the two most critical times for safety. In aviation the “sterile cockpit” procedure is used to avoid distractions and interruptions during these critical phases.)
The anesthetists in the study had 2 main strategies for coping with distractions and interruptions: 1) ignoring people and 2) asking people with non-urgent or irrelevant queries to return later. They tried to strike a balance between an assertive approach and a more proactive but less assertive approach but this was largely a function of the temperament of the individual anesthetist. But a third, more implicit, strategy was managing one’s own attention and filtering out constant distractions. They also had to recognize that they were themselves causes for distractions and interruptions for other team members at times. So changing the culture of the team and teamwork is also a key strategy. Other strategies include ergonomic elements such as redesign of workspace and avoiding the anesthesia room becoming a thoroughfare to reach the OR and organizational elements such as leaving mobile phones in the locker room.
Both these studies made good use of direct observational methodology. We’ve noted the utility of direct observation in several columns, most recently in our October 23, 2012 Patient Safety Tip of the Week “Latent Factors Lurking in the OR”.
Distractions and interruptions are a fact of life in all aspects of our work and home life. But that doesn’t mean we have to simply accept them all. Sometimes actually identifying the sources and frequency of distractions and interruptions allows us to implement strategies to avoid at least some of them.
We’ve done a number of columns on the deleterious effects of interruptions and distractions for physicians, nurses, pharmacists and others:
Freeman R, McKee S, Lee-Lehner B, Pesenecker J. Reducing Interruptions to Improve Medication Safety. Journal of Nursing Care Quality 2012; Published ahead of print POST AUTHOR CORRECTIONS, 23 October 2012
Kowinsky AM, Shovel J, McLaughlin M, et al. Separating Predictable and Unpredictable Work to Manage Interruptions and Promote Safe and Effective Work Flow. Journal of Nursing Care Quality 2012. 27(2): 109-115, April/June 2012
Campbell G, Arfanis K, Smith AF. Distraction and interruption in anaesthetic practice.
Br. J. Anaesth 2012; 109(5): 707-715
Print “Dealing with Distractions”
December 4, 2012
Unintentional Perioperative Hypothermia:
A New Twist
When we came across one of the Pennsylvania Patient Safety Authority’s excellent articles a few years ago on unintentional perioperative hypothermia (PPSA 2008) we debated whether to do a column on it. Yes we know that avoidance of hypothermia is a SCIP measure and it is important. But it just didn’t sound like a topic we thought the majority of our readers would be interested in.
But we’ve subsequently seen a few cases of unintentional perioperative hypothermia with a new twist and there just happened to be a new article on this unusual phenomenon (Ryan 2012). Specifically, there appears to be a syndrome related to cases (most often obstetrical) in which spinal anesthesia with morphine is used and patients develop hypothermia with paradoxical sweating. Though most cases in the literature have followed cesarean sections, the case described by Ryan et al. was in a patient who underwent a knee arthroplasty. Spinal anesthesia was used with 11 mg of isobaric 0.5% bupivacaine, 15 micrograms of fentanyl, and 150 micrograms of morphine. The patient’s temperature reached a low point of 33.6 degrees C four hours after surgery, though at times her temperature could not be recorded by any route. Despite the hypothermia she felt hot and was diaphoretic without shivering. Warming efforts using forced air warming blankets, infusion of warmed intravenous fluids, and hourly bladder irrigation with warm saline were not successful in elevating her temperature. But a quick literature search by the authors showed the syndrome often responds to benzodiazepines and their patient rapidly became normothermic after receiving a small sublingual dose (0.5 mg) of lorazepam. The authors go on to discuss the cases in the literature and the current theory of the pathogenesis of this syndrome. The theory is that enough of the morphine ascends in the subarachnoid space to reach the hypothalamus where it interacts with receptors important in thermoregulation. Essentially this leads to alteration of the hypothalamic thermoregulatory set point causing the body to feel hot and sweat in attempt to adapt to heat. Benzodiazepine receptors are also found in the hypothalamus and are probably also involved in thermoregulation.
In at least 2 cases hypothermia after intrathecal morphine has improved promptly after administration of naloxone. In one case (Sayyid 2003) the patient’s temperature had dropped to 33.6 degrees C after a cesarean section and the patient was sweating excessively despite the hypothermia. She also had nausea, vomiting, pruritis and some sedation. Following naloxone administration all the above symptoms disappeared and she developed shivering and cessation of sweating concomitant with rising body temperature.
In the other case (Mangus 2011) a patient developed hypothermia unresponsive to usual warming measures several hours after a cesarean section in which she received intrathecal morphine. Severe pruritis and lethargy were also present. Naloxone was administered intravenously in incremental doses and her temperature began to rise within 5 minutes. The pruritis and lethargy also improved and her pain control was never compromised.
Hess et al reported on 14 patients who developed hypothermia following cesarean sections in which they had received spinal anesthesia with bupivacaine, morphine and fentanyl (Hess 2005). All had diaphoresis and felt hot. Four of the 14 were given lorazepam and had prompt resolution of symptoms and rapid increase in temperature. The remainder, who received conventional management of hypothermia, were hypothermic and symptomatic for 6 hours on average. The authors subsequently observed 100 consecutive patients and found 6% developed symptomatic hypothermia lasting for several hours.
There is some evidence suggesting that this phenomenon might be dose-related. In a randomized controlled trial Hui and colleagues randomized patients undergoing elective cesarean section to receive either 150 micrograms of morphine or normal saline along with the bupivacaine in their spinal anesthesia (Hui 2006). They found that both groups developed hypothermia but that the maximum decrease in temperature was greater in the morphine group and of longer duration. This suggests that even a low dose of morphine may intensify the hypothermic effect of spinal anesthesia. However, they point out that many of the cases in the literature had much higher doses of morphine. In fact, they note that larger doses are avoided because they are often associated with nausea, vomiting, pruritis and shivering. Note that nausea, vomiting and pruritis were prominent in the cases described by Mangus and Sayyid.
Interestingly, this phenomenon receives little or no attention in most of the major guidelines on perioperative hypothermia (ASPAN 2010, PPSA 2007, NICE 2008, AORN 2007 and AORN 2013) though the NICE guideline specifically excludes pregnant women.
The importance of these cases is twofold. First, you may want to limit the dose of intrathecal morphine used. Second, you need to amend your hypothermia management protocols to take this phenomenon into account. Specifically there should be a prompt to consider the phenomenon if the expected improvement in hypothermia is not occurring within a reasonable amount of time after conventional warming procedures have been instituted. Perhaps even a prompt at the beginning of your protocol to look for signs you would not expect with hypothermia (i.e. sweating, hot feeling, vasodilation) might suggest this unusual etiology for the hypothermia. The presence of nausea and pruritis might be an additional clue. In either case the prompt should remind you to consider a trial of either low dose benzodiazepine or naloxone.
You probably should have a formal protocol you follow for prevention and management of perioperative hypothermia. Use one of the above mentioned guidelines to start with. Another recent article (Ford 2012) provides some good case scenarios to help you choose when and how you might intervene. But make sure that whatever protocol you choose you add that prompt we noted above to at least consider the possibility of the morphine-induced syndrome because its management requires additional considerations.
PPSA (Pennsylvania Patient Safety Authority). Prevention of Inadvertent Perioperative Hypothermia. Pa Patient Saf Advis 2008; 5(2): 44-52
Ryan KF, Price JW, Warriner CB, Choi PT. Persistent hypothermia after intrathecal morphine: case report and literature review. Can J Anesth 2012; 59: 384-388
Mangus DB, Neumann M, Patchin R. Naloxone reversal of hypothermia following intrathecal morphine for cesarean delivery, a case report. Society for Obstetric Anesthesia and Perinatology 2011; SOAP 2011 Abstract #201
Sayyid SS, Jabbour DG, Baraka AS. Hypothermia and Excessive Sweating Following Intrathecal Morphine in a Parturient Undergoing Cesarean Delivery. Reg Anesth Pain Med 2003; 28(2): 140-143
Hess PE, Snowman CE, Wang J. Hypothermia after cesarean delivery and its reversal with lorazepam. Int J Obstet Anesth 2005; 14(4): 279-283
Hui C-K, Huang C-H, Lin C-J, et al. A randomised double-blind controlled study evaluating the hypothermic effect of 150 μg morphine during spinal anaesthesia for Caesarean section. Anesthesia 2006; 61(1): 29-31
Hopper VD, et al. ASPAN’s Evidence-Based Clinical Practice Guideline for the Promotion of Perioperative Normothermia: Second Edition. Journal of PeriAnesthesia Nursing 2010; 25(6): 346-365
AORN Recommended Practices Committee. Recommended practices for the prevention of unplanned perioperative hypothermia. AORN J 2007; 85(5): 972-988
AORN. Prevention of Hypothermia. In: Perioperative Standards and Recommended Practices. Denver, CO: AORN, Inc; 2013
NICE. Perioperative hypothermia (inadvertent): the management of inadvertent perioperative hypothermia in adults. NICE Clinical Guideline 29. London: National Institute for Health and Clinical Excellence, 2008
Quick reference guide
Ford D. How Would You Warm This Patient? Use these 6 case scenarios to determine which warming methods you'd choose. Outpatient Surgery Magazine 2012; November 2012
December 11, 2012
Breastfeeding Mixup Again
Many were shocked at the news of an incident last week in Minnesota in which a newborn was breastfed by a woman on the maternity unit who was not his mother (AP 2012). But in reality what’s amazing is that we don’t hear about many more similar incidents. Our November 17, 2009 Patient Safety Tip of the Week “Switched Babies” had an extensive discussion of the risk factors and contributory factors to incidents of both switched babies and breastmilk mixups. If you do a FMEA (failure mode and effects analysis) in your own organization we suspect that you will find numerous potential vulnerabilities to either error.
In the Minnesota case the wrong infant was given to another new mother to breastfeed. That mother initially sensed this might not be her own newborn but her husband apparently reassured her she was just tired so she proceeded to breastfeed (Lerner 2012). Several minutes later she noted the ID tag on the infant was not the name of her own newborn infant. They immediately contacted nurses, who confirmed this was not her baby. In addition to causing anxiety and stress for both families and staff, the newborn who received the wrong breastmilk will need to undergo HIV testing over the next year, adding to the stress even though the ultimate risk of HIV transmission in this case is probably quite low.
In our November 17, 2009 Patient Safety Tip of the Week “Switched Babies” we did a fairly extensive review of the problem of the wrong babies being given to the wrong mothers. The exact incidence of this problem is unknown but in doing our research at that time we found an article in the news about such switches occurring somewhere almost every year. Another incident occurred in 2010 in Virginia and a Washington Post article about that case noted several other near misses in the Washington, DC area (Suh 2010). And in our September 2011 What’s New in the Patient Safety World column “Another Breastfeeding Mixup” we highlighted another episode that occurred in Australia (Cooper 2011). So the occurrence of yet another case this year comes as no surprise. In fact, one whitepaper from Intel Corporation and partners estimates that of over 23 million infant transfers to and from mothers during initial hospital stays in the US annually, there are over 23,000 erroneous infant-mother transfers per year (Dalton 2005) but it is not clear where that data came from.
As is typical in most serious incidents a single error is seldom responsible for the adverse outcome. Instead, a cascade of errors and contributing factors come together to enable the event to occur. The current incident is no different. In the Minnesota case the failure to match the ID bracelets of the baby and mother was only the immediate cause at the sharp end. Prior to that the babies apparently had been placed in the wrong bassinets (Daily Mail 2012). Add to that a form of confirmation bias or ignoring disconfirming evidence (the mother was uncertain this was her baby but the husband attributed her concern to her being tired). The mother who did the breastfeeding also apparently had just given birth to twins (Kennedy 2012). Could that have played a role in the identification process? Did it somehow contribute to the infants being in the wrong bassinets? And we don’t know what root causes will be uncovered in the hospital’s root cause analysis (RCA). But undoubtedly they will look at issues such as workload, time pressures, staffing issues, change of shift, handoffs, staff education and orientation. And the safety culture will be addressed. The most difficult question to answer will be how often do nurses or aides bring a baby from a bassinet to a mother’s room for breastfeeding and actually check the ID bracelets against each other.
The latter error (failure to check that the ID bracelets match) is, in fact, a predictable error. In the Australian case details of the hospital’s investigation are sparse but apparently there was failure to verify identities on the bracelets (Cooper 2011). And in the Virginia case an aide apparently failed to ensure that the ID bracelets matched (Suh 2010). It is no different from the wrong patient errors we frequently saw in medication incidents before widespread adoption of barcoding systems. So we know that under enabling circumstances (for example, a busy night with several deliveries or C-sections pending and maybe suboptimal staffing) an anticipated human error might be to bring a baby to a mom and forget to match the ID bracelets.
We’ve done FMEA’s (Failure Mode and Effects Analysis) on this potential issue in the past and no matter how safe you think your present system is your FMEA will likely uncover potential vulnerabilities. See our November 17, 2009 Patient Safety Tip of the Week “Switched Babies” for an extensive discussion of the risk factors and contributory factors to incidents of both switched babies and breastmilk mixups.
Aside from the failure to match the ID bracelets on mother and baby, there are numerous other potential problems that can contribute to misidentifications. One potential problem involves similar names. Often newborns have not yet been named so their ID tags often have names like “baby boy smith” or “bb smith” (the “bb” standing for baby boy) and you might have more than one family with the last name “Smith” at one time. In our May 20, 2008 Patient Safety Tip of the Week “CPOE Unintended Consequences – Are Wrong Patient Errors More Common?” we noted you would be surprised to see how often patients with the same or very similar names may be hospitalized at the same time. Shojania (2003) described a near-miss related to patients having the same last name and noted that a survey on his medical service over a 3-month period showed patients with the same last names on 28% of the days. The problem is even more significant on neonatal units, where multiple births often lead to many patients with the same last name being hospitalized at the same time and medical record numbers being similar except for one digit. Gray et al (2006) found multiple patients with the same last names on 34% of all NICU days during a full calendar year, and similar sounding names on 9.7% of days. When similar-appearing medical records numbers were also included, not a single day occurred where there was no risk for patient misidentification.
Language barriers, of course, might be another contributing factor in some cases. While all hospitals are required to have access to translation services, it is not clear how often those are accessed just for the act of breastfeeding a newborn.
And what about room changes? In the Virginia incident apparently the baby’s mother had had a room change (AP 2012). There are a variety of reasons a patient might be moved from one room to another. Particularly in cases where something like a bassinet number in the nursery is “tied” to a room number special care must be taken ensure that “tie” to the mother is appropriately maintained.
The mother’s ability to recognize the baby is also an issue. The mother may be tired or may have received sedating drugs. In some cases the mother has only seen the baby once or twice. The baby may be swaddled and only his/her face showing. The babies often wear similar caps (blue for boys, pink for girls). And if the baby is brought for breastfeeding at night the room may be relatively dark, further impairing recognition of the baby.
Certainly, a number of patient safety tools are available that might reduce the chance of baby mixups. These include both high tech and low tech tools. Barcoding is an obvious tool, given that so many hospitals have now moved to barcoding systems to improve medication safety. And, though barcoding is a great tool, it doesn’t help if the bracelets/labels were already mixed up and it can often give rise to a false sense of security.
We discussed design issues related to ID bracelets in our November 17, 2009 Patient Safety Tip of the Week “Switched Babies”. The hospital in the Virginia case moved to a digital monitoring system that responds to incompatibility of the baby and mother by sounding an audible alarm (AP 2012). Incorporating RFID (radiofrequency identification) technology into systems is another technological advance (Dalton 2005) capable of helping in correct identification. And one has to expect Bluetooth technological solutions can’t be far behind. If we can use low-power Bluetooth to sound an alert on our keychain when our smartphone is no longer within 80 feet, someone will figure out how to use that to keep our infants nearby.
But even technological solutions will have failures. With barcoding systems we’ve certainly seen instances where the wireless access fails or the batteries in the scanners run down and providers resort to shortcuts and workarounds. Barcoding systems and other new technologies are still subject to numerous workarounds (see our June 17, 2008 Patient Safety Tip of the Week “Technology Workarounds Defeat Safety Intent”).
So what about low tech solutions? The timeout is a logical tool to use. Just as in the OR we use a timeout to verify the correct patient (and many other things) you could use a timeout to verify the correct baby/mother combination or identify the correct baby going for any other procedure. Certainly at least asking the mother to verbally provide her name and date of birth plus the name of the baby makes sense.
Use of checklists could also be very valuable. Almost all maternity units keep at the bedside a log where the mother or nurse records the time breastfeeding took place. It would be very easy to add a checklist item to that for the mother/baby verification.
What about double checks? A point we have made over and over is that double checks are very weak safety interventions (see our October 16, 2012 Patient Safety Tip of the Week “What is the Evidence on Double Checks?”). From all industries we know that the error rate when a supervisor checks someone else’s work may be 10% or higher. And we don’t know what influence the double check has on the error rates of the original person. It is quite conceivable that the original person may make more errors if they feel that their errors will be intercepted by a second reviewer. We did discuss the possibility of using double checks to prevent mother/baby mismatching in our November 17, 2009 Patient Safety Tip of the Week “Switched Babies”. We noted there might be some potential benefit if double checks, particularly at discharge, were applied to the baby/mother identification verification process. However, we suspect that requiring double checks for every breastfeeding occurrence on a maternity unit would be burdensome and become easily susceptible to workarounds.
And, importantly, we feel that you must have some way of auditing your processes to ensure compliance with your well-intentioned policies. The best policies in the world will not help if no one adheres to them. Plus auditing helps you identify when workarounds are being used. Workarounds are almost always indicative of a flaw in your policy or procedure and should tip you off that you need to fix the underlying system. The audits could be random spot audits or “secret shopper” type audits.
Our November 17, 2009 Patient Safety Tip of the Week “Switched Babies” also discussed the risk of babies being fed expressed breast milk from the wrong mother. The Pennsylvania Patient Safety Authority issued a Patient Safety Advisory on Mismanagement of Expressed Breast Milk in 2007 (PPSA 2007). The Pennsylvania Patient Safety Reporting System (PA-PSRS) had received 20 reports of infants being fed another mother’s expressed breast milk. They identified risk factors that involved not only identification issues but also labeling issues, and problems with verification, storage and dispensing. The Advisory has good recommendations on risk reduction strategies and an excellent section on how to respond and manage patients when such exposures do occur, particularly managing the risk for infectious disease transmission. All those recommendations obviously would also apply in cases where infants were directly exposed to breastfeeding by the wrong mother.
So, is your organization at risk? This is another great topic for a FMEA (failure mode and effects analysis).
See also our columns on infant abductions, which contain further pertinent information about infant identification:
Associated Press. Baby given to wrong mother at Minneapolis hospital. Duluth News Tribune 2012; December 7, 2012
Lerner M. Newborn at hospital is brought to wrong mom for feeding. Minneapolis Star Tribune. December 6, 2012
Sun LH. Baby is breast-fed by wrong woman at Virginia Hospital Center. Washington Post 2010; July 28, 2010
Cooper A. Switch shock as newborns go to wrong families. Sydney Morning Herald. July 18, 2011
Dalton J, Kim I-H, Lim B-K. RFID Technologies in Neonatal Care. White Paper by Intel Corporation, LG CNS, ECO Inc., and WonJu Christian Hospital. September 2005
Daily Mail Reporter. Baby given to WRONG mother to breastfeed after hospital mixes up newborns. Daily Mail Online 2012; December 7, 2012
Kennedy C. Baby Mix-up Has Apple Valley Mom Seeing Red. Apple Valley-Rosemount Patch 2012; December 6, 2012
Shojania KG. AHRQ Web M&M Case and Commentary. Patient Mix-Up. February 2003. http://www.webmm.ahrq.gov/case.aspx?caseID=1&searchStr=shojania
Gray JE, Suresh G, Ursprung R, Edwards WH, Nickerson J, Shiono PH, Plsek P, Goldmann DA, Horbar J. Patient Misidentification in the Neonatal Intensive Care Unit: Quantification of Risk. Pediatrics 2006;117;e43-e47
PPSA (Pennsylvania Patient Safety Authority). Mismanagement of Expressed Breast Milk. PA PSRS Patient Saf Advis 2007; 4(2): 46-50
Print “Breastfeeding Mixup Again”
December 18, 2012
Unintended Consequences of the CAUTI Measure?
We’ve long been staunch supporters of the CAUTI pay-for-performance (P4P) measure. Avoiding CAUTI’s was one of our very first quality improvement projects on a neurology service way back in the 1980’s. The key to success is obviously avoiding unnecessary use of indwelling urinary catheters and limiting duration in those cases where such originally has a legitimate indication. So we were on board when CMS began its program of nonpayment for CAUTI’s. But now, multiple years into the CMS program, we’re beginning to see that there may be unintended consequences of continuing to use CAUTI as a P4P measure.
In our November 2012 What’s New in the Patient Safety World column “CAUTI Conundrum” we pointed out a recent article (Lee 2012) that concluded that the financial disincentive of CMS’ nonpayment policy for hospital-acquired conditions did not lead to lower rates of CAUTI. Rates for CAUTI’s were already declining prior to CMS’ implementation of its reimbursement policy. Specifically, for CAUTI’s the preimplementation decline was 3.9% per quarter and only 0.9% per quarter afterward.
Though we discussed many potential explanations for this, we think that it simply reflects that we were already targeting CAUTI’s long before CMS implemented their policy so there was little change in CAUTI rates before and after implementation.
But in that column we cautioned that when we implement “evidence-based” quality pay-for-performance metrics we sometimes find out later that either the evidence was not so strong or that we get unintended consequences. We think that the evidence base for preventing CAUTI’s is strong. But what about the unintended consequences? We noted that it would be interesting to see how many patients got unnecessary antibiotics for asymptomatic bacteruria because of the CMS nonpayment policy for CAUTI’s. If the latter rate is high that might be a reason to change the metric.
The U.S. Preventive Services Task Force Guideline on Screening for Asymptomatic Bacteriuria in Adults (USPSTF 2008) recommends against screening in men and nonpregnant women. The USPSTF does recommend screening for asymptomatic bacteruria in pregnant women at 12-16 weeks’ gestation or at the first prenatal visit, if later. Other indications include those undergoing invasive urological procedures where mucosal bleeding is likely and possibly surgical procedures with implant material (Wagenlehner 2005, Nicolle 2005).
Even though treatment of asymptomatic bacteruria is not recommended in most circumstances we have seen multiple hospitals in which urine cultures are done on admission so that if the patient later develops a UTI following an indwelling urinary catheter the hospital can say this was “present on admission” and not have to report it as a CAUTI. Some of those patients do get antibiotic treatment for their asymptomatic bacteruria. And while there is little evidence of a beneficial effect of treatment in such cases, the treatment has the potential to have adverse effects.
The Infectious Diseases Society of America (IDSA) guidelines note that potential unintended consequences of treatment of asymptomatic bacteriuria include subsequent antimicrobial resistance, adverse drug effects, and cost (Nicolle 2005). Other potential unintended consequences would be increased hospital lengths of stay, delays in procedures, and the potential for diarrhea and C. difficile infections.
Now a new study (Drekonja 2012) makes us further question whether the CAUTI measure (as either a patient safety measure or P4P measure) may be inadvertently leading to other unintended and unwanted complications. The authors did a retrospective review of urine culture practices preoperatively in patients undergoing nonurologic surgeries in a VA hospital setting. In 25% of the surgeries a urine culture was obtained prior to surgery, though the frequency varied greatly by the service involved. Bacteruria was detected in 11% of these cultures though in most cases it was not treated. However, when they compared those patients in whom the preop bacteruria was treated with antibiotics vs. those not treated, the results were unexpected. The treated group had higher rates of surgical site infections (SSI’s) and higher rates of post-op UTI’s.
The above study had relatively small numbers and there may have been confounding factors (eg. were factors that led to the decision to treat the preoperative bacteruria also ones that led to higher rates of SSI’s?). So the study is not a definitive one but rather a hypothesis-generating one. A larger prospective study would need to be done. If it does turn out that obtaining urine cultures on admission in asymptomatic patients leads to unnecessary antibiotic treatment and that the treatment leads to an increase in post-op infections we clearly have an unintended consequence of the CMS metric of CAUTI as a never event. Thus, it may be time to retire CAUTI as the CMS metric. A more appropriate metric might simply be the percentage of urinary catheters meeting appropriateness criteria.
Continued focus on avoiding CAUTI’s is the right thing to do from a quality and patient safety perspective regardless of whether P4P or nonpayment policies are in effect or not. However, we need to make sure that using CAUTI’s as a P4P metric or flag for nonpayment is not causing more harm than good. The time may have come to retire the CAUTI metric.
Our other columns on urinary catheter-associated UTI’s:
Lee GM, Kleinman K, Soumerai SB, et al. Effect of Nonpayment for Preventable Infections in U.S. Hospitals. N Engl J Med 2012; 367: 1428-1437
U.S. Preventive Services Task Force (USPSTF). Screening for Asymptomatic Bacteriuria in Adults. July 2008
Wagenlehner FME, Naber KG, Weidner W. Asymptomatic Bacteriuria in Elderly Patients: Significance and Implications for Treatment. Drugs & Aging 2005; 22(10): 801-807
Nicolle LE, Bradley S, Colgan R, et al. Infectious Diseases Society of America Guidelines for the Diagnosis and Treatment of Asymptomatic Bacteriuria in Adults. Clinical Infectious Diseases 2005; 40: 643–54
Drekonja DM, Zarmbinski B, Johnson JR, et al. Preoperative Urine Cultures at a Veterans Affairs Medical Center. Arch Intern Med 2012; (): 1-2
Published online December 2012
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