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April 1, 2014
Expensive Aspects of Sepsis Protocol Debunked
In the past decade we’ve had considerable focus on identifying and managing sepsis. Because of the high mortality and morbidity rates associated with sepsis it’s logical that we should apply the same efforts to sepsis that we apply to conditions such as MI, stroke, and other conditions. Over the past few years the Surviving Sepsis Campaign has focused on improving morbidity and mortality from sepsis, stressing early recognition, timely antibiotics and goal-directed therapy, with adequate fluid resuscitation.
We all pretty much agree on the importance of early recognition, timely antibiotics, and early fluid resuscitation. As we noted in our March 15, 2011 Patient Safety Tip of the Week “Early Warnings for Sepsis” the Surviving Sepsis Campaign protocols focus on delivery of antibiotics within 3 hours of an emergency department admission and one hour of a non-emergency department admission. One study confirmed the impact on mortality of antibiotic administration in the emergency department within the first hour (Gaieski 2010). The use of serum lactate levels as a measure of possible tissue hypoperfusion has also helped in recognizing sepsis earlier.
But some of the more invasive aspects of existing guidelines and protocols, specifically interventions such as use of central venous catheters for measurement of central venous pressure and central venous oxygen saturation, have often been subject to criticism. These also stress the capabilities of some of our smaller hospitals. Similar criticisms have also been made about the role of vasopressors and inotropes in protocols.
In New York State our Department of Health has mandated that all hospitals have in place protocols for managing sepsis (NYSDOH 2013). The regulations require the hospitals to include in their protocols reference to specific physiologic thresholds or clinical conditions that would trigger use of centeral venous catheters.
It’s thus very timely that the results of the ProCESS trial have just been published in the New England Journal of Medicine (The ProCESS Investigators 2014). The ProCESS trial involved 31 medical centers and over 1300 patients with sepsis. The patients were randomized to one of 3 treatment arms. One arm received the full early goal-directed therapy (EGDT) protocol, which included the invasive monitoring plus guidelines for vasopressors and blood transfusions. The second arm also received management by a protocol but it did not require the invasive monitoring, vasopressors/inotropes, or blood transfusions. The third arm was the “usual care” group where the clinicians basically decided how to manage the patient.
The primary end-point of the trial, mortality at 60 days, did not differ across the 3 trial arms. There were also no differences in secondary outcomes such as 90-day mortality, one-year mortality, and need for organ support.
In the accompanying editorial (Lilly 2014) Craig Lilly, MD notes that guidelines such as those included in state legislation and those endorsed by the National Quality Forum (NQF) need to be updated now to remove the requirement for central hemodynamic monitoring. It’s pretty clear now that the expense and potential unintended consequences of such monitoring are no longer necessary.
And now a moment on our “soapbox”: It’s also interesting that sepsis mortality rates for even “usual care” now are on the order of 18-21% compared to over 40% a couple decades ago. While we like to think that’s because we have gotten so much better at identifying and managing sepsis, might there be other reasons contributing to that “decline”? Some authors (Lynn 2014) have questioned how we can rely on a simple definition for sepsis which requires the breach of only a few static thresholds. We like to point out that 2 significant drivers may have changed the landscape and created a population of “sepsis” that has a lesser mortality rate. CMS data clearly show that a few years back there was a significant change in the number of pneumonia cases and sepsis cases (Lindenauer 2012). The number of pneumonias decreased and sepsis cases increased. Why? Hospitals (often with the help of the third party "clinical documentation programs" that help billing) began using the definition of sepsis that required two of the SIRS criteria in a patient suspected of having infection in order to have a DRG for sepsis. You could have a patient with pneumonia happily pushing his IV pole up and down the hallway who meets those threshold criteria and now gets a label of "sepsis", which of course gets a significantly higher reimbursement than pneumonia. The same research group just recently showed how such coding changes have affected reported mortality rates for both pneumonia and sepsis (Rothberg 2014). They note that such shifts in coding reduce the pneumonia mortality rate lower (because sicker patients are shifted to the sepsis or respiratory failure diagnosis codes) and also reduce the mortality rate for sepsis (because the newly added patients are less sick than the average sepsis patient).
Also, CMS readmission penalties apply to pneumonia but not to sepsis. So there was additional pressure on hospitals to see if patients met the sepsis "criteria". And, as pointed out in the recent coding impact article (Rothberg 2014) the Surviving Sepsis Campaign may have increased awareness of sepsis, resulting in more patients with pneumonia being coded as sepsis since they met the SIRS criteria requirement.
Another recent retrospective analysis from Australia and New Zealand (Kaukonen 2014) showed that the mortality rates for ICU patients admitted with severe sepsis declined from 35% to 18.4% over the period 2000-2012. The trend was steady and amounted to a 1.3% annual decline in mortality for severe sepsis. There was a similar decline in mortality for patients with non-sepsis diagnoses. There was also a trend toward greater discharge to home in patients with severe sepsis compared to other diagnoses.
The accompanying editorial (Angus 2014) cites reasons why they think changes in coding are not the culprit. However, they do note that these data once again strongly demonstrate that false conclusions may easily arise from studies with before-and-after designs. They also note that this trend of declining mortality in patients with severe sepsis means we need to be looking at outcome measures other than death when designing studies of interventions in sepsis (and other conditions).
Soapbox aside, we still need to focus on early recognition, timely antibiotics and adequate fluid rescuscitation to reduce morbidity and mortality from sepsis. But let’s do away with the recommendations for invasive interventions of questionable value.
Surviving Sepsis Campaign. Website.
Gaieski DF, Mikkelsen ME, Band RA, et al. Impact of time to antibiotics on survival in patients with severe sepsis or septic shock in whom early goal-directed therapy was initiated in the emergency department. Crit Care Med 2010; 38(4): 1045-53
NYSDOH. Sepsis Regulations: Guidance Document 405.4 (a)(4). 2013
The ProCESS Investigators. A Randomized Trial of Protocol-Based Care
for Early Septic Shock. N Engl J Med 2014; published online March 18, 2014
Lilly CM. The ProCESS Trial - A New Era of Sepsis Management. N Engl J Med 2014; published online March 18, 2014
Lynn LA. The diagnosis of sepsis revisited - a challenge for young medical scientists in the 21st century. Patient Safety in Surgery 2014; 8:1 (2 January 2014)
Lindenauer PK, Lagu T, Shieh M-S, et al. Association of Diagnostic Coding With Trends in Hospitalizations and Mortality of Patients With Pneumonia, 2003-2009. JAMA 2012; 307(13): 1405-1413
Rothberg MB, Pekow PS, Priya A, Lindenauer PK. Variation in Diagnostic Coding of Patients With Pneumonia and Its Association With Hospital Risk-Standardized Mortality Rates: A Cross-sectional Analysis. Ann Intern Med 2014; 160(6): 380-388
Kaukonen K-M, Bailey M, Suzuki S, et al. Mortality related to severe sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-2012. JAMA 2014; Published online March 18, 2014
Angus DC, Iwashyna TJ. Declining case fatality rates for severe sepsis good data bring good news with ambiguous implications. JAMA 2014; Published online March 18, 2014
April 8, 2014
FMEA to Avoid Breastmilk Mixups
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. Breastmilk mixups are far more common than switched babies and have potentially serious consequences. Our December 11, 2012 Patient Safety Tip of the Week “Breastfeeding Mixup Again” further defined the magnitude of the problem and described the numerous factors that contribute to such occurrences. We noted that if you do a FMEA (failure mode and effects analysis) in your own organization we suspect that you will find numerous potential vulnerabilities to these errors. We’ve done FMEA’s with hospitals in the past on both topics (switched babies and breastmilk mixups) and are always amazed at the complexities involved.
We came across a newly published FMEA on breastmilk feeding (Zhang 2014) that provides a good model for organizations to use for their own FMEA on the topic. Their interdisciplinary team of involved stakeholders began with a mapping of the baseline processes and flow in their level IV NICU. They then developed an evaluation grid that included the risks associated with each failure mode from three perspectives (severity, occurrence, and detection). A scale of 1 to 10 was used for each of those risks and an overall risk priority number (RPN) was estimated by multiplying the ratings for those three risk ratings. They then tested the feasibility of potential interventions and did benchmarking with both regional and national similar organizations.
One extremely important point they found is that it’s simply not enough to flowchart the processes you think are in place. You need to actually observe and talk to all involved parties. You will typically find that, in practice, things are frequently done differently than expected. For example, though their policy required that only nurses could receive and handle breastmilk they found that breastmilk was often handled by family, visitors or unit coordinators. Even though nurses were the only ones who could prepare the milk and mix in any additives and warm the milk, parents (who would feed the baby) in some cases had unrestricted access to the preparation area and could conceivably take the wrong milk to their baby. As we’ve pointed out in many of our columns, when you identify a workaround or deviation from expected processes you always need to find out why. Workarounds are a red flag that you have a flawed process and you need to do a root cause analysis (RCA) to determine the factors contributing to the need (perceived or real) for that workaround. The authors did just that. Whenever they found a deviation of process steps they did an RCA.
Their flowcharting sorted the process into three phases: (1) intake and storage (2) milk preparation and (3) feeding. They found 32 failure modes that had a severity of 10 and would not be detected automatically. They found multiple complexities and potential risks in all phases. For example, they found that a nurse needed to make 18 different decisions in the preparation phase for just one patient. Compound that with the need to prepare milk for multiple patients and the issues of multiple users, interruptions and multiple handoffs. Moreover, the same nurse preparing the milk likely had multiple other patient care duties.
They did a Pareto diagram of the potential interventions ranked by the RPN scores. The top six interventions (that put them above 80% on the Pareto diagram) were:
Other interventions identified included patient and nurse education, communication and handoff issues, and others.
After the FMEA, RCA’s and benchmarking, some of the key recommendations they made were finding dedicated preparation spaces, developing a staffing model that included milk technicians, and creating a process for tracking feedings in the electronic medical record.
This is a well-done FMEA and should help you and your organization do your own FMEA. We are often asked by hospitals what topics are best for FMEA’s (remember you have a Joint Commission requirement to do FMEA’s). For those hospitals that have obstetrics or otherwise care for neonates and young infants, we usually recommend doing a FMEA on either the risk of switched babies or switched breastmilk
We again refer you to our Patient Safety Tips of the Week for November 17, 2009 “Switched Babies” and December 11, 2012 “Breastfeeding Mixup Again” for comments on multiple other risks and contributing factors you are likely to find. Among such are issues related to similar names, language barriers, room changes, and failure to correctly identify the infant or milk preparation. We discuss technologies (barcoding, RFID) and bedside tools (checklists, timeouts) that are important considerations in your interventions.
In our December 11, 2012 Patient Safety Tip of the Week “Breastfeeding Mixup Again” we also noted the Pennsylvania Patient Safety Authority had issued a Patient Safety Advisory on Mismanagement of Expressed Breast Milk in 2007 (PPSA 2007) after 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.
And, lastly, don’t stop after you’ve implemented changes. Make sure you go back and audit your new processes to ensure you’ve not created new workarounds and unintended consequences. Because the outcomes you are trying to prevent (giving the wrong breastmilk to the wrong baby) are rare, you’ll have to measure other parameters to assess that you are likely reducing the risk of such undesired outcomes.
Zhang B, LaFleur EA, Ballweg DD, et al. Use of Healthcare Failure Mode and Effect Analysis (HFMEA) to Quantify Risks of the Human Milk Feeding Process. Journal of Nursing Care Quality 2014; 29(1): 30-37
PPSA (Pennsylvania Patient Safety Authority). Mismanagement of Expressed Breast Milk. PA PSRS Patient Saf Advis 2007; 4(2): 46-50
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April 15, 2014
Specimen Identification Mixups
Mixups… Last week we talked about breastmilk mixups. And we’ve previously talked about baby mixups. And recently we’ve had a flurry of hits on our previous columns regarding specimen mixups (Patient Safety Tips of the Week for October 9, 2007 “Errors in the Laboratory”, November 16, 2010 “Lost Lab Specimens”, March 6, 2012 ““Lab” Error”, and January 22, 2013 “You Don’t Know What You Don’t Know” and our April 2012 What’s New in the Patient Safety World column “Specimen Labeling Errors”).
Standardized measurements of surgical specimen identification defects have been lacking. But recently multidisciplinary members of a panel from hospitals participating in the Michigan Health and Hospital Association (MHHA) Keystone Center for Patient Safety and Quality developed a set of practical measures to quantify specimen identification defects in the preanalytic phase (Bixenstine 2013). They developed 12 measures (6 container and 6 requisition identification defects), then piloted data collection at 69 hospitals participating in the MHHA Keystone project over a 3-month period. Overall, there were identification defects in 2.9% of cases. There were defects in 1.2% of containers and in 2.3% of requisitions.
An excellent review on preventing specimen mixups was published earlier this year by Dr. Wolfgang Weyers (Weyers 2014). Though written from the perspective of a dermatopathologist, it really applies to all surgical specimen mixups (and really to a whole host of laboratory specimen mixups, too). He nicely describes the literature on the issue of specimen mixups and discusses ways to minimize the risks using several themes:
Weyers notes that in the lifecycle of a surgical specimen it may go through 20+ people and several workplaces. It can be even more complicated when specimens are going to another facility or organization.
Weyers emphasizes that good organization of all the steps involved is the best way to prevent specimen mixups. That begins with standardization. Examples he provides are always taking sample bottles with formalin from the same place, always depositing specimens in the same way, arranging slides or cassettes in the same manner, and many others. Color-coding of specimens is another standardized method often used, though Weyers notes even it is subject to error.
Using computers and technology is another means to prevent mistakes. Because manual labeling of specimens is error-prone, automatic labeling of blocks or specimens in a printer may help prevent mistakes. Barcoding significantly helps alleviate transcription errors.
Readability and Understandability
While illegible handwriting is a frequent source of error leading to specimen mixups, even computer use can lead to errors. For example, he notes that short codes inadvertently keyed into the computer transposed can result in serious errors. He therefore notes that sometimes using a longer code that conveys more obvious meaning may be preferable.
Using at least 2 unrelated data elements (as required anyway by Joint Commission) is important in avoiding mixups. That is particularly important when names are the same or similar.
Weyers would be appalled to see our desk when we are doing columns! He really emphasizes how workplaces in the lab must be tidy and the need to keep only one procedure in sight. That applies equally in the operating room where files and specimens of the current patient should be kept separate from all other files and specimens.
He also cautions against labeling bottles and request forms prior to biopsies because the course of action is sometimes changed during the procedure (eg. change in the sequence of biopsies or addition of another biopsy).
Checking the specimen bottles and request forms for completeness is extremely important. Even the simple act of ensuring that any adhesive labels adhere firmly to the specimen bottle is critical.
Order also needs to be maintained during unpacking of specimens and all other subsequent work.
In discussing cleanliness, he notes how specimens or pieces thereof may slip and fall or flip away. For that reason (and others) the floor should be kept very clean. For the same reason the floor should be kept a light uniform color without decorations that might make it difficult to spot a dropped specimen. (See also our November 16, 2010 Patient Safety Tip of the Week “Lost Lab Specimens” for more information on lost specimens.) He also notes how “ribbons” of tissue specimens may be transferred from an instrument to a slide or float in a bath and be inadvertently picked up on another slide (see also our January 22, 2013 Patient Safety Tip of the Week “You Don’t Know What You Don’t Know”).
Weyers describes two forms of mutual control: simultaneous and downstream. By simultaneous mutual control he means having two individuals involved in the same action calling attention immediately to any error by the other. He notes these should be done in the most vulnerable steps of the biopsy pathway. He notes that accessioning of specimens in the laboratory, including unpacking and sorting and numbering bottles and request forms, is one particularly vulnerable time and therefore should be done by two individuals simultaneously. (Note, however, some of our prior comments on double checks as in our October 16, 2012 Patient Safety Tip of the Week “What is the Evidence on Double Checks?”).
An example of downstream mutual control might be identifying and marking any discrepancies so that downstream work recognizes those errors.
Communication is two-way. Adequate completion of the request forms is so important that Weyers recommends the physician himself or herself complete these. Delegation to someone who may not understand the importance of such entries often results in errors or incomplete requests. Similarly, communication back to the requesting physician is important, particularly when there has been incomplete information on the request form.
Weyers also has lots of other practical recommendations in his review:
It’s Everybody’s job!
Weyers notes that every one of the 20+ people who may be involved with the specimen start-to-end processes has a role in detection of potential or actual errors. He notes that even the secretaries transcribing reports can identify such errors. For example, they might note inconsistencies such as description of a cancer in a report that concludes “no cancer found”.
The paperclip did it! We almost used this for the title of today’s column! Weyers even notes the role the lowly but highly utile paperclip can play in causing specimen mixups. He notes that paperclips that attach some additional information to a request form may catch another request form, resulting in more than one form being put aside after dictation, and the next report may be issued erroneously for the wrong patient. Of course, in the old paper medical record era we often saw reports in the wrong patient chart because they adhered to another report.
Weyers also issues a warning we’ve made on multiple occasions: “Don’t ever allow files on 2 patients open at same time”. That significantly increases the possibility that data meant for one patient may be interpreted or included for another patient. He also reminds us to beware of “cut and paste” noting that sometimes there is on the computer clipboard information from a previous patient that inadvertently gets pasted into a new patient record.
He also discusses how interruptions and distractions may contribute to errors and how both high and low workloads may facilitate errors.
He has a good discussion about the importance of documentation of errors. That obviously should include not only errors that resulted in patient harm or near misses but also minor errors that may uncover latent factors that may contribute to future errors. Along that vein, the system described by Bixenstine et al. looks all the more important.
He also describes DNA molecular identity testing for cases in which specimen mixups are suspected (we’ve also discussed such testing in several of the columns referenced below).
Read the Weyers article. It has many more good ideas than we can summarize in our column. And read our many prior columns addressing the serious issue of specimen mixups.
Some of our other columns on errors related to laboratory studies:
Bixenstine PJ, Zarbo RJ, Holzmueller CG, et al. Developing and Pilot Testing Practical Measures of Preanalytic Surgical Specimen Identification Defects. American Journal of Medical Quality 2013; 28(4): 308-314 first published on January 15, 2013
Weyers W. Confusion - specimen mix-up in dermatopathology and measures to prevent and detect it. Dermatol Pract Concept 2014; 4: 27-42
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April 22, 2014
Impact of Resident Workhour Restrictions
In the late 1980’s New York State adopted recommendations of the Bell Commission to limit the number of hours housestaff could work in a week. The Bell Commission was convened after the Libby Zion case had highlighted issues related to fatigue and supervision of physicians in training. At the time we actually asked Dr. Bell what the evidence base was that the change in housestaff hours would have a beneficial effect on patient outcomes. His response was that incidents reported in NYS were more frequent on evenings and weekends. We pointed out that those were also the times where cross-coverage occurred most frequently and that important information was often suboptimally transmitted during handoffs. There is no question that fatigue can result in diminished performance and has been associated with many adverse events (see the list of our prior columns on fatigue in healthcare at the end of today’s column). But we suspected that benefits from reduced housestaff fatigue might well be offset by detrimental effects of an increased number of handoffs that would occur after the change in housestaff hours.
NYS proceeded with the 80-hour weekly maximum for housestaff without any formal or systematic measurement of its impact on patient outcomes or for recognition of unintended consequences. Subsequently other states and ACGME have adopted significant restrictions in housestaff hours. The ACGME 80-hour work week restriction was implemented in 2003 and the ACGME in 2011 mandated 16-hour duty maximums for PGY-1 residents.
As you all probably know, the evidence of an impact of restricted housestaff hours on patient outcomes and patient safety has been mixed and contradictory. And any study looking at the impact of restricted work hours needs to look at patient outcomes, adverse events, housestaff wellness and well-being, and how well we educate and prepare our residents for their future practice in healthcare.
A new systematic review looks at the impact of restricted hours in surgical residency programs from all those perspectives (Ahmed 2014). The authors review the literature on the impact of surgical resident workhour restrictions from a patient safety perspective and note that the impact is uncertain by objective measures but that overall perceptions of patient safety by residents are worse. And while resident well-being is perceived as being improved the overall impact from their educational and training perspective is worse. They note that while overall numbers of surgical procedures may be unchanged, there is a decrease in the number of emergency procedures they do. Those emergency procedures often help better prepare residents for recognition of rapidly changing circumstances and better deal with unexpected events.
They do note that overall there has been a trend toward increased patient mortality since implementation of resident workhour restrictions but that this has not reached statistical significance. Studies on the impact on morbidity and complication rates have been mixed and inconclusive. Studies in neurosurgery, cardiac surgery and critical care have shown increased complication rates.
Regarding the 16-hour maximum workday they again conclude that there is no conclusive answer from objective measures but, again, outcomes are worse from a subjective perspective. Residents frequently note diminished continuity of care, increased handoffs, and work compression as having negative impacts on patient care, safety and outcomes. They also note that shorter hours result in residents not fully seeing the natural course or trajectory of the patients’ conditions, perhaps delaying recognition of early clinical deterioration. From the resident wellness/well-being perspective they note no significant change. From the educational perspective they note decreased readiness for real world practice. They also note that, while resident performance on written board exams has remained unchanged, there has been a substantial decline in resident performance on the oral portion of board exams since implementation of the restrictions.
The authors also note that “night float” systems put in place to deal with care gaps caused by the resident workhour restrictions results in decreased learning opportunities.
They do discuss interventions that should be considered as alternatives or adjuncts to residency programs. These include simulation programs, programs to improve sleep opportunities, wellness programs, more use of other healthcare providers, better handoffs, and maintenance of the 24-hour circadian cycle (eg. no float systems or shift work).
Though many of the conclusions in the Ahmed review weigh heavily on subjective rather than objective measures, this is a very good review of studies to date on the impact of workhour restrictions in surgical training programs.
Note that a UK task force has also just released a report showing European residency workhour restrictions have had a negative impact on training for some specialties, particularly surgery (Rimmer 2014).
Studies on the impact of the 2011 ACGME workhour changes on medical residents have been mixed. One study (Sen 2013) found that although interns report working fewer hours under the new duty hour restrictions, this decrease has not been accompanied by an increase in hours of sleep or an improvement in depressive symptoms or well-being but has been accompanied by an unanticipated increase in self-reported medical errors. A more recent study (Block 2014) found no change in patient safety outcomes in patients treated by general medicine residents compared to those treated by hospitalists after implementation of the 2011 changes.
Some of our other columns on housestaff workhour restrictions:
December 2008 “IOM Report on Resident Work Hours”
February 26, 2008 “Nightmares: The Hospital at Night”
January 2011 “No Improvement in Patient Safety: Why Not?”
November 2011 “Restricted Housestaff Work Hours and Patient Handoffs”
January 3, 2012 “Unintended Consequences of Restricted Housestaff Hours”
June 2012 “Surgeon Fatigue”
November 2012 “The Mid-Day Nap”
December 10, 2013 “Better Handoffs, Better Results”
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 “Surgeon Fatigue”
Ahmed N, Devitt KS, Keshet I, et al. A Systematic Review of the Affects of Resident Duty Hour Restrictions in Surgery: Impact on Resident Wellness, Training, and Patient Outcomes. Annals of Surgery 2014; Published ahead-of-print POST AUTHOR CORRECTIONS, 21 March 2014
Rimmer A. Implementation of the working time directive has had an adverse impact on training in the UK, taskforce says. BMJ 2014; 348: g2599 (Published 4 April 2014)
Sen S, Kranzler HR, Didwania AK, et al. Effects of the 2011 Duty Hour Reforms on Interns and Their PatientsA Prospective Longitudinal Cohort Study. JAMA Intern Med. 2013; 173(8): 657-662
Block L, Jarlenski M, Wu AW, et al. Inpatient safety outcomes following the 2011 residency work-hour reform. Journal of Hospital Medicine 2014; Article first published online 22 FEB 2014
April 29, 2014
More on the Unintended Consequences of Contact Isolation
An elderly nursing home resident with diabetes and dementia was admitted to an acute care facility because of a UTI and hyperosmolar state with increased confusion. Because of the presence of MRSA on a previous admission the patient was placed on isolation and contact precautions. She subsequently developed delirium and a sacral decubitus. Though she eventually recovered enough to return to the nursing home, her acute care hospitalization was prolonged and costs were over $50,000.
We’ve done a few columns on the unintended consequences of contact isolation precautions (see the list at the end of today’s column). Would the above patient still have developed the decubitus and delirium had she not been put on isolation and contact precautions? We’ll never know for sure. But we do know that less contact by healthcare workers (and visitors) with patients in contact isolation leads to errors and omissions in care and other unintended consequences.
A new study used location tracking via RFID chips embedded in hospital ID badges to compare the amount of time interns spent with patients in contact isolation vs those not in contact isolation (Dashiell-Earp 2014). They found that interns, on average, spent 5.2 minutes per day with their patients in contact isolation vs. 6.9 minutes in those not in isolation (p <0.001).
We and the authors of that study are surprised at the low number of minutes per day that interns spend in direct contact with even their non-isolation patients. Nevertheless, the study again validates previous studies that patients having contact isolation precautions have reduced contact with their physicians.
We’ve discussed some of the unintended consequences of contact isolation in prior Patient Safety Tips of the Week (January 17, 2012 “Delirium and Contact Isolation” and March 25, 2008 “More on MRSA”). Kirkland and Weinstein (Kirkland 1999) found that healthcare workers who treated patients in contact isolation entered their rooms less frequently and had significantly less direct contact with them. Saint et al. (2003) found that attending physicians in two teaching hospitals were about half as likely to examine patients in contact isolation. Another study (Stelfox et al. 2003) showed that isolated patients are twice as the likely as control patients to suffer an adverse event during hospitalization. The difference was primarily due to preventable adverse events and included events such as falls, decubiti, and fluid/electrolyte disorders. In fact, the latter events were 8 times more likely in isolated patients. They also had a cohort of congestive heart failure patients in isolation and these patients were much less likely to have certain interventions and evidence-based care than a control group of congestive heart failure patients. And we have all seen that patients in contact isolation often do not get services such as active rehabilitation that they might get were they not in isolation. A review of the literature (Morgan 2009) found 15 studies relating to adverse outcomes of contact isolation and identified these in four main themes: less patient-healthcare worker contact, changes in systems of care that produce delays and more noninfectious adverse events, increased symptoms of depression and anxiety, and decreased patient satisfaction with care. The University of Maryland group (Morgan 2011) had also previously poor adherence to core measures for patients on contact isolation. And another study from the University of Maryland (Day 2012) found that delirium was 75% more common in patients who are put into contact isolation during admission (as opposed to those placed in contact isolation at the time of admission).
Our January 2013 What’s New in the Patient Safety World column “More on the Downside of Contact Isolation” highlighted another study from the researchers at the University of Maryland (Morgan 2013) further quantifying some of the impact of contact precautions on patient care. Patients on contact precautions had 36.4% fewer hourly visits by healthcare workers (HCW’s) than patients not on contact precautions (2.78 vs 4.37 visits per hour). They also had 17.7% less direct patient contact time with HCWs (13.98 vs 16.98 minutes per hour). The latter difference, however, was largely accounted for by patients who were not in ICU’s (those in ICU’s did not have a significant difference in contact time with HCW’s). Those on contact precautions also had 23.6% fewer visitors.
These studies all reinforce the observation that patients in contact isolation (particularly those in non-ICU settings) have considerably reduced contacts and contact time with both providers and visitors, likely increasing the potential for more adverse events.
The process used at some hospitals of cohorting patients with MRSA may also raise their risk of reacquiring MRSA (or other multiple drug resistant organisms).
One factor often not considered in studies on the impact of contact isolation is the duration of the isolation. While guidelines for putting a patient in isolation are available, there are few evidence-based guidelines for discontinuation of contact isolation, resulting in widespread variability of hospital protocols for discontinuation of contact precautions (Shenoy 2012). Many patients are kept on isolation and contact precautions unnecessarily because they never complete the screening criteria (Pegues 2013).
To evaluate the impact of passive vs. active MRSA screening on contact precaution discontinuation, researchers at the Massachusetts General Hospital did a randomized trial (Shenoy 2013). One arm received the local standard of care (which relied upon identifying candidates at risk for MRSA and getting 3 negative cultures 24 hours apart before discontinuing contact precautions) and the other received active screening with study staff immediately taking a nasal swab for culture and one for PCR (polymerase chain reaction) testing for MRSA, repeated on subsequent days. Patients in the active intervention arm had their contact precautions discontinued over 4 times more frequently than those in the passive (standard care) arm. Moreover, screening with the PCR technique revealed excellent sensitivity, specificity, and positive and negative predictive values. The number of contact precaution days avoided was substantial in the active screening arm. In particular, the strategy of active screening with PCR resulted in a 55% reduction in patient days on contact precautions. Though PCR testing is more expensive than cultures on a per test basis, the resultant avoidance of precaution days resulted in an estimated annualized savings of over $1.5 million for the hospital.
Both the authors of the MGH study (Shenoy 2013) and the accompanying editorial (Pegues 2013) suggest that use of electronic alerts and clinical decision support tools might help get more patients screened appropriately and promptly, thereby improving the effectiveness of such screening programs and avoiding more unnecessary days in contact isolation.
A 2010 systematic review of the adverse effects of contact isolation (Abad 2010) noted all of the unintended consequences noted above but also stressed that patients on contact isolation are generally more dissatisfied with their care. Those authors stress the importance of good communication with such patients and preparing them emotionally prior to isolation.
Make your decisions wisely about who and when to use contact isolation and make sure you appropriately assess the need for continued isolation. But make sure that your care plan includes appropriate interventions and monitoring to ensure that patients on contact isolation get all their medical and psychological needs met.
Some of our prior columns on the unintended consequences of contact isolation:
Dashiell-Earp CN, Bell DS, Ang AO, Uslan DZ. Do Physicians Spend Less Time With Patients in Contact Isolation? A Time-Motion Study of Internal Medicine Interns. JAMA Intern Med 2014; Published online March 31, 2014
Kirkland KB, Weinstein JM. Adverse effects of contact isolation. The Lancet 1999; 354: 1177-1178 http://www.thelancet.com/journals/lancet/article/PIIS0140673699041963/abstract
Saint S, Higgins LA, Nallamothu BK, Chenoweth C. Do physicians examine patients in contact isolation less frequently? A brief report. Am J Infect Control 2003; 31: 354-356 http://www.ajicjournal.org/article/S0196-6553(02)48250-8/abstract
Stelfox HT, Bates DW, Redelmeier DA. Safety of Patients Isolated for Infection Control. JAMA. 2003;290:1899-1905
Morgan DJ, Diekema DJ, Sepkowitz K, Perencevich EN. Adverse outcomes associated with contact precautions: A review of the literature. Am J Infect Control 2009; 37(2): 85–93
Morgan DJ, Day HR, Harris AD, et al. The Impact of Contact Isolation on the Quality of Inpatient Hospital Care. PLoS One. 2011; 6(7): e22190
Day HR, Perencevich EN, Harris AD, et al. Association Between Contact Precautions and Delirium at a Tertiary Care Center. Infection Control and Hospital Epidemiology 2012; 33(1): 34-39
Morgan DJ, Pineles L, Shardell M, et al. The Effect of Contact Precautions on Healthcare Worker Activity in Acute Care Hospitals. Infection Control and Hospital Epidemiology 2013; 34(1): 69-73
Shenoy E, Hsu H, Noubary F, et al. National Survey of Infection Preventionists: Policies for Discontinuation of Contact Precautions for Methicillin-resistant Staphylococcus aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE). Infect Control Hosp Epidemiol 2012; 33(12): 1272–1275
Pegues DA. Editorial Commentary: Search, Destroy, and Confirm: How to Maximize the Benefit and Reduce the Unintended Consequences of Contact Precautions for Control of Methicillin-Resistant Staphylococcus aureus Clin Infect Dis 2013; 57(2): 185-187
Shenoy ES, Kim J, Rosenberg ES, et al. Discontinuation of contact precautions for methicillin-resistant staphylococcus aureus: a randomized controlled trial comparing passive and active screening with culture and polymerase chain reaction. Clin Infect Dis 2013; 57(2): 176-84
Abad C, Fearday A, Safdar N. Adverse effects of isolation in hospitalised patients: a systematic review. Journal of Hospital Infection 2010; 76(2): 97-102
May 6, 2014
Monitoring for Opioid-induced Sedation and Respiratory Depression
Long at the top of our list of hospital-based patient safety issues is opioid-induced respiratory depression. Opioid use in the hospital setting is substantial and it’s not just surgical patients who are receiving opioids. Over half (51%) of medical inpatients receive opioids, often in high doses (Herzig 2014).
We recently came across an article in the nursing literature describing one hospital’s efforts to implement change in policy, practice and culture regarding monitoring of sedation in patients receiving opioids for pain (Smith 2014). Smith and colleagues assembled a multidisciplinary team in an academic medical center and did an extensive review of the literature on opioid-induced sedation and respiratory depression. They very appropriately concluded that all patients on opioids are at risk for these complications. Because sedation often precedes respiratory depression in patients on opioids they focused their attention on how they monitored sedation.
After reviewing the various sedation assessment tools available, they chose the Pasero Opioid-induced Sedation Scale (POSS). While many organizations utilize other assessment tools, most notably the Richmond Agitation and Sedation Scale (RASS), we’ve always liked the Pasero scale for its simplicity and actionability (see our Patient Safety Tips of the Week for “Monitoring the Postoperative COPD Patient” and February 19, 2013 “Practical Postoperative Pain Management”).
They included in their policy a good description of the appropriate assessment of respiration, conducted at the same intervals as the sedation assessment. As we’ve indicated on numerous occasions, it is critical that the patient not be aroused before doing that assessment of respiration. The patient is then aroused before the sedation assessment is done.
Built into their policy is the requirement that the nurses consider opioid pharmacokinetic and pharmacodynamics factors. That includes factors such as peak effect time of the opioid and frequency/route of administration. One important point is the need to reassess respiratory status and the POSS at the time of expected peak opioid effect.
They created a documentation flowsheet and added it to the electronic medical record. We recommend you take that even a step further. With today’s sophisticated systems for barcoding, pharmacy management and electronic medical records we can use forcing functions to ensure the appropriate assessment of sedation is done prior to administration of the next dose of opioids and embed actions to be taken right into the system based upon results of the sedation assessment.
Their rollout included educational programs using PowerPoint slides, computer-based learning sessions, unit-based reference binders, a one-page flier, and pocket-sized reference cards.
They assessed the impact of their initiative in two ways. One was administering a questionnaire to nurses before the implementation began and about 6 months after implementation. This showed that nurses were better able to recognize patients at risk and understood use of the assessment tool. They also did regular audits for compliance with the policy (a copy of the audit tool is available in the supplemental materials accompanying the journal article). Audits showed an initial need to improve compliance but then showed improvement in most, but not all, measures. They note the need for a continued focus is needed to fully integrate the changes into daily practice.
This is a well-done article and provides insights into useful tools and issues you’ll encounter as you attempt to change the culture and practice regarding this significant patient safety issue.
We also refer you back to our February 19, 2013 Patient Safety Tip of the Week “Practical Postoperative Pain Management” that highlighted a great overview and recommendations by Chris Pasero (Pasero 2013). That article and the many columns we’ve done on opioid-induced respiratory depression (see list below) emphasizes such issues as recognition of snoring as a red flag, pitfalls of pulse oximetry, benefits of capnography for monitoring, ability of nurses to administer naloxone when necessary, and recognition of the renarcotization phenomenon after narcotic reversal.
The Smith article and the Pasero article are very valuable reads to help you get your practices regarding patient safety and opioids up to standard.
Other Patient Safety Tips of the Week pertaining to opioid-induced respiratory depression and PCA safety:
And we think you’ll learn a lot from our prior articles pertaining to long-acting and/or extended release preparations of opioids:
June 28, 2011 “Long-Acting and Extended-Release Opioid Dangers”
September 13, 2011 “Do You Use Fentanyl Transdermal Patches Safely?”
May 2012 “Another Fentanyl Patch Warning from FDA”
July 24, 2012 “FDA and Extended-Release/Long-Acting Opioids”
Herzig SJ, Rothberg MB, Chekung M, et al. Opioid utilization and opioid-related adverse events in nonsurgical patients in US hospitals. Journal of Hospital Medicine 2014; 9(2): 73-81
Smith A, Farrington M, Matthews G. Monitoring Sedation in Patients Receiving Opioids for Pain Management. J Nurs Care Qual 2014; published ahead of print 28 March 2014
Pasero C. The Perianesthesia Nurse’s Role in the Prevention of Opioid-Related Sentinel Events. Journal of PeriAnesthesia Nursing 2013; 28(1): 31-37
May 13, 2014
Perioperative Sleep Apnea: Human and Financial Impact
Our numerous columns on the obstructive sleep apnea (OSA) in the perioperative period (see the list at the end of today’s column) have emphasized that most cases of OSA are unrecognized and that such patients are at risk for complications and even death following surgery. In parallel with the obesity epidemic, the prevalence of OSA has been steadily increasing.
A new study sought to quantify outcomes and resource utilization in patients with known sleep apnea who underwent total hip or knee arthorplasty (Memtsoudis 2014). The authors reviewed data on over 500,000 patients from 2006 to 2010 in a large database. The prevalence of diagnosed sleep apnea was 8.4%. This actually increased from 6.2% to 10.3% over the course of the study period. Compared to those patients without sleep apnea diagnoses, patients with sleep apnea had a higher incidence of post-op complications, including a 47% increased risk of major postoperative morbidity. They also more frequently used critical care, telemetry, stepdown services, mechanical ventilation and noninvasive ventilator support, though they had less frequent blood transfusions. Patients with sleep apnea also had longer lengths of stay and consumed more economic resources (about 14% higher). Keep in mind that these were patients with diagnosed sleep apnea. As we’ve noted previously the vast majority of patients with sleep apnea are undiagnosed at the time they have surgery. It therefore is very likely that the impact of sleep apnea on both outcomes and resource utilization is actually much more substantial.
Interestingly, compared to other studies showing increased in-hospital mortality this study and some other recent ones have failed to demonstrate increased mortality in those patients with OSA undergoing surgery. In an accompanying editorial Chung and Mokhlesi (Chung 2014) speculate about this mortality issue. They suggest that the obesity paradox or ischemic preconditioning might play a protective role or that patients with known OSA simply have impending respiratory failure recognized and managed earlier. They stress that CPAP can be effective in the perioperative period, though compliance with CPAP is suboptimal (see our September 24, 2013 Patient Safety Tip of the Week “Perioperative Use of CPAP in OSA”).
Speaking of mortality and sleep apnea, a recent study has demonstrated an association between OSA and maternal mortality in pregnancy (Louis 2014). Because of a recent trend in increasing rates of severe maternal morbidity and mortality despite quality improvements, the authors sought to see if obstructive sleep apnea (OSA) in pregnant women was impacting pregnancy-related morbidities and in-hospital maternal mortality.
They looked at a nationally representative sample of 55,781,965 pregnancy-related inpatient hospital discharges from 1998-2009. The rate of OSA increased from 0.7 in 1998 to 7.3 in 2009, an average annual increase of 24%. After controlling for obesity and other potential confounders, OSA was associated with increased odds of preeclampsia, eclampsia, cardiomyopathy, and pulmonary embolism. Women with OSA experienced a more than fivefold increased odds of in-hospital mortality. The adverse effects of OSA on selected outcomes were exacerbated by obesity.
Back to OSA and surgery, another very interesting study provides some insight into sleep-disordered breathing in patients undergoing surgery (Roggenbach 2014). The authors looked at breathing patterns in 37 patients undergoing major surgery who had not already been diagnosed with OSA. They did polygraphic recordings on these patients the pre-op night and 6 consecutive nights following surgery. They did not have full polysomnograms. Rather, O2-saturation, pulse, nasal air flow and snoring were monitored. 59% of the patients had abnormal nocturnal breathing patterns (AHI = 5 or higher) on the pre-op night, with 22% having AHI’s of 15 or higher. The median apnea-hypopnea index (AHI) was 6.0 for the group as a whole on the pre-op night. The AHI increased on the 6 nights following surgery, with the increases on the third through sixth nights being significant (median AHI’s being 16.9, 11.6, 15.2, and 22.5 respectively for those subsequent nights). Previous observations had demonstrated a delayed increase in OSA after surgery, usually in conjunction with the return of REM sleep on the second or third post-op day. But this appears to be the first study to monitor for a longer duration and it shows a substantial increase in the risk of OSA in the late post-op period.
Those authors speculate that the surgery itself may have a modulating effect on nocturnal breathing patterns. Their patients underwent major prostate or abdominal surgeries. They note that such surgeries are regularly associated with substantial fluid accumulation and speculate that peripharyngeal soft tissue edema might contribute to reduced airway patency. They also speculate that some of the cytokines typically released with surgery may lead to the early REM suppression seen after surgery, with the subsequent REM rebound appearing later.
Overall, their findings would certainly have implications about the duration of monitoring of patients with suspected OSA post-operatively. It would also seem to challenge performance of surgery in the ambulatory setting. But keep in mind that these were cases of major surgery. It would probably not be appropriate to generalize these findings to cases of more minor surgery. Note that Society for Ambulatory Anesthesia Consensus Statement on Preoperative Selection of Adult Patients with Obstructive Sleep Apnea Scheduled for Ambulatory Surgery (Joshi 2012) emphasizes the need for opioids and control of comorbidities as the most important considerations in deciding whether someone with suspected OSA should have their surgery as an inpatient or outpatient. But even that consensus statement emphasizes to patients and their families that the risks related to OSA persist for several days after surgery.
Reggenbach and colleagues also found little difference in self-reported snoring or daytime drowsiness in their patients who had sleep-disordered breathing compared to those who did not, but the small number of cases makes that difficult to interpret. While the small numbers would not suggest we need to stop using screening tools such as the STOP-Bang questionnaire, the observation does warn us that some patients will have abnormal AHI’s in the post-op period even in the absence of pre-existing symptoms. They also surprisingly found no correlation between AHI values and daily opioid dosing but, again, the numbers were small.
Speaking of screening tools, another recent study found a screening tool for OSA to be of little value in children (Wild 2014). The authors found that, though identifying 85% of children with moderate to severe OSA, the American Society of Anesthesiologists screening tool for moderate to severe OSA (MSOSA) had a 78% false positive rate.
And, speaking of children, don’t forget that the recent warnings about use of codeine in children first originated after deaths of pediatric patients receiving codeine after adenotonsillectomy for OSA (see our What’s New in the Patient Safety World columns for September 2012 “FDA Warning on Codeine Use in Children Following Tonsillectomy” and March 2013 “Further Warning on Codeine in Children Following Tonsillectomy” and our May 2014 “Pediatric Codeine Prescriptions in the ER”). And a study done last year focusing on death and neurological injuries following tonsillectomy (Cote 2013) concluded that at least 16 children could have been rescued had respiratory monitoring been continued throughout first- and second-stage recovery, as well as on the ward during the first postoperative night. Those authors also stress the need for a validated pediatric-specific risk assessment scoring system to assist with identifying children at risk for OSA. That might help determine which children are not appropriate to be cared for on an outpatient basis.
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”
February 12, 2013 “CDPH: Lessons Learned from PCA Incident”
February 19, 2013 “Practical Postoperative Pain Management”
March 26, 2013 “Failure to Recognize Sleep Apnea Before Surgery”
September 24, 2013 “Perioperative Use of CPAP in OSA”
What’s New in the Patient Safety World columns:
November 2010 “More on Preoperative Screening for Obstructive Sleep Apnea”
Memtsoudis SG, Stundner O, Rasul R, et al. The Impact of Sleep Apnea on Postoperative Utilization of Resources and Adverse Outcomes. Anesth Analg 2014; 118: 407-418
Chung F, Mokhlesi B. Postoperative complications associated with obstructive sleep apnea: time to wake up! Anesth Analg 2014; 118: 251–253
Louis JM, Mogos MF, Salemi JL, et al. Obstructive sleep apnea and severe maternal-infant morbidity/mortality in the United States, 1998-2009. Sleep 2014; 37(5): 843-849
Roggenbach J, Saur P, Hofer S, et al. Incidence of perioperative sleep-disordered breathing in patients undergoing major surgery: a prospective cohort study. Patient Safety in Surgery 2014; 8: 13
Joshi GP, Ankichetty SP, Gan TJ, Chung F. Society for Ambulatory Anesthesia Consensus Statement on Preoperative Selection of Adult Patients with Obstructive Sleep Apnea Scheduled for Ambulatory Surgery. Anesthesia & Analgesia 2012; 115(5): 1060-1068
Wild D. OSA Screener of Limited Clinical Use in Children, Study Finds. Anesthesiology News 2014; 40:4 April 2014
Cote CJ, Posner KL, Domino KB. Death or Neurologic Injury After Tonsillectomy in Children with a Focus on Obstructive Sleep Apnea: Houston, We Have a Problem! Anesth Analg 2013; Published Ahead-of-Print 10 July 2013
May 20, 2014
Blue Dye Mixup
We don’t get to do very many ophthalmology patient safety columns. But here’s a case with a risk that we suspect could be present at many hospitals or ambulatory surgery centers (CDPH 2014).
In the case a 71 y.o. man was undergoing cataract removal and insertion of an intraocular lens. VisionBlue (trypan blue) is often used to stain the lens capsule to enhance its visualization during cataract surgery. When the surgeon requested VisionBlue she was handed a syringe by the surgical tech and injected the contents of the syringe into the eye. When the surgeon then examined the eye through the operating scope she found the entire area to be stained an opaque dense blue. The contents of the syringe had been methylene blue rather than trypan blue. Methylene blue is a long-lasting tissue staining dye not intended for eye injection. Despite multiple irrigations with saline the eye remained opaque and the patient was transferred to another facility for possible corneal transplant. The ultimate outcome was not known.
There appears to have been a communication error between the surgical tech and the RN in the OR. The RN understood the request as being for methylene blue, which is apparently used by some surgeons to mark the location of the incision (note that it also has other uses such as determination of extravasation from some cavities). Only a small drop is necessary for that purpose. Unable to find a suitable receptacle at the table to deposit several drops of methylene blue, the RN drew the methylene blue into a syringe and handed the syringe to the surgical tech saying “all you need is a few drops”. The surgical tech labeled the syringe as “VisionBlue”. Had facility policy and procedure been followed it would have required both verbal and visual verification of the dye and the labeling of the syringe by 2 qualified personnel.
The facility subsequently educated OR staff on the policy and added competency assessment on it to the annual list of competencies. More importantly, they removed methylene blue from all Ophthalmology preference cards. In addition, medication carts were removed from the eye rooms and replaced with Pyxis machines which stored all eye medications by the physician’s name and included drug name, concentration, and amount.
Somewhat bothersome is that the surgeon indicated she almost always has her eye on the operating scope and trusted that the syringe contained the correct solution. If that is the case, which is understandable, it’s really incumbent upon the surgeon to participate in the verification of the drawing up of the substance in the syringe and the labeling of the syringe. We can think of a host of other toxic or caustic substances you would not want injected into your eye.
The Joint Commission, of course, has standards on preparation and labeling of medications and other substances in syringes or basins in the sterile field. And this does not just apply to the OR. In our October 22, 2013 Patient Safety Tip of the Week “How Safe Is Your Radiology Suite?” we noted there have been numerous cases where the wrong type or wrong dosage of a contrast agent has been injected during myelography with disastrous results, often because of inadequate labeling or storage. And most of us remember an unfortunate case a few years ago where a patient was inadvertently given the antiseptic skin prep solution, chlorhexidine, instead of contrast media intraarterially (ISMP 2004).
This is really also an example of confusion about LASA (look-alike, sound-alike) drug pairs. So if you are an OR or ASC that does eye surgeries, you should add this drug pair (methylene blue and trypan blue) to your LASA list and take appropriate precautions to minimize the chance they might be mixed up. If you are a facility that only does eye cases, you probably have no need for methylene blue and therefore should not stock it at all. In other facilities you clearly need to store the two blue dyes separately. If you have a dedicated “eye” room and can store all the medications and materials for eye surgery there (or in an automated dispensing cabinet dedicated to ophthalmology) make sure that methylene blue is not in those areas. It might even be worth considering putting warning labels on methylene blue stating “not for eye cases” or something to that effect. We are unaware of any “tallman” lettering conventions for this drug pair. A logical one might be “METHYLENE blue” and “TRYPAN blue” but you’d have to make sure that these choices are not confused with any other drugs or substances you stock.
Some of our previous patient safety columns involving ophthalmology issues:
June 5, 2007 “Patient Safety in Ambulatoy Surgery”
March 11, 2008 “Lessons from Ophthalmology”
June 8, 2010 “Surgical Safety Checklist for Cataract Surgery”
June 2012 “Tailored Timeouts for Ophthalmologists”
CDPH (California Department of Public Health). 2014. Intake Number CA00368387.
ISMP (Institute for Safet Medication Practices). Loud wake-up call: Unlabeled containers lead to patient's death.ISMP Safe Medication Safety Alert! Acute Care Edition.December 2, 2004
Print “Ophthalmology: Blue Dye Mixup”
May 27, 2014
A Gap in ePrescribing: Stopping Medications
A recent case report in the Medical Journal of Australia (Tong 2014) brought to light a substantial gap in our current systems for e-prescribing. The authors describe a case where an 82 y.o. man on warfarin for atrial fibrillation develops bruising with a severely prolonged INR after cessation of rifampicin, which he had been taking for treatment of tuberculosis. The patient had previously been on warfarin 4 mg. daily and that dose had been increased to 12 mg. daily in conjunction with monitoring of INR levels while the patient was on the anti-TB regimen. The warfarin therapy was managed by his PCP, while the antimicrobial therapy was managed by a specialist. The rifampicin had been discontinued by the specialist 7 weeks before the hospital admission for the bruising. It was concluded that there had been a significant drug-drug interaction between the warfarin and rifampicin and that the cessation of rifampicin therapy had led to the prolonged INR when the warfarin dose was not readjusted.
The case, of course, raises multiple issues. The most obvious would be a problem in communication between the physicians managing the various medications. This might be an endorsement for our frequent use of “coumadin clinics” where a nurse or pharmacist in conjunction with a supervising physician regularly review all the patient’s medications and adjust warfarin dosage based on expected interactions and INR results.
But it also illustrates some of the issues we have with our IT systems. Even though most regions are developing HIE’s or RHIO’s that integrate health information from multiple sources, those resources are often not routinely accessed by physicians and may not yet be intergrated into the EMR’s and e-prescribing systems in physician offices.
But, importantly, this case illustrates another critical issue: stopping a medication is much different than starting one. The clinical decision support built into our EMR’s and e-prescribing systems generally is pretty good at identifying potentially serious drug-drug interactions and generating alerts at the time a medication is prescribed. That presumes the alerts are turned on and the “severity” threshold for the particular alert is enabled. (To avoid alert fatigue we usually recommend that only the more serious alerts are enabled.)
But stopping a medication is much different. Most systems are not programmed to generate any alerts at the time you discontinue a medication. Hence, even if your system would have generated a drug-drug interaction alert when you first prescribed a medication, it would not likely generate an alert later when you discontinue that medication. Moreover, starting a medication requires an active process – you either write a prescription, enter one into a computer, or call the pharmacy. Whereas discontinuing a medication is often more passive – you may just tell the patient over the phone to stop it when the patient calls about a potential side effect. You don’t call the pharmacy to stop it. And, if there was no associated office visit, you might forget to update the patient’s medication list in your EMR (or paper records) until the patient’s next office visit.
Another problem is that a patient may continue to get medications that you thought you had stopped. A study done in a large multispecialty group practice in Massachusetts (Allen 2012) showed that among targeted medications that were electronically discontinued (on the practice’s EMR) 1.5% were subsequently dispensed by a pharmacy at least once. And this was just at the practice’s internal pharmacy. How often this happened at community pharmacies was not known. Moreover, when they did manual chart reviews of selected high-risk medications that had been discontinued they found that 12% of cases were associated with potential harm.
The authors note that when a physician discontinues a medication on an EMR he/she often (erroneously) assumes that such information is being transmitted to the pharmacy. Such is seldom the case with today’s EMR systems. Further, many pharmacies today have sophisticated systems that let you know, as a patient, that you have a refill waiting for you at the pharmacy. Patients may erroneously presume that their physician restarted that medication.
These examples highlight the continuing struggles we have in optimizing medication reconciliation. The need to do medication reconciliation at every office (or hospital) visit is obvious.
While we need to rely on technology vendors and HIE/RHIO’s to come up with some better electronic and interoperability solutions, you also need to look at your own practice. How do you update your patients’ medication lists after you do that over-the-phone medication discontinuation? How do you let the pharmacy know you have stopped a medication? How do you find out if your patient is still being dispensed a discontinued medication? How do you find out that another physician has discontinued a medication on one of your patients? And how do you recognize that the medication you’ve discontinued may have had a drug-drug interaction with another medication (the dose of which you may now need to adjust)?
Lots of questions. No easy answers.
Tong EY, Kowalski M, Yip GS, Dooley MJ. Impact of drug interactions when medications are stopped: the often forgotten risks
Med J Aust 2014; 200 (6): 345-346
Allen AS, Sequist TD. Pharmacy Dispensing of Electronically Discontinued Medications. Ann Intern Med 2012; 157(10): 700-705
June 3, 2014
More on the Risk of Sedative/Hypnotics
In our What’s New in the Patient Safety World columns for May 2012 “Safety of Hypnotic Drugs” and November 2012 “More on Safety of Sleep Meds” we discussed the issue of a possible link between sedative/hypnotic drugs and mortality. One study (Kripke 2012) found the risk for death was about 4.5 times higher in those patients who had been prescribed hypnotics. They found a dose-response relationship where the risk increased with increasing numbers of sleep pills taken. A second paper by the same group and same database found that the risk of death was even higher in the subset of patients having obesity (Langer 2012). The authors speculated about the role of sleep apnea and its interaction with the sleep meds in this population. While those two studies may have uncovered an association between mortality and use of hypnotics, they do not confirm a cause-effect relationship.
Another study challenged the strength of the association between hypnotic use and mortality (Hartz 2012). One key question unanswered in previous studies showing a higher mortality in patients using hypotics was whether sicker or higher risk patients were more likely to use these drugs. The Hartz study used data from the well-known long-term Women’s Health Initiative (WHI) and was able to adjust for a host of other clinical factors. They did note that those women using almost daily hypnotic drugs had a 62% increased risk of mortality. However, after adjusting for a variety of risk factors associated with poor health there was a great attenuation of the relationship between hypnotic use and mortality (adjusted odds ratio 1.14) for those using hypnotics almost daily and the relationship disappeared entirely for those using them less frequently. However, since the study period for the WHI ended in 1998 most women in the study did not take any of the currently used sedative/hypnotic agents that may have been used in the more recent studies.
Now a new study again notes an association between anxiolytic and hypnotic medications and increased mortality (Weich 2014). Researchers in the UK, using the General Practice Research Database were able to compare mortality risks in over 100,000 patients prescribed anxiolytics or hypnotic medications compared to age- and sex-matched controls followed for a mean of 7.6 years. They found that mortality rates for those patients prescribed such drugs were over three times higher than those not taking such medications, even after adjustment for likely confounding factors. Moreover, there appeared to be a dose-dependent association in that the mortality rates were even higher in those taking such drugs for at least 90 days per year. While benzodiazepines were the most widely prescribed and had the highest association with mortality, the association and dose-dependent effect were seen for all drugs studied, including the so-called “Z drugs” (zolpidem, zaleplon, and zopiclone). The authors do point out that, because this is an observational study, confounding due to unknown factors cannot be excluded. Also, they cannot exclude a bias related to indications for prescribing such drugs.
Over the years we’ve discussed many of the safety issues related to sedative/hypnotic drugs (see the links to prior columns below). They frequently are contributing factors to patient falls, hip fractures, delirium, and opioid-related respiratory depression. Sometimes we’ll see withdrawal syndromes in patients who have been receiving such drugs chronically. They may also play a role in predisposing some patients to aspiration. Anecdotally, they are a frequent contributor to events occurring in patients with sleep apnea and a recent study (Li 2014) demonstrates a reliable association between a history of high-dosage hypnotics and sleep related breathing disorders. Zolpidem has been associated with increased visits to the emergency department and another recent study (Huang 2014) has shown an association between zolpidem use and infections.
And, of course, sedative/hypnotics have been linked to next-day impairment of activities requiring mental alertness, such as driving. In our March 2013 What’s New in the Patient Safety World column “Sedative/Hypnotics and Falls” we noted that the FDA (FDA 2013) had recommended lower doses of certain drugs containing zolpidem (Ambien, Ambien CR, Edluar, and Zolpimist) because of potential next-day impairment of activities requiring mental alertness, such as driving. Just recently the FDA (FDA 2014) issued a similar alert recommending lower doses for eszopiclone (Lunesta). The FDA cited studies in healthy adults showing next-morning psychomotor and memory impairment after dosing with 3 mg. eszopiclone compared to placebo and that such impairments were most severe at 7.5 hours but still present 11 hours after dosing. The new FDA recommendation is for a starting dose of Lunesta of 1mg. at bedtime.
While the nature of most studies linking sedative/hypnotic drugs to these undesirable outcomes precludes conclusion of a cause-and-effect relationship, the frequency with which these associations appears in observational and retrospective cohort studies is strong enough to make you question prescribing these drugs for your patients. Prescribing sleep meds, whether for inpatients or outpatients, is often done without much thought. All too often they are thought of as being relatively harmless. Knowing the potential downside is an important first step. On the inpatient side, putting in place various system fixes (eg. removing them from standardized order sets, using clinical decision support tools, etc.) may play a more important role. On the outpatient side, knowing and understanding how to promote good sleep hygiene is extremely important in helping patients avoid the need for such drugs in the first place. You need to help patients adopt practices that promote good nocturnal sleep. That includes things like counseling them about eating and drinking habits in relation to time of day (eg. avoiding caffeinated beverages at night or avoiding large volumes of fluid that will lead to awakening to void). And you need to make sure that noise and light levels are not barriers to sleep and that the ambient temperature is conducive to sleep. Similarly, activities earlier in the day may be important. Getting some exercise, particularly outdoors, may benefit sleep as well as overall health. Attention to patterns of any naps may also identify why a patient has trouble sleeping at night.
Some of our previous columns on safety issues associated with sleep meds:
August 2009 “Bold Experiment: Hospitals Saying No to Sleep Meds”
March 23, 2010 “ISMP Guidelines for Standard Order Sets”
May 2012 “Safety of Hypnotic Drugs”
November 2012 “More on Safety of Sleep Meds”
March 2013 “Sedative/Hypnotics and Falls”
June 2013 “Zolpidem and Emergency Room Visits”
August 6, 2013 “Let Me Sleep!”
Kripke DF, Langer RD, Kline LE. Hypnotics' association with mortality or cancer: a matched cohort study. BMJ Open 2012; 2: e000850 doi:10.1136/bmjopen-2012-000850
Published 27 February 2012
Langer RD, Kripke DF, Kline LE. Abstract 052: Short-acting Hypnotic Drugs Increase Mortality and Obese Patients are Particularly Vulnerable. Circulation. 2012; 125: A052
Hartz A, Ross JJ. Cohort study of the association of hypnotic use with mortality in postmenopausal women. BMJ Open 2012; 2(5). pii: e001413. http://bmjopen.bmj.com/content/2/5/e001413.long
Weich S, Pearce HL, Croft P, et al. Effect of anxiolytic and hypnotic drug prescriptions on mortality hazards: retrospective cohort study. BMJ 2014; 348:g1996 (Published 19 March 2014)
Li CT, Bai YM, Lee YC, et al. High dosage of hypnotics predicts subsequent sleep-related breathing disorders and is associated with worse outcomes for depression. Sleep 2014; 37(4): 803-809
Huang CY, Chou FH, Huang YS, et al. The association between zolpidem and infection in patients with sleep disturbance. J Psychiatr Res 2014 Mar 27. pii: S0022-3956(14)00090-9 [Epub ahead of print]
FDA. FDA Drug Safety Communication: Risk of next-morning impairment after use of insomnia drugs; FDA requires lower recommended doses for certain drugs containing zolpidem (Ambien, Ambien CR, Edluar, and Zolpimist). January 10, 2013
FDA. FDA Drug Safety Communication: FDA warns of next-day impairment with sleep aid Lunesta (eszopiclone) and lowers recommended dose. FDA Safety Announcement 5/15/2014
June 10, 2014
Another Clinical Decision Support Tool to Avoid Torsade de Pointes
Last month ISMP Canada did a safety bulletin on a suspected preventable death due to a known drug-drug interaction (ISMP Canada 2014). The case involved an elderly woman admitted with fever and presumed pneumonia. Prior to admission she was on citalopram 40 mg. daily, an anticoagulant, an antihypertensive, and nonprescription supplements. Initial antibiotics were ampicillin and gentamycin but these were later switched to azithromycin and ceftriaxone. She subsequently suffered a series of syncopal spells and a cardiac arrest. She had a markedly prolonged QT interval and was also hypokalemic. The citalopram and azithromycin were discontinued. She ultimately died. It was felt she had a prolonged QT interval syndrome secondary to citalopram and azithromycin that contributed to her death.
The article discusses the literature on the QT interval-prolonging effect of both citalopram and azithromycin and notes the effects may be additive. They note the warnings on both drugs that have been disseminated by both Health Canada and the US FDA. They note 2 potential points for intervention: (1) when the pharmacy processed the order for azithromycin and (2) when the prolonged QT interval was first noted.
In several of our prior columns (see list at the end of today’s column) we’ve discussed the risks of developing ventricular tachycardia and, specifically, Torsade de Pointes in hospitalized patients with prolonged QT intervals. There are a number of reasons why this syndrome is more likely to both occur and result in death in hospitalized patients. Hospitalized patients have a whole host of other factors that may help precipitate malignant arrhythmias in vulnerable patients. They tend to have underlying heart disease, electrolyte abnormalities (eg. hypokalemia, hypomagnesemia, hypocalcemia), renal or hepatic impairment, and bradycardia, all of which may be precipitating factors. More importantly they may have the sorts of conditions for which we prescribe the drugs that are primarily responsible for prolonging the QT interval (eg. haloperidol, antibiotics, antiarrhythmic agents, etc.). And many of those drugs are given intravenously and in high doses in the hospital as compared to the outpatient arena. Rapid intravenous infusion of such drugs may be more likely to precipitate Torsade de Pointes than slow infusion.
In our previous columns we provided a number of steps your organization should be taking to minimize the risks in such cases. We’ve recommended use of clinical decision support systems (CDSS) and computerized alerts as an important step. No one could possibly remember all the drugs that can prolong the QT interval. For a full list of drugs that commonly cause prolongation of the QT interval and may lead to Torsade de Pointes, go to the CredibleMeds™ website. That site also has a list of drugs that prolong the QT interval and might possibly cause Torsade de Pointes and another list of drugs that have conditional risk (eg. only when combined with other drugs). Hence, the need for other tools to help alert the clinician that a drug he or she is about to order might prolong the QT interval. In our April 9, 2013 Patient Safety Tip of the Week “Mayo Clinic System Alerts for QT Interval Prolongation” we discussed one such CDSS tool that had been implemented at the Mayo Clinic (Haugaa 2013).
Now another new study has demonstrated that use of CDSS and computerized alerts can reduce the risk of QT interval prolongation (Tisdale 2014). One of the most important considerations is developing a system in which the risk of alert fatigue is minimized. We know from multiple studies done in the past that physicians override over 90% of computer alerts during CPOE (computerized physician order entry). To minimize the risk of alert fatigue and still accomplish your goal of reducing the risk to patients it is important to (1) deliver the alert to the right person (2) deliver alerts only for the most potentially serious events and (3) provide alternative options for the physician’s response.
They system developed and implemented by Tisdale and colleagues did all three. First, the alerts first went to the pharmacist, who would then evaluate the situation and decide whether discussion with and recommendations for the physician were appropriate. Second, the thresholds to trigger the alerts were set at levels expected to minimize alert fatigue. And, third, the pharmacist responding to the alert would present the physician with some options for actions.
After reviewing extensive data on prior patients in their CCU’s and reviewing the literature, the researchers opted to trigger the alert when the QTc interval was >500 ms or there was an increase in QTc of ≥60 ms from baseline. Their system also identified through the electronic medical record multiple other conditions or laboratory results that identified patients at higher risk for QT interval prolongation.
After implementation of the CDSS system the found a significant reduction in the risk of QT prolongation (odds ratio 0.65). In addition, they found a significant reduction in the prescription of non-cardiac drugs known to prolong the QT interval (especially fluoroquinolone antibiotics and intravenous haloperidol).
Overall, 82% of alerts were overridden. That still compares favorably to the frequency with which other alerts are overridden. Most of the overrides were for cardiac drugs (eg. amiodarone or other anti-arrythmic drugs). The authors point out that overriding the computer alert did not mean that nothing was done. For example, even though the order for the drug may have been overridden the pharmacist and physician may have modified some other risk factor (eg. corrected an electrolyte disturbance or stopped another medication) or increased the frequency of QTc surveillance.
We recommend you read our previous columns listed below for suggestions on what your organization should be doing. Since many of the risk factors in hospitalized patients are potentially modifiable or avoidable it is imperative that we put into place systems that will help early identification of patients at risk.
Some of our prior columns on QT interval prolongation and Torsade de Pointes:
June 29, 2010 “Torsade de Pointes: Are Your Patients At Risk?”
February 5, 2013 “Antidepressants and QT Interval Prolongation”
April 9, 2013 “Mayo Clinic System Alerts for QT Interval Prolongation”
ISMP Canada. Preventable Death Highlights the Need for Improved Management of Known Drug Interactions. ISMP Canada Safety Bulletin 2014; 14 (5): 1-7 May
Haugaa KH, Bos JM, Tarrell RF, et al. Institution-Wide QT Alert System Identifies Patients With a High Risk of Mortality. Mayo Clin Proc 2013; 88(4): 315-325
Tisdale JE, Jaynes HA, Kingery J, et al. Effectiveness of a Clinical Decision Support System for Reducing the Risk of QT Interval Prolongation in Hospitalized Patients. Circulation: Cardiovascular Quality and Outcomes 2014; published online before print May 6, 2014
June 17, 2014
SO2S Confirms Routine Oxygen of No Benefit in Stroke
In several of our prior columns on use of oxygen (see our Patient Safety Tips of the Week April 8, 2008 “Oxygen as a Medication” and January 27, 2009 “Oxygen Therapy: Everything You Wanted to Know and More!”) we have commented that in the past we often routinely gave oxygen to patients with myocardial infarction or stroke. But such use was more reflexive in nature and not evidence-based.
In our What’s New in the Patient Safety World columns for July 2010 “Cochrane Review: Oxygen in MI” and February 2012 “More Evidence of Harm from Oxygen” we discussed the lack of evidence to support the routine use of oxygen in the acute MI patient and the possible deleterious effects in these and some other cardiac patients.
Then in our March 2014 What’s New in the Patient Safety World column “Another Strike Against Hyperoxia” we noted a study (Rincon 2014) showing that hyperoxia was independently associated with in-hospital death as compared with either normoxia or hypoxia in ventilated stroke patients admitted to ICU’s.
Such studies have called for large randomized controlled trials to answer the important questions about if and when to use oxygen in patients with stroke or MI. Well, one such study has now been done in stroke patients. The Stroke Oxygen Study (SO2S) in the UK was established to determine whether routine use of oxygen acutely in stroke patients is of value. The Stroke Oxygen Study website has a video of the recent presentation of preliminary findings at the European Stroke Conference.
The video notes that many stroke patients have nocturnal hypoxia. Over half (52%) have nocturnal hypoxia for 5 minutes or more, 23% for 30 minutes or more, and 15% for an hour or more. The study included over 8000 patients at 136 centers. Patients were randomized to one of three arms: (1) routine continuous oxygen for 72 hours (2) nocturnal oxygen for 72 hours and (3) no routine oxygen (O2 only as needed). The primary outcome was functional status (disability as measured by a modified Rankin Score) at 90 days. Secondary outcome was survival. The study showed no difference in the primary outcome between the combined oxygen groups and the control group and no difference between the continuous vs. nocturnal oxygen groups. Similarly, there was no difference in the secondary outcome of survival. Subgroup analysis has yet to be done but the message is clear: routine supplemental oxygen does not benefit stroke patients.
As we’ve recommended before, hospitals need to look at their existing protocols (and actual practices) for managing a variety of medical conditions where oxygen use may be considered. How many of you have standardized order sets that directly (or indirectly by poor use of checkboxes) encourage inappropriate use of oxygen in MI or stroke patients? Going back to our Patient Safety Tips of the Week April 8, 2008 “Oxygen as a Medication” and January 27, 2009 “Oxygen Therapy: Everything You Wanted to Know and More!” we strongly support facilities doing audits of their oxygen practices. You’ll probably be surprised at the opportunities you uncover to improve practices (and save money at the same time!).
And don’t forget that in many cases high doses of oxygen are administered by the pre-hospital emergency response teams. Making them aware of the potential dangers is also important.
The other important consideration, in view of the high incidence of nocturnal hypoxia in stroke patients, is sleep-disordered breathing and obstructive sleep apnea (OSA) in particular. While we screen all stroke patients for swallowing dysfunction prior to feeding them by mouth, there are likely many stroke patients who have subclinical weakness of pharyngeal muscles and may be prone to OSA. In fact, in a meta-analysis of the frequency of sleep apnea in stroke and TIA patients, Johnson and Johnson found 72% of stroke patients had sleep disordered breathing and almost all were due to obstructive sleep apnea rather than central sleep apnea or Cheyne-Stokes respirations (Johnson 2010). This was independent of the type of stroke or timing of the stroke and there was little correlation with traditional symptoms of OSA such as snoring. So clearly a high index of suspicion for OSA is needed in patients with acute stroke.
If the cause of the nocturnal hypoxia in stroke patients is OSA, it is not surprising that supplemental oxygen does not lead to improvement. We’ve noted in many of our columns on OSA that oxygen supplementation in OSA patients may provide a false sense of security and actually mask the occurrence of apneic spells, particularly if the only monitoring is oximetry. So it is imperative that you monitor such patients not just with pulse oximetry but also with capnography and/or some other monitoring for apnea.
So the purported lesson from the SO2S study is “don’t routinely use oxygen in stroke patients”. But we are taking away a second, perhaps more important, lesson: you need to consider stroke patients as being at risk for obstructive sleep apnea and its potential acute and long-term consequences.
Kudos to the UK researchers who did the SO2S study. Recruiting patients for the study must have been difficult given that so many physicians have followed the time-honored tradition of using oxygen in stroke patients. This study has done a valuable service for all.
Some of our prior columns on potential harmful effects of oxygen:
April 8, 2008 “Oxygen as a Medication”
January 27, 2009 “Oxygen Therapy: Everything You Wanted to Know and More!”
July 2010 “Cochrane Review: Oxygen in MI”
February 2012 “More Evidence of Harm from Oxygen”
March 2014 “Another Strike Against Hyperoxia”
Rincon F, Kang J, Maltenfort M, et al. Association Between Hyperoxia and Mortality After Stroke: A Multicenter Cohort Study. Critical Care Med 2014; 42(2): 387-396
Stroke Oxygen Study website
Johnson KG, Johnson DC. Frequency of sleep apnea in stroke and TIA patients: a meta-analysis. J Clin Sleep Med 2010; 6: 131-137
June 24, 2014
Lessons from the General Motors Recall Analysis
Our readers know we often cull lessons learned from root cause analyses done in industries other than health care. Most often those have come from RCA’s involving serious incidents in the airline or transportation fields but we’ve also learned from incidents like the BP gulf oil spill.
The report on GM’s investigation into events surrounding its recent recall of automobiles because of a faulty ignition switch that had been a likely contributing factor in many accidents, including at least 13 reported fatalities, offers many valuable lessons for healthcare organizations. Interestingly, many of the lessons are about diagnostic error in addition to the more traditional lessons about system and organizational root causes.
GM hired outside help, former US Attorney Anton R. Valukas from Jenner and Block LLP, to find out how and why it took GM so long to recall the Chevrolet Cobalt and several other models. The investigators were given unfettered access to documents and witnesses. GM then made public the full 325-page report of the investigation and analysis (Valukas 2014).
To briefly summarize the overall scenario, a faulty ignition switch was approved in 2002 despite it not meeting GM’s own specifications. The torque required to move the key in the ignition switch (eg. from “OFF” to “ACC” or “RUN”) was too low, meaning that in some circumstances the switch could easily and inadvertently be moved from “RUN” to “ACC”. Such a move resulted in loss of power to the vehicle, in turn leading to loss of power steering and power brakes. In addition, airbag deployment is not possible once the switch is out of the “RUN” mode. After introduction of the faulty switch into multiple auto lines (most notably the Chevrolet Cobalt), GM began receiving complaints about “moving stalls”, i.e. the cars would suddenly lose power while driving. This resulted in multiple accidents and many fatalities. Most of the fatalities and serious injuries might have been prevented if the airbags had deployed. For almost a decade, GM did not understand the connection between the switch and the failure of airbag deployment and characterized the moving stalls as “customer inconvenience” rather than as safety issues. To complicate matters, a new switch introduced in 2008 models actually corrected the problem but that switch change was poorly documented in GM records. Because of that, GM investigators focused their attention away from the faulty switch as a cause for the failed airbag deployments. Though several outside investigators identified the switch/airbag connection as a likely cause of accidents, it was not until a plaintiff’s expert identified the disparity between ignition switches in the pre- and post-2008 models that the connection was recognized. GM finally issued a recall of affected autos in 2014, a decade after issues were first noted.
One thing that comes out early in the report is that much at GM is done in silos. That is, engineers may be focused on just one piece or part or system and not fully understand how that piece/part/system interacts with all the other parts and systems of the vehicle. Sound familiar? In healthcare we often find silo mentalities where healthcare personnel focus their thinking on their particular department, often without understanding the roles and functions of all other departments and how they interact with them.
In 1997 the ignition switch was designed to communicate with other car components, be less prone to failure and fire, and be less expensive. GM wanted a “corporate common” switch that could be used across multiple platforms/lines. Parameters for the technical specifications for the switch were developed by a GM engineer. Over the next several years there were at least 2 transitions of the engineer responsible for oversight of the ignition switch specifications. In healthcare, we know such transitions as “handoffs” or “handovers” and understand them as events very vulnerable to error. Handoffs entail both transfer of information and transfer of responsibility. During one such transition at GM it was noted that the specifications for the torque to move the ignition switch between settings were not being met by the prototype switch. Several potential options for changes in design to meet the specs were apparently discussed but it is unclear whether any were implemented. It appears GM really left the internal design and construction of the switches to the supplier and just cared that they met the GM specifications.
In early 2002, as the date for launch of the Saturn Ion neared, the GM engineer now in charge of the ignition switch (whom we will refer to as RD) noted that the switches often failed to meet the torque specification requirements. But the switch also had multiple other problems, particularly on the electrical rather than mechanical side. In fact, RD often referred to it as “the switch from hell” and seemed very concerned about the electrical issues. Was this a “salient distracting feature” (see our January 14, 2014 Patient Safety Tip of the Week “Diagnostic Error: Salient Distracting Features”)? Did the focus on the electrical issues so dominate the evaluation that the mechanical (torque) issue was overlooked?
During validation testing every sample set had at least some switches that fell below the torque specification. RD discussed potential design changes with the supplier engineer, who noted that he could probably fix the torque issue but was concerned that might introduce some other problems. Apparently it was decided not to alter the switch at that time. This is probably an example of an ETTO (efficiency-thoroughness trade-off) as we discussed in our September 15, 2009 Patient Safety Tip of the Week “ETTO’s: Efficiency-Thoroughness Trade-Offs”. At any rate, RD eventually approved the switch despite the fact that it did not meet the specifications for required torque.
Interestingly, the Valukas report just focuses on the approval of this one item without going into detail about the approval process in general. If we were doing the RCA we would have asked “how often are approvals given when parts do not meet specification requirements?” not just for this one engineer but for all GM engineers. We would want to know whether the GM culture had adopted “normalization of deviance”. In our July 5, 2011 Patient Safety Tip of the Week “Sidney Dekker: Patient Safety. A Human Factors Approach” we noted the Challenger disaster, in particular, brought to light the importance of concepts like “normalization of deviance” where successes despite problems lead to the acceptance of such problems as “normal” and therefore tolerable. We would also want to know how GM audited for such practices (the Valukas report simply states that it appears RD was the only one who ever reviewed the results showing the switch had failed to meet the specs).
Shortly after launch of the Saturn Ion and Chevrolet Cobalt with these ignition switches complaints began to appear about the switch inadvertently moving out of the “RUN” position, causing moving stalls. After reviews this problem was classified as a “customer inconvenience” rather than a safety issue, apparently because it was felt that a driver could still maneuver the vehicle even if the power steering and ABS braking system were not functioning. It appears GM engineers did not appreciate that the power failure also prevented deployment of airbags, which would have made it a clearcut safety issue. The report on numerous occasions notes how difficult it is to change an issue classification once it is originally made. Hence, for a decade this was never seen as a safety issue.
There were also numerous complaints that, particularly in cold weather, the ignition switch would not “crank’ or start. The report notes that this issue was an embarrassment to RD and that he seemed to focus more on that problem than the stall problem.
In 2004 the Cobalt was put into production with the same switch. GM workers drive such cars as part of the “captured test fleet” (CTF) to assess the cars. Apparently there were instances in which the switch was inadvertently turned off, leading to moving stalls but the drivers did not consider this to be a significant safety issue so it was not officially reported as a safety issue. But the CTF data collected from the Ion and Cobalt did note that the switch was “vulnerable” to being bumped by a knee and shutting the engine off. Again, this is a prime example of someone knowing that something is wrong but not speaking up about it. That happens in healthcare all the time. Often it is because they do not feel the problem is significant. At other times they fear speaking up may lead to other problems.
In the summer and fall of 2004 more complaints about the stalls arose and even attracted media attention and GM engineers could even replicate the problem. But they still considered it an isolated problem and not a safety issue. Throughout 2004 and 2005 multiple GM committees reviewed the complaints and, again, they never were elevated above a severity level 3 (on a scale of 1 to 4 with 1 being the most severe). Again, no one seemed to be aware of the airbag issue. Again, silo thinking was apparent. The airbags were part of the car that these engineers did not oversee and it was apparent that few understood the overall integration of the systems in the vehicles. GM did notify dealers, but not consumers, about the problem of the switch easily moving out of the “RUN” position and advised dealers to tell consumers with the problem to take unnecessary items off their key chains to reduce the risk.
In early 2005 potential solutions were discussed but none involved change in the switch itself. The report describes problems with the committees reviewing the problems. There was never an “owner” or person responsible for the problem and the committee structure allowed for individuals to easily disavow responsibility. They describe the “GM salute” in which individuals cross their arms and point to others. For non-safety issues an acceptable business plan was required that: (1) solved the issue (2) was cost-effective and (3) had acceptable lead time to implement changes. Non-safety issues had to clear numerous financial hurdles. Many of the committee meetings addressing the stall issue ended with the “GM nod” in which heads nodded, knowing that no action would be taken. Think about your healthcare organization. How many issues are discussed ad nauseum by committees that shield individuals from responsibility and accountability and subsequently don’t get anything done?
In 2004 the NHTSA (National Highway Traffic Safety Administration) was reviewing moving stalls industry-wide. A GM committee again addressed the issue and asked what would happen if a moving stall occurred. They addressed steering, brakes, and warnings but not airbag deployment. No one seemed to be aware that airbags would not deploy during such stalls. Interestingly, the system design to prevent airbag deployment when the car is not moving came about because of unintended airbag deployment accidents when cars were parked or not moving. So the current problem is actually an unintended consequence of a prior solution to another problem. That is a reminder in healthcare to always consider and monitor for unintended consequences when we implement changes to fix problems.
It appears during this time that GM also did not have good tracking systems or reporting systems for complaints or industry-wide issues. In healthcare we know that having such reporting systems, particularly those that also capture near-misses, are essential to identifying problems that need to be addressed before untoward outcomes occur.
In 2005 both short-term and long-term potential solutions to the switch problem were considered. A short-term fix was approved and consisted of a change in the key head design. Customers who had complaints were offered a plug insert but this was still only for those who complained. After some more negative press coverage, another GM performance improvement team re-evaluated the issue and again concluded it did not merit a recall. Apparent rationale was that the episodes were infrequent and the drivers still had control over steering and brakes. Again they failed to understand the airbag issue. So GM still considered this a “convenience” issue rather than a safety issue. Though they made over 10,000 such plugs apparently only 430 were ever requested! And new cars continued to be produced without even this temporary fix. Also of note was that the technical services bulletin issued by GM to dealers did not mention the word “stall”. That term had specifically been excised from the early drafts, presumably because it was considered a “hot” item that might attract attention of the NHTSA.
In 2006 engineer RD approved a new switch. While one type of document (Form 3660) noted the mechanical change improving the torque issue, the work order mentioned only changes to the electrical components of the switch and there was no change made in the part number. This was a critical event, since the issue of moving stalls disappeared in models produced after this new switch was in place. When subsequent investigations looked to see why the problem appeared to disappear with 2008 and subsequent models they ruled out a problem with the switch because their document searches focused on the work order and engineer RD did not recall making any change. The report indicates that GM policy would have required a change in part number. Again, if we were doing the RCA at this point we’d be asking “was such failure to change the part number an isolated occurrence or in fact had this become something more widely accepted in the culture at GM?”, in essence another form of “normalization of deviance”.
In mid-2006 GM was publicly stating there was no safety issue. Note that once a public position is taken on an issue one seldom changes his/her mind, even when confronted with contradictory evidence. The powerful influence of public commitment cannot be overestimated. In our September 28, 2010 Patient Safety Tip of the Week “Diagnostic Error” we mentioned anchoring becomes a more significant problem once a diagnosis or other decision has been declared publicly. Many of you may have done an exercise in executive training where a scenario is presented in which you must state a position publicly. You are then given a bit of disconfirming evidence and a chance to change your decision. Almost no one changes their decision! (The scenario is actually a poorly disguised parallel of the Challenger disaster).
In 2006 the legal department at GM, in conjunction with some representation from engineering and other departments, began addressing some cases of fatalities or serious injuries in which airbags did not deploy. They failed to make any connection with the defective ignition switch. But in 2007 two separate outside investigations into an accident did make a connection. Keith Young, an astute Wisconsin state trooper investigating a fatal crash in which airbags did not deploy, noted the ignition switch was in the “ACC” position and postulated that was why the airbags failed to deploy. He also noted that there had been reports on the NHTSA website about switch issues. And a team of researchers at Indiana University commissioned by NHTSA to look at the airbag nondeployment issue came to the same conclusion. GM apparently did not learn of the Indiana University report until 2012. It did apparently have in its files the state trooper’s report as early as 2007 but it is not clear who, if anyone, ever actually reviewed that report at GM. It’s also unclear from the Valukas report what the NHTSA did with the Indiana University report.
Apparently GM did not routinely monitor the NHTSA website. That is similar to the issue of hospitals lacking systems for routinely monitoring websites for recalls and other patient safety issues (see our February 26, 2013 Patient Safety Tip of the Week “Insulin Pen Re-Use Incidents: How Do You Monitor Alerts?”).
In 2007 NHTSA had expressed interest in the issue of airbag nondeployment but never formally requested GM information. GM did take another look and had one engineer develop a spreadsheet to begin tracking such events but, again, there was no sense of urgency nor clear instructions what to do with that data nor a timeframe for reporting.
In 2009 another review of airbags noted in one such case that the sensing and diagnostic modules (SDM) did not deploy the airbags because the algorithms were disabled at the start of the event with 2 possible causes: (1) loss of battery power or (2) the SDM received a power mode signal status of “OFF”. The Valukas report notes this should have been an “aha” moment but the engineers focused more on the electrical system. They were unaware of the previous issues related to the torque of the ignition switch. Instead, they developed a theory (the “contact bounce” theory) in which a sudden jarring event caused the electrical components in the switch to “open up” and send a signal that the switch had moved from “RUN” to “ACC”. However, field engineers could not replicate this problem in field testing. But one fact that seemed to lend credence to this theory was that many of the crashes with nondeployment were “off-road” accidents where such jarring bumps were likely.
The above issues raise several concepts we’ve discussed in our many articles on diagnostic error such as confirmation bias, ignoring disconfirming information, anchoring, and early closure. The fact that many accidents were “off-road” probably injected confirmation bias into this theory. The disconfiming evidence (that the field tests could not replicate the problem) were ignored or at least failed to sway opinion in another direction. And these may have led to anchoring/early closure that moved investigators away from looking at the ignition switch torque issue.
The Valukas report summarizes the 2006-2010 events as having multiple failures, including the failure to change the part number, failures to share information, failure to gather basic facts, and failure to understand the overall design or the vehicles.
In 2011 the GM legal department began receiving claims and warnings that GM might be liable for punitive damages. This led to more multidisciplinary meetings but they often again ended with the “GM nod” (i.e. nothing would be done).
Two of the GM investigators continued with the working theory of “contact bounce”. They were bothered by the fact that there had been no problems in models from 2008 and later and that in half the cases tracked the switch was in the “RUN” position. That led them away from the ignition switch torque issue as a causative factor. The Valukas report notes some difficulty the investigators may have had in tracking cases. One of the data bases (TREAD) was apparently very difficult to use and the GM investigators did not have access to that part that had fatalities. They thus may have missed some of the cases of fatalities that had occurred in 2003-2004 Ion models. And there was also a question of some “privileged” information not being readily available to the GM investigators.
Note that the report raises considerable questions about the legal atmosphere at GM. While all formal documents emphasize the obligation to come forward with anything that might impact safety, many GM employees were reluctant to do so. Also, many did not take formal notes at some meetings because they were under the impression that the legal department discouraged such. Again, that’s something we see in hospitals all the time, i.e. that a policy may say one thing but actions say another. And actions and culture typically trump policy.
In June 2012 a plaintiff’s lawyer notes the Indiana University report. This apparently is the first time GM is made aware of that report. And a GM investigator and electrical engineers visited a junkyard in working on their theory that jarring led to some sort of electrical event (the “contact bounce” theory). When they examined a Cobalt they were amazed at how “extraordinarily easily” the ignition switch key turned. They put together a home-made system to estimate torque and their measurements suggested that it was possible a vehicle could hit a pothole and have the switch move out of the “RUN” position.
In a May 2012 meeting a slide prepared by one of the GM investigators concluded that airbag nondeployment was likely related to the torque issue of the ignition switch. That was based on how easy it was to turn the key, the prior technical service bulletins regarding the switch torque issues, and review of the records from the sensor module in some crash cases. Further, an explanation was put forth as to why the switch was sometimes in the “RUN” position after the crash. The system has an algorithm which is inactive during the initial 3 seconds after transitioning from “OFF/ACC” to “RUN” (so it can run self-diagnostics). Since many of the crashes occurred within 3 seconds of the loss of power, the reported position of the switch on the sensor module would not have been reset from “RUN”.
Another trip to the junkyard was made so formal torque measurements could be made. But torque values were similar in some 2007 and 2008 models so the investigator could not conclude that the switch had changed in 2008. An investigator asked engineer RD again whether there had been a part change and he said no. That investigator relied on RD’s statement and did not access the Form 3660 (which would have shown the change). The work order did not reflect a change in part.
In June 2012 a plaintiff’s expert concluded, based on the state trooper/Indiana University reports and the previous GM technical service bulletins about the torque issue, that airbag deployment would not occur when the switch was in the “ACC” position. At a meeting of GM legal staff in July 2012 a new attorney asked why there had been no recall and the response was that the engineers did not know how to fix it, the incident rate was low, and engineering “was looking into it”.
In the summer of 2012 an attempt was made to use a standard engineering diagnostic, RedX, to determine how a 2007 Cobalt differed from a 2008 one. It was to compare a “best of the best” vs. a “worst of the worst” performing vehicle. But they could not find a vehicle to represent “worst of the worst” and did not complete the diagnostic.
Then, in April 2013, a plaintiff attorney at a deposition presented “bombshell” photographic evidence that the switches indeed differed between 2005 and 2008 models. GM subsequently confirmed that the torque was below the design specifications and found X-ray evidence that the switches differed. That led to a check of records of Delphi, the switch supplier, which confirmed that GM engineer RD had approved the change in April 2006.
The analogy we wish to draw here is with diagnostic error in healthcare. There was a failure and unwillingness to re-evaluate. One of the things we’ve stressed in our many columns on diagnostic error is the need to say “What might I be missing?” and go back and look at all the available information again. Other questions to ask are “What am I putting too much weight on?” and “What am I not paying enough attention to?”.
Yet GM still did not issue a recall until early 2014. The Valukas report goes on to describe the reasons for delays in the recall. These included requests for further analysis, focus on finding root causes, and perhaps most importantly lack of awareness by senior officials that any fatalities had been involved. It goes on to describe the corporate culture and that the CEO, General Counsel and Board of Directors really did not learn about this until January 2014. At Board meetings, safety issues were reported in aggregate, not as individual cases and the fatalities were not mentioned in those reports. Furthermore, it sounds like a lot of time was spent on JD Powers and Consumer Reports ratings rather than on fundamental safety issues. The report goes on to discuss a dichotomy of values: “when safety is an issue, cost is irrelevant” vs. “cost is everything”.
Valukas goes on to describe a cultural resistance to raising issues. The rate of reporting misconduct was low compared to other industries and companies. There was often a fear of retaliation. Despite the stated policy that it’s everyone’s responsibility to report safety issues, there were specific guidelines on how to write about safety issues (not to be judgmental or speculate). And we mentioned that many did not take notes at meetings because they thought the lawyers wanted it that way.
Valukas cites the lack of ownership and/or accountability, overreliance on committees to make decisions, silo thinking, delays while looking for root causes, the “GM salute” and the “GM nod” among other detrimental features.
The Valukas report makes numerous recommendations, many of which GM has already begun implementing. These deal with promoting a culture of safety, change in management and reporting structure, need to identify ownership and responsibility at the individual level, communications between GM groups and communication with the NHTSA, role of the legal department and its interaction with other departments, better interaction with suppliers, better access to information and tracking in both GM and industry databases, better documentation and record keeping, better structure to performance improvement projects, training, audit, oversight and compliance, and others.
One gets the overall image of a bureaucratic behemoth gone amok and unaware of many issues. Yet we see the same faulty processes in many of our healthcare organizations.
GM made a big deal about dismissing 15 employees as a result of the investigation and many in Congress have been calling for “more heads to roll”. We’re not sure what criteria they used to determine who should be fired. Clearly most of the issues here were organizational, cultural, and system issues. In fact, it’s quite likely that some of those fired would be the ones least likely to ever make similar mistakes in the future. An article in the New York Times (Vlasic 2014), using information from interviews with multiple parties in addition to the Valukas report, was very critical of the role of the GM legal department, noting that the secrecy promoted by the lawyers obscured the flaw both inside and outside the company.
Interestingly, one thing we never see any reference to is a FMEA (failure mode and effects analysis). We would have thought that FMEA would be part and parcel of the activities of any company in the automobile industry. Yes, a switch sounds like too small a part around which to merit a FMEA. But, in fact, this small switch interacted with multiple other components and systems in an extremely complex fashion. When we do FMEA’s in healthcare we are usually amazed at the potential vulnerabilities we uncover.
The Valukas report is 325 pages long and some of the terminology gets technical at times. Nevertheless, it is worth reading. You’ll find yourself saying “hey, that sounds just like something that happens in our organization!”. You’ll readily appreciate the system issues that led to this prolonged failure to recognize and implement a simple change that could have saved many lives and other serious outcomes. But you’ll also begin to appreciate that many of the basic concepts we see leading to diagnostic error also come into play when we are attempting to unravel puzzling non-medical issues.
Some of our previous columns with lessons learned from root cause analyses (RCA’s) done in other industries to demonstrate by analogy what can go wrong in various healthcare settings:
August 28, 2007 “Lessons Learned from Transportation Accidents”
October 2, 2007 “Taking Off From the Wrong Runway”
May 19, 2009 “Learning from Tragedies”
May 26, 2009 “Learning from Tragedies. Part II”)
August 24, 2010 “The BP Oil Spill - Analogies in Healthcare”
April 5, 2011 “More Aviation Principles”
April 26, 2011 “Sleeping Air Traffic Controllers: What About Healthcare?”
April 16, 2013 “Distracted While Texting”
January 7, 2014 “Lessons From the Asiana Flight 214 Crash”
Some of our prior columns on diagnostic error:
Valukas AR. Report to Board of Directors of General Motors Company Regarding Ignition Switch Recalls. Jenner and Block 2014; May 29, 2014
Vlasic B. G.M. Lawyers Hid Fatal Flaw, From Critics and One Another. New York Times 2014; June 6, 2014
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